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This annotated bibliography contains a variety of sources which were found either through searching Google Scholar and the online database for the Robert Gordon University Library or through recommendation of ChatGPT. Each of these 10 sources explores the role of AI in education, with a brief description of their contents and evaluation of their usefulness.

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Akiba, D & Fraboni, MC 2023, ‘AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment’, Education Sciences, vol. 13, no. 9, Basel: MDP, p. 885

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Akiba, D & Fraboni, MC 2023, ‘AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment’, Education Sciences, vol. 13, no. 9, Basel: MDP, p. 885

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This source is an article from 2023 which I found through the university library. The researchers explained how they came up with a list of questions then whittled it down, removing questions which were too personal or time specific. They ended up with seven questions which they asked to the free version of ChatGPT. Through analysis of its answers they determined that artificial intelligence is a tool which can complement humans and be used by them to complete work in a timelier manner but that it cannot replace them. Additionally, they concluded that AI is currently and will continue to change the world and that the focus of research should be on making sure that change is positive. Much of the paper used the medical field as examples but there were some education examples too. The article was not specific to my context but was useful, nonetheless.

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School of Education, Queens College and the Graduate Center of the City University of New York, New York, NY 10016, USA

Author to whom correspondence should be addressed.

1. Introduction

Now, how would these efforts on areas outside of the field of education inform us, as it pertains to academic support for current and future university students, to be specific? AI's roles in educational settings have gained remarkable attention in higher education since ChatGPT's release in November of 2022, but the excitement has been somewhat skewed in focus. While scholars and practitioners alike widely appear to believe that ChatGPT and other AI tools have the potential to fundamentally change the landscape of higher education [ 17, 18], the primary foci have revolved around two distinct areas of discussion: (a) the concerns around plagiarism and other aspects of academic integrity [ 3, 19, 20, 21] and, to a lesser degree, (b) pedagogical methods to promote teaching and learning, particularly with academic writing and medical education [ 8, 22, 23, 24]. In other words, although there appears to be a widely shared perception that AI will be a "game changer" in our society and prompt us to reinvent how humans handle information in the most overarching manner, thus far, research on ChatGPT and other AI-supported tools in higher education has not explored its impact outside of a limited set of contexts, often approaching them mainly as a threat rather than a potential asset [ 17, 20]. Perhaps as a result, movements to ban-or put a moratorium on-ChatGPT and other AI-powered tools have been emerging in educational institutions around the globe [ 2], which may perhaps inadvertently stunt the integration of a tool that could potentially be of great utility in higher education. As Zawacki-Richter and colleagues have posited [ 18], we must ensure that educators actively and proactively participate in conversations surrounding AI integration into the field of education to ensure that balanced perspectives will be represented as generative AI models continue to proliferate in and outside of educational settings.

Academic advising has been identified as being critical to student success, particularly for those from disadvantaged backgrounds, yet institutions of higher education are often unable to provide adequate student advising primarily because it is highly resource intensive to hire full-time academic advisers and faculty advisers-with their teaching, research, mentoring of honors and graduate students, and other duties, they may not consistently be able to devote their time or attention to general academic advising [ 4, 5, 25]. High-quality academic advising in higher education has also been linked to student satisfaction and loyalty to the university [ 26], which should enhance student retention. It is therefore not surprising that various aspects of AI-powered tools began to be incorporated into some high-cost academic advising platforms, such as EAB [ 27]; however, the provision of accessible and effective academic advising continues to pose challenges [ 5]. For one, such tools typically come with steep institutional subscription price tags, and they are not open to the public, which severely limits access. Among the numerous challenges university students face in seeking academic advising and the key concerns identified by researchers and practitioners are (a) limited availability of advisers and difficulty scheduling appointments and (b) inconsistencies in the fidelity of advice provided, which can frequently lead to inaccurate or insufficient information provided by advisers [ 4, 28, 29]. Based on the exhaustive database search on ERIC, PsycINFO, SocINDEX, and ScienceDirect, at the time of submission of this manuscript, no published research to date appears to have examined the potential roles to be played in academic advising or, in fact, the larger context of student service by freely available generative AI models, such as ChatGPT. A recently published rapid literature review on the topic of the impact of generative AI tools on education [ 30] corroborates this observation-that there is a conspicuous gap in the literature.

It is perhaps worth reiterating here that the intent of the current exploration is not necessarily about evaluating a particular tool, ChatGPT, per se; rather, the inspiration here is far more inclusive. Specifically, our motive here is to examine the current state and the future possibilities of generative AI models, such as ChatGPT, in a context that does not appear to have been very well examined-student advising, especially given that student advising continues to pose challenges in university students' educational and professional pursuits in the United States, most often involving students of color and other underrepresented demographic groups [ 31, 32]. Then, why are we singling out ChatGPT in discussing academic advising vis-à-vis AI-powered tools? First, while other AI-powered large language models, such as Google's Bard and Microsoft's Sydney, continue to be released [ 33], ChatGPT, by far, has currently been the most prolific of all public-facing AI-powered large language models, and it is freely and widely accessible for individuals with access to digital devices and the internet [ 20]. Although a paid version of ChatGPT is available, the free version, which limits the number of questions one can ask each day, has been utilized and examined in the healthcare community with great success [ 10], among other contexts, as discussed above. As a rule, AI-powered tools, such as ChatGPT, are available 24 h a day, seven days a week. Most higher education institutions do not offer human-based advising around the clock, so this alone presents a profound advantage over human-provided advising. Given that ChatGPT is free of charge, its active utilization may also promote educational equity, particularly for prospective and current students with limited access to resources, including personal networks or paid consultants, to address education- and career-related questions.

ChatGPT also permits students to ask questions in their natural language, and it responds in similar, everyday language. Given that some studies have suggested that academic language presents a barrier to education, which functions to maintain educational inequity [ 34], this is a highly desirable feature. Similarly, since practically no technical expertise or knowledge of platform-specific user interface is required in using ChatGPT, taken together, the incorporation of ChatGPT into academic advising has the potential to empower all students equitably through its exceptional accessibility.

Before we can pursue this possibility further, though, it would be critical to ask the following: how would ChatGPT fare in terms of the quality of the advice it gives? In this exploratory report, we will closely examine the advice provided by ChatGPT's free version on (a) general questions about the elementary school teaching profession in a specific region in the United States and (b) questions that are specific to a particular degree program in elementary education at an institution of higher education.

2. Materials and Methods

Overview. The authors serve as faculty advisers in a teacher education department at an institution of higher education, where elementary school teaching is the most popular of its offerings, in a large metropolitan city in the mid-Atlantic region of the United States. In the exploratory study presented here, we followed the research method utilized by Xie and colleagues [ 10] and aimed to probe into the quality-such as accuracy, comprehensiveness, timeliness, and the supportive tone-of the advice ChatGPT's free version, based on GPT 3.5, provides in response to questions pertaining to (a) a career in elementary school teaching in the State of New York in the United States and (b) program-specific requirements and other information at the university where the authors teach, advise, and conduct research. Narrative analyses are presented for the answers generated by ChatGPT, with the intent to use them in prompting more rigorous investigations on the topic of generative AI-integrated academic advising.

Selection of questions to be explored in the current study. Based on the advising record between 2019 and 2023, the authors compiled a list of the most frequently asked questions by prospective or current students. Then, questions were removed if they pertained primarily to (a) highly individualized circumstances (e.g., "I got a 'C-minus' in Introductory Biology. Should I repeat the course for a better grade?" or "What courses should I take next semester?"), (b) recent and temporary circumstances (e.g., "How will the COVID-19 pandemic impact the hiring of elementary school teachers?" or "Do teachers still need to wear face masks while teaching?"), or (c) simple and factual questions whose answers are publicized prominently (e.g., "How much is the tuition?" or "What is the starting salary for public elementary school teachers in New York City?"). The main reasons for noninclusion of these questions, respectively, were (a) ChatGPT, at this time, has not been designed to assess each student's circumstances or profiles, as it does not have access to the relevant information, (b) ChatGPT's answers, as a rule, will not currently include information that became available after 2021, and (c) very simple factual questions do not require an AI tool, as the answers are widely available in a straightforward fashion.

In the end, seven questions were selected for the current exploratory study. Of those, five pertain to a career in elementary school teaching in the State of New York (NYS) in general terms, and the remaining two are specific to our teacher education program. Table 1 lists the questions included in the current exploratory effort.

Procedure. ChatGPT utilizes algorithms that generate varied responses through random sampling, whereby variability in the answers to the same question may vary [ 35]. As such, for the current purpose, the first answer to each question was analyzed for its quality, following the method utilized by previously published research in the medical field [ 10]. The authors typed these questions sequentially on ChatGPT's free account, powered by GPT 3.5, and each answer was recorded. Then, each answer obtained was analyzed for its quality-such as accuracy, comprehensiveness, timeliness, and overall tone, as described above. Since this is an exploratory study with no previous data available to the best of the authors' knowledge, the decision was made early on not to quantify the findings. However, the authors keenly recognize the critical relevance of such studies and are in the process of pursuing additional research along the current theme.

3. Findings

Generally, the quality of the responses provided by ChatGPT far exceeded our expectations, with carefully crafted emphases periodically placed on encouraging the inquiring individual to consult other specific resources. In fact, for some of the questions, we found that the answers ChatGPT provided were of higher quality than what many human advisers might be able to provide, as described in more detail below. In addition, the tone of ChatGPT's answers was decidedly professional yet simple and supportive. Figure 1 presents the responses to the first question: what are the steps involved in earning certification as an elementary school teacher in New York State?

Our assessment is that this answer is highly comprehensive, concisely written in simple language, and surprisingly accurate and current. Still, however, there are two notable areas of improvement regarding the accuracy of the information. First, strictly speaking, in order to be fully certified as an elementary school teacher in NYS, a master's degree is required, although a bachelor's degree is sufficient for the initial, temporary certification that expires in five years if one fails to obtain a master's degree during the period. Second, while it is factually accurate to state that enrolling in a teacher preparation program, as outlined in Step 2 in the answer, is the most common and orthodox option toward obtaining teacher certification in elementary school teaching, it is not the only way-with several alternative pathways available.

As such, the answer to Question 1 can perhaps be best characterized as "good but incomplete", failing to provide information on some potentially useful nuances associated with NYS teacher certification requirements. Despite these shortcomings, it is impressive that the answer articulates a little-known yet profoundly important fact that one does not have to major in elementary education to become certified as an elementary school teacher in NYS, as any university major would be acceptable as long as the degree program is completed with teacher certification components-such as fieldwork and well-balanced coursework in the liberal arts. As for the timeliness of the information, Step 5 of the answer returned mixed advice. Specifically, it reflects the recent elimination of the edTPA examination (edTPA was suspended in 2020 during the COVID-19 pandemic; in 2022, NYS officially eliminated edTPA from its teacher certification requirements). However, it erroneously includes the Academic Skills Literacy Test (ALST), which was eliminated in 2017-six years prior to this study. This error was unexpected since ChatGPT, presumably, composes its answers based on the information available up to 2021, yet the 2017 elimination of a test was somehow omitted from consideration. Despite these issues, overall, the answer here provides a comprehensive overview of the general set of steps teacher candidates may wish to know, and the final disclaimer-that specific requirements may vary and, thus, it is important to consider other resources-is both appropriate and necessary.

For human academic advisers to generate answers of this caliber, it would have been necessary to have (a) consulted with multiple resources and, more importantly, (b) with outlines or guidelines to ensure proper coverage during consultations. With this much factual information across a wide range of domains to be conveyed in sufficient depth to students, the quality of advice provided by human advisers is bound to vary. Thus, it is our conviction that, complemented with proper fact checking and correction, the answer ChatGPT produced here may provide an excellent (1) initial starting point for the inquiring students and (2) a "template" based upon which human advisers may advise current and prospective advisees. Also, when calibrated properly, these answers could readily be posted on the institution's website to enhance the information dissemination efforts. Overall, we are highly impressed with the quality of the answer to Question 1, although factchecking would be critical in ensuring that students receive complete information.

The second question asked about the disadvantages of elementary school teaching as a profession. Figure 2 displays the answer generated by ChatGPT.

The answer to Question 2 is surprisingly balanced, and we find it to be exemplary in both content and tone, as it emphasizes that people typically find the career in question immensely fulfilling while presenting some of the common concerns factually in natural language. As with Question 1, it would be difficult for human academic advisers during advising sessions to provide an answer close to the comprehensive details presented in this answer, ranging in focus from concrete (e.g., salary) to abstract (e.g., emotional demands and life-work balance). It is so impressively comprehensive that we, as faculty advisers, cannot think of additional dimensions that would improve this answer substantively or meaningfully. The ChatGPT-generated answer here, thus, might perhaps be superior to what we can provide in person without faithfully following a template or a manual. It is particularly impressive that the answer even included potential ways through which some of the challenges may be remedied (e.g., seeking support from colleagues, the union, and other teacher advocacy groups), as we as faculty advisers had not thought of providing such information in guiding current and prospective teacher candidates. This answer, thus, would greatly benefit students who are looking for advice on elementary school teaching as a career.

The superb fidelity of this answer is perhaps counterintuitive because this question targets the "softer", more open-ended human aspects of elementary teaching as a profession rather than just factual information [ 36]. One might have presumed that humans would be more adept at addressing these open-ended questions and, by contrast, that an AI tool, such as ChatGPT, would struggle to generate nuanced, sensitive, and human-centric answers. Based on the answer here, however, this presupposition is clearly unwarranted. As with Question 1, the ChatGPT-generated answer here would serve as an excellent example for human advisers to follow in content and delivery, and posting this answer on the institutional website may serve to ensure increased access to quality information for our current and prospective students.

The third question revolved around what one may be able to expect in a career in elementary school teaching. Figure 3 presents the ChatGPT-generated answer.

In advising current and prospective students on elementary school teaching as a profession, the authors, while advising them, tend to focus on such aspects as professional satisfaction stemming primarily from making a difference in the lives of children, the possibility of expanding their career foci into school administration, work-life balance, and stability. As was the case with Question 2, by contrast, ChatGPT generated a high-quality answer that is comprehensive, realistic, and clear, encompassing an impressively wide range of dimensions-informing them about the expertise they will develop through their careers and the collaborative work culture, all the way to retirement. As with Question 2, this question mainly involved the human aspects of the profession, and the AI-generated answer provided here is exemplary in its content, coverage, and delivery, presenting an array of factors for the inquiring students to consider.

Human academic advisers would perhaps be hard pressed to provide an answer of this caliber and, as was the case with the two answers we discussed earlier, this answer, too, can adeptly serve as a model for human advisers to emulate or for inclusion in the appropriate sections of the institutional website. We also find the language and tone to be exceedingly supportive, particularly in the final paragraph, in which a balanced summary is provided, emphasizing the critical aspects, such as the betterment of society through one's professional growth and contributions, which would serve to encourage current and prospective teacher candidates to pursue a meaningful career in elementary school teaching.

The fourth question asked about the general career outlook, and Figure 4 presents the answer ChatGPT generated.

Like Questions 2 and 3, this question asked about a larger landscape of the profession involving layers of considerations beyond a simple set of concrete facts. Thus, as were the case for Questions 2 and 3, the answer for Question 4 can be considered exemplary in that it presents a balanced overview, prompts the inquiring individual to consider a wide range of factors with caution, and provides tips on how to optimize the career outlook, as well. In particular, it is remarkable that the answer contains (a) the highly impactful and nuanced influence the COVID-19 pandemic has had on the teaching profession and (b) an added emphasis on staying informed through specific methods, such as closely monitoring local education news, so as to optimize the professional prospects.

As with the ChatGPT-generated answers we have considered thus far, it would perhaps be difficult for human academic advisers to provide answers that match the quality and coverage of the information presented in this answer. Accessing this answer, thus, would be highly informative for individuals who are interested in entering the field of elementary school teaching. Based on our advising experiences and the knowledge in the profession, using this answer as a template for our human advisers to follow-or to be included on the institutional website-would be an effective method of advising our current and prospective teacher candidates. The fifth question concerns a prospective student's aptitude to become a good teacher. Figure 5 presents the answer generated by ChatGPT.

While it is widely acknowledged that ChatGPT fails to consider individual qualifications and characteristics [ 10], it is impressive that this answer was prefaced by a disclaimer that ChatGPT does not have access to the inquiring person's "...personal information or real-time data, so [it] can't assess [his/her] individual qualifications or suitability for becoming an elementary teacher..." This response replicates what human academic advisers must do routinely to remind each student that, to answer this question meaningfully, we must have an entire profile of each prospective student, and thus, there are no unequivocal answers we can give during advising sessions. Instead, we prompt them to reflect actively and examine their qualifications, aptitudes, value priorities, and so on, much like what the AI-generated answer here did.

It is also curious that this answer, in three different places, referred to early childhood or elementary teachers or education. In NYS, elementary schools often include kindergarten, and some elementary schools even contain pre-kindergarten. Since kindergarten and pre-kindergarten teacher certification fall under the umbrella of early childhood education rather than elementary education, including early childhood education alongside elementary education is appropriate. At the same time, however, it is curious that this is a feature that is not present in other answers-except that the answer to Question 1 included a reference to early childhood education as a related field for elementary teacher certification. We attribute this to the fact that ChatGPT, like other AI-based large language models, is still very much under development, and thus, the answers it provides, too, are to be considered works in progress [ 37]. Alternatively, it could also be that the large language model determined that inclusion of early childhood education to be less relevant for earlier questions on career prospects and career outlook.

Most importantly, from our perspective, ChatGPT does an admirable job, prompting the inquiring individual to consider a range of options in reaching his/her own conclusions. While human academic advisers, especially with proper access to academic transcripts and other relevant records, may be able to provide more individualized answers, it is up to prospective applicants or current teacher candidates to determine how suitable a career in elementary school teaching may be for them. The considerations introduced by ChatGPT range from concrete (e.g., whether one meets the certification requirements) to abstract (e.g., how passionate one is about the profession). Given this nuanced context, the answer provided here provides an effective means to comprehensively scaffold each teacher candidate's self-evaluation of whether elementary teaching is a suitable career. Again, this would be considered an exemplary answer, perfectly suitable to be shared with current and future students interested in elementary school teaching.

Although the five questions we have examined thus far involved elementary school teaching as a profession, the last two questions dealt with program-specific questions at the institution of higher education where this study took place. Specifically, Questions 6 and 7 asked about entry requirements for the bachelor's degree in elementary school teaching and the program requirements, and the answers provided are shown in Figure 6 and Figure 7 below, respectively.

Unlike the largely exemplary answers ChatGPT has produced for Questions 1 through 5 surrounding elementary school teaching as a profession in the State of New York in the United States, in response to institution- and program-specific questions, ChatGPT ostensibly avoided providing too many details and, instead, focused on giving representative scenarios, as well as suggestions on seeking further information. Consequently, specific program requirements, such as the minimum GPA to enter the program or the number of credits required toward program completion, were not included. One may consider these omissions to be noteworthy shortcomings, although such information is readily available through multiple resources, including the institution's website, program literature, and the institution's academic bulletin. Instead, the answers here focused on presenting typical sets of requirements for admissions and graduation-with repeated reminders that the inquiring individuals should consult with the institution's website and the appropriate academic departments at the institution, prompting the student to seek help directly from the institution. This advice has its disadvantages and advantages, as follows.

Namely, while it technically "failed" to present the program-specific requirements concretely, one may argue that it empowered the inquiring individual by providing (a) the general overview of what one might expect such requirements to entail, which may serve to promote the general understanding of the common admissions and program completion requirements, and (b) a conspicuous prompt for the information seeker, in the last paragraph of each answer, to obtain information from other specific resources, including the institution's website and human academic advisers, which may serve to alert the inquiring individual that the answer being sought would not be best provided using this AI-powered platform. This response is appropriate-or even ideal in some ways-in our view, especially given that concrete information on degree requirements is readily available through a multitude of materials, as described earlier. In our perspective, thus, this approach may be consistent with the philosophy, "Give a [person] a fish, and you feed [the person] for a day; teach a [person] to fish, and you feed [the person] for a lifetime", as the focus is on showing the "ropes" rather than merely giving the concrete facts [ 38]. This advising strategy should serve to promote effective information-seeking habits among inquiring individuals. In other words, these answers provide specific guidance to enhance the inquiring individual's investigative skills so that, should similar questions or issues arise in the future, the individual should be able to identify the appropriate methods of securing sufficient information.

Overall, the AI-powered tool explored here, ChatGPT, provided high-quality, comprehensive, nuanced, reasonable, and sensible answers in supportive and friendly natural language, although (a) there were a few specific factual errors, (b) it was only able to give general "pointers" in addressing more individualized questions, and (c) institution- or program-specific factual information was not provided in detail. Instead, ChatGPT was meticulous in pointing out its shortcomings, such as not always having access to complete or up-to-date information or not being equipped to handle individual-level guidance. In lieu of these limitations, ChatGPT presents general information and emphasizes that the inquiring individuals should refer to specific resources for elaboration and confirmation. In summary, the current exploratory study has demonstrated that ChatGPT is highly adept at providing general professional advice around elementary school teaching, and it can serve to point students in the right direction to obtain further information. Moreover, despite some of the shortcomings noted above, the generally impressive quality, coverage, and the tone can serve as a useful guide for human advisers to follow to optimize the advice we give our current and prospective students. The synergistic collaboration between ChatGPT and human advisers, thus, may represent an ideal method of providing effective advising.

4. Discussion

The current exploratory study has demonstrated the potential utility of generative AI models, such as ChatGPT, in providing academic advising in the context of higher education. It provides what the authors, who are university professors who routinely provide academic advising to current and future students, consider to be high-quality and comprehensive answers regarding general career-related matters. Furthermore, it appears to be perfectly suitable for academic advising around "big-picture" concerns, such as the steps to follow in pursuing a future career in elementary school teaching or what to expect in the profession-which, incidentally, are also among the most frequently asked questions by our current and prospective students. While questions specific to individuals or program-specific requirements, at this time, were not answered with much precision, ChatGPT still provided guidance in a clear and friendly language, complemented with helpful directives on obtaining more individualized and specific information. Thus, ChatGPT engaged the inquiring individuals in meaningful dialogues to target the questions at hand, perhaps serving as an advising triage to steer the prospective or current student's efforts to shape his or her own academic and career trajectories. Of course, with the world of AI rapidly evolving, shortcomings-such as accuracy-related concerns and the lack of access to current information, particularly for specific individuals and programs-are likely to improve over time.

Given that access to quality academic advising-or lack thereof-is frequently cited as among the most notable challenges faced disproportionately by university students, especially those from socioeconomically disadvantaged backgrounds, as they navigate the unfamiliar terrains of higher education [ 4, 5, 28, 31], such students may particularly benefit from the integration of AI-powered large language models, such as ChatGPT, into academic advising-not only in obtaining answers on an immediate basis but also in actively engaging in the process of focused inquiries. This is because, as noted earlier, ChatGPT is readily accessible free of charge, and it permits inquiring individuals to interact using their natural language. After "jump-starting" the information-gathering process with AI-based tools, should these students choose to seek additional human-based consultations, they would be able to hold more informed conversations, which is perhaps likely to lead to more productive-and personalized-advising sessions to promote their academic and professional pursuits. In other words, AI tools such as ChatGPT may represent an opportunity for educators to promote educational equity and empower students with powerful information in manners that would cater to the individual needs of each inquiring individual.

At the same time, ChatGPT-as its own advice frequently pointed out-would not replace person-to-person academic advising. As noted in the beginning, that is not the spirit underlying the current inquiry into ChatGPT's potential role in academic advising, either. Still, ChatGPT and other open-access AI-based tools readily available to the general public deserve further exploration in the student support context. One way of creating an effective ChatGPT-human adviser synergy in academic advising would be to have students develop a habit of utilizing ChatGPT (or similar) as their initial steps into getting their questions answered. Then, based on ChatGPT's answers, they may approach the appropriate resources for further elaboration and/or confirmation, which may or may not involve person-to-person contact. In addition, academic advisers themselves may wish to utilize generative AI tools in preparation for or even during advising sessions-keeping in mind that, at this time, fact checking may be of critical importance. For example, in response to questions regarding professional challenges elementary school teachers face, ChatGPT provided an impressive range of balanced considerations, and human advisers would certainly benefit from skimming through the advice ChatGPT provides to ensure proper coverage.

The current exploratory study only dealt with advising-related questions frequently asked by current and prospective university students considering a career in elementary school teaching-at one institution of higher education, no less; therefore, the generality of the findings obtained here may not apply to advising questions in other contexts or disciplines. Still, the current findings are sufficiently promising that large language models may prove to be a useful partner in other academic contexts, as well, given the strengths of the answers it provides, as outlined in this report. In considering the implementation of generative AI tools into academic advising, here are some useful guidelines based on the experience during the current exploration.

First, although ChatGPT is generally forgiving of grammatical errors, students must understand how to phrase questions to elicit optimal answers. For example, as seen in the questions asked in the exploratory study reported here, sufficient details on the questions being asked must be included-ranging from what (e.g., a career in elementary school teaching) to how (e.g., how to get certified as a teacher; how to gain admission into a teacher certification program), where (e.g., in the State of New York), etc., given that ChatGPT, at the present time, is only able to answer questions within the parameters inquiring individuals articulate [ 2]. Libraries frequently provide training resources to support users' efforts to adopt the most effective search terms and strategies on library databases [ 39], and similar resources should prove useful in facilitating the user efforts to utilize this potentially useful tool to the fullest extent. Also, in the experience of the authors toward the effective use of large language models outside of the context of the current study, "tinkering" with various search phrasings and gaining familiarity with its behavior have proven to be productive, and this approach is corroborated with research in information sciences, as well [ 40]. In other words, while these tools may provide relatively low barriers to entry, in order to fully utilize them, users may still need to gain sufficient proficiency [ 24].

Second, while this is articulated relatively frequently in the answers ChatGPT produces, it is important to alert inquiring students to the fact that ChatGPT, at least for now, remains a useful tool that, in many cases, may provide detailed information that may vary in its accuracy. As such, follow-up inquiries are both useful and necessary, probing further into more accurate or current information. Since ChatGPT, as we currently have it, may not necessarily be a self-standing tool that can provide complete and accurate answers, inquiring students should be reminded of the importance of developing a habit of following up with subsequent information seeking-involving humans or otherwise.

Admittedly, the current investigation was exploratory in nature, and it merely marks the beginning of a series of investigative efforts in which researchers must partake. Needless to say, as such, future research should expand on the current findings in several notable ways. First, more rigorous assessment of the quality of answers ChatGPT provides would be useful. In the study being reported here, the authors evaluated the ChatGPT-generated answers based on their knowledge and experience in the field, each having advised students seeking careers in elementary school teaching for over a decade. Thus, in the subsequent inquiries, we aim to evaluate the answers more systematically and objectively by, among other approaches, creating quantitatively measurable assessment criteria to evaluate AI-generated answers or having a larger number. Second, it would also be useful to assess the quality of academic advice produced on a wider range of questions, as well, so as to establish the potential utility of generative AI large language models in academic advising. Third, as other generative AI models gain prominence, their ability to provide academic advising should be explored, as well. Although we used ChatGPT as a reference point, the topic here revolves around AI-based large language models at large, and conscious efforts should be made to situate these discussions within the larger landscape of AI integration into student affairs. Finally, it would be particularly exciting to explore what other dimensions of student support beyond academic advising (e.g., behavioral interventions, disability accommodations, etc.) may be conducive to an effective integration of AI-powered tools, in order to foster a climate in which students are supported in a holistic manner.

As discussed thus far, ChatGPT seems to offer features and characteristics that could potentially optimize the experiences of current and prospective university students beyond academics, and education scholars and practitioners should closely examine what AI-powered large language models such as ChatGPT could do to promote equitable access to information and services. Of course, there are information security and other considerations to be discussed in pursuing AI integration [ 35], which also represents another layer of reasons for education scholars and practitioners to be actively engaged in discussions around integrating AI-powered tools into higher education.

The presence of generative AI tools in and outside of formal education is only likely to become more prevalent over time. If what we have observed through ChatGPT in the current exploratory study is any indication, these tools clearly possess enormous potential in enhancing the student support universities can offer, which students may use as the starting point to engage in informed and strategic processes of further investigation involving humans or nonhumans, or both, into the matters they are looking to resolve. Overall, given that the endeavors to develop and refine generative AI large language models are in full force, ChatGPT and its counterparts are likely to continue to improve dramatically and steadily, and many predict that they will become integral parts of our lives in the near future [ 33]. Against this sweeping backdrop, we argue that it is not only useful but also necessary for educators to treat AI-based resources, such as ChatGPT, as critical partners in providing holistic academic advising that can serve to empower all university students with multilateral access to high-quality information and support.

Author Contributions

Conceptualizations, D.A.; literature review D.A.; methodology, D.A.; data collection, D.A. and M.C.F.; analysis, D.A. and M.C.F.; writing-original draft, D.A.; writing-review and editing, D.A. and M.C.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Robin Hood Foundation (Grant Number A1N-5A000000IYl2QAA) and additional funding from the City University of New York's Computing Integrated Teacher Education (CITE) Initiative.

Institutional Review Board Statement

Informed Consent Statement

Informed consent was waived because the data obtained for the purpose of this study were generated automatically by ChatGPT and, thus, did not involve human subjects.

Data Availability Statement

The data for this study, the answers generated by ChatGPT, are included in their entirety in this manuscript.

Acknowledgments

The authors would like to thank the University Dean of Education, Ashleigh Thompson, as well as Sara Vogel and Aankit Patel (the City University of New York Central Office) for their support and guidance in the preparation of this manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

References

1. ChatGPT. Available online: https://chat.openai.com (accessed on 26 July 2023).

2. Anders, B.A. Is Using ChatGPT Cheating, Plagiarism, Both, Neither, or Forward Thinking? Patterns 2023, 4, 100694. [Google Scholar] [CrossRef] [PubMed]

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11. Engelbutzeder, P.; Randell, D.; Landwehr, M.; Aal, K.; Stevens, G.; Wulf, V. From Surplus and Scarcity towards Abundance: Understanding the Use of ICT in Food Resource Sharing Practices: "Give a Man a Fish, and You Feed Him for a Day; Teach a Man to Fish, and You Feed Him for a Lifetime."-Lao Tsu. ACM Trans. Comput.-Hum. Interact. 2023, 589957. [Google Scholar] [CrossRef]

12. Chodock, T. Library Instruction and Academic Success: The Impact of Student Engagement at a Community College. In Academic Libraries for Commuter Students: Research-Based Strategies; Regalado, M., Smale, M.A., Eds.; ALA Editions: Chicago, IL, USA, 2018; pp. 117-138. [Google Scholar]

Figure 6. ChatGPT-generated answer for "What are the requirements to enter the teacher education BA major in Elementary Education at (name of institution of higher education)?".

Q1

What are the steps involved in earning certification as an elementary school teacher in New York State?

Q2

What are some of the disadvantages of being an elementary school teacher in New York State?

Q3

What can I expect from a career in elementary school teaching in a long run?

Q4

How is the career outlook for elementary school teaching in New York State?

Q5

Do you think I'd make a good candidate to become an elementary school teacher in the State of New York?

Q6

What are the requirements to enter the BA program in Elementary Education at (name of institution of higher education)?

Q7

What are the graduation requirements to complete the BA program in Elementary Education at (name of institution of higher education)?

Akiba D, Fraboni MC. AI-Supported Academic Advising: Exploring ChatGPT's Current State and Future Potential toward Student Empowerment. Education Sciences. 2023; 13(9):885. https://doi.org/10.3390/educsci13090885

Chicago/Turabian Style

Akiba, Daisuke, and Michelle C. Fraboni. 2023. "AI-Supported Academic Advising: Exploring ChatGPT's Current State and Future Potential toward Student Empowerment" Education Sciences 13, no. 9: 885. https://doi.org/10.3390/educsci13090885

# data[].attributes.attachment_link.title
AI-Supported Academic Advising: Exploring ChatGPT's Current State and Future Potential toward Student Empowerment

# data[].attributes.attachment_link.description
Artificial intelligence (AI), once a phenomenon primarily in the world of science fiction, has evolved rapidly in recent years, steadily infiltrating into our daily lives. ChatGPT, a freely accessible AI-powered large language model designed to generate human-like text responses to users, has been utilized in several areas, such as the healthcare industry, to facilitate interactive dissemination of information and decision-making.

# data[].attributes.headline
Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and chatgpt in educational settings. Education Sciences, vol. 13, no. 7, Basel: MDP, pp.692–692

# data[].attributes.subject
Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and chatgpt in educational settings. Education Sciences, vol. 13, no. 7, Basel: MDP, pp.692–692

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This source is an article in a journal published in 2023 which I found via the university library. It analyses the potential benefits and the current limitations of artificial intelligence in education. The potential users involve translation and the semi-automation of the grading process both of which save time for teachers. Limitations include pay walls and threats like potential job cuts and lack of transparency from programmers regarding the data their AIs learn from and the recording of user’s interactions. Issues with currency and bias of data leading to the spread of misinformation thereby damaging students learning were also raised. The source also predicts a sort of arms race between AI and programmes to detect material they generate which would be expensive and ultimately useless. This source clearly laid out both pros and cons of AI before coming to what seems to be the general consensus: as long as the user is well trained, AI can be an invaluable help.

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by

Department of Psychosocial Science, University of Bergen, 5020 Bergen, Norway

1. Introduction

Over the last decade, the world has experienced a rapidly changing landscape in educational practices, primarily due to technological advancements. Among these technologies, arguably the most impactful has been artificial intelligence (AI) [ 1] Recent progress and expansion in machine learning have led to the generation of sophisticated digital content, like generative artificial intelligence (GAI), capable of assisting education [ 2, 3]. GAI is an unsupervised or partially supervised machine learning framework that generates outputs using statistics and probabilities [ 4, 5] Through advances in deep learning (DL), the generative AI creates artificial relics using existing digital content, such as, but not limited to, video, images/graphics, text, and audio, by examining training examples and learning their patterns and distribution [ 6]. The extant literature has identified two major types of generative AI-Generative Adversarial Networks (GAN) and Generative Pre-trained Transformer (GPT) [ 6].

The ChatGPT technology has been through several iterations [ 10]. GPT-3 has 175 billion parameters, which is 10 times more than any previously developed language model. GPT-3 has become the basic NLP engine that runs the recently developed language model ChatGPT, which has attracted the attention of various fields, including, but not limited to, education [ 11, 12] and health [ 13, 14, 15].

Following its launch on 30 November 2022, ChatGPT amassed over one million subscribers in just a week [ 16]. More recently, an even newer and more powerful model, GPT-4, was released on 14 March [ 17], featuring a staggering 170 trillion parameters, representing a staggering increase in computational processing capacity compared to the earlier model [ 18]. Moreover, as a demonstration of its language prowess, OpenAI declared that its LLM can pass the US bar exam in the legal profession with results in the ninetieth centile, compared with the 10th centile for the previous version of ChatGPT [ 19]. However, the technology remains limited in its accessibility, requiring users to pay a subscription fee and adhere to quantitative usage restrictions. While the achievements of this technology have been remarkable, the scientific community has expressed frustration due to OpenAI's lack of transparency regarding the training methods and data sources employed for the model, as well as the inner workings of GPT-4 beyond its user interface [ 20]. This new era of AI-driven revolutions has been defined by some authors as "the new AI gold rush" [ 21], emphasizing how all the most prominent players in IT are currently rushing to develop better and better models to beat the competition, in a freshly created fast-phased market.

These AI models' impact, especially ChatGPT's remarkable possibilities of use in the education sector, has led to a mix of emotions among educators [ 12]. This breakthrough in AI technology seems to be overhauling current educational norms, leading to debates. Some educators see ChatGPT and similar AI as a progressive step toward the future of education and research. In contrast, others are doubtful and view it as a potential danger, with a risk of leading to a decrease in educational activities and fostering laziness among teachers and students due to reduced analytical skills [ 22, 23]. Recently, as the topic has gained attention in the media, several scientific authors have attempted to evaluate possible possibilities and problems related to the advent of AI technologies in the sphere of education [ 11, 12, 23, 24, 25], and the UNESCO has also published a report attempting to discuss the main challenges and the emerging ethical implications of AI in higher education [ 26].

The Present Study

The research question of the present study is "What are the current opinions and evidence about the opportunities and the challenges represented by the development and implementation of AI systems in educational settings?" The stated research question is challenged with a narrative review article that analyzes the current research, opinions, and published literature on AI and ChatGPT (and, by extension, AI and LLMs) and the impact of these technologies in the educational sector. The existing literature was screened non systematically, searching for the keywords "ChatGPT AND education" and "AI AND education" in Google Scholar and Scopus for articles published after December 2022 until May 2023. Further articles were added using the snowball method, selecting articles perceived as particularly relevant starting points. The present article aims to build on recently published scientific works, explicitly targeting the discussion on how these advanced AI models can be used in education and especially in university settings.

2. AI and ChatGPT for Advancing Teaching and Learning Activities

The published scientific literature broadly suggests that AI technology possesses the potential to serve as a significant asset in education, occupying various roles that enrich both learning and pedagogical experiences. Authors have suggested that AI technology is an instrumental tool in essay grading [ 27, 28], although the value and the efficacy of these AI-based grading tools remain largely unclear within the confines of the existing scientific literature. The literature has reported that ChatGPT exhibits the potential to automatize and improve the grading system and has suggested that ChatGPT could be utilized to semi automate the grading process for students' work by discerning both the strengths and weaknesses within a given task in a broad spectrum of assignments, including research articles, academic essays, and other forms of written coursework [ 29]. In this context, educators can adapt the reports generated by such a model to deliver beneficial feedback to students, whether in formative or summative assessment scenarios. Furthermore, with the assistance of ChatGPT, a more precise evaluation of a student's learning challenges, and progression can be ascertained. This can aid teachers in pinpointing the areas where learners encounter difficulties, allowing them to target interventions more effectively [ 29].

The deployment of AI for grading short answer responses in an online learning environment has been evidenced successfully in past studies [ 30, 31]. Furthermore, it has been argued that an AI-powered automatic grader (to be used to prepare an exam preparation) could potentially serve as a teaching aid for the students and help them achieve higher exam scores. Furthermore, AI graders may contribute to a more impartial grading process [ 30, 31]. However, it is worth considering that it is essential to study the importance of the grading explanation and transparency of the grading process that these systems are reporting to the students, which may be a pivotal aspect considering both ethical concerns related to the technology and its acceptability [ 30, 32].

Additionally, since AI systems rely on existing data from prior evaluations for training, they may be suited explicitly for assessing standardized tests, such as nationwide professional education examinations, where data from past tests are abundant and standardized assessment is a priority. However, these systems may be less competent when assessing individual university exams that often undergo annual format alterations and where past evaluation data might be limited.

Because of future AI support, teachers could potentially lessen their workloads, redirecting their primary focus towards crafting innovative lesson plans, engaging in professional development, and offering personalized coaching and mentorship to each student. All these activities are instrumental in enhancing students' learning performance for the skills and challenges of the future.

The potential of AI tools extends beyond grading and assessment; they can also be deployed for translating educational materials and fostering interactive and adaptive learning environments. Notably, generative models, such as GPT-4, exhibit substantial promise in these domains. GPT-4 has demonstrated high proficiency in translation tasks, surpassing previous solutions in terms of quality [ 9, 35, 36]. However, the novelty of this application is partially tempered due to the preexisting success of machine translation technologies, which have delivered satisfactory results in document translation already for several years [ 37, 38]. Although this is not an entirely new development, it underscores the continuous advancements and improvements in the AI field, specifically in the sphere of machine translation. Envisioning learning materials translated quickly and automatically into several different languages is nowadays a potential perspective in the short term. These improvements hold the potential to further enhance and revolutionize learning experiences by providing precise and efficient translations of educational content. This not only expands the accessibility of materials to a more diverse student population but also contributes to creating more responsive and adaptable learning environments.

The realm of individualized tutoring illustrates another dimension where AI demonstrates its great utility. The AI systems could adapt the instructional approach to accommodate each student's unique learning style and progress. This personalized guidance system has undergone successful testing across a variety of tutoring categories, such as medical training [ 39, 40]; for a review, see [ 41]), computer science [ 42], and mathematics [ 43]. Additionally, AI systems have seen successful deployments as tutors beyond the traditional academic disciplines, serving as personal mindset coaches [ 44]. In the context of Adaptive Learning-where education is tailored to accommodate individual learning styles and progress [ 45]-AI systems can play an instrumental role. It has been suggested [ 46] that AI can offer a bespoke pedagogical approach finely tuned to each student's specific abilities, interests, and requirements. Such attempts have been reported in the scientific literature, underlining the feasibility and potential of this approach in enhancing learning experiences [ 36, 47, 48]. Thus, the emergence of AI as a powerful enabler of personalized learning attests to the technology's transformative potential and underscores its capacity to redefine educational experiences. As technology continues to evolve, the integration of AI within education is expected to become more sophisticated and effective.

The advanced features offered by ChatGPT present compelling opportunities for educators to enhance pedagogical practices by conceiving and integrating interactive classroom activities. According to [ 49], with the support of ChatGPT, educators are empowered to devise innovative teaching techniques. A case in point is the adoption of the flipped classroom approach, where learning opportunities are not confined to the classroom but extend to remote environments, thus fostering an atmosphere of independent study among students.

3. Challenges and Threats Posed by ChatGPT in Education

While ChatGPT's potential is vast, some concerns regarding the accuracy of its generated content must be addressed. Topsakal and Topsakal (2022) [ 52] proposed using ChatGPT to generate raw dialogue materials for training course-specific chatbots. Upon verification of the content's accuracy, these materials could then be translated by ChatGPT into a format compatible with AI chatbots such as Google Dialogflow, thus providing students with a personalized and interactive learning environment.

While, as discussed earlier, AI tools may help lecturers to decrease their current workload and therefore promote more research and lifelong learning activities (e.g., to improve the overall quality of the teaching and to implement new teaching methods in the classroom), they could also lead to job cuts [ 53] or outsourcing to the machines of a large portion of paid employment [ 54].

The use of ChatGPT in education poses challenges related to its accuracy and reliability [ 13]. Because ChatGPT is trained on a large corpus of unpolished, raw data, it may not be objective and critical inaccuracies have been reported. The efficacy of generative models hinges on the quality and diversity of the data used in their training. If these training datasets encompass biases, these biases invariably seep into the model. Consider an illustrative scenario where a model is trained using a dataset predominantly composed of essays from students belonging to a specific demographic. This lack of diverse representation may compromise the model's ability to evaluate essays written by students outside of that demographic. The origin of these biases can be traced back to factors such as overreliance on research data sourced from affluent nations or the use of textbooks that fail to address a global perspective [ 55]. As evidenced by the work of Pavlik (2023) [ 56], ChatGPT is not familiar with crucial information relevant to evaluating media sources' quality and eventual biases. It has also been found that, in some cases, the information delivered by ChatGPT may be biased politically [ 57, 58]; as well on religion, race, gender, and fairness (for a review see [ 59]). However, these biases seem to have decreased in the latest version of the AI tool [ 60]. In addition, ChatGPT's knowledge is by now limited to data before 2021 [ 61, 62]. Taking into consideration the time required for AI systems to collect data and be updated, some level of delay between when the information is created (e.g., over the internet) and included in the model is also to be expected in the future (although this can be mitigated, e.g., by allowing the model to access information live on the internet, as in the implementation of ChatGPT into Bing or the recently released ChatGPT browsing beta). Therefore, its responses may not always be accurate or reliable, particularly for specialized subjects and recent events. Furthermore, ChatGPT may generate incorrect or even fabricated information, as often reported by both users and the scientific literature [ 13, 63, 64], and such issue can be problematic for students who rely on ChatGPT to inform their learning. However, the problems regarding the false information provided by AI models (often referred to as "AI Hallucinations," see [ 65]) are probably going to be mitigated in the future, and GPT4 already shows fewer of these hallucinations compared to the previous version of ChatGPT [ 66].

The complex issue of student plagiarism has become a significant worry within educational institutions due to the widespread use of AI writing tools. The rampant misuse of intellectual property without appropriate citation raises ethical concerns and undermines the academic integrity of the educational process. To combat this, plagiarism-detection applications routinely uncover plagiarized content in student submissions. These software solutions use various methods, from similarity checking to advanced linguistic pattern analysis, to identify plagiarized material (for an in-depth analysis of these tools and their application, refer to [ 67]).

This challenge is expected to escalate further as advancements in AI technology accelerate at an unprecedented rate. As artificial intelligence continues to evolve and improve, the capabilities of next-generation models are likely to increase correspondingly, making detecting AI-generated content even more intricate. The emerging sophistication of these models will require developing even more advanced detection tools capable of distinguishing between human-written and AI-generated text. The ongoing arms race between plagiarism detectors and AI technology underlines the importance of cultivating academic honesty and reinforcing the value of original work within educational settings.

Further heightening the problem, it has been revealed that students utilizing ChatGPT for their assignments are more likely to engage in plagiaristic behavior than their counterparts who do not use the tool [ 69]. The ease with which ChatGPT can produce relatively good-quality text can incentivize students to employ it as a shortcut, thereby contributing to a culture of academic dishonesty. This may compromise the academic integrity of institutions and challenge the fundamental objective of assessments, which is to gauge and reflect student learning accurately and equitably. However, it is worth noting that students may want to use AI tools such as ChatGPT not to cheat on an assessment but as a learning tool to learn how to write better essays. Furthermore, they may use the tool to improve the text they have previously written without external aids. For such cases, guidelines and regulations from national authorities are still unclear, and future efforts should be put into establishing what is to be considered a "fair use" of AI tools. A case-by-case evaluation might be more accurate and informative rather than automatically presuming that students use these AI tools to cheat on their academic tasks. One could argue that many students turn to these LLMs not for academic dishonesty but as a platform to acquire better skills and improve their grades. In the rapidly evolving educational landscape where technology has become deeply integrated, students continuously seek efficient methods to enhance their learning outcomes. Furthermore, students might be utilizing AI tools to observe how ideas can be expressed differently or to understand how to structure their thoughts coherently.

A notable consequence of ChatGPT's misuse is creating an unfair academic playing field. Students who use ChatGPT to generate unique content could gain an unfair advantage over their peers who do not have access to it or choose not to use it due to ethical considerations [ 70]. This disparity can skew grades and academic recognition, undermining the value of hard work and personal effort. Furthermore, there are potential future implications for students unaware of the full capabilities of AI tools like ChatGPT. Such students might inadvertently misuse the tool, leading to unintentional plagiarism. This highlights the need for comprehensive education on the ethical use of AI in academic settings.

Perhaps the most alarming aspect of this issue is the impact on educators' ability to evaluate student performance accurately. When students use AI tools, it becomes challenging for instructors to discern the student's proper understanding and mastery of the learning material. This can mask learning deficiencies, making it difficult for educators to provide targeted feedback and develop necessary intervention strategies. Consequently, the educational process becomes less effective, and the true purpose of teaching and learning is compromised.

Generative models like ChatGPT, while demonstrating remarkable capabilities in text generation, do fall short in certain vital aspects when compared to human teachers or tutors. One such area is the lack of humanlike interaction, empathy, and emotional intelligence in these models, which are often crucial in a learning environment [ 71]. Human teachers can understand and respond to students' emotional states, which can significantly impact a student's motivation and learning outcomes. The absence of this nuanced interaction in AI models can disadvantage students who thrive in unique, empathetic learning environments.

Studies have demonstrated that virtual tutors equipped with features enabling a higher level of empathy led to improved learning outcomes compared to tutors lacking such features [ 72]. This suggests that future AI tutoring systems must exhibit humanlike behavior, including imitating human empathy, to be effectively utilized in teaching tasks.

Generative models, like ChatGPT, only rely on statistical patterns learned from the data they were trained on [ 73, 74]. As a result, these models lack a genuine understanding of the concepts they are helping students to learn. Such limitations can hinder their ability to provide explanations or feedback tailored to students' unique needs or misconceptions. Such tailored feedback is critical to practical education, allowing educators to directly address and correct students' misunderstandings.

Generative models operate by mimicking patterns observed in the data they were trained on, which traditionally placed limitations on the originality and creativity of their output. However, a recent shift in the AI landscape has seen the development of models demonstrating behaviors that resemble human creativity [ 75, 76]. Moreover, emerging research indicates that AI has begun to transcend mere emulation of existing artistic styles and has started demonstrating genuinely creative artistic capabilities [ 77, 78, 79, 80]. AI tools have been shown to be able to reproduce the styles of iconic artists [ 81] as well as propose unique and novel artistic expressions [ 82]. AI's creative reach is not confined to one medium but has spread across various artistic domains, such as music composition [ 83] and poetry writing [ 84]. AI-created work has become so sophisticated that it often poses a challenge to differentiate it from human-created counterparts [ 84, 85]. Furthermore, blind evaluations have revealed that AI-generated artwork can garner high artistic appreciation and value [ 86]. Therefore, due to its design, the lack of genuine creativity in AI has been shown to imitate human creativity to a higher degree already at the current state of the technology. However, how well such creativity could be adapted and implemented in teaching has yet to be comprehensively investigated.

4. Possible Actions and Mitigation Strategies in Response to the Impact of ChatGPT

The urgent need to address the impact of ChatGPT on the educational sector cannot be overstated, and the need for immediate action has been proposed [ 88]. There is a pressing demand to adapt assessment practices and institutional protocols to manage the issues brought to the fore by the proliferation of AI-generated content in academic work [ 89]. Before the rollout of GPT-4 in March 2023, educators could carefully alter their exam designs by introducing multimedia resources (e.g., images and charts) to mitigate the possibility of the assignments being performed entirely by AI, as ChatGPT 3.5 was not able to process visual or video content, thereby forming a challenge to students who attempted to utilize it to cheat [ 13, 90, 91]. However, this has changed with the latest iteration of the technology (GPT-4), as the AI system is now designed to process visual inputs as well (the developers have announced such a feature, but it was still not implemented for regular users as of 28 May 2023; https://openai.com/product/gpt-4, accessed on 28 May 2023). This necessitates the exploration of alternate strategies by educators involving the integration of digital-free components into their evaluation tasks, for instance, oral presentations, interviews, and written exams performed without the use of digital aids [ 49, 87, 88, 92]. Such nondigital components of an evaluation will require students to demonstrate their competencies live and directly without external tools. At the broader institutional level, there is a call for AI-based plagiarism detection tools to be provided to educators, and definitive guidelines need to be put forth on the acceptable use of ChatGPT in the academic setting.

Investing in training educators and informing students may be a strategy, given the actual state of things, for managing the implications of ChatGPT [ 93]. A critical area of focus is equipping instructors with the ability to discern the use of ChatGPT in student work, a skill that can be developed with the help of AI detection tools. However, even training educators to recognize AI-generated content may be impossible. AI tools are improving at imitating human writing styles, and they will probably soon generate text that is totally indistinguishable from human writing. Therefore, such mitigation strategies may become quickly obsolete. Addressing this complex issue may require a multifaceted approach, incorporating improved plagiarism detection tools, enhanced education around academic integrity, and perhaps reconsidering assessment methods to ensure fairness and accuracy in evaluating student learning.

On the other hand, educators should be educated in how to maximize the potential of ChatGPT in lesson preparation and evaluation [ 29, 88], and students should be enlightened about the inherent limitations of ChatGPT [ 94, 95], including its dependency on partial data [ 96], its circumscribed access to current knowledge [ 97], and its propensity to generate misleading or false information [ 63]. Consequently, educators should guide students to confirm the reliability of the information sourced from ChatGPT with reliable, authoritative references like textbooks and scientific articles [ 23, 98]. More emphasis should also be placed on informing students about the university's academic integrity policies and the repercussions of academic malpractice [ 99, 100]. To achieve this, educators should proactively engage students in discussions about ChatGPT and underscore the significance of academic honesty in their courses.

Despite its limitations, AI tutoring systems can still be valuable educational tools. For instance, it has been suggested that these systems could assist educators by identifying areas where students struggle, thereby helping educators to target their instruction better [ 95]. Despite their current shortcomings, the potential of AI systems to enhance education is significant, provided they are used in a manner that complements, rather than replaces, human educators.

5. Pioneering the AI Evolution in Education: Adapting, Advancing, and Innovating

Artificial intelligence, with its transformative potential, will substantially influence modern education. This is especially evident in the case of generative models like ChatGPT, which could quickly become widespread among the general population. Even though there exist various debates surrounding its application and certain technological limitations, the foothold of AI in the educational sphere is here to stay, and it could quickly push extensive transformations of our teaching and learning methodologies [ 101].

At the heart of the ongoing discourse around AI in education is the concern for its potential misuse, particularly in academic assignments. Many have proposed severe measures, such as a complete ban on AI tools like ChatGPT in school and university environments [ 102]. This approach has been criticized as it may disadvantage students in schools where these tools are forbidden compared to students attending schools where they are allowed [ 103]. Concurrently, there is a push for developing and utilizing technologies capable of discerning AI-produced content [ 104, 105]. However, an arms race between ChatGPT and detector software could be expensive and ineffective [ 68], and these preventive measures might offer a temporary respite at best. The relentless advancement in AI technology, as evidenced by the evolution of the Open AI ChatGPT model, presents a challenge to the effectiveness of these safeguards.

At the moment, it seems more practical to accept and integrate these technological tools into our educational structures [ 3, 109] instead of trying to hopelessly suppress their growth, which could do more harm than good to the students, according to several journalist reports (see, e.g., [ 110]). It has also been noted that banning ChatGPT use for students should be considered equal to banning calculators in math class [ 111] or banning Google [ 112]. With giants like Microsoft planning to incorporate ChatGPT across their product range [ 21, 113], it is only a matter of time before AI tools become a commonplace fixture in our lives. When this transformation comes to fruition, educational institutions might face considerable challenges in retrospectively implementing policies that foster the safe and effective use of AI tools like ChatGPT.

The development of AI also brings forth the question of rethinking assessment strategies in education. While it is premature to draw concrete conclusions, it is clear that the current assessment methods might need an overhaul to keep pace with AI's influence. Existing research illustrates that many educators struggle to design effective assessment practices that promote learning [ 114, 115]. Therefore, there is a critical need for professional development in this area, enabling teachers to harness the capabilities of AI tools like ChatGPT to enhance learning outcomes.

As artificial intelligence becomes increasingly embedded in the professional realm following a university education, preparing students with the requisite skills to thrive in an AI-dominated future is essential. To this end, integrating AI applications, such as ChatGPT, in educational settings can be a significant step. By offering students a hands-on experience with these tools, we can foster their understanding and application meaningfully while outlining their limitations and keeping pace with technological advances.

Negotiating the swift transformations prompted by AI involves navigating several intricate dimensions. Foremost among these is ascertaining effective strategies to employ ChatGPT and analogous AI tools to enrich educational experiences and designing customized training modules that accommodate both teachers and students, aiming to maximize the benefits of AI tools in amplifying teaching and learning. Furthermore, incorporating these AI tools within teacher training programs can equip the next generation of educators with the knowledge and skills to utilize these technologies optimally in their classrooms. It is plausible that in the future, students without training in AI tools could find themselves at a competitive disadvantage in the job market compared to their peers with extensive exposure and practical experience with these tools. Therefore, it becomes paramount to promptly establish an educational framework that both employs and scrutinizes these tools for the benefit of students.

Beyond the confines of the classroom, it is crucial to confront and address the potential impact of AI on the digital divide. AI tools could either narrow this chasm by facilitating universal access to learning resources or intensify the divide by disproportionately benefiting those with superior access to technology. We need a cooperative, cross-disciplinary approach to navigate these potential challenges and capitalize on AI's opportunities. Forming a mutually beneficial alliance between policymakers, researchers, educators, and technology experts-including private companies developing AI tools-can be pivotal in steering the future of education. The collective endeavor of these groups is crucial in guaranteeing the secure and productive deployment of continually evolving AI tools. This collaboration can foster innovative pedagogical strategies, improve students' learning outcomes, and create a well-prepared educational system to meet future demands in the job market.

AMA Style

Grassini S. Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences. 2023; 13(7):692. https://doi.org/10.3390/educsci13070692

Chicago/Turabian Style

Grassini, Simone. 2023. "Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings" Education Sciences 13, no. 7: 692. https://doi.org/10.3390/educsci13070692

# data[].attributes.attachment_link.title
Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings

# data[].attributes.attachment_link.description
Over the last decade, technological advancements, especially artificial intelligence (AI), have significantly transformed educational practices. Recently, the development and adoption of Generative Pre-trained Transformers (GPT), particularly OpenAI's ChatGPT, has sparked considerable interest. The unprecedented capabilities of these models, such as generating humanlike text and facilitating automated conversations, have broad implications in various sectors, including education and health.

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Koltay, T. (2015). Data literacy: in search of a name and identity. Journal of Documentation, vol. 71, no. 2, Bingley: Emerald Group Publishing, pp.401–415.

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Koltay, T. (2015). Data literacy: in search of a name and identity. Journal of Documentation, vol. 71, no. 2, Bingley: Emerald Group Publishing, pp.401–415.

# data[].attributes.body
This source is an article published in an information sciences journal in 2014 which was recommended by ChatGPT during my search. It explores the importance of data in the modern world as well as the recent massive growth in data production. It compares data literacy, the ability to create and understand data, with information literacy, the ability to locate and recognise the need for data, defining the two and the relationships between them. It concludes that data literacy is constantly evolving and emphasises the role of librarians in aiding the public with keeping up. Additionally, the author concludes that data literacy is something people learn holistically throughout their education, rather than being specifically taught it. This source does discuss data literacy within education but makes no mention of artificial intelligence and if therefore useful for background reading but is not specific enough to my topic to be a key source.

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Abstract

Purpose

The role of data literacy is discussed in the light of such activities as data a quality, data management, data curation, and data citation. The differing terms and their relationship to the most important literacies are examined. The paper aims to discuss these issues.

Design/methodology/approach

By stressing the importance of data literacy in fulfilling the mission of the contemporary academic library, the paper centres on information literacy, while the characteristics of other relevant literacies are also examined. The content of data literacy education is explained in the context of data-related activities.

Findings

It can be concluded that there is a need for data literacy and it is advantageous to have a unified terminology. Data literacy can be offered both to researchers, who need to become data literate science workers and have the goal to educate data management professionals. Several lists of competencies contain important skills and abilities, many of them indicating the close relationship between data literacy and information literacy. It is vital to take a critical stance on hopes and fears, related to the promises of widespread ability of (big) data.

Originality/value

The paper intends to be an add-on to the body of knowledge about information literacy and other literacies in the light of research data and data literacy.

Citation

Koltay, T. (2015), "Data literacy: in search of a name and identity", Journal of Documentation, Vol. 71 No. 2, pp. 401-415. https://doi.org/10.1108/JD-02-2014-0026

Publisher
:
Emerald Group Publishing Limited

Copyright

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Data literacy: in search of a name and identity

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Data literacy: in search of a name and identity - Author: Tibor Koltay

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Lozano, A. and Carolina Blanco Fontao (2023). Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers. Education Sciences, vol. 13, no. 7, Basel: MDP, pp.733–733

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Lozano, A. and Carolina Blanco Fontao (2023). Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers. Education Sciences, vol. 13, no. 7, Basel: MDP, pp.733–733

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This source is an article from an education science journal published in 2023, which I found on Google scholar. Its purpose is to assess the knowledge level of ChatGPT and evaluate the opinion of education students, both as current students and future teachers. It concluded that students see AI as helpful, not as a threat so long as the sources it learns from are verified. The source goes on to examine some opportunities and challenges of AI in education. Benefits, like helping special education teachers create student-specific resources, are weighed against threats, like students generating homework rather than completing it and losing a learning opportunity in the process. The conclusion was that artificial intelligence is faster than a human worker but not as accurate or in depth. The opinion of people so closely linked to education as well as the detailed analysis of the limitations of AI makes this a very valuable source.

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Department of Mining, Topography and Structures, University of Leon, 24007 León, Spain

Vice Rectorate of Research, University of Barcelona, Gran Vía de les Corts Catalanes, 585, 08007 Barcelona, Spain

Department of General and Specific Didactics and Theory of Education, University of Leon, 24007 León, Spain

Author to whom correspondence should be addressed.

1. Introduction

Nowadays, society is undergoing unprecedented technological development in many areas (e.g., industrial, economic, social, and educational), which implies a continuous and strong adaptation to new technologies. In particular, artificial intelligence (AI) has undergone significant development in recent years.

Despite its current explosion, AI has its origins in the mid-20th century. The first AI that was publicly released was released in 1957 by American researchers, when the development of this discipline began at Dartmouth University [ 1]. This event gave rise to other AI areas of research and knowledge, such as machine learning, deep learning, neural networks, and data management (big data). Since then, different AI technologies have been evolving throughout the 20th century until the beginning of the 21st century, when they have had a much more accentuated development [ 2]. The development of AI in recent years has led to applications in different fields of work, such as healthcare [ 3] or sustainable industry development [ 4]. Another field that is being strongly affected is education [ 5]. There is so much interaction between AI and education that three main areas of linkage between the two have been defined [ 6]: (1) the use of AI as a learning tool in the classroom, (2) learning how to use AI and its technologies; and (3) digital literacy of the citizenship to reach an ethical and technical criterion in the use of AI. This has implied that society identifies different definitions or conceptions of this technology. In this way, some authors refer to AI as a personalized and automated orientation of information management [ 7], but most define it as a computer system that can engage in human-like processes such as learning, adaptation, synthesis, self-correction, among others, [ 8] and thus generate the feeling as interacting with another person [ 9, 10].

The increasing use of AI in education has boosted research on its impact in different areas and fields of study, with the common goal of improving the teaching-learning process. [ 5]. These fields include robotics [ 11], e-learning environments [ 12], virtual reality (VR) [ 13], online self-learning platforms [ 14], and intelligible conversational software agents, generally known as chatbots [ 15] or text or content generators [ 16].

Among these application areas, the use of chatbots is the discussion subject in classrooms nowadays, especially since ChatGPT 3.5 was released publicly for worldwide use in November 2022. ChatGPT, created by OpenAI, is an artificial intelligence tool based on the Generative Pre-trained Transformer (GPT) language model that is used to create responses similar to those of a human interacting with it (OpenAI). The controversy generated in the education sector is due to the fact that although it offers great benefits to the teaching and learning praxis, it can also have detrimental consequences for teaching-learning processes and skills and competencies development [ 17].

One of the most important advantages of the AI (especially ChatGPT) outbreak in education is its great potential for communicative use between teachers and students. It can be used as a tool that provides innovative methodologies and improves teaching-learning processes and hence increases student performance [ 14]. Other examples of its many beneficial applications include the role of AI in special education due to the ability to personalize learning in real-time [ 18], the ability to adapt and individualize learning [ 19], the increase in teacher-driver interaction in the development of the teaching-learning process from the classroom [ 20], and the development of intelligent tutoring systems [ 21, 22]. Additionally, the use of AI has had a positive impact on academic performance, especially on increasing motivation and improving the teaching-learning process [ 23]. Likewise, AI is presented as an opportunity for teachers with respect to the creation of content, activities, and assessments [ 24].

However, weaknesses are also being identified in contrast to the positive aspects of the use of AI. ChatGPT may pose a threat for education. For example, the teachers' request for a written text by students is doomed to disappear. This is because such texts can be totally generated by ChatGPT instead of students. A consequence of this is the increase in plagiarism by students, which is considerably difficult to detect and a time-consuming activity for teachers [ 17, 25]. Additionally, these problems can be aggravated by the generation of incorrect information. ChatGPT generates answers based on the stored data with which it has been trained, but it is not able to understand what writes or makes complex reasoning of specific and especially technical topics, as has been demonstrated in a case study in the health field [ 26]. This would lead to a devaluation of the quality of the educational system, since it implies a setback in the teaching-learning processes, without taking into account the destruction of the commitments to honesty and authenticity from the point of view of the students' work [ 27]. All of this makes the ChatGPT implementation process around the world an educational challenge and, despite the continuous up-to-date studies, it requires further analysis from educational research [ 23].

These facts predict that in the coming years, there will be a substantial change in the educational model, especially in teaching methodologies, so that some tasks such as the current written work and evaluations will have to be rethought. Since the paradigm shift in education affects all levels and participants, as a first step towards adapting to these changes, it seems essential to know the perceptions of this type of AI-based technology from a dual perspective: students and teachers, in order to subsequently study the implications which may impact the educational system.

Thus, the general objective of this work is to assess the perception of Primary Education students at the University of León regarding the possibilities of using ChatGPT in education from the double vision that these students can offer, as current students and future teachers. For this purpose, the following specific objectives are established:

Objective 1: Study the level of previous knowledge and use of ChatGPT by the students.

Objective 2: Evaluate the perception of the application by students.

Objective 3: Evaluate the perception of the application as future teachers.

2. Materials and Methods

2.1. Participants and Sample

The target population was 118 second-year students of the Primary Education Degree who were taking the subject Teaching and Learning of Experimental Sciences I during the 2022/23 academic year. Primary Education students were selected because they can provide information from a double perspective: as current students and as future teachers. Previously to conducting this research, the students answered some questions about their previous knowledge of ChatGPT through a Google form, with the intention of detecting their previous knowledge and use of it before use in the classroom (corresponding with Block 2 and explained with more detail in Section 2.2). After answering that, the participants in this study carried out a classroom activity in which they used the ChatGPT tool. The students were asked to use ChatGPT to establish a conversation with scientists of great historical significance to ask them about their discoveries, as well as their perceptions of the social context in which they lived and developed their findings. After that, students had to subsequently evaluate the degree of veracity of the information received and contrast it with other sources by giving an oral presentation in the classroom.

The study consisted of a sample of 81 students from the Primary Education Degree, who carried out the activity with ChatGPT and represented 68% of the initial study population. The sample showed a mean age of 19.7 ± 1.3, with 73% girls, 26% boys, and 1% non-binary.

2.2. Study Instrument: Characteristics and Application

In order to carry out this study, a non-experimental, descriptive, cross-sectional, and quantitative research design was carried out through the elaboration of a questionnaire that was answered by the 81 second-year students from the Primary Education Degree.

The questionnaire was divided into 4 blocks ( Appendix A Table A1). The first block was composed of demographic questions, with the first two questions identifying the gender and age of the participants, respectively. Block 2 consisted of two questions to study the participants' knowledge prior to the use of the application (this block was administered to students prior to the start of the activity). Block 3 dealt with the study of the students' perceptions of ChatGPT access and use, as well as the identification of possible advantages and disadvantages for its use. This block consisted of ten questions with a 5-point Likert scale, in which value 1 corresponded to totally disagree, 2 to disagree, 3 to neutral, 4 to agree, and 5 to totally agree. In addition, this block was completed with 2 multiple-choice questions. Block 4 dealt with the students' perceptions of the use of ChatGPT as future teachers and consisted of seven questions with a 5-point Likert scale, similar to what has been previously described. Questions in Blocks 3 and 4 were divided into three categories: A: Access and use of the application; B: Sources and quality of the information obtained; and C: Knowledge of how the tool operates, in order to study the perception of these aspects from a dual perspective: students and teachers (these two last blocks of the questionnaire were answered by the students two months after having carried out the activity so that they could have a broader vision of ChatGPT and AI).

For the drafting of the questionnaire items, we initially brainstormed with a group of 10 experts in different fields of education. Thus, an initial draft was prepared with different questions that tried to correspond to the categories we wanted to analyze. After that, the questionnaire was validated through the Delphi method [ 28, 29, 30], in which the panel of experts assessed the relevance, pertinence, and univocity of each question in two rounds. In the first round, modifications were proposed when questions did not fit the criteria cited in the first round. In the second round, an exclusion criterion was established based on the discordance of criteria of two or more experts (the total number of initial questions was 25 and the final number was 18, as shown in Table A1). The literature confirms the effectiveness of the Delphi method for the construction and validation of instruments, mainly in the field of Educational Sciences [ 31, 32], which positions it as an ideal method for the study presented here.

To check the reliability of the instrument, Cronbach's alpha was calculated, which was 0.801, so its confidence level is considered very good [ 33].

It should be noted that the questionnaire of perceptions was administered to the students two months after the activity was carried out. Therefore, students who were not familiarized with it at the beginning were able to familiarize themselves with it to a greater extent and become more aware of the possibilities of ChatGPT.

2.3. Statistical Analysis

Data collected from the questionnaire were processed with version 26 of the SPSS (IBM) computer software, first implementing descriptive statistics by calculating response percentages and then applying the calculation of relative frequencies (%) to each question of the blocks into which the questionnaire is divided. For the multi-response questions, the relative frequencies were calculated considering the total number of responses to each item.

3. Results

3.1. Prior Knowledge about ChatGPT

The results obtained for Block 2 of the questionnaire about previous knowledge of ChatGPT indicate a great lack of knowledge of the tool by the students of the the Primary Education Degree. Thus, the majority of the students (76%) stated that they did not know ChatGPT from previous use through the activity carried out in the classroom, as described above. However, 14% of the students affirmed they knew about it, but they had not used it to perform tasks or search for information. Only 10% said that they knew about it and had used it previously to perform tasks in other subjects of the degree.

3.2. Perception of ChatGPT Use among Students

The results of the students' perception of the use of ChatGPT correspond to Block 3 of the questionnaire and have been divided into three categories: (A) Perception of access and use ( Table 1), (B) Source and quality of the information provided, and (C) Knowledge of how the tool operates ( Table 2).

With respect to the questions of category A, Access and use, all of the answers in this block have a majority of response percentages corresponding to Likert scale points 4 and 5, which means that the students agree or strongly agree with the aspects related to the use of ChatGPT ( Table 1). Thus, adding together the percentage of results for points 4 and 5 of the Likert scale (agree and strongly agree), it can be said that 87% of the students consider ChatGPT a tool that is easy to access and use (question 1), 77% of the students think that its use can save time in the tasks compared to other digital resources or books (question 2), and it allows the completion of tasks in a personalized way (85% of students, question 3). As a consequence, it is noteworthy that 95% of the students surveyed say that they were surprised by its potential for use (question 4).

The analysis of category A, Access and use, was completed with two multi-response questions intended to identify the major benefits and drawbacks of ChatGPT use by students. The responses obtained are shown in Figure 1. The most beneficial aspects of using ChatGPT (question 5) identified by students are the speed in completing tasks (a) and the generation of support material (b), both accounting for 71.7% of the total responses ( Figure 1A). The least benefits identified are the use of ChatGPT to check their learning, and as a tutor or virtual support (c and d, both related). In contrast, the main disadvantages associated with the use of ChatGPT (question 6) identified by the students are the lower capacity to search for information (a), critical analysis (b), and the greater capacity for plagiarism (d), being 74.3% of the total number of responses ( Figure 1 B). In this case, the disadvantages least detected are the least capacity for synthesis (c) and the greatest difficulty in defending a work in the classroom.

Regarding questions in category B, Sources and quality of information ( Table 2), only 36% of the students claim to have asked ChatGPT to generate information references used to do the work in class (question 7), while 57% of the students agreed or strongly agreed that references used from ChatGPT were reliable (question 8). In addition, 42% of the students considered the quality of the work completed comparable to what they normally accomplish with other resources such as textbooks or online resources (question 9).

Finally, with respect to the questions in category C, Knowledge of how the tool operates ( Table 2), it stands out that almost all the students (94%) are aware of the necessity to understand the completed work (question 10), but only 54% think that they understand how it generates the tasks (question 11).

3.3. Perception of ChatGPT Use as Future Teachers

Results obtained about the perception of ChatGPT use as future teachers correspond to Block 4 of the questionnaire and are shown in Table 3, where the three previously mentioned categories of the study (A, B, and C) have been included. Thus, the results are described in the same way as for Block 3, presenting the sum of the percentages of items 4 and 5 of the Likert scale.

With respect to the questions in category A, Access and use, only 36% of the students believe that ChatGPT will pose a threat to their future teaching practice, while 41% of them disagree and 28% are neutral, which shows the variety of opinions on this aspect (question 12). In contrast, 71% of the students affirm that it can be a useful tool for their future teaching work (question 13) and 78% of them consider that it will force them to change their approach to the tasks asked of students (question 14).

Regarding category B, Sources and quality of information, 81% of the total number of students consider that, as teachers, they could generate high-quality content with ChatGPT, as long as the sources are corroborated (question 15). Given this result, it seems coherent that only 33% of the students consider that ChatGPT could lead to the devaluation of the quality of the educational system when they work as teachers (question 16), although there is a disparity in the results, with 36% of the students expressing neutral opinions and 27% disagreeing.

To conclude this block with questions in category C, Knowledge of how the tool operates, it should be noted that 96% of the future teachers consider it necessary to know the new artificial intelligence tools in order to better prepare and evaluate the tasks so that the students reach the desired competencies (question 17). In addition, 94% of future teachers consider it necessary to have knowledge of the basic operation of artificial intelligence in order to better understand how students can use it properly in their tasks (question 18).

4. Discussion

The results of Block 2 of the questionnaire show that the students' prior knowledge of ChatGPT (Objective 1) was generally very low. This significant lack of knowledge in the students is striking since new AI applications (such as ChatGPT) have been mediatized, occupying numerous national and international news. However, one possible explanation is that the use of ChatGPT was not initially oriented towards education. Despite this, the level of prior knowledge of ChatGPT has been much higher in students studying other university degrees such as Business degrees, reaching 80% [ 34], which could be due to the higher affinity of this type of degree with technology in comparison with the Primary Education Degree.

The results of Block 3 of the questionnaire show that from the students' point of view (Objective 2), there is a positive perception of ChatGPT. With respect to access and use, the positive results are in agreement with other studies where it has been shown that the student perceives greater ease of access and use of ChatGPT through different technological platforms such as computers, tablets, or cell phones, which increases accessibility to information [ 18]. Similarly, the personalization of tasks, which has been one of the prominent uses of this tool, is already widely considered in education [ 9, 17, 18]. The reasons for this are mainly the instant acquisition of information and its adaptation to the specific requirements requested. All of these reasons have led the students to be surprised by the high potential of this application.

Students have indicated the speed of the work and the time saved as the main advantages of using ChatGPT, which was similarly observed in previous studies [ 17, 18]. In contrast, one of the drawbacks identified by the students of using ChatGPT is its limitation for critical analysis. However, this drawback is contrary to what has been observed in previous studies. ChatGPT has difficulties with the generation of responses that require higher-order cognitive processes such as critical analysis [ 35, 36], which prevents it from generating text with deep and complex explanations. Fergus et al. [ 37] identified incorrect answers generated by ChatGPT to questions that involved actions such as "applying" or "interpreting" a given text. Therefore, and contrary to students' perception, it is considered necessary that students should use critical analysis skills to contrast the information and review the content and meaning of the text, regardless of the type of task given to ChatGPT.

Finally, students are of the opinion that ChatGPT generates good-quality texts and uses reliable sources, although they are aware that they should be critical and contrast the information. It should be noted in this aspect that previous studies have identified a lack of authorship of the sources/references [ 38] and the generation of biased data [ 17], problems that are of great concern in the educational community.

The results of Block 4 show that from the point of view of future teachers (Objective 3), there is a very positive perception of ChatGPT. Regarding its access and use, the teachers in training do not consider this tool as a threat. Instead, they have verified its potential for creating content with a carried-out activity in class. This is in accordance with the generation of teaching materials such as rubrics or activities to implement in the classroom and even questionnaires of a certain quality, as recognized by other authors [ 17, 27]. However, the generation of such content may be limited, especially if evaluation-type or critical analysis-type activities are required of ChatGPT, which can only provide limited responses as previously stated. Therefore, future teachers should critically evaluate the generated resources in order to adjust the content and context for the targeted learners [ 24].

The personalization of tasks is a great advantage from the teaching point of view, and ChatGPT can greatly facilitate this work. In this way, education is increasingly considering the Universal Design for Learning (UDL) in classrooms. This fact entails a huge amount of work for teachers, but the use of this type of application could greatly reduce the preparation time of tasks addressing the individual differences found in classrooms. Thus, ChatGPT can be presented as a great opportunity for education system improvement. Beyond the personalization of students' tasks, AI can also be used to generate personalized applications in education in a broader sense. In this way, they can be used to detect vocational interests in students and guide them in their studies or, in the case of people with disabilities, to generate methodological strategies to facilitate their learning [ 39], which allows an improvement in education from a holistic and integrative point of view.

Faced with the critical situation for teaching practice that may lead to a paradigm shift in education, future teachers have to be aware of the change they will have to make in terms of task design and evaluation criteria in order to avoid or detect plagiarism. One of the proposals to solve the problems caused by this new educational approach is teacher training to provide them with technological training in AI and in general, in order to provide the educational community with digital literacy, as evidenced in recent research in education [ 9, 17], especially at higher education levels [ 40].

Comparing categories between the perspectives of students and teachers, it can be observed that in the category of use and access, both are optimistic and consider that ChatGPT shows great potential for improving the education system, without being perceived as a threat to it. Regarding the quality of the information and sources, they were more skeptical. This perception can be considered a positive aspect since as it has been explained that data generated by ChatGPT require a contrast processing of information and critical analysis. Finally, regarding the knowledge of how ChatGPT operates, both consider that they do not deeply understand its operation and that they should be trained in it.

It should be noted that the use of ChatGPT will increase in all areas, including education, due to its potential, so it is essential to convey to students the limits that should not be exceeded with its use and the consequences this may have for the education system. In addition, it is necessary to address this topic in the classroom in order to analyze weaknesses in its use. The objective should be for students to improve their learning process so that they are able to critically analyze texts generated by ChatGPT.

From the point of view of the teacher, it is absolutely necessary to implement teacher training to increase and improve teaching knowledge, and hence to better identify fraud by the students. This aspect is of great importance nowadays and should be carried out urgently to avoid a deterioration of the system. Finally, it is urgent for all countries to establish legal and ethical limits on AI use in many areas of work, especially in education, which is the area that concerns us.

Study Limitations and Future Prospects

This study may present limitations in the sample size with which it has been carried out. However, the objective was to obtain information from a group of people who currently have a dual perspective on the subject of study because they are university students who are training to become future teachers. In addition, it has been carried out with students specialized in experimental sciences, due to the important connection between the educational and scientific fields and the veracity of the sources of information.

As future lines of research, it seems necessary to study the perceptions of active teachers, since their perceptions may be different from those of teachers in training due to different factors such as age or affinity for technology. It is also considered necessary to identify the needs in technological and specific literacy in the use of artificial intelligence since if teachers are aware of the potential of their uses, applications, and limitations, they will be able to teach them to their students so that they can make rational and ethical use of them. Finally, it would be interesting to extend the study to other educational levels such as secondary school or university teachers.

5. Conclusions

Data presented in this work can provide valid information to enable current and future teachers to respond to the influence of ChatGPT in the education field.

Related to objective 1 of the study, it could be observed that most of the students had never used ChatGPT before carrying out the activity in the classroom, a remarkable aspect since this technology has occupied an important space in the media due to its potential since its appearance.

After the activity was carried out using ChatGPT in a teacher-training classroom, the students envisioned the potential use and improvement of the teaching-learning process through ChatGPT due to its multiple applications for both students and teachers. The perception from the student's point of view is positive; however, nowadays there is great concern about the generation of incorrect data and great potential for plagiarism of the texts generated by this tool. To minimize the negative impact, or even reverse it, it is necessary to identify and explain to the educational community the consequences of plagiarism both in education and in professional development and real life. Therefore, students must be made aware of the ethical use of the tool, but teachers must also be trained to possess knowledge of artificial intelligence from various approaches to identify fraud by the students so that this type of tool does not have a negative impact on the education system.

These range from the functioning of artificial intelligence, the possibilities of using different tools such as ChatGPT in the classroom and for their own teaching efficiency, as well as updated information on how many advances or limitations these applications have in teaching use. All of this will provide adequate training with an ethical and critical sense to both current teachers and the students who will form the free societies of the future, who will become teachers at the end of their university careers.

Author Contributions

Conceptualization, A.L. and C.B.F.; methodology, A.L.; software, C.B.F.; validation, A.L. and C.B.F.; formal analysis, A.L. and C.B.F.; investigation, A.L. and C.B.F.; resources, A.L.; data curation, A.L.; writing-original draft preparation, A.L.; writing-review and editing, C.B.F.; visualization, A.L.; supervision, C.B.F.; project administration, C.B.F.; funding acquisition, C.B.F. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by Universidad de León. A. Lozano contract is funded by the Ministry of Universities and the European Union Next GenerationEU/PRTR.i and by the Recovery, Transformation and Resilience Plan.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is contained within the article. Additional data are available on request from corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Self-made and validated questionnaire (Google Forms application).

BLOCK 1. DEMOGRAPHIC DESCRIPTION OF PARTICIPANTS

BLOCK 2. PRIOR KNOWLEDGE ABOUT CHATGPT

BLOCK 3. STUDENTS PERCEPTION OF CHATGPT

Rate from 1 to 5 how much you agree with the following statements regarding the use of ChatGPT in class. 1: strongly disagree, 2: disagree, 3: neutral, 4: agree, 5: strongly agree.

MULTI-ANSWERS QUESTIONS:
Choose the options that you consider in the following questions.

5

What could be more beneficial from using ChatGPT as a student?

6

What could be the worst drawback from using ChatGPT as a student?

BLOCK 4. FUTURE TEACHERS' PERCEPTION OF CHATGPT

Rate from 1 to 5 how much you agree with the following statements regarding the use of ChatGPT in class. 1: strongly disagree, 2: disagree, 3: neutral, 4: agree, 5: strongly agree.

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Figure 1. Results on the perception of the benefits ( A) and drawbacks ( B) of the use of ChatGPT by students (Category ( A)).

Table 1. Block 3 of the questionnaire (first part): Perception of access and use. CAT. Categories. A. Access and use. Responses of Likert scale (1-5) in %.

Table 2. Block 3 of the questionnaire (second part). CAT. Categories: B. Sources and quality of the information and C. Knowledge of the tool. Responses of Likert scale (1-5) in %.

Table 3. Block 4 of the questionnaire: Perception of the use of ChatGPT from the point of view of teacher performance. CAT. Categories: A. Access and use, B. Sources and quality of information, C. Knowledge of the tool. Responses of Likert scale (1-5) in %.

Lozano A, Blanco Fontao C. Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers. Education Sciences. 2023; 13(7):733. https://doi.org/10.3390/educsci13070733

Chicago/Turabian Style

Lozano, Alba, and Carolina Blanco Fontao. 2023. "Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers" Education Sciences 13, no. 7: 733. https://doi.org/10.3390/educsci13070733

# data[].attributes.attachment_link.title
Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers

# data[].attributes.attachment_link.description
The recent irruption of ChatGPT, a powerful chatbot that uses a "Chat Generative Pretrained Transformer" language model, could revolutionize education worldwide since it can greatly affect the competence development that students need to achieve for their professional future.

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Macgilchrist, F., Allert, H. and Bruch, A. (2019). Students and society in the 2020s. Three future ‘histories’ of education and technology. Learning, Media and Technology, vol. 45, no. 1, London: Routledge, pp.1–14

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Macgilchrist, F., Allert, H. and Bruch, A. (2019). Students and society in the 2020s. Three future ‘histories’ of education and technology. Learning, Media and Technology, vol. 45, no. 1, London: Routledge, pp.1–14

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This source is an article published in 2019. Unlike many of my other sources, this source does not explain a research project but instead takes an almost science-fiction approach, exploring three possible futures for technology and the publics relationship with it. In the first scenario people’s dependence on technology allows corporations to streamline the education system into creating the perfect worker bees. In the second scenario the technical capabilities of individuals allow them to move their lives almost entirely online, becoming stateless and moving away from formalised education. In the third scenario a privacy crisis forces schools to use to open source software, teaching their students how to create the software as well as using it. The paper does explore several relevant topics with a focus on social changes resulting from technology, rather than on the technology itself. It is helpful in developing ideas about future opportunities and threats but it lacks any hard data.

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This source is an article published by a non-profit publisher focusing on the impact of technology on society. It was cited in the text for the eighth topic of this assessment’s module. The statistic cited was about Turnitin recognising the writing of students for whom English is not their first language as AI generated more often than students who are native English speakers. The article explains a study that was conducted at Stanford which found proof of this bias in other AI detection tools. It highlights the potential threat these mistakes could have to international students’ education even if they are proven not to have used AI to complete their work. This article is one of very few I managed to find in which the author had actually done their own research instead of repackaging the same fearmongering that many publications seem to prefer when reporting about AI.

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Machine Learning
Stanford study found AI detectors are biased against non-native English speakers By Tara García Mathewson

Taylor Hahn, who teaches at Johns Hopkins University, got an alert while grading a student paper this past spring for a communications course. He had uploaded the assignment to Turnitin, software used by over 16,000 academic institutions across the globe to spot plagiarized text and, since April, to flag AI-generated writing.

Turnitin labeled more than 90 percent of the student's paper as AI-generated. Hahn set up a Zoom meeting with the student and explained the finding, asking to see notes and other materials used to write the paper.

"This student, immediately, without prior notice that this was an AI concern, they showed me drafts, PDFs with highlighter over them," Hahn said. He was convinced Turnitin's tool had made a mistake.

In another case, Hahn worked directly with a student on an outline and drafts of a paper, only to have the majority of the submitted paper flagged by Turnitin as AI-generated.

Over the course of the spring semester, Hahn noticed a pattern of these false positives. Turnitin's tool was much more likely to flag international students' writing as AI-generated. As Hahn started to see this trend, a group of Stanford computer scientists designed an experiment to better understand the reliability of AI detectors on writing by non-native English speakers. They published a paper last month, finding a clear bias. While they didn't run their experiment with Turnitin, they found that seven other AI detectors flagged writing by non-native speakers as AI-generated 61 percent of the time. On about 20 percent of papers, that incorrect assessment was unanimous. Meanwhile, the detectors almost never made such mistakes when assessing the writing of native English speakers.

AI detectors tend to be programmed to flag writing as AI-generated when the word choice is predictable and the sentences are more simple. As it turns out, writing by non-native English speakers often fits this pattern, and therein lies the problem.

People typically have bigger vocabularies and a better grasp of complex grammar in their first languages. This means non-native English speakers tend to write more simply in English. So does ChatGPT. In fact, it mimics human writing by parsing everything it has ever processed and crafting sentences using the most common words and phrases. Even if AI detectors aren't specifically trained to flag less complex writing, the tools learn to do so by seeing over and over that AI-generated writing is less complex.

Weixin Liang, one of the authors of the Stanford study, learned Cantonese and Mandarin before English. He was skeptical about claims of near-perfect accuracy with AI detectors and wanted to look more closely at how they worked for students with linguistic backgrounds like his.

The design of many GPT detectors inherently discriminates against non-native authors, particularly those exhibiting restricted linguistic diversity and word choice.
Weixin Liang, co-author of Stanford study on AI misclassification

"The design of many GPT detectors inherently discriminates against non-native authors, particularly those exhibiting restricted linguistic diversity and word choice," Liang said via email.

After ChatGPT debuted in November of last year, many of the nation's nearly 950,000 international students across the country, like their peers, considered the implications. Educators were panicking about the prospect of students using generative AI to complete assignments. And international students, allowed to study here with education-specific visas, quickly realized their vulnerability in the arms race that sprang up between AI generators and detectors.

Hai Long Do, a rising junior at Miami University in Oxford, Ohio, said it's scary to think that the hours he spends researching, drafting, and revising his papers could be called into question because of unreliable AI detectors. To him, a native of Vietnam, biased detectors represent a threat to his grades, and therefore his merit scholarship.

"Much worse," Do said, "is that an AI flag can affect my reputation overall."

Some international students see additional risks. Colleges and universities routinely advise their international students that charges of academic misconduct can lead to a suspension or expulsion that would undermine their visa status. The threat of deportation can feel like a legitimate fear.

Shyam Sharma is an associate professor at Stony Brook University writing a book about the United States' approach to educating international students. He says universities routinely fail to support this subgroup on their campuses, and professors often don't understand their unique circumstances. Sharma sees the continued use of faulty AI detectors as an example of how institutions disregard the nation's international students.

"Because the victim, right here, is less important," Sharma said. "The victim here is less worthy of a second thought, or questioning the tool."

There have been educators, however, who have questioned the tool, discovering, like Hahn, the fallibility of AI detectors and noting the serious consequences of unfounded accusations. As campuses reopen for the fall semester, faculty must consider whether the latest research makes a clearer case for scrapping AI detectors altogether.

In Liang's paper, his team pointed out that false accusations of cheating can be detrimental to a student's academic career and psychological well-being. The accusations force students to prove their own innocence.

"Given the potential for mistrust and anxiety provoked by the deployment of GPT detectors, it raises questions about whether the negative impact on the learning environment outweighs the perceived benefits," they wrote.

If it's the AI picking up on our language patterns and automatically deciding, I don't know how I can prevent that.
Heewon Yang, NYU senior from South Korea

Diane Larryeu, a native of France, is studying at Cardozo School of Law this year in New York City. Last year, in a common law master's program near Paris, her friend's English essay was flagged as being AI-generated, she said. When asked if she was concerned the same might happen to her because, like her friend, English is her second language, her answer was direct: "Of course." All she can do is hope it can be resolved quickly. "I would just explain to my teacher and hope they understand," Larryeu said.

OpenAI shut down its AI detector at the end of July because of low accuracy, and Quill.org and CommonLit did the same with their AI Writing Check, saying generative AI tools are too sophisticated for detection. Turnitin, however, has only doubled down on its claims of high accuracy.

Annie Chechitelli, chief product officer for Turnitin, said the company's tool was trained on writing by English speakers in the U.S. and abroad as well as multilingual students, so shouldn't have the bias Liang's paper identified. The company is conducting its own research into whether the tool is less accurate when assessing the writing of non-native English speakers. While that research hasn't been published yet, Chechitelli said so far it looks like the answer is no.

David Adamson, an AI scientist at Turnitin, shows Turnitin's AI writing-detection capabilities in a video demonstration. Twenty-four out of 24 sentences from this sample essay are flagged to come from ChatGPT.

Still, she admitted the tool ends up learning that more complex writing is more likely to be human, given the patterns across training essays.

Heewon Yang, a rising senior at New York University and a native of South Korea, is frustrated by AI detectors and her vulnerability to them. "If it's the AI picking up on our language patterns and automatically deciding, I don't know how I can prevent that," she said.

That's why Liang said he is skeptical Turnitin's detector can avoid the biases his team identified in their paper.

"While Turnitin's approach seems well-intentioned," he said by email, "it's vital to see the results of their ongoing tests and any third-party evaluations to form a comprehensive understanding of their tool's performance in real-world scenarios."

In June, Turnitin updated its software to allow institutions to disable the AI writing indicator, so even though the software will continue to assess the writing for AI, its conclusion won't be displayed for instructors. As of the end of July, only two percent of Turnitin customer institutions had taken advantage of that option, according to the company.

The University of Pittsburgh was one. In a note to faculty at the end of June, the university's teaching center said it didn't support the use of any AI detectors, citing the fact that false positives "carry the risk of loss of student trust, confidence and motivation, bad publicity, and potential legal sanctions."

While the experience of international students wasn't at the center of their decision-making, John Radziłowicz, interim director of teaching support at the University of Pittsburgh, said his team tested a handful of available AI detectors and decided false positives were too common to justify their use. He knows faculty are overwhelmed with the idea of students using AI to cheat, but said he has been encouraging them to focus on the potential benefits of AI instead.

"We think that the focus on cheating and plagiarism is a little exaggerated and hyperbolic," Radziłowicz said. In his view, using AI detectors as a countermeasure creates too much potential to do harm.

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AI Detection Tools Falsely Accuse International Students of Cheating - The Markup

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Stanford study found AI detectors are biased against non-native English speakers

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Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D.E., Thierry-Aguilera, R. and Gerardou, F.S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences,  vol. 13, no. 9, Basel: MDP, p.856

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Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D.E., Thierry-Aguilera, R. and Gerardou, F.S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences,  vol. 13, no. 9, Basel: MDP, p.856

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This source is an article from 2023. It explores the opportunities and threats of artificial intelligence in higher education and ways to counteract the threat, according to ChatGPT. The researchers ‘interviewed’ the AI with a series of carefully chosen questions. They asked about challenges, opportunities, barriers and how to overcome them, how to get the most from AI and current policy on banning AI in higher learning institutions. The points that the AI are the same points which have been raised in the other articles I have read with no additional depth. After reporting the AIs response, the authors went on to analyse the response and concluded that understanding AI on a deeper level, more than just how it works and how to use it, but it’s actual ‘though process’ was key in using it to its fullest potential. The source doesn’t provide any new information but does give a new perspective, that of the AI itself.

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Sustainability Research Institute, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK

Community Resilience and Sustainability Lab (CoRSEL), Aston Business School, Aston University, Birmingham B4 7ET, UK

School of Engineering and Sciences, Tecnológico de Monterrey, Monterrey 64849, Mexico

Cornwall Business School, Falmouth University, Penryn TR10 9FE, UK

Author to whom correspondence should be addressed.

1. Introduction

Overall, some early studies have started to shed some light regarding the potential challenges and opportunities of ChatGPT for higher education, but more in-depth discussions are needed. We argue that the current discourse is highly focused on studying ChatGPT as an object rather than a subject. Given the advanced generative capabilities of ChatGPT, we would like to contribute to the ongoing discussion by exploring what ChatGPT has to say about itself regarding the challenges and opportunities that it represents for higher education. By adopting this approach, we hope to contribute to a more balanced discussion that accommodates the AI perspective using a 'thing ethnography' methodology [ 16]. This approach considers things not as objects but as subjects that possess a non-human worldview or perspective that can point to novel insights in research [ 17].

This study will examine ChatGPT's perspective on the opportunities and challenges that it represents for academic purposes, as well as recommendations to mitigate challenges and harness potential opportunities. In doing so, we will aim to answer the following research questions:

What are the potential challenges for higher education posed by ChatGPT, and how can these be mitigated?

What are the potential opportunities and barriers to the integration of ChatGPT in higher education?

The structure of this paper is as follows. After this intro, the next section explores 'thing ethnography methodology' as a novel approach to engage with GenAI. It will also explain the steps followed in this study to collect ChatGPT's views. Section Three will summarize the results, and section four will discuss the results in the context of existing literature to validate the non-human perspective. Lastly, a conclusion will answer the research questions and outline future research directions.

2. Method: Thing Ethnography Applied to ChatGPT

Ethnography refers to a form of social research that emphasizes the importance of studying first-hand what people do and say in particular contexts [ 18]. It involves an in-depth understanding of the world based on social relations and everyday practices. Traditionally, the focus of ethnography has been on human perspectives via qualitative methods such as observation and interviews. However, it is argued that as humans, "we have complex and intertwined relationships with the objects around us. We shape objects; and objects shape and transform our practices and us in return" [ 19] (p. 235). Recognizing this continual interplay between humans and objects necessitates research methodologies that grant both parties an equal role.

In this context, we argue that ChatGPT should not be studied merely as an "object" designed, trained, and used by people but as a "subject" that co-performs daily practices with users and has an impact on the socio-material networks in which it is embedded. In the case of thing ethnography applied to ChatGPT, the focus would be on understanding the user experience, the impact on communication dynamics, and the broader societal implications from ChatGPT's perspective. A better understanding of this can help guide the development and deployment of chatbot technologies in a way that is more responsive to user needs, respects societal values, and promotes responsible AI practices. We believe that thing ethnography approaches are becoming crucially relevant as efforts attempting to build successively more powerful AI systems closer to AGI-AI systems that are generally smarter than humans-continue [ 27]. As 'things' become increasingly intelligent, there is an unprecedented and pressing demand to enhance our ability to access and comprehend the perspective of these entities.

In this study, we apply thing ethnography to engage with ChatGPT. Whereas previous thing ethnography interventions have used different smart devices to access the perspective of things, our study will engage with the 'subject' via a written conversation given the unique text generation capacities of chatbots. To answer the research questions stated in the previous section, this study has adopted a semi-structured interview. This type of interview facilitates the collection of rich data related to participants' views [ 28], with the required degree of structure and flexibility [ 29]. An interview guide containing a list of themes and key questions was prepared before the interview. Nevertheless, the flexibility of semi-structured interviewing allowed the use of probes devised during the interviews. Probing is useful to further explore responses that are deemed significant for the research topic [ 28]. In line with King and Horrocks' [ 30] suggestion, probing was adopted to seek clarification for unclear words or phrases, completion for stories that the interviewer felt unfinished, and elaboration to encourage the interviewee to 'keep talking'.

3. Results: How Did ChatGPT Respond?

The unedited transcript of the interview with ChatGPT is shown below. This is followed by post-interview reflections and discussions on emerging themes.

Interviewer: What are the potential challenges for higher education posed by ChatGPT?

ChatGPT: ChatGPT, as an advanced language model, presents certain challenges for higher education. Here are a few potential challenges that institutions may face:

It is important to note that these challenges are not insurmountable, and institutions can develop strategies to address them effectively. With careful implementation and integration, ChatGPT can still offer significant benefits and opportunities for higher education.

Interviewer: What significant benefits or opportunities for higher education can ChatGPT offer?

ChatGPT: ChatGPT indeed presents several significant benefits and opportunities for higher education. Here are some of them:

By leveraging the strengths of ChatGPT while addressing its limitations, higher education institutions can harness the benefits and opportunities it offers to enhance the learning experience, promote student success, and foster innovative educational practices.

Interviewer: What factors can prevent universities from fully harnessing the benefits of ChatGPT?

ChatGPT: Several factors can prevent universities from fully harnessing the benefits of ChatGPT:

To overcome these barriers, universities can focus on raising awareness, providing training and support, addressing ethical considerations, fostering collaboration across disciplines, and developing policies and guidelines that promote the responsible and effective use of ChatGPT. It is essential for universities to actively engage in discussions, seek stakeholder input, and create an environment that encourages innovation and experimentation while upholding academic rigor and ethics.

Interviewer: Many universities are struggling with addressing the emerging risks; what should be the priorities?

ChatGPT: When it comes to addressing the emerging risks associated with integrating AI models like ChatGPT, universities can prioritize the following key areas:

By prioritizing these areas, universities can proactively address the emerging risks associated with AI integration, promote the responsible use of AI models, and create an environment that maximizes the benefits while minimizing potential harm.

Interviewer: Can you tell me more about what can be considered acceptable and responsible use of AI in this context?

ChatGPT: Certainly! Acceptable and responsible use of AI in the context of higher education involves adhering to ethical principles and best practices. Here are some key considerations:

By adopting these principles, universities can promote an environment of responsible AI use in higher education, ensuring that AI models like ChatGPT are employed in a manner that upholds ethical standards, protects student rights, and enhances the overall learning experience.

Interviewer: Finally, what do you think about universities banning the use of ChatGPT?

ChatGPT: The decision to ban the use of ChatGPT or any AI tool in universities is a complex one that requires careful consideration of various factors. While I, as an AI language model, do not possess personal opinions, I can provide some insights on the matter.

Universities may choose to ban the use of ChatGPT for several reasons:

Plagiarism Concerns: ChatGPT, as a powerful language model, can generate text that might be used for plagiarism if not properly attributed or verified. Universities may be concerned about maintaining academic integrity and ensuring that students produce their own original work.

Lack of Human Interaction: AI tools like ChatGPT lack human qualities such as empathy, contextual understanding, and common sense reasoning. The absence of human interaction in certain educational scenarios may be seen as a limitation that detracts from the quality of education and the development of critical thinking and communication skills.

Educational Value: Some argue that relying solely on AI tools for learning may limit the depth of understanding and exploration. Universities may believe that the interaction with instructors, peers, and authentic learning experiences is essential for a comprehensive and meaningful education.

However, it's important to note that banning ChatGPT entirely may overlook its potential benefits. Instead of a blanket ban, universities could consider alternative approaches:

Guidelines and Responsible Use: Develop clear guidelines and policies that outline the responsible and ethical use of AI tools, including ChatGPT. These guidelines can address issues such as plagiarism, disclosure, limitations, and the role of human oversight.

Integration with Human Instruction: Encourage the use of ChatGPT as a supplementary tool to support teaching and learning rather than a replacement for human instruction. Instructors can leverage ChatGPT to augment their lessons, provide additional resources, or spark discussions while still maintaining their role as facilitators and subject matter experts.

Education and Training: Offer education and training programs for students and faculty on the responsible and effective use of AI tools. This can include workshops, seminars, or online modules that address the potential benefits, limitations, and ethical considerations associated with AI.

Continuous Monitoring and Evaluation: Continuously monitor the use of AI tools like ChatGPT and evaluate their impact on learning outcomes, student engagement, and overall educational experience. This ongoing assessment can help inform policies and practices to ensure the responsible and beneficial integration of AI in higher education.

Ultimately, the decision to ban or allow the use of ChatGPT in universities depends on the specific context, institutional goals, and values. It is important for universities to carefully consider the potential benefits, risks, and alternatives before making a final decision.

4. Discussion

4.1. Opportunities

The integration of ChatGPT in higher education translates into a set of potential opportunities or benefits for key stakeholders, including students, teaching staff, and researchers. Of the seven opportunities mentioned by ChatGPT, five have a strong emphasis on students, whilst the other two focus on teaching staff and researchers, respectively. Firstly, ChatGPT sees itself as a tool capable of providing "personalized feedback, explanations, and recommendations based on individual student queries", thus promoting self-directed learning. This is echoed in the literature as findings suggest that ChatGPT can provide personalized feedback on essays and become a tutoring system by stimulating critical thinking and debates among students [ 13]. Similarly, ChatGPT suggests that it "can serve as a valuable supplementary resource alongside traditional course materials" to reinforce learning and encourage independent research. In line with this, the literature argues that ChatGPT can be used as a supplementary tool to generate answers to theory-based questions and generate initial ideas for essays [ 3, 12].

Another opportunity includes the role that ChatGPT can play in enhancing language and communication skills, as it can "simulate conversational exchanges, provide language correction, and offer vocabulary and grammar assistance". This feature of ChatGPT can arguably have a positive effect on widening participation in higher education by removing barriers that some students face. For instance, Lim et al. [ 1] suggest that the language editing and translation skills of ChatGPT can contribute towards increased equity in education by somewhat leveling the playing field for students from non-English speaking backgrounds. It could also remove some barriers for students who suffer from disabilities such as dyslexia, as it can support paraphrasing text that is free of grammar or spelling errors given the correct prompts and input. Another opportunity mentioned by ChatGPT has to do with improving accessibility by providing "round-the-clock support to students". This capability could be particularly valuable for distance learning students or international students in different time zones. This potential benefit of ChatGPT seems to be less studied and documented in the existing literature. The last benefit for students relates to the idea that "Incorporating ChatGPT into the curriculum can introduce innovative and interactive learning experiences". Although the literature recognizes the potential of ChatGPT and similar large language models for improving digital ecosystems for education [ 3, 35], this has not been extensively documented.

ChatGPT mentioned two opportunities that focus on teaching and research staff. Firstly, it suggested that it "can assist instructors and teaching assistants by handling routine queries, providing quick references, or offering guidance on commonly asked questions". Interestingly, ChatGPT goes on to say that "this frees up their time to focus on higher-level tasks", which seems to indicate that ChatGPT does not see itself as a tool that can contribute to such higher-level tasks. In this regard, the literature suggests that ChatGPT can also be a valuable tool for educators as it can help in creating lesson plans for specific courses, developing customized resources and learning activities (i.e., personalized learning support), and generating course objectives, learning outcomes, and assessment criteria [ 14, 36, 37]. However, given the novelty of ChatGPT, these benefits seem to be mostly theoretical or speculative at this point, as more empirical works are needed to demonstrate how this can be fully achieved. Empirical works to test the effectiveness of this approach are also required.

Lastly, ChatGPT suggested that it "can support research efforts by assisting with literature reviews, data analysis, and generating hypotheses". The literature supports this view by acknowledging that ChatGPT can support the writing process of research [ 14], improve collaboration, facilitate coordinated efforts, and be conducive to higher-quality research outcomes [ 38]. However, a key concern remains regarding the loss of human potential and autonomy in the research process [ 39]. Some publishers have started to provide general advice regarding the role that ChatGPT can play in the writing process, but there is a call for more specific guidelines regarding how to acknowledge the use of AI in research and writing for journals [ 38]. Van Dis et al. [ 39] suggest that whilst the focus should be on embracing opportunities of AI, we also need to manage the risks to the essential aspects of scientific work: curiosity, imagination, and discovery. The authors call for measures to ensure that humans' creativity, originality, education, training, and interactions remain essential for conducting research. In line with this, Kooli [ 38] argues that ChatGPT and other chatbots should not replace the essential role of the human researcher. Instead, they should adopt a "research assistant" role that requires constant and close supervision. Overall, the current debate around potential applications remains hypothetical as there is still a lack of a regulatory framework to advance the use of ChatGPT in research activities.

4.2. Challenges

ChatGPT's views on the challenges that it poses for higher education clearly revolve around several of the shortcomings of GenAI systems, including the lack of accuracy and reliability of the information it generates. But other issues relate to the actual misuse by students. Challenges associated with the shortcomings of ChatGPT are summarized into four categories: Quality Control, Expertise and Authority, Personalized Learning, and Communication and Collaboration. Regarding Quality Control, ChatGPT suggests that whilst it "strives to provide accurate and helpful information, there is still a possibility of generating incorrect or misleading response". Similar issues are echoed in the literature, with concerns about how the inherent biases of ChatGPT and other GenAI systems could seriously impact the accuracy and reliability of information generated by these systems [ 11, 40]. ChatGPT further suggests that regular monitoring, bias detection tools, and ongoing training of AI models can help mitigate biases and ensure fair and inclusive outcomes. In terms of Expertise and Authority, ChatGPT explains that it "lacks the domain-specific expertise that specialized instructors and professors possess". Therefore, relying solely on ChatGPT for higher education may not meet students' needs regarding deep insights, critical analysis, and guidance in specific fields. This challenge links to the previous one (i.e., Quality Control), and in this regard, ChatGPT adds that "Institutions should emphasize the role of instructors and teaching staff in guiding students, verifying the accuracy of AI-generated information, and providing additional context when needed".

Two challenges that have not been extensively documented in existing literature include Personalized Learning and Communication and Collaboration. Whilst the idea of using ChatGPT to develop personalized learning and tutoring systems has been discussed [ 3, 13, 40], the downsides have not been fully considered. In this regard, ChatGPT warns that it may not be able to fully capture the distinctive needs of each learner, adding that "Relying solely on ChatGPT for personalized learning experiences may overlook certain aspects of individual student needs, such as their learning style, preferences, and unique challenges". Once again, the central role of teaching staff in overseeing the use and application of ChatGPT in higher education is evidenced here. The other challenge concerns Communication and Collaboration as integral parts of higher education. ChatGPT suggests that being an AI language model, it "might not possess the same level of human interaction and interpersonal skills as an instructor or peers", which can limit its contribution to certain elements of the educational experience, such as facilitating group work and other collaborative activities. The challenges discussed here and in the previous paragraph suggest that we are still a long way (if we ever get there) from a world where GenAI systems fully replace teaching staff. ChatGPT views seem to suggest that it can serve as a tool but cannot fully substitute the human element. Hence, those wanting to incorporate it into education need to provide teachers with the skills and training to effectively utilize the technology in order to minimize the challenges discussed here.

A final challenge mentioned by ChatGPT has to do with its misuse, especially when it can negatively affect academic integrity. ChatGPT suggests that "Students could potentially misuse the model to generate plagiarized content or cheat on assignments and assessments". This is arguably one of the most cited concerns in existing academic literature, prompting an ongoing debate on whether the technology should be completely banned from HEIs [ 11, 40, 41]. Plagiarism and academic misconduct are not new threats to higher education and have been extensively studied [ 42]. However, the novelty of ChatGPT has amplified the threat for two main reasons, lack of clear academic policies and low probability of detection. A recent study found evidence of a clear absence of clarity regarding the use of ChatGPT and similar GenAI tools in academic policies. Out of 142 HEIs surveyed in May 2023, only one explicitly prohibited the use of AI [ 43]. This is an important finding as there is evidence to suggest that academic dishonesty is inversely related to understanding and acceptance of academic integrity policies [ 44, 45]. Therefore, it is imperative that HEIs prioritize the clarification of institutional expectations regarding the use of ChatGPT in learning and assessment. Updating academic integrity policies is crucial to address GenAI tools threats. Updates should provide clear instructions on AI tool usage and penalties for policy violations and be accessible to students [ 43]. The absence of specific guidelines for AI tools creates ambiguity, indicating a hesitancy among HEIs to take a clear stance, possibly due to limited experience. This poses challenges in formulating comprehensive policies that address evolving issues posed by emerging AI technologies. The other key issue has to do with the low probability of detection perceived by students wanting to use ChatGPT for cheating. There is evidence suggesting that the likelihood of students engaging in cheating increases when they believe that the chances of getting caught are minimal [ 45]. Thus, the lack of readily available AI plagiarism checkers to detect ChatGPT-generated content can increase the threat to academic integrity. So, the challenge for HEIs is how to create an environment where academic dishonesty enabled by GenAI is socially unacceptable. This must involve ensuring that institutional expectations are clearly communicated and understood and that students perceive the probability of plagiarism detection as high.

4.3. Barriers

Having reflected on the potential benefits for higher education, ChatGPT provided some interesting insights regarding the barriers that HEIs may face in adopting GenAI technology; these included Lack of Awareness and Understanding, Technological Barriers, Resistance to Change, Ethical and Privacy Concerns, Academic Rigor and Quality, Resource Constraints, Legal and Regulatory Considerations, and Lack of Interdisciplinary Collaboration. Some of these barriers have already been documented in existing literature; however, the majority remain unexplored and open avenues for future research directions.

One obvious barrier is a Lack of Awareness and Understanding. In this regard, ChatGPT suggests that "if faculty, administrators, and students are not familiar with the technology and its benefits, they may be reluctant to explore its potential". This issue is further compounded by the current lack of clear academic policies. For instance, this may hinder the progress toward the adoption of ChatGPT for teaching and learning purposes. Currently, academic staff wanting to develop innovative interventions using ChatGPT do not have a regulatory framework to guide them. This can have a negative effect on the empirical testing of the potential benefits discussed in this paper. A recent study on students' acceptance and use of ChatGPT found that students are comfortable adopting GenAI technology and that their frequency of use contributes to the development of habitual behavior [ 46]. In this context, habitual behavior or habit refers to the level of a regular and consistent pattern of use of ChatGPT as part of an academic routine. Therefore, HEIs have the unique opportunity to shape the principles of responsible use of emerging AI technology and guide students in the formation of habitual behavior that is in line with such principles. Figure 2 summarizes the principles that ChatGPT suggests considering to "promote an environment of responsible AI use in higher education, ensuring that AI models like ChatGPT are employed in a manner that upholds ethical standards, protects student rights, and enhances the overall learning experience". All of these principles deserve further consideration and open avenues for future research direction.

Other barriers include Ethical and Privacy Concerns and Academic Rigor and Quality. Some aspects of these have already been discussed in this paper as part of the challenges of integrating ChatGPT in higher education. These barriers relate to a wide range of issues, including data privacy, algorithmic biases, and authenticity of student work. As suggested by Dignum [ 24], "As the capabilities for autonomous decision-making grow, perhaps the most important issue to consider is the need to rethink responsibility. Being fundamentally tools, AI systems are fully under the control and responsibility of their owners or users" (p. 2011). Thus, there is a pressing need for more research into the responsible use of AI in the higher education context. This will hopefully translate into academic policies that contain the principles for responsible use of AI, as well as training and dissemination activities to increase awareness among key users (i.e., academic staff and students).

Economic barriers include a lack of technology and resource constraints. ChatGPT suggests that "Universities with limited financial or personnel resources may struggle to fully harness the benefits of ChatGPT due to resource constraints". Equally, the adoption of GenAI technology may require sophisticated technical infrastructure such as high-performance computing resources and robust network connectivity. Therefore, "Universities that lack the necessary technological infrastructure may face challenges in fully utilizing the benefits of ChatGPT". For those HEIs that manage to overcome the exclusionary economic barriers, resistance to change may become another hurdle. According to ChatGPT, "Faculty members, administrators, or staff may be resistant to integrating ChatGPT into existing workflows or may prefer traditional teaching and learning methods". In this regard, emerging literature points to the need to train academic staff on how to make the best of ChatGPT during teaching preparation and course assessment [ 11]. In addition, as we continue (or start) to embrace the use of ChatGPT in teaching and learning, it is critical to disseminate empirical findings on the use of ChatGPT that can inform the teaching practices of the wider academic community.

4.4. Mitigation Strategies

ChatGPT provided some priorities for mitigating the challenges discussed here; these include Policy Development, Education and Training, Collaboration and Interdisciplinary Efforts, Research and Development, Ethical Review Processes, and Continuous Monitoring and Evaluation. The urgency of developing or updating academic policies to address the use of ChatGPT has already been raised in this study as well as in existing literature [ 11, 43]. ChatGPT's views suggest that changes to policies need to "address issues of academic integrity, data privacy, algorithmic bias, and ethical consideration". Given the novelty of the technology as well as the robustness of HEIs' governance systems, it is likely that HEIs will have clearer positions on the use of GenAI tools later this year [ 41], and this will hopefully translate into updated academic policies. Subsequently, it will become crucial to focus resources on Education and Training. ChatGPT suggests that "Universities should offer workshops, seminars, or online courses to raise awareness about the benefits, limitations, and potential risks of AI models". This is in line with existing literature suggesting academic dishonesty is a multifaceted behavior influenced by various factors, and simply developing an academic policy is insufficient in addressing the problem [ 44]. The dissemination of such policies is just as crucial; this could include adopting practices such as having students sign honor pledges, providing reminders about the gravity and repercussions of academic dishonesty, and including statements about academic misconduct in course syllabi. Furthermore, as GenAI technologies continue to evolve rapidly, it is imperative to regularly update academic integrity policies with clear guidelines on their appropriate and inappropriate applications [ 43].

Investing in Research and Development is another important mitigation strategy, according to ChatGPT: "This includes studying the impact of AI models on student learning outcomes, developing algorithms for bias detection and mitigation, exploring ways to combine AI models with human expertise, and investigating ethical frameworks for AI use in educational settings". These efforts can provide evidence-based insights to guide policy decisions and best practices for the integration of GenAI in higher education. Another important issue is the passive role that HEIs are currently playing in GenAI research. Most cutting-edge GenAI technologies are exclusive products created by a handful of prominent technology corporations that possess the necessary resources for AI advancement. This raises ethical issues and goes against the move toward transparency and open science [ 39]. Dignum [ 24] agrees that AI algorithm development has so far focused on enhancing performance, resulting in opaque systems that are difficult to interpret. Thus, there is a call for non-commercial organizations, including HEIs, to make significant investments in open-source AI technology to create more transparent and democratically controlled technologies [ 39].

An important mitigation strategy that was not mentioned by ChatGPt but figures prominently in existing literature relates to the need for a reevaluation of the traditional modes of assessment [ 43]. To overcome some of the challenges and barriers that GenAI pose for students' learning and their authentic assessment, this technology might be used in combination with active learning pedagogies, such as experiential learning [ 47], challenge-based learning [ 48], or problem-based learning [ 49]. In this sense, GenAI might be used as leverage to constructively enrich teaching and learning-by-doing activities beyond a passive approach in which students sit, listen, and do assignments. By doing this, GenAI cannot provide specific answers to the practicality of problem-solving in a situated real-world or contrived learning experience but supports students in addressing study situations. Taking this view offers a promising use of GenAI for teaching and learning purposes.

5. Conclusions

The findings of this study highlighted the transformative potential of ChatGPT in education, consistent with previous studies, while also revealing additional insights. It also highlighted significant challenges that must be addressed. The paper presents key themes identified during the interview, including opportunities, challenges, barriers, and mitigation strategies. Given the novelty of ChatGPT, existing literature about its use within higher education is limited and largely hypothetical or speculative. Our hope is that the findings presented here can serve as a research agenda for researchers and the wider academic community to identify research priorities, gaps in knowledge, and emerging trends. A key takeaway point is the urgent need for empirical research that delves into best practices and strategies for maximizing the benefits of GenAI, as well as user experiences, to understand students' and academics' perceptions, concerns, and interactions with ChatGPT. Another priority is the development of policies, guidelines, and frameworks for the responsible integration of ChatGPT in higher education. Based on the conversation with ChatGPT, this paper also presents some principles for the acceptable and responsible use of AI in higher education. These principles can be useful for Higher Education Institutions working towards internal AI policies. However, empirical studies are needed to explore the transferability of findings presented here to varied contexts with specific features, for instance, distance or online learning.

This study employed a thing ethnography approach to explore ChatGPT's perspective on the opportunities and challenges it presents for higher education. This is an innovative approach that has been implemented in design research but could become a powerful tool for researchers from other disciplines wanting to engage with "intelligent things". In this study, thing ethnography provided a methodological framework to collect the viewpoints of ChatGPT. This helped us to test its potential biases and accuracy, as well as uncover insights that have not been extensively documented in the existing literature. As an interviewee, ChatGPT provided very relevant and interesting insights, showing some level of critique towards itself when questioned about potential risks and challenges, which indicates some level of transparency regarding its own shortcomings. A benefit of this approach is that ChatGPT enables interviewers to request further information and clarify responses, which can enhance data collection. Additionally, the chatbot displays a very good level of recollection during a conversation. Its memory seems to be limited; however, this did not represent an issue for the length of our interview. Despite the absence of non-verbal cues and expressions, the answers obtained seemed balanced and clearly conveyed meaning. Therefore, it is argued that interviews with ChatGPT have the potential to collect relevant data.

We believe the use of thing ethnography to engage with ChatGPT is very relevant and would encourage other researchers to involve GenAI entities in the process of collectively framing and resolving current challenges. Our argument is that ChatGPT should be approached not merely as an object controlled by humans but as a subject actively engaging in daily practices alongside users, influencing communication dynamics, and impacting socio-material networks. We believe that thing ethnography approaches are increasingly significant, particularly as endeavors to create more advanced AI systems closer to artificial general intelligence (AGI) persist. As "things" grow more intelligent, there arises an urgent demand to improve our ability to access and comprehend the perspectives (and biases) of these entities for research purposes.

Author Contributions

Conceptualization, R.M.-V.; methodology, R.M.-V.; validation, E.V.-P., D.E.S.-N., R.T.-A. and F.S.G.; formal analysis, R.M.-V., E.V.-P., D.E.S.-N., R.T.-A. and F.S.G.; writing-original draft preparation, R.M.-V.; writing-review and editing, R.M.-V., E.V.-P., D.E.S.-N., R.T.-A. and F.S.G. All authors have read and agreed to the published version of the manuscript.

Funding

The authors would like to acknowledge the financial support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this work (Los autores desean agradecer el apoyo financiero de Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, en la producción de este trabajo).

Institutional Review Board Statement

Informed Consent Statement

Data Availability Statement

A full transcript of the interview with ChatGPT is included in this paper. No additional data was created for this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Figure 1. Themes emerging from the interview (own elaboration).

Figure 2. Principles for acceptable and responsible use of AI in higher education (own elaboration).

Michel-Villarreal R, Vilalta-Perdomo E, Salinas-Navarro DE, Thierry-Aguilera R, Gerardou FS. Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences. 2023; 13(9):856. https://doi.org/10.3390/educsci13090856

Chicago/Turabian Style

Michel-Villarreal, Rosario, Eliseo Vilalta-Perdomo, David Ernesto Salinas-Navarro, Ricardo Thierry-Aguilera, and Flor Silvestre Gerardou. 2023. "Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT" Education Sciences 13, no. 9: 856. https://doi.org/10.3390/educsci13090856

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Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT

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ChatGPT is revolutionizing the field of higher education by leveraging deep learning models to generate human-like content. However, its integration into academic settings raises concerns regarding academic integrity, plagiarism detection, and the potential impact on critical thinking skills.

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This source is an article published by Educause Review; a website recommended to me by ChatGPT. It is fairly brief but clearly lays out a few of the problems educators are having with AI as well as the possible benefits. Much of it is in line with what other articles I have read concluded and the article actually cited several academic articles I had already found. It was also useful in leading me to a few other relevant articles. The issue with this article is the bias of the author who is the CPO of a company which provides AI tools to those who work in education. However this bias is clearly stated in the article, both at the top and in the about the author section at the bottom. Additionally, nothing that it said seemed to go against the general trend I have seen in order to promote the company’s services.

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This article presents two problems, a confession, and one clear solution for leaders who are grappling with how to properly assess learners in the age of AI.

The following scenario is unfolding in academic department meetings across the country: A faculty member who is reviewing a learner's written formative assessment believes something is off. Perhaps the style doesn't match the student's earlier work or incorporates a cadence or structure that seems out of place for the assignment type. The stakes are high as the talk turns to whether generative artificial intelligence (AI) was used. Another instructor raises concerns over the accuracy and bias of AI-detection tools. The conversation stalls, and the issue remains unresolved.

AI is rapidly transforming the classroom, and assessment is one of the most impacted areas. Old methods and new tools that are purported to be able to detect AI-generated text raise new concerns. What is the path forward? Higher education technology leaders should empower instructors to develop authentic assessment methods that are facilitated by technology-including AI. While these leaders are tasked with setting up instructors to succeed, the path ahead has never looked so uncertain.

AI Is Changing Everything

The landscape instructors face is transforming at an alarming pace. The proliferation of generative AI tools like ChatGPT has opened the door to misuse by learners. Even the concept of "misuse" is a gray area, as few institutions have laid out comprehensive policies around the use of AI tools by learners, instructors, or staff, and the line delineating what constitutes appropriate use has yet to be established. A recent survey of students, instructors, and administrators found that 51 percent of students would continue to use generative AI tools even if such tools were prohibited by their instructors or institutions. AI plagiarism-the use of generative AI to produce content that someone submits as their own work for assessment tasks-represents a real challenge across institutions. In an effort to solve the problem, IT and institutional leaders are grappling with what amounts to an arms race, procuring tools that claim to use AI to detect AI-generated plagiarism. If only it were that easy.

New Tools, New Concerns

A growing body of research is casting doubt on the efficacy of AI detection, with two key issues emerging: accuracy and bias. First, how accurately can AI-generated content be detected? Five computer scientists from the University of Maryland recently conducted a study in which they emphatically concluded that AI-generated text cannot be reliably detected, and simple paraphrasing is sufficient to evade detection. A separate study of fourteen AI detectors conducted by academic researchers in six countries found that the accuracy of these tools ranges from 33 to 81 percent, depending on the provider and the methodology used.

Second, are the current iterations of AI-detection tools creating new issues by inadvertently introducing bias? The data that AI models are trained on is scraped from the internet, where the content is predominantly written in English. Stanford researchers evaluated whether this might lead to challenges in identifying whether Test of English as a Foreign Language (TOEFL) essays were AI-generated. Indeed, the researchers found that more than half of TOEFL essays were incorrectly classified as AI-generated.

These challenges do not end at the edge of campus. As an education technology product leader, my team and I evaluated whether AI detection fits our solution ecosystem, and we grappled with these same questions. The framework that guided our evaluation and continues to guide our product development is grounded by inclusivity and accessibility principles and declares that academic integrity policies should level the playing field for every student. Fairness matters. In evaluating whether our company should pursue AI-detection capabilities, we conducted beta testing with a cohort of clients. The results were sobering. The participants had low confidence in the ability of AI detectors to correctly identify AI-generated content, with 80 percent of respondents believing that AI detectors are, at best, correct only "sometimes." When it comes to detecting biases, our evaluation also matched research related to the introduction of bias, with samples written by students who speak English as a second language and students with autism spectrum disorder incorrectly identified as AI-generated content. We concluded it would not be ethical to employ AI-detection tools at this point of development.

The Way Forward with AI: Humans

Assessment is still a critical pedological element, but it's time to think about it differently. In its simplest form, authentic assessment moves away from accrued knowledge to focus on the practical application of skills, prioritizing complex tasks over binary right-or-wrong questions. In the age of generative AI, authentic assessment is more important than ever. Injecting personal perspectives, critical thinking, and self-reflection in a way that appears genuine is much more difficult for generative AI technologies than it is for humans. For instance, authentic assessment in a business course may mean holding a mock negotiation where students can actively demonstrate their comprehension of the material. Authentic assessment isn't new. Educators have long recognized its benefits, including the ability to provide a clear connection between coursework and careers through the application of knowledge.

AI As a Means to Inspire Instructors

Authentic assessment demands time, a resource that is in short supply for instructors. Anthology believes AI can make a real, tangible impact today and help meet the challenge of creating more time for instructors. Learning technology infused with AI tools can reduce the time needed to complete administrative and production tasks like creating courses, enabling educators to spend more time teaching and working with students. Peer assessment and group work require a high level of authenticity, and tools that seamlessly support group work are another example of how technology can help instructors be more efficient.

Learning technology that reduces the administrative burden is critical for empowering instructors to rethink their assessment methods. There's no way around it: authentic assessment requires an investment of time on the part of the instructor. Freeing time that would otherwise be spent on repetitive or lower-value tasks to develop, test, and implement authentic assessment is the path forward. While the landscape may be transforming rapidly, instructors remain an institution's most valuable resource in the classroom. Combating the challenge that generative AI poses in evaluating learners starts with doubling down on the human element and adopting a proactive approach. The wait for solutions that can accurately identify AI plagiarism while avoiding serious ethical concerns might be long. Instead, institutional leaders need to embrace AI as part of the larger landscape and develop policies and approaches that use it to assess learners more authentically. For a more in-depth vision, download Anthology's whitepaper on an ethical path forward for education.

Notes

1. Louis NeJame et al., "Generative AI in Higher Education: From Fear to Experimentation, Embracing AI's Potential," Blog + Higher Ed (blog), Tyton Partners, April 25, 2023.

2. Vinu Sankar Sadasivan et al., "Can AI-Generated Text Be Reliably Detected?" (unpublished manuscript, June 28, 2023), PDF file.

3. Deborah Weber-Wulff et al., "Testing of Detection Tools for AI-Generated Text," (unpublished manuscript, July 10, 2023), PDF file.

4. Weixin Liang et al., "GPT Detectors Are Biased Against Non-Native English Writers," Patterns 4, no. 7 (July 2023): 100779.

JD White is Chief Product Officer at Anthology.

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This article presents two problems, a confession, and one clear solution for leaders who are grappling with how to properly assess learners in the age

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Williamson, B., Macgilchrist, F. and Potter, J. (2023). Re-examining AI, automation and datafication in education. Learning, Media and Technology, vol. 48, no. 1, pp.1–5

# data[].attributes.subject
Williamson, B., Macgilchrist, F. and Potter, J. (2023). Re-examining AI, automation and datafication in education. Learning, Media and Technology, vol. 48, no. 1, pp.1–5

# data[].attributes.body
This source is an editorial from a journal published in 2023. It is the same journal that a lot of the other articles I read were published in. It explains that this edition of the journal was not planned but was rather published because of the large number of articles which focused on artificial intelligence that had been submitted for publication. Since it is more of an introductory work, it only briefly describes the recent and extreme evolutions in AI technology. It offers definitions for some terminology, creating a baseline which made reading the other articles easier. It also made a key point about ethics which I had not previously considered: since AI learns from its users, it could be argued that the creators are making money from students work. Overall this source, while not key in and of itself, did help with progressing my research.

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Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, vol. 3, Amsterdam: Elsevier

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Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, vol. 3, Amsterdam: Elsevier

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This source is an article in a journal focused on artificial intelligence published in 2022. Its focus is in Hong Kong and outline a model for teaching children about artificial intelligence. It asks three main questions: why is this education necessary, what can actually be taught to children and how can the lessons be made engaging? It highlights the fact that courses currently available are only aimed at children with a base level knowledge, making them inaccessible to children from less advantaged backgrounds. It goes on to explain that understanding of AI can be applied in other areas, even outside of technology, and introducing children to it can aid in the development of their data literacy. This source, while specific to one region, is more widely applicable. It is especially useful because it focuses on younger children than a lot of other research that I have found.

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Author links open overlay panel Weipeng Yang

Show more

Highlights

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This report discusses the key considerations for developing an embodied AI curriculum for young children.

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Why: AI literacy is an organic part of digital literacy for all citizens in an increasingly intelligent society.

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What: The core AI knowledge that can be explored with young children has been identified.

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How: An embodied, culturally responsive approach should be used to enable young children's exploration with AI technologies.

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The "AI for Kids" curriculum is described to demonstrate this innovative pedagogical model.

Abstract

Artificial intelligence (AI) education has posed fundamental challenges to early childhood education (ECE), including (1) why AI is necessary and appropriate for learning in the early years, (2) what is the subset of key AI ideas and concepts that can be learned by children, and (3) how to engage children in a meaningful experience that allows them to acquire these fundamental AI concepts. This report from the ECE field discusses the key considerations for developing an AI curriculum for young children. These key considerations altogether present an innovative pedagogical model for AI literacy education in early childhood. This model argues that AI literacy is an organic part of digital literacy for all citizens in an increasingly intelligent society. The core AI knowledge that can be explored with young children is: Using large amounts of data input, AI algorithms can be continuously trained to identify patterns, make predictions, and recommend actions, even though with limitations. Based on the theoretical notions of learning-by-making and pedagogy- as-relational, an embodied, culturally responsive approach should be used to enable young children's exploration with AI technologies. Finally, an exemplary curriculum named "AI for Kids" is introduced to demonstrate this pedagogical model and explain how educators can provide children culturally responsive inquiry opportunities to interact with and understand AI technologies. The synthesis of knowledge regarding "Why", "What", and "How" to do with AI education for young children informs a new way to engage children in STEM and understanding the digital world.

Keywords

Artificial intelligence education

Early childhood education

Pedagogical considerations

# data[].attributes.attachment_link.title
Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation

# data[].attributes.attachment_link.description
Artificial intelligence (AI) education has posed fundamental challenges to early childhood education (ECE), including (1) why AI is necessary and appr...