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This session will focus on how we can promote good practice in AI among students. Some questions you might want to think about ahead of the session are:

What do we see as acceptable/unacceptable uses of AI for students? To what extent is there agreement on this at ULaw / within HE more widely?

How can we support students to be AI literate, and use AI in ethical and informed ways?

What examples of good teaching practice around AI have you encountered elsewhere?

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In this session, we will be discussing AI more generally and how it is transforming the learning landscape in higher education.

Before the session, it may be helpful for you to review the suggested reading and the below prompts:

What are your experiences with using AI?

Where have you seen AI being used within a University setting?

What are the benefits and challenges that AI might bring to ULaw?

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Great overview of AI in Higher education

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Automatic Impact: Robots to the Rescue?

One of the major benefits of AI is that it can decrease workload and increase efficiency. With the use of AI automation, higher education institutions (HEIs) are finding new ways to complete time-consuming and laborious administrative work and, instead, prioritise analysis and strategic planning.

In simple terms, automation is where technology is used to perform tasks that would normally be undertaken by humans, so as to reduce workload. AI is a type of automation technology, as are other forms of advanced technology such as machine learning and robotic process automation.

Real Automation for HE Marketers

Automation is being integrated into professional services in higher education on a number of different levels. For example, HE marketers have been harnessing automation for impact. This is an area in which the use of AI in higher education can be truly transformative, with marketing leaders ensuring that automation is part of wider digital transformation within their institutions.

The most obvious example of how AI is being used by marketers within the HE sector is through the integration of Customer Relationship Management technologies. This allows marketers to manage interactions with prospects and streamline their processes.

For further guidance on this, this interview between marketing leaders from Newcastle University and the University of East Anglia explores some of the opportunities and benefits automation offers HE marketers, what the use of AI looks like in practice.

Supporting the Student Experience

However, it's not just marketing teams in higher education that are exploring the use of AI in service delivery. Staffordshire University has developed an automated digital assistant that supports students' academic and emotional wellbeing. Bringing together many aspects of the student experience, this tool allows users to navigate their timetable, contact members of staff, request important documents, engage with their students' union (SU) and extracurricular activities, and much more. The app even offers students mental health check-ins, demonstrating how the use of AI in higher education, and automation in particular, can be used to support student success and wellbeing. And, as the software is the go-to resource for students to ask questions, it unburdens professional service staff from dealing with thousands of enquiries, freeing them to focus on how they can deliver more impact in their roles.

Similarly, AI may also be able to support in the realm of teaching and learning. Educators at the University of Syndey are trialling Cogniti, a new generative AI platform that allows teachers to feed in resources so that the content it produces is relevant and accurate. This new tool means that students aren't required to pay for the software or create an account, reducing unequal access to the technology and thereby helping to support excellence and fairness in the learning experience.

Reducing the Burden

So, while some may fear that automation is replacing the need for human labour, the use of AI in higher education is indicating that the opposite is true. By eliminating manual processes and providing actionable data, AI can be used to decrease administrative burden and allow service leader to focus on 'the big picture'. This extends into the realm of student experience, teaching and learning: researchers at the University of Surrey, for example, are utilising KEATH.ai to streamline educational assessments.

Seeing the Forest for the Trees: Data-Driven Decisions

The use of AI in higher education has the power to provide insight that can inform strategic planning. This ensures that the decisions made by professional service leaders are supported by data for greater impact.

AI can support this because it has the ability to analyse large sets of data from a variety of sources, such as student transcripts, course evaluations and enrolment trends. This creates immense opportunity for practitioners across different departments to plan and deliver based on trends and forecasting.

Student Engagement

One way in which the use of AI is being rolled out in higher education to make data driven decisions is through the provision of student engagement data. Many universities already access this insight from their learning systems or virtual learning environments (VLEs).

Importantly, this kind of use of AI has to capacity to identify students who might be at risk of dropping out or experiencing mental health issues. At Georgia State University in the US, professionals are using predictive analytics to track their undergraduates, identify at-risk behaviours and trigger alerts to advisers, who then intervene and offer students support. While this is a relatively new initiative, it's hoped that this intervention can support students to remain engaged in their education and create a pastoral student experience that is equally supportive, thereby helping to support student success, progression and retention.

Similarly, in the UK context, Jisc reports the use of tools such as Re-Up and Signal Vine to identify at-risk students and ensure they have access to open communication with universities. In addition to this, they also note the use of further technologies such as Ida and n-Powered to show how students can ask questions about student services and receive prompt answers.

Equality, Diversity and Inclusion

It's not just through engagement data that professionals in higher education are using AI's capacity for insight. At King's College London , researchers are trialling how AI can be used to gathered students' opinions on how to close the degree awarding gap . AI's capacity to glean data using language processing source meant that researchers could spend less time collecting and organising data, and more time analysing it - and developing responsive policies. The use of AI in this scenario also removed some of the power imbalances that can occur in student-staff interactions, encouraging more honest opinions and increased engagement from students.

However, the researchers from this project are keen to point out some of the limitations that AI has when it comes to EDI policy. In order for it to be inclusive, AI technology must be trained using diverse and representative data, to ensure it does not discriminate on characteristics such as race and gender.

Predicting the Future

Finally, predictive analytics is an advanced form of AI that is being used by higher education professionals across the sector. From HE marketers using insight to understand their audience, to staff monitoring academic performance to flag students who are at risk of failing, the technology is starting to become widely used across a number of services.

Intelligent forecasting can also be implemented to tackle some of the challenges the sector is facing right now, such as the student accommodation crisis . An insightful example comes from Bournemouth University, where staff have developed a unique analysis model that allows them to predict what demand for student housing will look like in the future. As a result, the university has been able to plan accordingly and offer a support package to students who were unable to secure long-term accommodation before the beginning of the academic year.

So, not only does the use of AI in higher education save valuable time for professional service teams, but it also guides them to make decisions that are informed by data and evaluation. This enables services to ensure effective resourcing and that their interventions and initiatives are having impact.

Data Democratisation

With AI may also come the opportunity to democratise access and use of data across universities. The University of Law has been exploring this possibility , to see how using generative AI tools can help to cultivate a data-friendly culture, provide tools and training for staff and empower staff to use data as a self-service resourced to make informed decisions.

When all staff have access to valuable data and are empowered to use it, it can lead to enhanced strategic planning that is backed up by facts. As a result, professional service teams can work towards enhancing the student experience.

Future Uses of AI for Professional Service Teams in HE

Here at HE Professional, we are always exploring the latest ideas and evidence on driving enhancement in front-line delivery for students to support professionals in their roles. With the advent of new AI technologies, HE professionals can expect their roles to change. While there may be challenges, as this article has explored, the use of AI in higher education offers a variety of opportunities that will allow professionals to deliver greater impact. Ensuring the sector is at the forefront of digital transformation is key to providing an excellent student experience.

If your institution is at the beginning of its AI journey and you aren't sure where to start, Jisc have a plethora of resources handy. Check out their blog article on first steps towards effective use of AI in HE and their maturity model for AI in tertiary education.

To explore in detail what a whole university approach to generative AI may look like, join us for A Whole University Approach to AI on 21 March 2024. This interactive virtual conference will examine the next steps in designing clear expectations and guidelines, and constructing an institution-wide view on equity, ethics and usage of AI.

Find out how you can attend this event and many more as part of a HE Professional membership.

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Understanding the Use of Artificial Intelligence (AI) in Higher Education - HE Professional

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Artificial Intelligence is asking some big questions around the future of higher education provision. But what does the use of AI mean for professional service leaders and practitioners in the sector?

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Definition of AI

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What Is Artificial Intelligence (AI)? | Built In

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Artificial intelligence refers to computer systems capable of performing tasks that are typically thought to require human intelligence.

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Another great overview on AI

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AI Literacy: Webinar 1 - What is Generative AI and how do we use it?

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Access recordings from the full JISC webinar series, including sessions on:

What is generative AI and how do we use it?

AI Safety

AI for Accessibility

Everyday AI Tools

Getting Creative with Generative AI

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AI Literacy Webinar Series: How to Access the Recordings and Presentations - Artificial intelligence

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Watch our AI Literacy Webinar Series which is designed to equip educational staff with an understanding of generative AI. It will look at what generative AI is, considerations when using it and how to use it through effective prompting.

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Link to sign up to SCONAL AI coffee mornings, and access past recordings (will need to create a free SCONAL account to access these)

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SCONUL | Society of College, National and University Libraries

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We provide leadership and support to our community through advocacy, policy development, sharing knowledge and good practice and direct services to members.

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This session will focus on how we can use AI effectively in our own teaching and professional practice. Some questions you might want to think about ahead of the session are:

What everyday ways have you found AI to be useful for saving time/enhancing productivity?

What more creative uses of AI have you heard of or tried?

How can we develop our own AI literacy and skills?

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This is quite long, but it is a useful read for how the law profession already uses AI and how it is likely to change in the future. This is from 2018 so we can 100% expect that this is now all happening.

One of the conclusions is that there will be fewer roles for more junior employees as presumably AI can do some of that work better. So even if our students aren't interested in AI, they must be focused on other employability if there is going to be a lack of jobs for them.

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This horizon scanning report examines the potential influence of artificial intelligence (AI) technology in legal services and its impact on legal processes, jobs and values.

The term AI can be applied to computer systems which are intended to replicate human cognitive functions.

In particular, it includes 'machine learning', where algorithms detect patterns in data, and apply these new patterns to automate certain tasks.

There are rapid developments in artificial intelligence that will have significant implications, both for the legal profession and a number of areas of the law itself.

This report explores developments including:

document analysis

contract intelligence

document delivery

legal adviser support

clinical negligence analysis

case outcome prediction

public legal education

This page was printed on 10/07/2024 and the up-to-date version can be found online at https://www.lawsociety.org.uk/topics/research/ai-artificial-intelligence-and-the-legal-profession

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Artificial intelligence (AI) and the legal profession

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Our report examines the potential influence of artificial intelligence (AI) technology in legal services and its impact on legal processes, jobs, and values.

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Another long one but it has an index!

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Kings College London - guidance for students on Generative AI

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Kings College London - guidance for students on Generative AI

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This was shared with the study skills team as an excellent exemplar of good practice

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Teaching resource on the intersections of gender, race and ethnicity within the realm of AI

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Teaching resource on the intersections of gender, race and ethnicity within the realm of AI

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#Take5 #105 - Unveiling “Generative AI: a problematic illustration of the intersections of racialized gender, race and ethnicity” - ALDinHE

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This blog is brought to you from Nayiri Keshishi (Senior Lecturer in Learning Development, University of Surrey) and Dustin Hosseini (Learning Innovation

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Because artificial intelligence will likely become the primary way humans access information, professors must prepare students to use the technology effectively in their lives and careers.

Students will especially need to learn skills related to effective prompt engineering, which refers to the ability to craft questions that elicit the most useful answers from AI platforms.

The more comfortable that faculty become with using AI, the better they will be at teaching students how to use this skill ethically and effectively in the years to come.

While ChatGPT has only recently captured public attention, artificial intelligence (AI) is not new. Some form of the technology has been around since the mid-20th century. However, the fact that AI is now being used for more applications and is more accessible to the general public has changed the conversation, as we realize that the technology will have a significant impact on 80 percent of jobs -including teaching.

Indeed, in the very near future, AI models will likely be the primary way we access knowledge-and higher education institutions will be where many people learn to use the technology effectively. This new reality makes it clear that it's time for educators to master a new skill set relevant to AI and to teach those skills to their students.

Model the Technology

Although many learners are experimenting with AI models such as ChatGPT, the first place most learners should learn how to use AI effectively is in the classroom. But this will happen only if schools have introduced relevant learning activities into their curricula and have linked those activities to appropriate learning objectives.

However, because many faculty are not comfortable using AI, they will need to learn how to integrate the technology into their classrooms. Schools can start by showing students and faculty how AI can be viewed as an ally, rather than an enemy. To convey this message, schools can take several steps to expose students and staff to the technology:

Create seminars to train faculty in how to introduce use cases of AI and how to emphasize the benefits and limitations of this technology.

Use learning experience platforms (LXPs) that leverage adaptive learning and AI processes that allow faculty to detect when students are having difficulty with the material and to customize their courses. Faculty can use feedback from an LXP to help students gain a deeper understanding of their weaknesses and enhance academic outcomes.

Use robotic process automation (RPA) systems to automate repetitive tasks, such as the students' submission of assignments to correctors. Such automation frees up faculty's time so they can concentrate on their primary missions.

Delegate to AI other routine administrative tasks, such as accepting admissions forms and generating emails and automatic replies, allowing staff more time to offer individualized support to learners.

Perfect the Art of 'Prompt Engineering'

Once faculty are comfortable with the technology, the most critical competency they will need to teach is the art of prompt engineering -the skill of formulating questions in ways that elicit the most useful answers. Effective prompt engineering encompasses the following areas where both faculty and their students will need to refine their knowledge and abilities:

Large language models (LLMs). Understanding LLMs-the algorithms that lie behind the output of generative AI-is a vital component to harnessing the potential of and tailoring interactions with ChatGPT. Only through meticulous and unambiguous prompt construction can users elicit desired responses from the language model.

That makes it critical that faculty incorporate the use of platforms such as ChatGPT into their classrooms. Then, they can teach students how to steer ChatGPT's output toward their intended objectives. For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human. To do this, they must first understand how LLMs work.

Communication. Students might view effective communication as less important when they are inputting a prompt into ChatGPT than when they are interacting with their professors or peers. But providing clear and explicit instructions in an AI prompt is just as essential as providing clear instructions to colleagues-good communication helps users streamline their interactions with AI.

Faculty can help students learn how to refine their questions to achieve increasingly precise responses (known in research as an iterative approach). They will learn to establish context, define the task, and specify the desired outcome for the language model.

For students, the goal is to interact with ChatGPT as if they were engaging in a conversation with a human.

The better students are at communicating with AI, the more likely it is that they will have seamless and rewarding learning experiences as they use AI to deepen their understanding of complex concepts, find solutions to problems, or explore new areas of knowledge.

Contextualization. When it comes to mastering prompt engineering, contextualization can be just as important as an iterative approach. With this skill, students will provide relevant factors and background information within the prompt to help the language model understand the specific context of each query. By setting the stage and giving necessary details, they increase the chance of receiving accurate and meaningful responses.

Role-playing. Here, students learn to assume different personas or perspectives in different prompts. This can help students obtain responses that align with specific viewpoints or generate creative outputs based on the chosen character.

Those who learn the skills listed above will become adept prompt engineers who will make the most of this technology in a variety of job roles and situations. They will be able to use AI effectively to streamline the problem-solving process, achieve a specific result, or improve their overall job performance. But faculty can set them up for success only by embracing ChatGPT and generative AI in the classroom, as pedagogical tools to help students exercise and expand their critical thinking abilities.

Disrupting Traditional Teaching Models

It's an understatement to say that AI technology is having a seismic effect on faculty. It clearly is disrupting traditional teaching methods and practices, so much so that many faculty initially reacted by banning its use in their classrooms. But just as ChatGPT offers students a new way of learning, it compels faculty to adopt a new way of teaching.

In fact, there is immense potential in utilizing ChatGPT as a practical learning tool to foster and enhance students' creativity and design thinking. If faculty incorporate relevant exercises into their courses, students can learn to use AI not only to write better questions and generate more innovative ideas, but also to discover the technology's limitations.

So, how should faculty embrace AI in their classrooms instead of banning its use? They can adopt evolved pedagogical models that use AI to develop skills in several areas:

Assessment. The rise of AI will inspire the revision and rethinking of teaching and assessment methods. Faculty can use AI platforms to diversify student assessments, including formative, normative, and ipsative evaluations. They can even use AI to assess the new set of skills related to AI itself. These skills include the development of analytical mindsets, familiarity with intelligent user interfaces, the ability to look beyond statistics to instead use predictive analytics, and an understanding of artificial neural networks.

However, while looking at students' final deliverables in a particular course still will be an important part of assessment, those deliverables will not be the only measure of student learning. The objective should shift from focusing on deliverables to evaluating the different stages of the learning process itself.

Faculty can use AI to streamline their own workloads, turning to ChatGPT to handle repetitive tasks while they concentrate on the most valuable aspects of teaching and learning

In other words, educators will need to do more than confirm that students solved a problem when they assess student learning. Educators also will need to ask students to explain how and why they solved a problem in a particular way. For example, faculty can ask learners to detail how they have used AI tools to create their deliverables-from case studies and analyses to full-length dissertations. Learners also could share whether they found the technology useful and how they adjusted to make AI work for them.

Critical thinking. Using AI as a complementary tool may improve students' learning process while challenging their critical thinking abilities. Encouraging human-machine collaboration reinforces a student's ability to adapt the technology to any environment or job role.

Adaptability. There is an urgent need to prepare the future users, designers, and shapers of these technologies to keep up with the pace of change. An essential part of teaching students to use AI is to introduce them to new platforms and functionalities as these innovations arise.

Better yet, faculty also can use AI to streamline their own workloads. They can turn to ChatGPT to handle the repetitive tasks. They can use the platform for help writing syllabi, for example, while they concentrate on the most valuable aspects of teaching and learning: adopting innovative pedagogy, nurturing creative thinking and problem-solving abilities, and ensuring that students develop essential future skills.

AI Is Here to Stay

It is inevitable that faculty increasingly will be working hand-in-hand with AI models to support their teaching. For that reason, higher education institutions must support faculty as they face this new challenge and do as much as possible to make that collaboration a success.

In essence, university faculty are, in a sense, gardeners who are nurturing two different seeds in fertile ground. On the one hand, they are developing AI-ready students; on the other, they are shaping the future use of AI technologies. Faculty might not be able to stop the AI trend from growing, but in this role, they can direct its growth by preparing students to use it as effectively and ethically as possible.

In the coming years, it will be interesting and enriching to observe how faculty teach AI models, as well as how students decide to use AI models to solve problems in the classroom. The technology might also help us address one of the more challenging aspects of teaching: how to engage students in their learning process.

Students will need to master the competencies we outline above if they are going to be able to work effectively with AI. In fact, we believe that as faculty and students experiment more with AI models, they will come to view the technology not as a threat, but as a teammate in their work.

The more schools enable faculty and students to strengthen their technological skills, the more they will support successful AI-human interactions. And the more they support these interactions, the faster we all will accelerate a shift in our mindset, from merely assessing AI's capabilities and implications to improving and refining the way we use it.

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How AI Is Reshaping Higher Education | AACSB

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With the rise of generative artificial intelligence, students need to develop new skills-and educators need to embrace new ways of teaching.

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Empowering Future-Ready Students: Teaching AI Ethics and Information Literacy through Scaffolded Assignments

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Empowering Future-Ready Students: Teaching AI Ethics and Information Literacy through Scaffolded Assignments

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Paper from LILAC 2024 by Hanna Primeau & Amanda Larson, from the Ohio State University

More details on the assignments here: https://librarianyarns.notion.site/Empowering-Future-Ready-Students-Teaching-AI-Ethics-and-Information-Literacy-through-Scaffolded-Ass-3a0e1ebcf52c40478c8c6f77754f579f

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Empowering Future-Ready Students: Teaching AI Ethics and Information Literacy through Scaffolded Assignments - Hanna Primeau, Amanda Larson

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Empowering Future-Ready Students: Teaching AI Ethics and Information Literacy through Scaffolded Assignments - Hanna Primeau, Amanda Larson - Download as a PDF or view online for free

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This session aims to explore how AI is impacting learning and teaching within the wider academic community at ULaw, while also giving participants at the L&T conference the chance to participate in a TC session.

Some questions you might want to think about during the session are:

How is AI impacting learning and teaching within your programme, discipline or team?

How can colleagues across the University work together to support students to become AI literate?

How do you use AI within your own teaching/professional practice and how can we share best practice around this?