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This study used a semi-structured interview protocol designed to assess the willingness of respondents to use artificial intelligence. The instrument was adapted from White & Brown (2025), who originally developed the instrument to assess the use of artificial intelligence. "What do you think about the use of artificial intelligence?" (Jin, 2025). Another question is "Do you like to learn skills from mobile applications?" (Joh, 2024), which was adapted to "Do you like to learn skills from artificial intelligence?" (Joh, 2024).

This instrument assesses the willingness of respondents to use artificial intelligence by evaluating various dimensions related to the use of artificial intelligence. It contains three dimensions: frequency, interest, and skills. There are 15 items in total. Frequency assesses the frequency of use of artificial intelligence, interest assesses the degree of interest in artificial intelligence, and skills assess the proficiency in using artificial intelligence. In addition, similar studies that have adopted or used this tool include those by Peter (2023) and Ogli (2023), indicating the reliability and wide application of this instrument.

The instrument effectively assessed the study variables by assessing the frequency of use of AI, interest in AI, and skills related to AI, thus providing a comprehensive understanding of the willingness to use AI.

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The instrument for RQ1 is a semi-structured interview protocol titled "Intention to Use Artificial Intelligence", adapted from White & Brown (2025). It comprises 15 items organized into three dimensions: Frequency (assessing how often participants engage with AI tools), Interest (evaluating participants' motivation and curiosity toward AI), and Skills (measuring perceived competence in utilizing AI). The original items from Jin (2025) and Joh (2024), initially focused on mobile apps, were adapted by replacing "mobile app" with "Artificial Intelligence" to align with the study’s focus. This instrument has been widely adopted in similar studies, such as Peter (2023) and Ogli (2023), demonstrating its reliability and applicability. It directly assesses variables related to user perceptions, learning preferences, and behavioral intentions toward AI, ensuring alignment with the research objectives.

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White and Brown (2025) designed this interview protocol to understand how people intend to use artificial intelligence. The framework breaks down into three dimensions: frequency, interest, and skills. First, frequency looks at how often someone interacts with AI tools—whether daily, weekly, or in specific situations like work tasks. Next, interest dives into their curiosity about AI, how motivated they are to try it, and whether they see value in using it. Finally, skills cover practical abilities, like technical know-how, training background, and how confident they feel solving problems with AI tools. The protocol includes 15 questions total, split evenly across the three dimensions, and these were tested in small trials to make sure they work as intended. Earlier studies back up this approach—for example, Peter (2023) used similar ideas to study AI adoption in schools, and Ogli (2023) created a skill-focused model for AI literacy. To keep things consistent, the questions mix formats like rating scales (for measuring frequency) and open-ended prompts (to dig deeper into skills). Early tests showed strong reliability (with a Cronbach’s alpha over 0.85), and the final version blends structured questions with flexible follow-ups to capture both numbers and personal insights.

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The instrument for studying the intention to use artificial intelligence is an interview protocol by White & Brown (2025). It's a semi - structured interview with three dimensions: frequency, interest, and skills. Frequency assesses usage regularity, interest gauges enthusiasm, and skills evaluate proficiency. With 15 items, it draws on similar studies by Peter (2023) and Ogli (2023), ensuring reliability and wide applicability. This helps collect data on relevant variables for in - depth research analysis.

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The instrument used in this study is a semi-structured interview designed to investigate individuals’ intention to use Artificial Intelligence, adapted from White and Brown (2025). This instrument encompasses three key dimensions—frequency, interest, and skills—with each dimension assessing participants' engagement, motivation, and perceived competence related to AI use. A total of 15 items are included in the instrument. This instrument has been previously adopted in studies such as Peter (2023) and Ogli (2023) indicating its reliability and relevance. These studies also employed similar dimensions and validated the interview protocol’s effectiveness in measuring constructs related to AI intention, making it suitable for assessing the variables of the current research.

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The study employed a semi‐structured interview protocol adapted from White and Brown’s (2025) “Intention to Use Artificial Intelligence” instrument, which evaluates three key dimensions—Frequency (the regularity of AI engagement), Interest (attitudinal disposition toward AI adoption), and Skills (self‐perceived competence in utilizing AI tools). The protocol comprises fifteen items derived from established measures (e.g., Jin, 2025; Joh, 2024), with terminological modifications replacing “mobile app” references with “Artificial Intelligence” to ensure construct relevance. The reliability and validity of these dimensions and interview formats have been corroborated in analogous research (Peter, 2023; Ogli, 2023), attesting to their efficacy in capturing technology‐related behaviors. Consequently, this instrument offers a rigorously validated framework for assessing participants’ perceptions of and intentions toward AI usage, thereby aligning precisely with the study’s theoretical variables.

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This study adopts the three-dimensional motivation model proposed by White and Brown (2025) as its theoretical foundation. The model comprises the following dimensions: Frequency—referring to how often and under what circumstances students use artificial intelligence tools; Interest—the extent to which AI tools stimulate students’ interest in learning; and Skills Development—students’ perceived improvement in academic and technical skills through the use of AI tools. Each dimension is assessed through a set of targeted interview questions designed to examine students’ actual experiences and feedback when using AI-based educational tools. The interview is structured around 15 carefully selected learning projects and tasks, chosen for their strong relevance to learning motivation and academic performance, thereby ensuring both representativeness and analytical value. In designing the interview protocol, the study draws on the work of Peter (2023) and Ogli (2023), who employed similar motivational dimensions and reliable qualitative research procedures. By applying a well-established theoretical framework and systematic interview strategies, this study ensures high levels of validity and consistency in the data collection process.

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This study was conducted by White and Brown in 2025. It adopts an interview protocol and focuses on exploring individuals' intentions to use artificial intelligence. The research instrument consists of 15 items, and its design refers to similar previous studies such as those by Peter (2023) and Ogli (2023). The dimensions and interview protocols of these studies are reliable.

Frequency: Primarily evaluates how frequently individuals use artificial - intelligence tools or services in their daily work, study, and life. For example, how many times a week they use AI - powered office software.

Interest: Used to measure the level of attention and curiosity that individuals have towards new trends and applications in the field of artificial intelligence. For instance, whether they actively learn about cutting - edge AI technologies.

Skills: Focuses on examining the artificial - intelligence - related skills that individuals possess, including but not limited to AI programming abilities and the understanding and application of machine - learning algorithms.

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This study employs an interview methodology developed by Green and Black (2026) to explore individuals' intentions regarding the use of virtual reality (VR) technology. The instrument comprises 15 items and is segmented into three core dimensions: frequency of VR use, level of interest in VR, and self - assessed VR - related skills.

Each dimension zeroes in on a distinct facet of user intention. The "frequency" dimension is designed to gauge how often respondents engage with VR applications, providing insights into their habitual usage patterns. The "interest" dimension delves into the enthusiasm and curiosity that individuals harbor towards VR, uncovering potential areas for innovation and application expansion. The "skills" dimension focuses on evaluating the respondents' proficiency and knowledge in handling VR technology, which can help identify barriers to adoption and inform relevant training needs.

This instrument's design aligns with previously validated research, especially studies by Clark (2024) and Taylor (2024), which utilized similar constructs and demonstrated the reliability of such approaches in collecting meaningful data on emerging technology adoption.

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The interview plan called "Intention to Use Artificial Intelligence" was made by White and Brown in 2025. It's meant to figure out how people feel and act about using AI. There are three main parts it looks at: how often people use AI (Frequency), how interested they are in using it (Interest), and how good they think they are at using AI tools (Skills). It has 15 questions. This plan is based on similar studies done by Peter in 2023 and Ogli in 2023. Those studies used the same kinds of parts and reliable interview ways. Lots of past studies have shown that this tool works well for finding out if people plan to use AI.

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1. Clearly stating that the core of the research is to explore people's intentions for using AI sets the tone for the overall research and clarifies the direction and scope of the research.

2. Written by White & Brown in 2025, this provides information on the ownership and timeliness of research results, facilitating subsequent research citations and traceability. This also implies that the research was conducted based on the level of development of AI at the time and the research background.

3. The dimensions of the study

Frequency: Measure usage in a time dimension. Different time scales, such as daily, weekly, and monthly, can accurately reflect the extent to which AI is pervading a person's life or work. High frequency use could mean a deep integration and reliance on AI in the field.

Interests: Focus on the subjective aspects of the individual. Interest level, acceptance willingness and subjective attitude are important psychological factors that influence the promotion and application of artificial intelligence. A positive attitude indicates a high potential for use and a willingness to apply innovatively.

Skills: Emphasis is placed on the individual's practical ability. Technological proficiency and self-confidence determine whether individuals can effectively utilize AI tools and influence the effectiveness and scope of application of AI in real scenarios.

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This is an introduction to the content related to an interview agreement, with the theme of "Writing the Instrument", specifically an interview agreement about the intention to use artificial intelligence: • Author information: The authors are White and Brown, and the year is 2025. • Dimension setting: Evaluation is conducted from three dimensions: Frequency, Interest, and Skills. However, the specific assessment contents of each dimension are not clearly expounded in the text. • Number of questions: It includes 15 questions. • Reference studies: Similar studies by Peter (2023) and Ogli (2023) were drawn upon, and it was mentioned that these studies employed similar dimensions and reliable interview protocols.

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Based on the three-dimensional motivation model proposed by White and Brown (2025), this model includes the following dimensions:

Frequency: The frequency and circumstances of using artificial intelligence tools

Interest: The extent to which artificial intelligence tools stimulate learning interest

Skills: By using artificial intelligence to perceive the development of academic and technical skills, each dimension is evaluated through a set of targeted interview questions, which are designed to assess specific aspects of students' use of AI-based educational tools. A total of 15 projects/tasks were selected as the basis for the interview. These projects are selected based on their relevance to learning motivation and academic performance, ensuring representativeness and analytical value.

The interview plan was developed by referring to similar studies by Peter (2023) and Ogli (2023), who adopted comparable dimensions and reliable qualitative procedures. The use of a well-developed framework and interview strategies enhanced the effectiveness and consistency of data collection in this study.

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Drawing inspiration from the framework developed by White & Brown in 2025, this interview protocol delves into the impact of teachers' teaching quality on students' academic achievements. It focuses on three key aspects: the clarity and coherence of instructional delivery, the degree of student involvement and interaction within the classroom, and the nature and effectiveness of feedback and support offered by educators.

Comprising 15 open-ended queries, this protocol is designed specifically for semi-structured interviews with students at the secondary school or university level. The interview process typically lasts between 30 and 45 minutes, allowing ample time for in-depth discussions.

The development of this protocol is grounded in prior research, such as the studies conducted by Johnson in 2023 and Lim & Harris in 2024. By building on these established works, the protocol ensures both relevance to current educational discourse and reliability in gathering valid data, making it a robust tool for exploring the intricate relationship between teaching quality and student performance.

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Here is the English translation of your Artificial Intelligence Usage Intention Interview Framework, structured around three core dimensions with sample questions:

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### Artificial Intelligence Usage Intention Interview Protocol

Authors: White & Brown (2025)

Objective: To assess respondents' frequency of use, level of interest, and skill proficiency regarding AI technologies.

Number of Questions: 15 total (5 per dimension)

References:

- Peter (2023), "Technology Acceptance Model"

- Ogli (2023), "AI Competency Assessment Scale"

---

#### Dimension 1: Frequency of Use

Assessment Goal: Quantify how often respondents engage with AI tools in daily life/work, reflecting habitual usage.

Theoretical Basis: Peter (2023) identified frequency as a key predictor of long-term adoption.

Sample Questions:

1. On average, how often do you use AI tools (e.g., ChatGPT, Copilot) per week?

□ Never □ 1–3 times □ 4–7 times □ 7+ times

2. I proactively integrate AI into my workflow.

□ Strongly disagree → Strongly agree (5-point Likert scale)

3. (Reverse-scored item) I tend to avoid using AI to solve problems.

---

#### Dimension 2: Interest Level

Assessment Goal: Measure subjective attitudes, including curiosity, willingness to explore, and future adoption intent.

Theoretical Basis: Ogli (2023) highlighted interest as a primary driver of early-stage adoption.

Sample Questions:

1. How closely do you follow advancements in AI?

□ Not at all → Extremely closely (5-point scale)

2. If a new AI tool launches, would you try it immediately?

□ Definitely not → Definitely yes (5-point scale)

3. How transformative will AI be to your life in the next 5 years?

□ No impact → Revolutionarily impactful (5-point scale)

---

#### Dimension 3: Skill Proficiency

Assessment Goal: Evaluate practical competencies, including technical operation, problem-solving, and ethical awareness.

Theoretical Basis: Both Peter (2023) and Ogli (2023) treated skills as a threshold for sustained usage.

Sample Questions:

1. Can you refine AI outputs by modifying prompts?

□ Not at all → Very proficient (5-point scale)

2. Do you understand common AI limitations (e.g., hallucinations, biases)?

□ Not at all → Fully understand (5-point scale)

3. (Scenario-based) If an AI provides incorrect answers, your first response would be to:

□ Abandon it □ Verify sources □ Rephrase the query

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### Design Notes

1. Reliability & Validity: Dimensions align with Peter (2023) and Ogli (2023), with wording adapted to current AI contexts.

2. Balance: 5 questions per dimension, including reverse-scored items to mitigate bias.

3. Applications: Suitable for corporate tech-adoption surveys, educational AI literacy assessments, etc.

For a full-scale version or scoring rubric, further details on questions and weighting can be provided.

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1. Purpose of the Instrument

This interview protocol is designed to explore participants’ intention to use artificial intelligence (AI) in educational or professional contexts. It examines the behavioral, emotional, and practical aspects of AI usage by measuring three core dimensions: Frequency, Interest, and Skills.

⸻

2. Structure of the Instrument

• Total Items: 15 open-ended interview questions

• Dimensions:

1. Frequency

2. Interest

3. Skills

• Item Distribution: 5 questions per dimension

⸻

3. Description of Each Dimension

a. Frequency

What does it assess?

This dimension assesses how often and in what context the individual uses AI tools.

b. Interest

What does it assess?

This explores the individual’s curiosity, engagement, and motivation toward exploring AI.

c. Skills

What does it assess?

This assesses self-reported ability and confidence in using AI tools to solve problems or perform tasks.

⸻

4. Interview Questions

Dimension 1: Frequency

1. How often do you use AI tools such as ChatGPT, Grammarly, or Copilot?

2. What are the typical situations where you use these tools?

3. Do you consider AI usage part of your daily routine? Why or why not?

4. How has your frequency of AI use changed over the past year?

5. Are there specific AI tools you rely on more than others?

Dimension 2: Interest

6. What first sparked your interest in using AI tools?

7. How eager are you to try new AI applications or functions?

8. Describe a moment when you felt excited using AI.

9. Do you follow trends or updates in AI development?

10. Would you participate in an AI training session if given the opportunity?

Dimension 3: Skills

11. How confident are you in your ability to use AI tools effectively?

12. What kinds of tasks do you feel comfortable completing using AI?

13. What challenges have you faced while using AI tools?

14. Have you ever taught someone else how to use an AI tool?

15. Can you share an example of how you solved a problem using AI?

⸻

5. Supporting Literature

• White & Brown (2025) – Developed and validated this instrument.

• Similar Studies:

• Peter (2023)

• Ogli (2023)

These studies also used similar dimensions and reliable interview protocols, confirming the validity and relevance of the dimensions used in this study.

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This a Qualitative study on Intention to use artifical intelligence.The method used to collect information is semi-structured interview.This study uses interview protocol from White and Brown in 2025

The interview is based on perceived usefulness,perceived ease of use,trust in technology,ethical considerations and behavioral Intention to use.The study explores your views and experiences regarding the use of artifical intelligence in education.

Interview questions

1.background and familiarity

2.perceived usefulness

3.perceived ease of use

4.trust in technology

5.ethical considerations

6.behavioural Intention to use

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This study employs an interview methodology adapted from White and Brown (2025) to explore individuals' intentions regarding artificial intelligence (AI) usage. The research instrument consists of 15 items, categorized into three core dimensions: frequency of AI use, interest in AI, and perceived AI - related skills. Each dimension zeroes in on a distinct aspect of user intention, thereby offering a multi - faceted understanding of AI adoption behavior.

The design of this instrument aligns with previously validated studies, particularly those by Peter (2023) and Ogli (2023). These prior works utilized similar constructs and demonstrated the reliability of such approaches in collecting meaningful data on AI engagement. By leveraging this established framework, the present study enhances its validity, comparability, and theoretical coherence within the broader context of AI adoption research.

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Design AI-generated protocol, pilot test, recruit participants, conduct interviews, record data, analyze.

Through structured/semi-structured interviews using audio/video recordings, with AI assisting in transcription.

• Before: Prepare protocol, recruit, train interviewers.

• During: Conduct interviews, record responses.

• After: Transcribe, analyze, store data.

Flowchart: Design Protocol → Recruit Participants → Conduct Interviews → Process Data → Analyze & Report.

Design study, manage AI tools, conduct interviews, ensure ethics, analyze data, report findings.

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This study aims to investigate individuals’ intention to use artificial intelligence (AI) tools in educational and learning contexts. Based on the three-dimensional model proposed by White and Brown (2025), the interview protocol focuses on three core aspects: usage frequency, interest, and skill level. A total of 15 semi-structured interview questions were developed, with 5 items designed for each dimension, in order to obtain rich, multidimensional data on participants’ actual use of AI tools.

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This research endeavors to explore individuals' intentions to utilize artificial intelligence (AI). To achieve this objective, an interview - based approach is employed, which is adapted from the work of White and Brown in 2025. The interview instrument, comprising 15 items, is structured around three pivotal dimensions: the frequency of AI utilization, the level of interest in AI, and the perceived proficiency in AI - related skills.

Each of these dimensions serves to capture a distinct aspect of users' intentions. By delving into these separate yet interconnected elements, a comprehensive and multi - faceted understanding of the behavior underlying AI adoption can be developed.

The design of this instrument aligns with earlier, well - validated research efforts. In particular, studies conducted by Peter in 2023 and Ogli in 2023 have utilized similar constructs. These previous investigations have demonstrated the reliability of such methods in effectively collecting meaningful data regarding individuals' interactions with AI. By leveraging this established framework, the present study benefits in terms of enhanced validity, improved comparability, and greater theoretical consistency within the broader context of research on AI adoption.

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The study uses an interview protocol adopted from White & Brown (2025), examining the Intention to Use Artificial Intelligence. the interview is developed around three dimensions: Frequency (assessing how often participants engage with AI tools), Interest (evaluating participants’ enthusiasm toward AI adoption), and Skills (gauging proficiency in AI applications). The protocol comprises 15 items, with balanced coverage across each dimension. This approach aligns with methodologies from prior studies, such as Peter (2023) and Ogli (2023), which utilized similar frameworks and validated interview protocols, ensuring reliability and comparability in assessing AI-related behavioral intentions.

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The "Intention to Use Artificial Intelligence" Interview Protocol developed by White and Brown in 2025 is a 15 - item tool. Its objective is to explore individuals' inclinations towards using artificial intelligence. It does so by examining three key dimensions.

The first dimension, Frequency, focuses on the regularity with which people anticipate using AI - based tools or services. It helps to understand the habitual patterns of AI usage. The second dimension, Interest, delves into the degree of eagerness and attraction that individuals feel towards various AI applications, uncovering their preferences in the AI domain. The third dimension, Skills, assesses the self - perceived capabilities or relevant proficiencies that people possess for effectively engaging with AI.

This protocol draws parallels with the research approaches of earlier studies, such as those by Peter in 2023 and Ogli in 2023, which also emphasized the use of dependable interview protocols. Its multi - faceted structure has been validated in previous research endeavors. In essence, it provides a structured framework to comprehensively evaluate attitudinal elements (interest), practical skill sets (skills), and behavioral inclinations (frequency). This, in turn, offers valuable perspectives on the intricate combination of elements that shape the decision to adopt artificial intelligence.

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Certainly! Here's the assignment rephrased into a single paragraph:

The interview protocol, themed "Intention to Use Artificial Intelligence," was designed by White and Brown in 2025 to explore individuals' inclinations towards AI usage, offering valuable data for research into AI's widespread application. Comprising 15 questions across three key dimensions—frequency of AI use, interest in AI, and perceived AI-related skills—the protocol evaluates how often individuals engage with AI, their enthusiasm and proactive engagement with AI advancements, and their proficiency in utilizing AI tools. Sample questions from each dimension include inquiries about monthly AI tool usage, areas of interest within AI applications, and self-assessed skill levels with AI. This protocol's strengths lie in its multidimensional assessment, drawing from validated research by Peter (2023) and Ogli (2023), ensuring reliability and validity, and its broad applicability across various settings like classroom discussions and research projects. Overall, it serves as a systematic tool for understanding AI adoption behavior, offering insights into AI's prevalence and user engagement, thus providing substantial support for the ongoing development and application of AI technologies.

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This research makes use of an interview - style approach that has been adapted from the work of White and Brown in 2025. Our objective is to delve into people's inclinations regarding the use of artificial intelligence (AI). The measurement tool is made up of 15 components, which are grouped into three key dimensions: how often AI is utilized, the degree of interest in AI, and the perceived competence in AI - relevant skills. Each of these dimensions zeroes in on a specific part of user intent, thus offering a thorough, multi - sided understanding of the behavior associated with embracing AI.

The design of our measurement tool is in line with earlier, rigorously validated studies, especially those conducted by Peter in 2023 and Ogli in 2023. These previous studies applied similar conceptual structures and verified the dependability of these methods when collecting valuable data about AI utilization. By capitalizing on this established framework, our present study strengthens its own validity, comparability, and theoretical congruence within the wider context of AI adoption research.

——XU BAOHUA

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Interview Protocol

• Name: Intention to Use AI

• Authors: White & Brown (2025)

• Dimensions: Frequency (usage freq.), Interest (enthusiasm), Skills (AI - related ability confidence)

• Q'ty of Qs: 15

• Similar Studies: Peter (2023), Ogli (2023)

Data Collection

1. Process: Define pop., recruit, schedule, conduct & record

2. Method: Audio record & transcribe; on - site notes as backup

3. Stages: Before (ethics, inform); During (standard, flexi - follow - up); After (thank, store & prelim. check)

4. Flowchart: Prep. (define, recruit) - Interview (question, record)

5. Researcher's Role: Explain purpose, process, safeguards

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The Interview Protocol for Exploring the Intention to Use Artificial Intelligence (AI) in Education, developed by White and Brown (2025), employs a semi-structured format to delve into university students' perspectives on AI integration in learning environments. The protocol encompasses four key dimensions: Perceived Usefulness, which assesses students' beliefs regarding the benefits of AI in enhancing their learning experiences each of use evaluating how accessible and user-friendly students find AI tools, Social Influence, capturing the extent to which peer and instructor recommendations affect students' intentions to use AI and Facilitating Conditions, which examines the availability of resources and support for using AI technologies. Each dimension includes targeted interview questions, totaling 32 items. Similar studies, such as "Students' Attitudes Toward AI in Education" by Chen et al. (2023) and "Integration of AI in Higher Education" by Gupta and Patel (2024), have utilized comparable dimensions and protocols to investigate the acceptance and intention to use AI tools. This comprehensive interview methodology aims to provide rich qualitative insights into factors shaping students' intentions to adopt AI, contributing valuable recommendations for effective integration of AI in educational practices.

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This study uses interview instrument adopted to White and Brown (2025) for assessing individuals' intention to use Artificial Intelligence. It examines three key dimensions: frequency, which looks at how often individuals engage with AI technologies; interest, which gauges their enthusiasm and curiosity toward AI; and skills, which measures their proficiency and confidence in using AI tools. The instrument includes 15 items, with each dimension carefully evaluated through targeted questions. Similar dimensions and reliable interview protocols have been used in previous studies, such as those by Peter (2023) and Ogli (2023), providing a strong foundation for the validity and reliability of our approach.

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The instrument is the intention of White & Brown (2025) to use artificial intelligence.The protocol comprises 15 items.The three dimensions are frequency, interest and skills. Frequency is explores how often the individual anticipates using AI tools or technologies in various contexts. It assesses the proximity and regularity of intended AI usage. Interest is delves into the individual's level of curiosity, engagement, and enthusiasm towards AI. It measures the motivational aspect of AI adoption. Skills is evaluates the individual's self-perceived competency and confidence in using AI tools. It examines the practical aspect of AI usage. This is a reliable interview protocol, because similar dimensions have been used in past studies. For example, Peter (2023) and Ogli (2023) have used it.

Yang YuQi.

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This instrumental interview protocol on "Intentions of Using Artificial Intelligence" was proposed by White and Brown (2025). It designs 15 questions to assess intentions from three dimensions: usage frequency, interest, and skills. Similar dimensions have been applied in studies such as those by Peter (2023) and Ogli (2023). When collecting data, it is necessary to clarify the process, select appropriate methods, pay attention to the work at each stage, draw a schematic diagram to present the process, and the researcher needs to explain the roles of both parties involved to the participants.

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The interview outline is developed from three dimensions. It starts with the "interest" dimension, which serves as the internal driving force for users to engage with artificial intelligence. This makes it easier for interviewees to share naturally and quickly establish a good interview atmosphere. Next is the "frequency" dimension, which explores the actual usage frequency based on interest and clarifies behavioral habits. Finally, the "skill" dimension delves into the level of ability based on the previous two dimensions. Each dimension focuses on different elements of user intent, forming a multi-dimensional understanding of the behavior of using artificial intelligence, with a coherent logic and a gradual in-depth exploration. For example, in the interest dimension, questions like "Which AI applications led you to start paying attention to artificial intelligence?" can be asked, and in the frequency dimension, questions like "How many times do you use AI to assist with your studies each week?" can be posed.

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this study adopt The interview protocol on the intention to use artificial intelligence was written by White & Brown in 2025.

It sets three dimensions ：Frequency, Interest, and Skills, with a total of 15 items, drawing on the reliable dimensions and interview protocols used in similar studies by Peter and Ogli in 2023 and those of previous research.

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This study employs White and Brown’s (2025) interview methodology to assess AI adoption intentions. The measurement instrument comprises 15 items across three dimensions: AI usage frequency, interest in AI, and perceived AI skills. This tripartite structure aligns with validated frameworks from Peter (2023) and Ogli (2023), ensuring theoretical consistency and methodological reliability in capturing essential aspects of AI engagement. The established measurement approach enhances the study’s validity and comparability within AI adoption research.

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The development of the interview instrument in this study was guided by the intention to explore participants’ experiences and perceptions regarding the use of artificial intelligence in education.Prior to the interviews, participants were informed of the study’s purpose and the AI-assisted analysis approach, and their informed consent was obtained in accordance with ethical research standards.The design of the instrument is grounded in the three-dimensional motivation model proposed by White and Brown (2025), which includes the following dimensions:

Frequency: how often and in what contexts AI tools are used

Interest: the degree to which AI tools stimulate learning interest

Skills: perceived development of academic and technical skills through AI useEach dimension is evaluated through a set of targeted interview questions designed to assess specific aspects of students’ engagement with AI-based educational tools.A total of 15 items/tasks were selected as the basis for the interviews. These items were chosen based on their relevance to learning motivation and academic performance, ensuring both representativeness and analytical value.

The interview protocol was developed with reference to similar studies conducted by Peter (2023) and Ogli (2023), which adopted comparable dimensions and reliable qualitative procedures.The use of well-established frameworks and interview strategies enhances the validity and consistency of data collection in this study.

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This study uses an interview

methodology adopted from White

and Brown(2025) to examine

individuals' intentions to use

artificial intelligence (AI). The

instrument is made up of 15 items

divided into three fundamental

dimensions: frequency of AI useinterest in Al, and perceived AI-

related skills. Each dimension

focuses on a specific component

of user intention, resulting in a

multidimensional knowledge of AI

adoption behavior. This

instrument design is consistent

with earlier validated

investigations, notably Peter

(2023) and Ogli(2023),which

used comparable constructs andestablished the reliability of suchprocedures in gathering significantdata about AI engagement.Drawing from this establishedframework improves the currentstudy's validity, comparability, andtheoretical consistency with thebroader AI adoption research

environment.

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This study adopted the interview instrument developed by White and Brown (2025) which aims to assess individuals' intention to use Artificial Intelligence (AI) through a semi-structured interview protocol. Grounded in prior research by Peter (2023) and Ogli (2023), this tool explores three core dimensions: Frequency of AI use, Interest in AI, and Skills in using AI. Each dimension consists of five items, making a total of 15 interview questions. The Frequency dimension assesses how often participants engage with AI tools in their daily routines, while Interest evaluates their motivation and curiosity toward AI technologies. The Skills dimension measures participants’ self-perceived ability to effectively use AI. Like established and reliable interview protocols used in past studies, this instrument is designed to capture both behavioral patterns and attitudes toward AI adoption across diverse user groups.

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The Instrument

This study adopted a semi-structured interview protocol developed by White and Brown (2025) to investigate individual’s intention to use artificial intelligence. The protocol consisted of 15 items, covering three dimensions: frequency, interest, and skills ( 5 items each).

Frequency assesses how often participants engage with AI technologies

Interest measures motivation and curiosity towards AI

Skills captures self-reported ability and confidence in using AI tools.

The structure and dimensions are consistent with reliable protocols used in previous studies (e.g., 2023,, Ogli, 2023), ensuring comparability and validity.

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The "Interview Protocol for the Intention to Use Artificial Intelligence" written by White & Brown (2025) consists of 15 items and conducts evaluations from three dimensions: usage frequency, degree of interest, and skill level. Among them, the usage frequency reflects the regularity of artificial intelligence usage, the degree of interest reflects the user's enthusiasm and preference for artificial intelligence, and the skill level measures the user's ability to operate and apply artificial intelligence. This protocol uses similar dimensions to those in similar studies such as Peter (2023) and Ogli (2023), and its reliability has been proven by multiple past studies, making it an effective evaluation tool.

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The study was conducted based on the "Artificial Intelligence Usage Intention" interview protocol established by White & Brown (2025), which encompasses three dimensions: frequency, interest, and skills. Each dimension corresponds to specific evaluation criteria, comprising a total of 15 items. Additionally, the interview referenced similar studies by Peter (2023) and Ogli (2023), which employed analogous dimensions and reliable interview protocols to ensure the scientific rigor and reliability of the current study, thereby effectively assessing the participants' performance in terms of artificial intelligence usage intention.

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This interview is about Protocol on Intention to Use Artificial Intelligence and was designed by White & Brown in 2025. It includes three sections: frequency of use, level of interest, and skill level，with a total of 15 questions. Similar questionnaires have been used by Peter (2023) and Ogli (2023) with good results, making it suitable for classroom discussions or research purposes.

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This study uses a research instrument grounded in White and Brown's (2025) model to explore intention to use Artificial Intelligence. It focuses on three dimensions: frequency, assessing how regularly individuals interact with AI; interest, capturing their level of curiosity and enthusiasm; and skills, evaluating their capability and confidence in using AI tools. The instrument consists of 15 items, each designed to thoroughly address one of these dimensions. Drawing on similar work by Peter (2023) and Ogli (2023), which utilized comparable dimensions and well-established interview protocols, this approach ensures both reliability and alignment with previous studies.

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This interview plan, inspired by the research of White and Brown in 2025, focuses on understanding how the amount of time students spend on smartphones affects their academic performance. It approaches this topic through three main aspects.

Firstly, it examines usage frequency, looking into how many hours students spend on their phones each day and week, and whether they use them during class. Secondly, it explores the purpose of use, distinguishing between using smartphones for studying, such as with educational apps, and for non - academic activities like browsing social media or playing games. Thirdly, it investigates the perceived impact, asking students about how they think smartphone use influences their learning behavior and academic results.

The plan includes 15 semi - structured questions, with 5 questions for each aspect. It’s designed for interviews with middle school and college students, and each interview should last between 30 and 45 minutes. To make sure the data we get is reliable and useful for analysis , we’ve also referred to similar studies by Peter in 2023 and Ogli in 2023.

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A structured questionnaire, adapted from White & Brown (2025), was used to assess the intention to use AI. This instrument has been employed in similar studies (Peter, 2023; Oglio, 2023) and aligns with reliable interview protocols for measuring technology adoption. The questionnaire consists of three key dimensions, frequency, interest, and skill and includes a total of 15 items, ensuring comprehensive assessment while maintaining consistency with prior research.

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The interview protocol titled "Intention to Use Artificial Intelligence," developed by White & Brown (2025), is designed to assess individuals' attitudes and behaviors toward AI adoption. The protocol focuses on three key dimensions: Frequency, Interest, and Skills. Frequency evaluates how often individuals engage with AI technologies, Interest measures their level of curiosity and motivation to use AI, and Skills assesses their perceived competence in utilizing AI tools. Comprising 15 items, this instrument builds upon similar studies conducted by Peter (2023) and Ogli (2023), which employed comparable dimensions and reliable interview protocols. The tool has been validated by various past studies, demonstrating its effectiveness in capturing users' intentions toward AI adoption.

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This interview protocol explores how teachers’ teaching quality affects students’ academic performance, based on a framework from White & Brown (2025). It includes three main areas: clarity and organization of lessons, student engagement and interaction, and the feedback and support teachers provide. The protocol contains 15 open-ended questions for use in semi-structured interviews with secondary or university students and takes about 30 to 45 minutes. It is informed by studies like Johnson (2023) and Lim & Harris (2024), ensuring its relevance and reliability.

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The "Intention to Use Artificial Intelligence" Interview Protocol, developed by White and Brown (2025), is a 15-item instrument designed to assess individuals' intention to adopt AI through three conceptual dimensions: Frequency (how often one intends to use AI), Interest (level of interest in AI adoption), and Skills (perceived ability or relevant competencies for AI use). While the slide presentation does not explicitly define the specific content of each dimension, this multi-dimensional structure aligns with established methodological practices in similar studies, such as Peter (2023) and Ogli (2023), which emphasize reliable interview protocols grounded in psychometrically robust dimensions to capture behavioral intentions. Conceptually, the tool provides a framework to systematically evaluate both attitudinal factors (interest) and practical considerations (skills) alongside behavioral patterns (frequency), offering insights into the interplay of cognitive and experiential variables influencing AI adoption.

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This content about "Writing the Instrument" shows an interview protocol put forward by White and Brown in 2025. It aims to research the usage intention of [the research object]. The protocol contains three dimensions: Frequency, Interest, and Skills. These dimensions are used to evaluate how often [the research object] is used, how interested people are in it, and the related skill levels respectively. There are 15 items in total. Its dimensions have been verified as reliable in past studies, and similar research like that of Peter (2023) and Ogil (2023) has also applied it.

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This interview is about Interview Protocol on Intention to Use Artificial Intelligence and was designed by White and Brown in 2025. It includes three sections: frequency of use, level of interest, and skill level，with a total of 15 questions. Similar questionnaires have been used by Peter (2023) and Ogli (2023) with good results, making it suitable for classroom discussions or research purposes.

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This study uses an interview protocol adopted from White and Brown (2025) to examine individuals' intentions to use artificial intelligence (AI). The instrument is made up of 15 items divided into three fundamental dimensions: frequency of AI use, interest in AI, and perceived AI-related skills. Each dimension focuses on a specific component of user intention, resulting in a multidimensional knowledge of AI adoption behavior. This instrument design is consistent with earlier validated investigations, Peter (2023) and Ogli (2023), which used comparable constructs and established the reliability of such procedures in gathering significant data about AI engagement. Drawing from this established framework improves the current study's validity, comparability, and theoretical consistency with the broader AI adoption research environment.

Sarah Yassin

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White and Brown wrote an interview plan about people's intention to use artificial intelligence.in2025.

It three parts to look at: how often people use it (Frequency), how interested they are (Interest), and what skills they have (Skills).

There are 15 questions in total.

The plan is based on good parts from similar studies done by Peter and Ogli in 2023 and other past research.

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Our interview instrument is designed to assess individuals' intention to use Artificial Intelligence, based on the framework by White and Brown (2025). It examines three key dimensions: frequency, interest, andskills. The instrument includes 15 items, with each dimension carefully evaluated through targeted questions. Similar dimensions and reliable interview protocols have been used in previous studies, such as those by Peter (2023) and Ogli (2023), providing a strong foundation for the validity and reliability of our approach.

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-Interview Protocol: Made by White and Brown in 2025. It has 15 questions.

- Purpose: To see if people want to use AI.

- Dimensions:

- Frequency: How often you'll use AI.

- Interest: How much you like the idea of using AI.

- Skills: How good you think you are at using AI.

- Similar Studies: Like those by Peter in 2023 and Ogli in 2023. They also use good ways to ask questions to understand what people will do.

- Concept: This tool helps check how you feel (interest), what you can do (skills), and what you'll do (frequency). It shows how your thoughts and experiences affect if you'll use AI.

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Writing the Instrument follow the guide below. In your writing, you must write this instrument:

Interview Protocol Name: Intention to Use Artificial Intelligence

•Author/s: White & Brown (2025)

•Three Dimension: Frequency; Interest; Skills

•Each dimension – what does it assess?

•Number of Items: 15i interview questions

•Similar studies which hvae used this interview protocol: Peter (2023); Ogli (2023)

•Similar dimension, reliable interview protocols, used by various past studies.