The DOI matches its Crossref record; 122 of the 122 references it cites were found in a registry or an index; none of the 108 sources its claims cite is checked for support yet.
The role of ChatGPT in higher education: Benefits, challenges, and future research directions
Open accessAbstract
This paper examines the potential benefits and challenges of using the generative AI model, ChatGPT, in higher education, in the backdrop of the constructivist theory of learning. This perspective-type study presents five benefits of ChatGPT: the potential to facilitate adaptive learning, provide personalised feedback, support research and data analysis, offer automated administrative services, and aid in developing innovative assessments. Additionally, the paper identifies five challenges: academic integrity concerns, reliability issues, inability to evaluate and reinforce graduate skill sets, limitations in assessing learning outcomes, and potential biases and falsified information in information processing. The paper argues that tertiary educators and students must exercise caution when using ChatGPT for academic purposes to ensure its ethical, reliable, and effective use. To achieve this, the paper proposes various propositions, such as prioritising education on the responsible and ethical use of ChatGPT, devising new assessment strategies, addressing bias and falsified information, and including AI literacy as part of graduate skills. By balancing the potential benefits and challenges, ChatGPT can enhance students’ learning experiences in higher education.
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Claims the paper makes
72 Not checked yet · 25 Own interpretation
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By engaging students in conversation and encouraging them to participate in the learning process, ChatGPT can scaffold their prior knowledge and experiences to help them construct new knowledge.”
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“ChatGPT's logical algorithms that build new knowledge based on existing knowledge align with this approach (Hein, 1991).”
What the sources say
- Not checked yetcites Hein, 1991
plaincorrelational- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Incorporating ChatGPT into the assessment process can help students construct their knowledge actively.”
plainconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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None of the sources cited for this claim have been checked yet.
In the paper
“Additionally, ChatGPT's individualised feedback can support this process by building on their prior knowledge and experiences and providing personalised suggestions for further learning (Ippolito et al., 2022;Vygotsky, 1962).”
What the sources say
- Not checked yetcites Ippolito et al., 2022
- Not checked yetcites Vygotsky, 1962
plainconditional- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, it is clear that ChatGPT, as an AI-powered tool, has the potential to facilitate a constructivism learning experience for students by enabling them to explore and experiment with ideas, ask questions, and receive immediate feedback that allows them to construct their own understanding of knowledge.”
boostedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: unclear — It is unclear whether it could be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Specifically, the diagnostic feature of ChatGPT has the potential to serve as the MKO, providing diagnostic individualised (formative) feedback that helps students detect errors and guides them to improve successfully.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim have been checked yet.
In the paper
“By focusing on authentic assessments, in line with the constructivist theory (Wiggins, 1990), and allowing students to engage with topics they are genuinely interested in, ChatGPT can foster creativity and critical thinking skills (Rudolph et al., 2023a;Dennick, 2016).”
What the sources say
- Not checked yetcites Rudolph et al., 2023a
- Not checked yetcites Dennick, 2016
plainconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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In the paper
“Large Learning Models (LLMs) such as ChatGPT provide a scaffolded approach to learning that is consistent with the constructivist theory of learning (Schunk, 2012).”
What the sources say
- Not checked yetcites Schunk, 2012
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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None of the sources cited for this claim have been checked yet.
In the paper
“In higher education, large language models like ChatGPT have the potential to greatly assist researchers and students with various tasks, such as efficiently and effectively completing research and writing tasks, including text generation, language translation, and responding to academic queries (Dwivedi et al., 2023;Kasneci et al., 2023;Lund et al., 2023).”
What the sources say
- Not checked yetcites Dwivedi et al., 2023
- Not checked yetcites Kasneci et al., 2023
- Not checked yetcites Lund et al., 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“Similar to tools like Leximancer (Smith & Humphreys, 2006), LLMs can also reliably conduct text analysis for sentiment analysis, pattern detection, and emotion detection (Dwivedi et al., 2023;Guo et al., 2023).”
What the sources say
- Not checked yetcites Dwivedi et al., 2023
- Not checked yetcites Guo et al., 2023
plaindirect- Asserted: passes — The authors put it forward as true.
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- Probably not a substantial claim. 24
- It may state two separate claims as one. 34
None of the sources cited for this claim have been checked yet.
In the paper
“Furthermore, recent studies have shown that GPT-3 can stimulate curiosity, enhance students' questionasking skills, and generate programming code explanations (Abdelghani et al., 2022;MacNeil et al., 2022).”
What the sources say
- Not checked yetcites Abdelghani et al., 2022
- Not checked yetcites MacNeil et al., 2022
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“It leverages deep learning and powerful algorithms to perform various language-related tasks, such as text generation, question answering, and translation, while comprehending the context to produce responses that resemble human language (Lund et al., 2023).”
What the sources say
- Not checked yetcites Lund et al., 2023
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“This feedback can help students detect errors and guide them towards successful improvement, making ChatGPT an effective”
What the sources say
- Not checked yetcites Geng & Razali, 2020
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Generative Pre-trained Transformer (GPT), which was released by OpenAI (San Francisco, California) in 2018, is a type of Large Language Model (LLM) that aims to replicate human language processing capabilities (Cascella et al., 2023).”
What the sources say
- Not checked yetcites Cascella et al., 2023
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“OpenAI released the ChatGPT-3.5language model family in November 2022 and, subsequently, the ChatGPT-4 family in March 2023 (Skavronskaya et al., 2023).”
What the sources say
- Not checked yetcites Skavronskaya et al., 2023
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Large language models have become a subject of interest in higher education due to their extensive range of applications, especially as there are now other similar options, such as Bing Chat, Bard, and Ernie (Rudolph et al., 2023b).”
What the sources say
- Not checked yetcites Rudolph et al., 2023b
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“This chatbot can engage in coherent and contextually relevant conversations by responding based on its comprehension of the language and context of the prompts (Gilson et al., 2023;Pavlik, 2023).”
What the sources say
- Not checked yetcites Gilson et al., 2023
- Not checked yetcites Pavlik, 2023
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Academics acknowledge that ensuring the responsible integration of AI into education is critical (Fadel et al., 2019;Polak et al., 2022).”
What the sources say
- Not checked yetcites Fadel et al., 2019
- Not checked yetcites Polak et al., 2022
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Overall, incorporating ChatGPT in the learning process enables educators and students to benefit from personalised learning experiences, efficient and effective use of resources, and adaptive learning approaches that enhance the learning outcomes for all, consistent with the principles of constructivist theory (Bada & Olusegun, 2015;Stapleton & Stefaniak, 2019).”
What the sources say
- Not checked yetcites Bada & Olusegun, 2015
- Not checked yetcites Stapleton & Stefaniak, 2019
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Such LLMs can help conduct initial literature reviews, summarise research papers, generate draft versions of research papers (Rahman et al., 2023;Rudolph et al., 2023a), and even assist authors from non-English speaking backgrounds in overcoming language barriers (Gao et al., 2022).”
What the sources say
- Not checked yetcites Rahman et al., 2023
- Not checked yetcites Rudolph et al., 2023a
- Not checked yetcites Gao et al., 2022
plainconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“In the higher education sector, innovative assessment activities have gained a lot of attention because they assist students in getting involved with learning resources to think critically and have real learning experiences (Boud & Soler, 2016).”
What the sources say
- Not checked yetcites Boud & Soler, 2016
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, ChatGPT's ability to provide individualised feedback based on the constructivist theory of learning has significant potential to enhance the learning experience and promote successful learning outcomes.”
plainconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“ChatGPT's research and analysis support, though currently at a basic level, has the potential to fundamentally impact research and higher education, depending on the quality of the prompts (Dwivedi et al., 2023).”
What the sources say
- Not checked yetcites Dwivedi et al., 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Nevertheless, users should exercise caution as ChatGPT may be prone to hallucinations (Alkaissi & McFarlane, 2023) and fabricate references and quotes (Sallam, 2023;Shen et al., 2023).”
What the sources say
- Not checked yetcites Alkaissi & McFarlane, 2023
- Not checked yetcites Sallam, 2023
- Not checked yetcites Shen et al., 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“ChatGPT can act as a research assistant, answering users' questions based on the related literature it has learned (Lin, 2023), and analysing data (Goel, 2020).”
What the sources say
- Not checked yetcites Lin, 2023
- Not checked yetcites Goel, 2020
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Automated administrative support through ChatGPT can use data and analytics to provide timely and personalised non-academic feedback to students, such as notifications about upcoming deadlines, reminders about incomplete tasks, and progress reports on completed tasks, based on individual needs and preferences.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While further research is needed to fully understand the potential of ChatGPT in the tertiary education sector, the constructivist theory of learning supports the use of ChatGPT for automated administrative support as it can facilitate active participation in learning, provide personalised feedback to students, and create a supportive learning environment.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“For academic staff, ChatGPT may be able to summarise and clarify student emails for administrative members to process more efficiently and generate personalised response templates for staff to address students' queries (Dwivedi et al., 2023).”
What the sources say
- Not checked yetcites Dwivedi et al., 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“As indicated earlier, ChatGPT can provide individualised feedback based on the students' prompts, making learning a more rewarding experience (Bridges, 2009;Weldy & Turnipseed, 2010).”
What the sources say
- Not checked yetcites Bridges, 2009
- Not checked yetcites Weldy & Turnipseed, 2010
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In contributing to a smart learning environment, ChatGPT can utilise big data and learning analytics to monitor student performance, predict success, and respond to students, including their emotional states, in real-time, resulting in personalised adaptive learning (PAL) that is consistent with constructivist theory (Peng et al., 2019;Rudolph et al., 2023a).”
What the sources say
- Not checked yetcites Peng et al., 2019
- Not checked yetcites Rudolph et al., 2023a
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The integration of ChatGPT can assist in creating a supportive learning environment for students by providing timely and accurate information, reducing administrative burdens, and presenting a cost-saving measure for higher education institutions.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This provides a degree of efficiency and effectiveness, allowing for a synchronous interaction for students (Howlett, 2017;Okonkwo & Ade-Ibijola, 2021) and presenting a cost-savings measure for higher education institutions (Merelo et al., 2022).”
What the sources say
- Not checked yetcites Howlett, 2017
- Not checked yetcites Okonkwo & Ade-Ibijola, 2021
- Not checked yetcites Merelo et al., 2022
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is obvious that the implementation of advanced LLMs like ChatGPT has the potential to revolutionise the tertiary education sector by automating some elements of administrative support and providing a degree of efficiency and effectiveness.”
boostedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The conversational nature of LLMs such as ChatGPT facilitates the active construction of students' knowledge as they are continuously engaged with the task, encouraged to find patterns through a scaffolded approach (Stapleton & Stefaniak, 2019), and learn through experimentation and experience, which is an important part of knowledge generation (Rudolph et al., 2023a).”
What the sources say
- Not checked yetcites Stapleton & Stefaniak, 2019
- Not checked yetcites Rudolph et al., 2023a
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“AI applications like ChatGPT can provide accurate and efficient individualised feedback and automated grading, but users need to carefully check the outputs as they depend on the prompts (Rudolph et al., 2023a).”
What the sources say
- Not checked yetcites Rudolph et al., 2023a
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Furthermore, ChatGPT-generated text may contain factual biases due to biased training data, which could perpetuate misconceptions held by learners (Karim, 2023).”
What the sources say
- Not checked yetcites Karim, 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“According to the constructivism learning theory, learning happens best when there are good interactions between the instructor and learner (Schuh, 2003).”
What the sources say
- Not checked yetcites Schuh, 2003
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It is no secret that ChatGPT challenges ethical and equity practices in the higher education sector, as it potentially contradicts the constructivist theory of learning that emphasises active student participation and the construction of knowledge.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
In the paper
“Using ChatGPT as a tool for exploration and inquiry, students can actively construct their own knowledge and meaning, reducing the likelihood of academic dishonesty, such as plagiarism or cheating (Keith, 2022).”
What the sources say
- Not checked yetcites Keith, 2022
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“ChatGPT can generate initial ideas for assessment design, create multiple-choice or short-answer questions for academics, and produce drafts of case studies or other assessments for further editing (Bridgeman et al., 2023;Liu & Bridgeman, 2023).”
What the sources say
- Not checked yetcites Bridgeman et al., 2023
- Not checked yetcites Liu & Bridgeman, 2023
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Creating authentic learning experiences would require collaborative and consultative learning experiences (Muhajirah, 2020).”
What the sources say
- Not checked yetcites Muhajirah, 2020
hedgeddirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Passive shortcuts, potentially resulting in academic integrity breaches, hinder the active involvement of learners and hence impede learning.”
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
In the paper
“Another challenge of ChatGPT is the acceptance of feedback provided by AI rather than human instructors, which is against the constructivist theory of learning that emphasises interactions and social collaboration in learning (Hein, 1991).”
What the sources say
- Not checked yetcites Hein, 1991
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
In the paper
“However, ChatGPT could impact students' ability to actively construct their own knowledge, as some students may have greater access to ChatGPT than others, resulting in a knowledge gap between students (Hein, 1991).”
What the sources say
- Not checked yetcites Hein, 1991
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The misuse of ChatGPT to create content instantly as a shortcut goes against the philosophy of constructivism and any learning theory, for that matter.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Proposition 10 (P10): ChatGPT's ability to develop innovative and authentic student assessments depends on its focus on the work context and the students' existing knowledge.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
In the paper
“It can also be integrated into assessment tasks, where students critique generated text or essays and build high-quality articles based on generated drafts, provoking students' existing mental models and developing critical thinking skills (Dennick, 2016).”
What the sources say
- Not checked yetcites Dennick, 2016
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“This technology can be integrated into innovative assessment activities, facilitating collaborative learning, scaffolding, real-time feedback, personalised learning, scalability, interactivity, and fostering knowledge creation and dissipation effectively (Kumar, 2021).”
What the sources say
- Not checked yetcites Kumar, 2021
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Proposition 12 (P12): The integration of ChatGPT in innovative assessment activities can promote critical thinking, problemsolving, and collaboration skills among students.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
In the paper
“Furthermore, the learning environment includes social groups, instructional strategies, and a motivational atmosphere, to name a few (Zajda, 2021).”
What the sources say
- Not checked yetcites Zajda, 2021
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“Although chatbot technology has shown positive influences on explicit reasoning, learning achievement, knowledge retention, and learning interest, studies have not yet demonstrated significant improvements in critical thinking, learning engagement, and motivation (Deng & Yu, 2023).”
What the sources say
- Not checked yetcites Deng & Yu, 2023
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Using ChatGPT to facilitate learning could lead to unethical and inequitable practices, destroying the spirit of learning (Hein, 1991).”
What the sources say
- Not checked yetcites Hein, 1991
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“However, the constructivist theory of learning suggests that learners actively develop knowledge for themselves through experiences and interactions with others rather than passively acquiring it through external tools like ChatGPT (Geary, 1995).”
What the sources say
- Not checked yetcites Geary, 1995
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, incorporating AI literacy as part of graduate skills could enhance graduates' employability and preparedness for the rapidly evolving job market.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Proposition 18 (P18): The use of ChatGPT in learning and assessment can impact the development of graduate skills, such as critical thinking and problem-solving.”
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Graduate skills, including critical thinking and problemsolving, communication, collaboration and teamwork, leadership, adaptability, digital literacy, global and cultural awareness, ethics, and professionalism, are essential for future professional and personal success (Abelha et al., 2020;Osmani et al., 2019;Oliver & de St Jorre, 2018; University of Adelaide, 2022; University of Sydney, 2022).”
What the sources say
- Not checked yetcites Abelha et al., 2020
- Not checked yetcites Osmani et al., 2019
- Not checked yetcites Oliver & de St Jorre, 2018
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This could also make it challenging to evaluate the effectiveness of group learning activities and assess students' ability to work collaboratively.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“However, the use of ChatGPT for assessment is a passive process and does not allow for social interaction, hindering students' ability to construct meaning through reflection on their experiences (Biggs, 2014).”
What the sources say
- Not checked yetcites Biggs, 2014
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The use of ChatGPT presents an opportunity to incorporate artificial intelligence literacy as part of graduate skills, preparing graduates for effective workplace application of large language models that may replace some existing jobs and create new ones (Cradle, 2023).”
What the sources say
- Not checked yetcites Cradle, 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Therefore, the incorporation of these methods into the curriculum and assessment could promote the development of graduate skills beyond the use of ChatGPT alone.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
- Rests on an assumption: Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
The paper relies on this without support.
LLMs like ChatGPT are ubiquitous in higher education.
“The ubiquity of LLMs like ChatGPT has prompted a reevaluation of assessment design, with a focus on fostering creativity, critical thinking, authenticity, practicality, and collaboration (Nieminen et al., 2022;Villarroel et al., 2018), aligning with the constructivist theory's emphasis on authentic and formative assessment (Wiggins, 1990;Black & Wiliam, 2009).”
The paper relies on this without support.
Constructivist learning theory is the appropriate framework for evaluating ChatGPT's role in higher education.
“The paper presented five challenges and five benefits of ChatGPT for the higher education sector in the backdrop of the constructivism learning theory (Figure 1).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“However, this shift toward individual learning raises important considerations for business education, where teamwork and interpersonal skills are crucial for professional success [15].”
From Scaffolding Creativity: Integrating Generative AI Tools and Real-World Experiences in Business Education (2025) · cites this paper as [15]
The cited source says what the claim attributes to it.
In the citing paper
“The arrival of AI in education has potential to produce significant transformations in the teacher-student relationship [54].”
From New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023) · cites this paper as [54]
The cited source says what the claim attributes to it.
In the citing paper
“The diverse learning trajectories observed in these cases illustrate how AI tools can facilitate non-linear, adaptive learning processes by enabling students to dynamically integrate new information with prior knowledge and external resources [15, 16].”
From Scaffolding Creativity: Integrating Generative AI Tools and Real-World Experiences in Business Education (2025) · cites this paper as [15]
In the citing paper
“ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [60]
In the citing paper
“Recent studies have brought to light the potential for students to exploit ChatGPT for academic dishonesty.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [6]
In the citing paper
“The primary concern lies in the potential compromise to academic integrity presented by AI essay-writing systems, particularly ChatGPT.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [6]
In the citing paper
“There is an apprehension that students might submit essays that do not authentically represent their work, thus contravening ethical standards within educational institutions [4,6].”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [6]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Evaluate graduate skill sets
“(Fosnot, 1996)”
§ References
“40. Fosnot, C. T. (2013). Constructivism: Theory, perspectives, and practice. Teachers College Press.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Constructivist theory of learning
“(Taber, 2011)”
§ References
“125. Taber, K. S. (2012). Constructivism as educational theory: Contingency in learning, and optimally guided instruction.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Adaptive learning
“(White et al., 2014;Kasneci et al., 2023)”
§ References
“139. White, P. J., Larson, I., Styles, K., Yuriev, E., Evans, D. R., Rangachari, P. K., Short, J. L., Exintaris, B., Malone, D. T., Davie, B., Eise, N., McNamara, K., & Naidu, S. (2016).”
Citations
Cites
Yaşlı Kadınlarda Üreme Sağlığı
Kokanalı, D., & Engin Üstün, Y. (n.d.) · DergiPark (Istanbul University) · Cited by 170,090
Hattie, J., & Timperley, H. (2007) · Review of Educational Research · doi:10.3102/003465430298487 · Cited by 12,905
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 24×
“LLMs like ChatGPT can also be incorporated into assessment tasks as text-generators, with students tasked to critically evaluate the generated output (Monash University, 2023).”
BackgroundInfluentialZawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242 · cited 2×
“Nonetheless, adaptive learning systems aim to transform students from passive recipients to active collaborators through a scaffolded approach to learning (Deng & Yu, 2023; Zawacki-Richter et al., 2019).”
Background(2023) · doi:10.1126/science · Cited by 6,063
Nicol, D. J., & Macfarlane‐Dick, D. (2006) · Studies in Higher Education · doi:10.1080/03075070600572090 · Cited by 5,846
Signals from Chloroplasts Converge to Regulate Nuclear Gene Expression
Koussevitzky, S., Nott, A., Mockler, T. C., Hong, F., Sachetto‐Martins, G., Surpin, M. A., Lim, J. C.-S., Mittler, R., & Chory, J. (2007) · Science · doi:10.1126/science.1140516 · Cited by 5,765
Shute, V. J. (2008) · Review of Educational Research · doi:10.3102/0034654307313795 · Cited by 4,631
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Research works printed but not linked: 13
- Adar, N., & Kandemir M. C (2008, May 8). M-learning tools for palm device: M-test and m-exercise [Paper presentation]. 8th International Educational Technology Conference, Anadolu University, Eskisehir.
- Bada, S. O., & Olusegun, S. (2015). Constructivism learning theory: A paradigm for teaching and learning. Journal of Research & Method in Education, 5(6), 66-70.
- Bruner, J. S. (1961). The act of discovery. Harvard Educational Review, 31, 21-32.
- Dijkstra, R., Genç, Z., Kayal, S., & Kamps, J. (2022, July 27-31). Reading comprehension quiz generation using generative pre-trained transformers [Paper presentation]. The 23th International Conference on Artificial Intelligence in Education (AIED' 2022).
- Jansen, S. C., & Martin, B. (2015). The Streisand effect and censorship backfire. International Journal of Communication, 9, 656-671.
- June, S., Yaacob, A., & Kheng, Y. K. (2014). Assessing the use of YouTube videos and interactive activities as a critical thinking stimulator for tertiary students: An action research. International Education Studies, 7(8), 56-67. https://doi. org/10.5539/ies. · DOI
- Kılıç, E., Karadeniz, Ş., & Karataş, S. (2003). İnternet destekli yapici ogrenme ortamlari. Gazi University Journal of Gazi Educational Faculty, 23(2), 149-160.
- Makewa, L. N. (2019). Constructivist theory in technology- based learning. In L. N. Makewa, B. M. Ngussa, & J. M. Kuboja (Eds.), Technology-supported teaching and research methods for educators (pp. 268-287). IGI Global.
- Piaget, J. (1980). The psychogenesis of knowledge and its epistemological significance. In M. Piatelli-Palmarini (Ed.), Language and learning: The debate between Jean Piaget and Noam Chomsky (pp. 1-23). Harvard University Press.
- Qiu, J. (2019). A preliminary study of English mobile learning model based on constructivism. Theory and Practice in Language Studies, 9(9), 1167-1172. http://dx.doi. org/10.17507/tpls.0909. · DOI
- In J. Hassaskhah (Ed.), Educational theory (pp. 39-61). Nova.
- Vygotsky, L. S. (1962). Thought and language. MIT Press.
- Yang, T. C., Hwang, G. J., & Yang, S. J. H. (2013). Development of an adaptive learning system with multiple perspectives based on students' learning styles and cognitive styles. Journal of Educational Technology & Society, 16(4), 185-200.
Cited by
Sorted by citations
New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution
Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023) · Sustainability · doi:10.3390/su151612451 · Cited by 1,089
Imran, M., & Almusharraf, N. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13605 · Cited by 421
AI literacy and its implications for prompt engineering strategies
Knoth, N., Tolzin, A., Janson, A., & Leimeister, J. M. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100225 · Cited by 368
“…ChatGPT ’ s, capacity to enrich the educational experience by supporting a wide range of learning methodologies, including adaptive learning, personalized learning, and self-directed learning (Rahman & Watanobe, 2023; Rasul et al., 2023; Ruwe & Mayweg-Paus, 2023; Zhu, Sun, Luo, Li, & Wang, 2023).”
BackgroundWang, H., Dang, A., Wu, Z., & Mac, S. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100326 · Cited by 272
“Then we performed a systematic search using”
BackgroundHigher education students’ perceptions of ChatGPT: A global study of early reactions
Ravšelj, D., Keržič, D., Tomaževič, N., Umek, L., Brezovar, N., A. Iahad, N., Abdulla, A. A., Akopyan, A., Aldana Segura, M. W., AlHumaid, J., et al. (2025) · PLOS ONE · doi:10.1371/journal.pone.0315011 · Cited by 376
Drivers and Consequences of ChatGPT Use in Higher Education: Key Stakeholder Perspectives
Hasanein, A. M., & Sobaih, A. E. E. (2023) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe13110181 · Cited by 366
A Systematic Review of Generative AI for Teaching and Learning Practice
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O., & Sharma, H. (2024) · Education Sciences · doi:10.3390/educsci14060636 · Cited by 251
“2024 , 14 , 636 2 of 20 However, concerns including hallucinations [10], bias [11], ethical and privacy concerns [12,13], accidental plagiarism [14], and academic integrity [15–20] have been raised regarding GenAI tools; such tools have been praised for their potential benefits in relation to HE.”
BackgroundEffects of Generative Chatbots in Higher Education
Ilieva, G., Yankova, T., Klisarova-Belcheva, S., Dimitrov, A., Bratkov, M., & Angelov, D. (2023) · Information · doi:10.3390/info14090492 · Cited by 258
“Rasul et al. [44] have presented a framework for usage of ChatGPT in universities based on the constructivism learning theory.”
MethodAnsari, A. N., Ahmad, S., & Bhutta, S. M. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12223-4 · Cited by 198
“…prepare for exams, and enhance language skills, including writing and communication, as well as information and digital literacy (Bishop, 2023; Choi et al., 2023; Cotton et al., 2023; Cox & Tzoc, 2023; Currie, 2023; Ivanov & Soliman, 2023; Lee, 2023; McGrath et al., 2023; Rasul et al., 2023).”
InfluentialDabis, A., & Csáki, C. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03526-z · Cited by 318
“…may be utilised to automate a range of educational tasks, such as test question generation, including open-ended questions, test correction, or even essay grading, feedback provision, analysing student feedback surveys, and so on (Mollick and Mollick, 2022; Rasul et al. 2023; Gimpel et al. 2023).”
A systematic literature review of empirical research on ChatGPT in education
Albadarin, Y., Saqr, M., Pope, N., & Tukiainen, M. (2024) · Discover Education · doi:10.1007/s44217-024-00138-2 · Cited by 191
“This finding aligns with other recent studies [26–28, 60, 66] which revealed that ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities.”
Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N.-J., & Ertz, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12936-0 · Cited by 229
“By fostering creativity, improving language precision, and ensuring grammatical accuracy, ChatGPT may empower users to become more effective and confident writers in various domains (Rasul et al., 2023).”
Kofinas, A. K., Tsay, C. H., & Pike, D. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13585 · Cited by 207
ChatGPT—A Challenging Tool for the University Professors in Their Teaching Practice
Kiryakova, G., & Angelova, N. (2023) · Education Sciences · doi:10.3390/educsci13101056 · Cited by 171
Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning
Guettala, M., Bourekkache, S., Kazar, O., & Harous, S. (2024) · Acta Informatica Pragensia · doi:10.18267/j.aip.235 · Cited by 218
Looking Beyond the Hype: Understanding the Effects of AI on Learning
Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10020-8 · Cited by 153
Balalle, H., & Pannilage, S. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101299 · Cited by 137
Boudouaia, A., Mouas, S., & Kouider, B. (2024) · Journal of Educational Computing Research · doi:10.1177/07356331241247465 · Cited by 186
“The fi ndings are also in line with the studies of Rasul et al. (2023) and Rudolph et al. (2023), which acknowledged that using ChatGPT-4 in EFL education has a number of advantages.”
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.12 · Cited by 132
Will artificial intelligence drive the advancements in higher education? A tri-phased exploration
Kumar, S., Rao, P., Singhania, S., Verma, S., & Kheterpal, M. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123258 · Cited by 131
Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania
Rudolph, J., Mohamed Ismail, F. M., & Popenici, S. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/54fs5e77 · Cited by 189
“This development challenges the nurturing of a suite of graduate skills identified as pivotal for future success, including but not limited to critical thinking, communication, collaboration, leadership, adaptability, digital literacy, and ethical professionalism (Rasul et al., 2023).”
BackgroundInfluentialAlmulla, M. A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e32220 · Cited by 174
“…a viable resolution to these issues by offering assistance with a number of research-related tasks, including 1) Coming up with research questions and theories [13,14]; ChatGPT can help academics come up with creative study questions and ideas by analysing large datasets and finding trends [15].”
BackgroundOpportunities, Challenges, and Strategies for Using ChatGPT in Higher Education: A Literature Review
Sok, S., & Heng, K. (2024) · Journal of Digital Educational Technology · doi:10.30935/jdet/14027 · Cited by 120
“Indeed, students ’ learning outcomes may be restricted if they are solely dependent upon ChatGPT for producing their written work and fail to engage in reflection and critical thinking (Firat, 2023; Rasul et al., 2023).”
BackgroundGenerative-AI, a Learning Assistant? Factors Influencing Higher-Ed Students' Technology Acceptance
Kanont, K., Pingmuang, P., Simasathien, T., Wisnuwong, S., Wiwatsiripong, B., Poonpirome, K., Songkram, N., & Khlaisang, J. (2024) · The Electronic Journal of e-Learning · doi:10.34190/ejel.22.6.3196 · Cited by 155
Jafari, F., & Keykha, A. (2023) · Journal of Applied Research in Higher Education · doi:10.1108/jarhe-09-2023-0426 · Cited by 164
Schmidt, D. A., Alboloushi, B., Thomas, A., & Magalhães, R. (2025) · Computers and Education Open · doi:10.1016/j.caeo.2025.100274 · Cited by 171
Bobula, M. (2024) · Journal of Learning Development in Higher Education · doi:10.47408/jldhe.vi30.1137 · Cited by 113
Cai, L., Msafiri, M. M., & Kangwa, D. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13112-0 · Cited by 104
Adapting to the Future: ChatGPT as a Means for Supporting Constructivist Learning Environments
Kim, M., & Adlof, L. (2024) · TechTrends · doi:10.1007/s11528-023-00899-x · Cited by 97
“In constructivist theories, students learn through a dynamic knowledge-creation process shaped by the surrounding learning environment, tools, and experiences (Ertmer & Newby, 1993; Rasul et al., 2023).”
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Artificial intelligence for higher education: benefits and challenges for pre-service teachers
Kalniņa, D., Nīmante, D., & Baranova, S. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1501819 · Cited by 162
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.34 · Cited by 91
Mohammadkarimi, E. (2023) · Journal of Applied Learning and Teaching · doi:10.37074/jalt.2023.6.2.10 · Cited by 90
“This implication aligns with the findings of multiple scholarly investigations conducted by Cotton et al. (2023), Rasul et al. (2023), and Rudolph et al. (2023b).”
ResultNavigating the landscape of AI literacy education: insights from a decade of research (2014–2024)
Yang, Y., Zhang, Y., Sun, D., He, W., & Wei, Y. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04583-8 · Cited by 128
ChatGPT-Supported Education in Primary Schools: The Potential of ChatGPT for Sustainable Practices
Uğraş, H., Uğraş, M., Papadakis, S., & Kalogiannakis, M. (2024) · Sustainability · doi:10.3390/su16229855 · Cited by 130
AI in the classroom: Exploring students’ interaction with ChatGPT in programming learning
Güner, H., & Er, E. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13337-7 · Cited by 134
“Incorporating AI into collaborative learning activities can also enhance peer-to-peer learning, as students can collectively refine their problem-solving approaches with AI support (Rasul et al., 2023; Suciati et al., 2024).”
Lin, C.-J., Lee, H.-Y., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13072-5 · Cited by 83
Duan, S., Liu, C., Rong, T., Zhao, Y., & Liu, B. (2025) · BMC Medical Education · doi:10.1186/s12909-025-07177-9 · Cited by 85
“Additionally, researchers have highlighted ethical and academic integrity issues, including authorship disputes, copyright, authenticity, plagiarism, and the potential misuse of AI-generated content in assessments [20, 22].”
Naznin, K., Mahmud, A. A., Nguyen, M. T., & Chua, C. (2025) · Computers · doi:10.3390/computers14020053 · Cited by 123
Exploring learners’ experiences and perceptions of ChatGPT as a learning tool in higher education
Monib, W. K., Qazi, A., & Mahmud, M. M. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13065-4 · Cited by 80
“They further maintained that Piaget identified two learning processes: assimilation, where new experiences fit into existing schemata, and accommodation, where schemata are adjusted based on new information.”
InfluentialChatbots and AI in Education (AIEd) tools: The good, the bad, and the ugly
Ifelebuegu, A. O., Kulume, P., & Cherukut, P. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.29 · Cited by 109
Shaping integrity: why generative artificial intelligence does not have to undermine education
Tan, M. J. T., & Maravilla, N. M. A. T. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1471224 · Cited by 78
“According to Rasul et.al (2023), ChatGPT supports the constructivist principle that learners construct their own understanding of knowledge by enabling students to explore and experiment with ideas, ask questions, and receive immediate feedback.”
BackgroundThe Impact of AI on the Personal and Collaborative Learning Environments in Higher Education
Msambwa, M. M., Wen, Z., & Daniel, K. (2025) · European Journal of Education · doi:10.1111/ejed.12909 · Cited by 76
Enhancing academic integrity among students in GenAI Era:A holistic framework
Rasul, T., Nair, S., Kalendra, D., Balaji, M. S., Santini, F. D. O., Ladeira, W. J., Rather, R. A., Yasin, N., Rodriguez, R. V., Kokkalis, P., et al. (2024) · The International Journal of Management Education · doi:10.1016/j.ijme.2024.101041 · Cited by 82
Self-citationUso y percepción de ChatGPT en la educación superior
Sánchez, O. V. G. (2023) · Revista de Investigación en Tecnologías de la Información · doi:10.36825/riti.11.23.009 · Cited by 75
“Los beneficios y desafíos del uso de ChatGPT, en la educación superior desde una perspectiva constructivista, se examinan en [21].”
Saihi, A., Ben-Daya, M., Hariga, M., & As'ad, R. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100274 · Cited by 75
Salih, S., Husain, O., Hamdan, M., Abdelsalam, S., Elshafie, H., & Motwakel, A. (2025) · Results in Engineering · doi:10.1016/j.rineng.2024.103837 · Cited by 74
Nelson, A. S., Santamaría, P. V., Javens, J. S., & Ricaurte, M. (2025) · Education Sciences · doi:10.3390/educsci15050611 · Cited by 79
Perceptions of Higher Education Students towards ChatGPT Usage
Das, S. R., & Madhusudan, J. V. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.583 · Cited by 103
Demystifying ChatGPT: An In-depth Survey of OpenAI’s Robust Large Language Models
Bhattacharya, P., Prasad, V. K., Verma, A., Gupta, D. K., Sapsomboon, A., Viriyasitavat, W., & Dhiman, G. (2024) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-024-10115-5 · Cited by 84
ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia
George Pallivathukal, R., Kyaw Soe, H. H., Donald, P. M., Samson, R. S., & Hj Ismail, A. R. (2024) · Cureus · doi:10.7759/cureus.53032 · Cited by 68
“There is an apprehension that students might submit essays that do not authentically represent their work, thus contravening ethical standards within educational institutions [4,6].”
BackgroundApplication of ChatGPT in Higher Education and Research – A Futuristic Analysis
Aithal, P. S., & Aithal, S. (2023) · International Journal of Applied Engineering and Management Letters · doi:10.47992/ijaeml.2581.7000.0193 · Cited by 71
Charting the Future of AI in Project-Based Learning: A Co-Design Exploration with Students
Zheng, C., Yuan, K., Guo, B., Hadi Mogavi, R., Peng, Z., Ma, S., & Ma, X. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642807 · Cited by 70
Using ChatGPT in Education: Human Reflection on ChatGPT’s Self-Reflection
Loos, E. F., Gröpler, J., & Goudeau, M.-L. S. (2023) · Societies · doi:10.3390/soc13080196 · Cited by 88
“…from forbidding the use of ChatGPT or adapting the assessment of students’ learning, to creative ways to embedding it in educational practices [22–24, ChatGPT also does not mention the important risk of social inequality arising in the future due to groups of students not having been exposed to…”
Adarkwah, M. A., Amponsah, S., van Wyk, M. M., Huang, R., Tlili, A., Shehata, B., Metwally, A. H. S., & Wang, H. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.26 · Cited by 85
Elshaer, I. A., Hasanein, A. M., & Sobaih, A. E. E. (2024) · European Journal of Investigation in Health Psychology and Education · doi:10.3390/ejihpe14070132 · Cited by 65
Daniel, K., Msambwa, M. M., & Wen, Z. (2025) · European Journal of Education · doi:10.1111/ejed.70036 · Cited by 71
Wang, P., Jing, Y., & Shen, S. (2025) · The Internet and Higher Education · doi:10.1016/j.iheduc.2025.100996 · Cited by 93
Youssef, E., Medhat, M., Abdellatif, S., & Al Malek, M. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100316 · Cited by 65
Li, H., Wang, Y., Luo, S., & Huang, C. (2024) · Journal of Asian Public Policy · doi:10.1080/17516234.2024.2363128 · Cited by 73
“In this environment, learners need to construct knowledge through multiple rounds of interaction and discussion with the LLM-powered chatbot, rather than simply copying AI-generated content as their output, which has the potential to reduce students’ academic misconduct (Rasul et al., 2023).”
Guizani, S., Mazhar, T., Shahzad, T., Ahmad, W., Bibi, A., & Hamam, H. (2025) · Discover Education · doi:10.1007/s44217-025-00424-7 · Cited by 99
“Because ChatGPT provides feedback after every interactive iteration, the curriculum can be modified and enhanced based on the model’s observations and recommendations [95, 96].”
Rethinking online assessment strategies: Authenticity versus AI chatbot intervention
Ifelebuegu, A. O. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.2 · Cited by 74
“According to Seo et al. (2021), if ChatGPT and other AI models are used for rapid and superficial learning, they may hinder the development of graduate-level skills such as critical thinking and problem-solving.”
BackgroundInfluentialChatGPT and higher education assessments: More opportunities than concerns?
Gamage, K. A. A., Dehideniya, S. C. P., Xu, Z., & Tang, X. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.32 · Cited by 84
Chaka, C. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.14 · Cited by 85
Empowering learners with ChatGPT: insights from a systematic literature exploration
Mohebi, L. (2024) · Discover Education · doi:10.1007/s44217-024-00120-y · Cited by 56
Monib, W. K., Qazi, A., Apong, R. A. A. H. M., Azizan, M. T., Silva, L. D., & Yassin, H. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2105 · Cited by 119
Mumtaz, S., Carmichael, J., Weiss, M., & Nimon-Peters, A. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13099-8 · Cited by 55
“Academ-ics have begun to outline how AIT can be used beneficially to improve the student learning experience (Cowen & Tabarrok, 2023 ), and to identify what they believe are the challenges and benefits of AIT (e.g., Cotton et al., 2024 ; Rasul et al., 2023; Sardana et al., 2023 ).”
Younis, B. (2024) · Journal of Digital Learning in Teacher Education · doi:10.1080/21532974.2024.2365663 · Cited by 79
“Furthermore, AI is capable of fostering continuous improvement in the educational system by analyzing data to inform data-driven decisions (Rasul, 2023).”
García-Alonso, E. M., León-Mejía, A. C., Sánchez-Cabrero, R., & Guzmán-Ordaz, R. (2024) · Behavioral Sciences · doi:10.3390/bs14070612 · Cited by 53
“User acceptance, mediated by information quality, system quality, perceived learning value, and perceived satisfaction, plays an important role in determining users’ acceptance of ChatGPT [103,104].”
BackgroundHow understanding the limitations and risks of using ChatGPT can contribute to willingness to use
Murshidi, G. H. A., Shulgina, G., Kapuza, A., & Costley, J. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00322-9 · Cited by 62
“Not all students may have access to high-speed internet and up-to-date technological devices that allow for the full use of the ChatGPT (Rasul et al., 2023).”
BackgroundCodeTailor: LLM-Powered Personalized Parsons Puzzles for Engaging Support While Learning Programming
Hou, X., Wu, Z., Wang, X., & Ericson, B. J. (2024) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3657604.3662032 · Cited by 74
Assessing second-language academic writing: AI vs. Human raters
Geçkin, V., Kızıltaş, E., & ÇINAR, Ç. (2023) · Journal of Educational Technology and Online Learning · doi:10.31681/jetol.1336599 · Cited by 61
“The benefits and challenges ChatGPT offers have been well articulated in the field of higher education (Rasul et al., 2023) and foreign language teaching, learning, and assessment (Hong, 2023).”
Mohammadi, E., Thelwall, M., Cai, Y., Collier, T., Tahamtan, I., & Eftekhar, A. (2026) · Information Processing & Management · doi:10.1016/j.ipm.2025.104350 · Cited by 47
Imran, M., Almusharraf, N., Abdellatif, M. S., & Abbasova, M. Y. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i18.49143 · Cited by 51
Exploring the influence of ChatGPT on student academic success and career readiness
Dahri, N. A., Yahaya, N., & Al-Rahmi, W. M. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13148-2 · Cited by 69
“ChatGPT can enhance cognitive skills such as critical thinking and problem-solving by engaging users in interactive dialogue (Rasul et al., 2023).”
InfluentialMei, P., Brewis, D. N., Nwaiwu, F., Sumanathilaka, D., Alva-Manchego, F., & Demaree-Cotton, J. (2025) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2025.100140 · Cited by 50
“In addition, GenAI may help to promote inclusion in learning through expanding readily available access to knowledge (Elbanna & Armstrong, 2024; Rasul et al., 2023), regardless of geographical, socio-economic, or educational barriers.”
Exploring prompt pattern for generative artificial intelligence in automatic question generation
Wang, L., Song, R., Guo, W.-T., & Yang, H.-W. (2024) · Interactive Learning Environments · doi:10.1080/10494820.2024.2412082 · Cited by 56
“The emergence of LLMs has revolutionized the AI field, providing unprecedented capabilities in natural language understanding and generation and offering the potential for educational change (Adeshola & Adepoju, 2023; Rahman & Watanobe, 2023; Rasul et al., 2023; Rospigliosi, 2023).”
Amin, M. A., Kim, Y. S., & Noh, M. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13095-y · Cited by 55
“Furthermore, in the field of higher studies, students can get several benefits by using ChatGPT, for instance, getting personalized feedback, improving academic effectiveness, and accelerating their research activities (Rasul et al., 2023).”
Enough of the chit-chat: A comparative analysis of four AI chatbots for calculus and statistics
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.22 · Cited by 50
Learning Mathematics with Large Language Models
Matzakos, N., Doukakis, S., & Moundridou, M. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i20.42979 · Cited by 51
Hatmanto, E. D., & Sari, M. I. (2023) · E3S Web of Conferences · doi:10.1051/e3sconf/202344005001 · Cited by 77
“Personalized learning experiences and differentiated instruction are supported by Chat GPT conversation [19].”
BackgroundZhang, Y., & Dong, C. (2024) · Systems · doi:10.3390/systems12110462 · Cited by 59
Generative AI, Large Language Models, and ChatGPT in Construction Education, Training, and Practice
Jelodar, M. B. (2025) · Buildings · doi:10.3390/buildings15060933 · Cited by 56
Zhou, X., & Schofield, L. (2024) · Journal of Learning Development in Higher Education · doi:10.47408/jldhe.vi30.1031 · Cited by 45
Cheng, M. W. T., & YIM, I. H. Y. (2024) · Discover Education · doi:10.1007/s44217-023-00081-8 · Cited by 44
“Previous studies [3, 20, 27, 34, 48], examined the benefits and threats posed by ChatGPT in the educational setting.”
Wei, X., Chu, X., Geng, J., Wang, Y., Wang, P., Wang, H., Wang, C., & Lei, L. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102566 · Cited by 48
Sánchez, F. Á. B., & Cruz, J. (2024) · Education Sciences · doi:10.3390/educsci14050484 · Cited by 59
“This timely feedback helps students to rapidly make necessary improvements, identify misconceptions, or recognize inaccurate or incomplete ideas about a concept [20].”
BackgroundInfluentialThe artificial intelligence literacy (AIL) scale for teachers: A tool for enhancing AI education
Younis, B. (2025) · Journal of Digital Learning in Teacher Education · doi:10.1080/21532974.2024.2441682 · Cited by 80
Exploring the Utility of ChatGPT for Self-directed Online Language Learning
Li, Z., Wang, C., & Bonk, C. J. (2024) · Online Learning · doi:10.24059/olj.v28i3.4497 · Cited by 53
“They emphasized that ChatGPT encourages students to independently explore learning topics by inputting keywords or questions to access relevant information and resources (Firat, 2023; Rasul et al., 2023).”
BackgroundIsiaku, L., Muhammad, A. S., Kefas, H. I., & Ukaegbu, F. C. (2024) · Quality Education for All · doi:10.1108/qea-07-2024-0055 · Cited by 66
Wang, L., & Ren, B. (2024) · Education Sciences · doi:10.3390/educsci14121329 · Cited by 38
Higher education assessment practice in the era of generative AI tools
(2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.1.28 · Cited by 37
Can generative AI motivate management students? The role of perceived value and information literacy
Jose, E. M. K., Prasanna, A., Kushwaha, B. P., & Das, M. (2024) · The International Journal of Management Education · doi:10.1016/j.ijme.2024.101082 · Cited by 55
Artificial intelligence in higher education. A protocol paper for a systematic literature review
Ismail, F. M. M., Tan, E., Rudolph, J., Crawford, J., & Tan, S. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.34 · Cited by 39
Outsourcing Humanity? ChatGPT, Critical Thinking, and the Crisis in Higher Education
Royer, C. (2024) · Studies in Philosophy and Education · doi:10.1007/s11217-024-09946-3 · Cited by 48
RETRACTED: ChatGPT in the classroom: navigating the generative AI wave in management education
Leelavathi, R., & Surendhranatha, R. C. (2024) · Journal of Research in Innovative Teaching & Learning · doi:10.1108/jrit-01-2024-0017 · Cited by 54
RetractedGuiding principles of generative AI for employability and learning in UK universities
Nartey, E. K. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2357898 · Cited by 54
“For instance, the imposition of constraints such as the 1,000-character limit on ChatGPT ’ s computation input and restricted message input frequency (Rasul et al., 2023) may lead to inadequacies in communication.”
Students' perceptions of artificial intelligence integration in higher education
Slimi, Z., Benayoune, A., & Alemu, A. E. (2025) · European Journal of Educational Research · doi:10.12973/eu-jer.14.2.471 · Cited by 38
Using ChatGPT for medical education: the technical perspective
Chan, K. Y., Yuen, T. H., & Co, M. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06785-9 · Cited by 34
“On the other hand, there was a significant change in traditional classroom learning due to the outbreak of COVID-19 [7–13].”
Maaß, L., Grab‐Kroll, C., Koerner, J., Öchsner, W., Schön, M., Messerer, D. A. C., Boeckers, T. M., & Böckers, A. (2024) · Journal of CME · doi:10.1080/28338073.2024.2437293 · Cited by 40
Metadata
- Authors
- Rasul, T., Nair, S., Kalendra, D. R., Robin, M., Santini, F. D. O., Ladeira, W. J., Sun, M., Day, I., Rather, R. A., & Heathcote, L.
- Affiliations
- Australian Institute of Business (AU)
- Universidade do Vale do Rio dos Sinos (BR)
- ORCID
- Venue
- Journal of Applied Learning & Teaching
- Publisher
- Open Access Publishing Association
- Published
- 2023-05-11
- Volume
- 6
- Issue
- 1
- ISSN
- 2591-801X (ISSN-L)
- OpenAlex
- W4376139682
- Semantic Scholar
- 9e7cd4ce1ed4b842e8a428c3774bd06ca3a5b769
- Cited by
- 561
- References
- 122
- Citations by year
- 2026: 69 · 2025: 235 · 2024: 209 · 2023: 47
- FWCI
- 131.92
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Applied Learning & Teaching (publishedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Keywords
- ChatGPT, generative AI in education, higher education, constructivist learning theory, adaptive learning, personalized feedback, academic integrity, AI evaluation, AI literacy, algorithmic bias, ethical use of AI, graduate competencies
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