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
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“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).”
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Items 501–566 of 566
Determinants of ChatGPT Adoption in Higher Education Students: A UTAUT Framework Analysis
Wijaya, L., Cheng, K. M., Lasian, L., Lestari, M. I., Wahono, J. W., & Anisa, N. N. (2025) · International Conference on Creative Communication and Innovative Technology (ICCIT) · doi:10.1109/iccit65724.2025.11167221 · Cited by 1
Gomathy, C., Sujatha, S., Indrani, G., Ambika, T., & Kanimozhi, R. S. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-031-96530-2_16
Batani, J., & Mbunge, E. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-00236-5_29 · Cited by 1
Analyzing Students' Use of Generative Artificial Intelligence in Collaborative Problem Solving
Chen, X., & Feng, S. (2025) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/3715070.3749257
Navigating the Double-Edged Sword of AI Integration in Higher Education
Hashemi, S. S., Lundin, M., & Lantz-Andersson, A. (2025) · Proceedings for the European Conference on Reflective Practice-based Learning 2025 · doi:10.54337/ecrpl25-10936
Li, Y., Meng, J., & Wu, Q. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11227929
Abdulrab, M. (2025) · Open Psychology Journal · doi:10.2174/0118743501416115251129091125 · Cited by 2
Challenges and Strategies of Social Studies Teachers in Evaluating AI-Generated Student Work
Mayuga, A. M., Pasahol, J., & Perez, J. M. (2025) · Psychology and Education A Multidisciplinary Journal · doi:10.70838/pemj.500406
Murshidi, G. A., Shulgina, G., Kapuza, A., & Costley, J. (2024) · Figshare · doi:10.6084/m9.figshare.26757733
Murshidi, G. A., Shulgina, G., Kapuza, A., & Costley, J. (2024) · Figshare · doi:10.6084/m9.figshare.26757736
Gulbahar, Y. (2025) · Artificial intelligence · doi:10.5772/intechopen.1012778
Assessing the Success of Chatgpt in Higher Education: an Empirical Study of the Benefits and Impacts
Nanang, H., Sukmana, H. T., Durahman, Y., Khairani, D., Arifin, V., & Saputrie, F. P. (2025) · International Conference on Cyber and IT Service Management (CITSM) · doi:10.1109/citsm67730.2025.11291423
“GPT Chat can understand human language well and can produce faster responses [16].”
AI in Computer-Aid Design of Components and Assemblies in Mechanical Engineering Education
Bashev, A., & Asenov, S. M. (2025) · doi:10.1109/telecom66943.2025.11304041
Technology-mediated Feedback in Writing Classes: Towards a Learning-Oriented Approach
Gebril, A. (2026) · Educational linguistics · doi:10.1007/978-3-032-08518-4_2
Redefining the Teacher’s Role in the AI Era: From Content Expert to Learning Facilitator
Yang, N., & Li, M. (2025) · Journal of higher education teaching. · doi:10.62517/jhet.202515553
Navigating Social Media: How Utilization by Students Affects Academic Performance
Billones, J. L., Canon, I. M. –., Paloma, M. R., & Hungo, M. O. (2025) · JPI (Jurnal Pendidikan Indonesia) · doi:10.23887/jpi-undiksha.v14i4.86167
Review of Policies for the Use of Generative Artificial Intelligence in Leading Foreign Universities
Gorlacheva, E. N., Леонидович, О. П., & Андреевна, П. Е. (2026) · University Management Practice and Analysis · doi:10.15826/umpa.2025.04.028 · Cited by 1
Wang, K., Shen, L., Duan, B., Zhang, C., & Xue, Y. (2026) · Asia Pacific Journal of Education · doi:10.1080/02188791.2026.2625132
Fath, S. N., Amus, S., Hasdin, H., Jamaludin, Idrus, & Nadjamuddin, L. (2025) · Jurnal Pedagogi dan Pembelajaran · doi:10.23887/jp2.v8i3.103205
The Jogja Library Center Tour: Literacy-Based Inquiry Model to Improve Historical Thinking Skill
Wilis, R., & Kumalasari, D. (2025) · Jurnal Pedagogi dan Pembelajaran · doi:10.23887/jp2.v8i3.100800
Analyzing University Students’ Perceptions of ChatGPT: A Case Study at Ajman University, UAE
Alqawasmi, A., Alsalhi, N. R., Eltahir, M. E., Al-Qatawneh, S. S., Aljarrah, K. H., & Al-Taani, A. A. K. (2025) · International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams67467.2025.11391238
Gawande, V., & Gajan, E. R. (2026) · Contributions to finance and accounting · doi:10.1007/978-3-032-13485-1_50
A systematic literature review of ChatGPT adoption in Arab higher education
Assad, A., & Alomari, M. S. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01227-x · Cited by 5
ChatGPT in Educational Research: A Case Study of Graduate Students' Use and Ethical Perceptions
Lim, E., Lee, H., & Choi, Y. (2026) · Future in Educational Research · doi:10.1002/fer3.70043
Ratniyom, J., Boonphadung, S., Intaraprasit, M., & Chumkaeo, P. (2026) · Chemistry Teacher International · doi:10.1515/cti-2025-0097 · Cited by 2
“3,10 13 In such contexts, students frequently struggle to make sense of abstract concepts and often experience persistent confusion without timely and individualized feedback.”
An Exploratory Analysis of Perceptions and Uses of Generative AI Tools for Higher Education
Paullet, K., Chawdhry, A. A., & Pinchot, J. (2026) · Information Systems Education Journal · doi:10.62273/upwn3714
Mulder, S. L., & Carrera, M. (2026) · Discover Education · doi:10.1007/s44217-026-01549-z
“Although AI tools can support learning through personalized feedback and structured assistance, uncritical use may limit student engagement with deeper intellectual processes [44].”
InfluentialDizbay, A. K., & Özelçi, S. Y. (2026) · MIER Journal of Educational Studies Trends & Practices · doi:10.52634/mier/2026/v16/i1/2975
Galdames, I. S., & Chaple-Gil, A. M. (2025) · De Gruyter eBooks · doi:10.1515/9783112206393-003
Instructors' Strategies in Creating and Implementing Constructivist LLM-Based Learning Activities
Aurelia, E., Yeo, S., Lui, M., Law, E. L., & Tang, A. (2025) · International Conference on Human-Engaged Computing (ICHEC) · doi:10.1145/3786995.3787043
Australian Initial Teacher Educators’ Perspectives on Artificial Intelligence
Waters, K., Tafazoli, D., Spray, E., Burgess, R., Shaw, E., Southgate, E., Rendoth, T., & Ledger, S. (2026) · Springer eBooks · doi:10.1007/978-3-032-12174-5_6
Structured Prompting for Human-AI Collaboration as Cognitive Partners in Project-Based Learning
Qi, Y., Jia, F., Dai, H., & Wang, Y. (2026) · International Conference on Educational and Information Technology · doi:10.1109/iceit68991.2026.11521291
Tikhonova, E. A., & Raitskaya, L. (2026) · Journal of language and Education · doi:10.17323/jle.2026.33523
“…2025; Kohnke et al., 2023; Lee et al., 2024; Lodge et al., 2023; Michel-Villarreal et al., 2023; Nicol, 2021; Perkins, 2023; Rapanta et al., 2021; Rasul et al., 2023; Shutaleva et al., 2023; Turnbull et al., 2021 Positivist / Post-positivist (n=16) Al-Bashayreh et al., 2022; Escalante et al.,…”
The Productivity Myth and Learning Paradox of Generative AI in Higher EducationPreprint
Anwar, M. R., Ali, B., & Arif, A. (2026) · Research Square · doi:10.21203/rs.3.rs-9869630/v1
Cook, J., & Cook, J. (2026) · Artificial Intelligence in Education · doi:10.1108/aiie-06-2025-0129 · Cited by 1
Karaismailoğlu, F., Sürmeli, H., & Yıldırım, M. (2026) · Journal of Science Education and Technology · doi:10.1007/s10956-026-10342-4
Detecting and Visualizing LLM Usage in Students' Essays Leveraging Past Assignments and LLM Answers
Zhao, Y., Lueder, R., Zhang, Q., & Starner, T. E. (2026) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3774398.3811559
Investigating ChatGPT Usage in High Schools: Student Perspectives on Policy and Practice
Chanenson, J., Eschebach, T., & Chetty, M. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3812305
A Longitudinal Analysis of Generative AI’s Impact on Computer Architecture Learning
Mirmotahari, O., Mahmood, S., & Berg, Y. (2026) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon67543.2026.11574147
“Constructivist learning theories emphasize the critical role of active engagement, experimentation, and reflection in developing understanding, particularly in abstract domains such as digital logic and Boolean algebra [4].”
A framework for AI and vocational assessment in higher education
Balducci, B. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1703130 · Cited by 1
Edam-Agbor, I. B., Orim, F. S., Ovat, S. V., Ofem, U. J., Ukatu, J. O., Ekpang, P. O., Igajah, M. N., Ebaye, A. S., & Asukwuo, P. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2690902
ChatGPT and student well-being: The cultural bridge of Mianzi
Noor, N., Zainol, Z., Tong, A., Duong, D. T. T., & Agarwal, M. (2026) · Journal of Tropical Futures Sustainable Business Governance & Development · doi:10.1177/27538931261465814
Ding, L., Rodenberg, R., Er, E., Nguyen, H., & Yoon, M. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2702559
Kumar, J. A., Salim, Z., Annamalai, N., Dhaliwal, J., & Singh, A. D. (2026) · Quality & Quantity · doi:10.1007/s11135-026-02982-w · Cited by 1
Wang, H., Fu, F., Li, L., & Liu, M. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1861541 · Cited by 1
Gezgin, D. M., Nurlu, O., Arapoğlu, Ç., & DEMİRELLİ, M. M. (2026) · Open Praxis · doi:10.55982/openpraxis.18.3.1142
Ibrahim, I., Firmansyah, J., Jalaluddin, J., & Marwan, M. (2026) · Research Square · doi:10.21203/rs.3.rs-8675352/v1 · Cited by 1
Guerra-Mera, A., Manzano, J. M. B., & Mera, F. D. C. G. (2026) · ARKSIS-Journal · doi:10.63957/arksis.v1i2.0012
AI-Powered Learning Through ChatGPT-4: Simplifying Complex Concepts with Creative Pedagogy
Allam, H., Dempere, J. M., Kumar, L., Alagure, Z., Davison, C. B., & Lazaros, E. J. (2026) · Advances in Science, Technology & Innovation/Advances in science, technology & innovation · doi:10.1007/978-3-032-24784-1_16
The Impact of ChatGPT on the Academic Performance of TESOL Students at Kabul Education University
Afghan, K. R., Ahmadzai, N. M., & Zafarmal, A. (2026) · International journal of social sciences · doi:10.64394/ijss.v2i2.179
“As Kasneci et al. (2023) innovation (Moreno et al., 2022 ; Rasul et al., 2023).”
Debs, L., Talley, K. G., & Souza, A. (2026) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--59370
Adeniranye, D. I., Brijmohan, Y., Jacobs, M., Laghari, A. W. K., & Osunbunmi, I. S. (2026) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--61157
Wang, X., Liu, X., Zhang, H., & Li, R. (2026) · Research Square · doi:10.21203/rs.3.rs-10560352/v1
Cempellin, L., Serfling, N., Brink, M. T., Biesecker, M., Abbasi, S., Won, K., & Tazarv, M. (2026) · Teaching & Learning Inquiry The ISSOTL Journal · doi:10.20343/teachlearninqu.14.42
Mahboob, N., & Quraishi, T. (2026) · Jurnal Penelitian Pendidikan IPA · doi:10.29303/jppipa.v12i8.16269
“Generative AI systems such as ChatGPT are now used widely by chemistry students and instructors (Kasneci et al., 2023; Rasul et al., 2023), and they are already being tested as tutoring aids in universities that face severe resource constraints, including Afghan higher-education institutions (Fazil…”
Erdemir, N., Tekeli, H., & SAYIN, İ. (2026) · Journal of Computer and Education Research · doi:10.18009/jcer.1847945
ChatGPT Sensemaking and Appropriation in Everyday Life
Ma, R., McGrenere, J., & Lindqvist, J. (2026) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3816911
Torion, J. G., Baguhin, C. L. N., Mamba, H. L., & Reyes, J. (2026) · Studies in big data · doi:10.1007/978-3-032-20412-7_47
ChatGPT in Higher Education: Conceptual Framework of Pedagogical Opportunities and Risks
Frough, E. M., Hassan, H., & Nathan, R. J. (2026) · Studies in big data · doi:10.1007/978-3-032-20412-7_19
A survey study of Cambodian university lecturers’ experiences and perceptions of AI use
Heng, K., Sok, S., Sol, K., & Sor, R. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-02313-w
“Hence, it can be concluded that AI-powered tools can be leveraged for a variety of purposes in higher education, such as supporting students’ learning, enhancing lecturers’ instructional practices, and facilitating administrative work [51, 62].”
Shahzad, M. F., Asif, M., Xu, S., Bilal, A. R., & Zahid, I. (2026) · International Journal of Information and Learning Technology · doi:10.1108/ijilt-11-2025-0340
Research on ChatGPT in higher education: shifting from exploration to policy development
Qi, B., Poo, M. C., Wang, C., & Wang, B. (2026) · Journal of Further and Higher Education · doi:10.1080/0309877x.2026.2744212
Mendoza-Zenozain, E. A., & Córdova-Buiza, F. (2026) · Contemporary Educational Technology · doi:10.30935/cedtech/19597
Doan, C. T. (2026) · Educational Media International · doi:10.1080/09523987.2026.2748545
Andayesh, S., Kianrad, Z., & Sana, S. S. (2026) · SN Social Sciences · doi:10.1007/s43545-026-01862-2
Pizarro, L. I. M., & Chávez, A. A. (2026) · Erevna Research Reports · doi:10.70171/wrwxkz66
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-05, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-05 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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