The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index; none of the 8 sources its claims cite is checked for support yet.
Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education
Open accessAbstract
The sudden popularity and availability of generative AI tools, such as ChatGPT that can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains, raises questions about the sustainability of traditional assessment practices. To seize this opportunity for innovation in assessment practice, we conducted a survey to understand both the educators' and students' perspectives on the issue. We measure and compare attitudes of both stakeholders across various assessment scenarios, building on an established framework for examining the quality of online assessments along six dimensions. Responses from 389 students and 36 educators across two universities indicate moderate usage of generative AI, consensus for which types of assessments are most impacted, and concerns about academic integrity. Educators prefer adapted assessments that assume AI will be used and encourage critical thinking, but students' reaction is mixed, in part due to concerns about a loss of creativity. The findings show the importance of engaging educators and students in assessment reform efforts to focus on the process of learning over its outputs, higher-order thinking, and authentic applications.
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“It shows that educators have a strong preference for the adapted prompt while students are less convinced by the adaptation, especially for the essay prompt.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — 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 assignment types rated to be least impacted are presentations and discussions that are either pre-recorded or live.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“A similar pattern was observed for students' ratings of the assessment's authenticity.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, only one in four students used it weekly or daily for coursework (29% Australia; 24% US) and for fun (25% Australia; 14% US).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — 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 shows that educators have a strong preference for the adapted prompt while students are less convinced by the adaptation, especially for the essay prompt.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, only one in four students used it weekly or daily for coursework (29% Australia; 24% US) and for fun (25% Australia; 14% US).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Educators were using it weekly or daily for professional purposes (35% Australia; 10% US), for research (15% Australia; 30% US), and for fun (31% Australia; 40% US).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Assessments that require product design or creative/artistic work are also rated as moderately affected.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — 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 proposed adaptation to the original prompt was generally thought to restore the level of academic integrity.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Educators were using it weekly or daily for professional purposes (35% Australia; 10% US), for research (15% Australia; 30% US), and for fun (31% Australia; 40% US).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- It may state two separate claims as one. 11
- Probably not a substantial claim. 12
- The quote only partly states this claim. 3
A result the paper reports from its own data — 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 sample we have collected thus far consists of 389 students and 36 educators from two selective institutions of higher education, one in Australia (338 students; 26 educators) and one in the United States (51 students; 10 educators).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > METHODS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We find that almost every student and all educators in our sample have heard of ChatGPT.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Besides ChatGPT, students and educators use tools like Anthropic, Bard, BingChat, ClaudeAI, DALL-E, Midjourney, and Stable Diffusion.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An important exception is that students are more hesitant to endorse the adapted prompt than educators for reasons including a perceived loss in creativity.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 5 DISCUSSION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the coding assessment, students noted that they are already using various tools:”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one. The quote only partly states this claim.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Students also had forward-looking ethical concerns:”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Students also raised concerns about the adapted coding assessment:”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. The quote only partly states this claim.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Students also raised concerns about the adapted coding assessment:”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“that essays (incl.reports, literature review, case studies, research papers), computer code (incl.pseudo-code, mathematical proofs), short-answer and multiple-choice questions are very or at least moderately impacted.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Yet students also indicated that ChatGPT is useful to get them started”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 4 PRELIMINARY FINDINGS
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one. The quote only partly states this claim.
- The authors state this as an assumption: In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
- Rests on an assumption: Pooling responses across the two institutions is valid for observing major trends.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This yields a clear within-participant comparison of how the adaptation affects their judgement of assessment quality.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > METHODS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Researchers have identified several challenges educators face in designing and implementing new online assessments [4].”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 1 INTRODUCTION
What the sources say
- Not matchedcites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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In the paper
“Unless educators and academic institutions adapt to this new reality, generative AI can undermine academic integrity in online assessment and the purpose of higher education to educate students, and ultimately reduce the value of a university degree [1].”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 1 INTRODUCTION
What the sources say
- Not matchedcites [1]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Online assessment presents practical challenges for student authentication and academic integrity: identity verification is especially difficult in online essays, and remote invigilation is challenging for online examinations [2,4].”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 2 RELATED WORK
What the sources say
- Not matchedcites [2]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [4]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“Building on an extensive literature review, they identified six design criteria and four contextual factors at play (Figure 1).”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 2 RELATED WORK
What the sources say
- Not matchedcites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The survey format and questions were almost identical for educators and students since our goal is to compare their perspectives.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > METHODS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Generative AI tools can write human-like text in a conversational style, and ChatGPT has been applied in language translation, chat bots for conversations with humans, writing articles, stories, computer code, and other types of writing [1].”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > 1 INTRODUCTION
What the sources say
- Not matchedcites [1]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“The survey instrument we developed allows us to evaluate the impact across various dimensions of online assessments [5] and evaluate similarities and differences between the student and educator perspectives.”
§ Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education > METHODS
What the sources say
- Not matchedcites [5]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
- Not matched
The authors state this as an assumption.
The framework for online assessment quality is likely to generalize across countries.
“We believe that the framework is likely to generalize across countries and we are interested in examining if it can accurately reflect students' perspectives on assessment as well.”
The authors state this as an assumption.
In today's context, generative AI tools such as ChatGPT are widely available and students have equal access to the tool.
“Now consider the same assessment prompt again but in today's context when generative AI tools, such as ChatGPT, are widely available (i.e., students have equal access to the tool).”
The paper relies on this without support.
ChatGPT can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains.
“The sudden popularity and availability of generative AI tools, such as ChatGPT that can write compelling essays on any topic, code in various programming languages, and ace standardized tests across domains, raises questions about the sustainability of traditional assessment practices.”
The paper relies on this without support.
Pooling responses across the two institutions is valid for observing major trends.
“To analyze the data we have collected so far, we compute percentages and means of participants' ratings to observe major trends pooling across the two institutions.”
The paper relies on this without support.
Students can potentially use generative AI tools like ChatGPT to cheat on online assessments by submitting essays that are not their own work.
“Students can potentially use generative AI tools like ChatGPT to cheat on online assessments by submitting essays that are not their own work.”
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 doesn’t support the claim as written.
In the citing paper
“In a survey by Intelligent.comconducted in May 2023 among 3,017 high school and college students, it was found that nearly one-third of the students admitted to using ChatGPT to complete their homework [6].”
From Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integrity (2024) · cites this paper as [6]
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“On the other, it may erode students' critical thinking and reflection if used uncritically, leading to what scholars have termed 'metacognitive laziness' (Fan et al., 2025;Smolansky et al., 2023).”
From Enhancing service-learning through Generative AI: a mixed-methods study on educational Game design in a finance course (2025) · cites this paper as Smolansky et al., 2023
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While much of the discourse around students' use of GenAI tools has tended to focus on academic integrity concerns, our understanding of the sociotechnical implications on an increasingly diverse student population is still in its infancy [33, 41, 101, 116].”
From "I'd Never Actually Realized How Big An Impact It Had Until Now": Perspectives of University Students with Disabilities on Generative Artificial Intelligence (2025) · cites this paper as [101]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“While educators favor adapted assessments integrating GenAI to maintain academic integrity and encourage critical thinking, students express mixed reactions, particularly concerning the loss of creativity [40].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [40]
The cited source says what the claim attributes to it.
In the citing paper
“While educators favor adapted assessments integrating GenAI to maintain academic integrity and encourage critical thinking, students express mixed reactions, particularly concerning the loss of creativity [40].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [40]
The cited source says what the claim attributes to it.
In the citing paper
“Although initial research (Smolansky et al., 2023) suggests that there may be gaps between students' and educators' opinions on how to achieve the best assessment approach, further research is required in this area.”
From The Artificial Intelligence Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment (2024) · cites this paper as Smolansky et al., 2023
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.
Impact ratings are attributed to the wrong figure
MinorThe text cites Figure 1 for Australian educators' and students' impact ratings, but the paper identifies Figure 2 as showing those ratings. Figure 1 is the assessment framework.
“Educators, especially in Australia (Fig. 1), rated the impact of generative AI higher than students for all types of assignments.”
“Figure: 2 Figure 2 : Figure 2: Australian educators' and students' ratings of how impacted different types of assessment are by generative AI.Mean ratings with standard error bars are shown.”
Citations
Cites
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
Assessment in the age of artificial intelligence
Swiecki, Z., Khosravi, H., Chen, G., Martinez-Maldonado, R., Lodge, J. M., Milligan, S., Selwyn, N., & Gašević, D. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100075 · Cited by 409 · cited 1×
“However, AI also raises serious concerns about the validity of assessment practices, including issues of academic integrity, especially honesty and plagiarism [3].”
BackgroundMarkauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Buckingham Shum, S., Gašević, D., et al. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100056 · Cited by 353
Mate, K. E., & Weidenhofer, J. (2021) · FASEB BioAdvances · doi:10.1096/fba.2021-00075 · Cited by 67
Towards a framework for designing and evaluating online assessments in business education
Huber, E., Harris, L. M., Wright, S., White, A. W., Raduescu, C., Zeivots, S., Cram, A., & Brodzeli, A. (2023) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2023.2183487 · Cited by 48
Self-citationOnline Assessment in Australian University Business Schools: A Snapshot of Usage and Challenges
Cram, A., Harris, L. M., Raduescu, C., Huber, E., Zeivots, S., Brodzeli, A., Wright, S., & White, A. W. (2022) · ASCILITE Publications · doi:10.14742/apubs.2022.181 · Cited by 7
Self-citation
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Guruge, D. B., Kadel, R., Shailendra, S., & Sharma, A. (2025) · Societies · doi:10.3390/soc15010011 · Cited by 5
Evaluating LLM-Generated Q&A Test: A Student-Centered Study
Wróblewska, A., Grabek, B., Świstak, J., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-98417-4_20 · Cited by 5
“The study in [7] expresses the importance of engaging students in the process of building AI-based educational solutions.”
Visual Generative AI Tools Acceptance by Multimedia and Animation University Students
Norizan, A. R., & Zamri, M. F. M. (2024) · International Visualization, Informatics and Technology Conference (IVIT) · doi:10.1109/ivit62102.2024.10692837 · Cited by 7
“In particular, the literature on the adoption of AI in teaching and learning environments [1][20][22][26] only highlighting LLMs such as ChatGPT.”
BackgroundRevell, T., Yeadon, W., Cahilly-Bretzin, G., Clarke, I., Manning, G. C., Jones, J., Mulley, C., Pascual, R., Bradley, N., Thomas, D., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3483059/v1 · Cited by 5
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“However, integration of Gen AI tools in academic environments has been met with both enthusiasm and reservations (Smolansky et al., 2023).”
The Power and Perils of AI-Driven Assessment in Higher Education
LaFrance, J. A. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-7873-1.ch010 · Cited by 4
Stewart, C. M., Nugent, P. A., Newman, R. W., Burns, M., Jeremiah, J., & Barrio, G. (2025) · The International Journal of Management Education · doi:10.1016/j.ijme.2025.101313 · Cited by 10
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“Although there is a growing body of empirical studies aiming on the usage of GAITs in higher education settings (Chan and Hu 2023; Chiu 2025; Smolansky et al. 2023), a notable gap remains: most existing research tended to utilise a fragmented approach, focussing on the core constructs of…”
Qadhi, S. M., Alduais, A. M. S., Chaaban, Y., & Khraisheh, M. A. M. (2026) · The International Information & Library Review · doi:10.1080/10572317.2026.2626122 · Cited by 7
“The findings reveal a complex interplay of opportunities and challenges, echoing the mixed perceptions highlighted in previous research (Amani et al., 2023; Smolansky et al., 2023).”
Osunbunmi, I. S., Cutler, S. L., Dansu, V., Brijmohan, Y., Bamidele, B., Udosen, A. N., Arinze, L., Oje, A. V., Moyaki, D., Hicks, M., et al. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--47041 · Cited by 6
Ahmad, M., Ravi, P., Karger, D. R., & Facciotti, M. T. (2025) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3698205.3729542 · Cited by 8
Academic dishonesty out, use of resources in
Vaezi, S., Vaezi, M., & Nami, F. (2024) · Computers and Education Open · doi:10.1016/j.caeo.2024.100193 · Cited by 6
Reconceptualizing assessment design in the age of AI: Is it genuine or faux?
Pramjeeth, S., & Ramgovind, P. (2024) · New Directions for Teaching and Learning · doi:10.1002/tl.20625 · Cited by 6
“Smolansky et al. (2023) argued that educators prefer to use adapted assessments, assuming that AI will encourage critical thinking, and focus instead on the importance of educator and student engagement in assessment reform.”
Basri, W. S., Attar, R. W., Albagmi, S., Alibrahim, D., Alanezi, F., Almutairi, S. A., AboAlsamh, H. M., Alsedrah, I. T., Arif, W. M., Alsadhan, A. A., et al. (2025) · Nutrition and Health · doi:10.1177/02601060251315795 · Cited by 4
“Studies (Carrera, 2023; Montenegro-Rueda et al., 2023; Rose, 2023) highlighted the role of ChatGPT in promoting re fl ective teaching practices among educators, leading to enhanced self-awareness and re fi nement of instructional strategies.”
Munisamy, M., Osman, S. Z. M., & Sanmugam, M. (2024) · International Journal of Modern Education · doi:10.35631/ijmoe.620027 · Cited by 4
Generative AI: Challenges and Opportunities in the Higher Education Sector in Cambodia
Islam, M. M. (2024) · Springer eBooks · doi:10.1007/978-981-97-3512-9_6 · Cited by 5
Wan, K., Woo, Y. Y., & Ho, G. T. S. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2592370 · Cited by 10
“On the other, it may erode students ’ critical thinking and reflection if used uncritically, leading to what scholars have termed ‘ metacognitive lazi-ness ’ (Fan et al., 2025; Smolansky et al., 2023).”
AI-Assisted Assessment: A Dual Perspective on Effective Usage Plans for Students and Teachers
Ferreira, J. M. M. (2025) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016448 · Cited by 5
Singh, P., & Anthonysamy, L. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13773-5 · Cited by 6
Adoption and perceptions of generative AI among South African academics
Schoon, A., Smit, A., Uzuegbunam, C. E., & Bosch, T. E. (2025) · Teaching in Higher Education · doi:10.1080/13562517.2025.2571911 · Cited by 5
“Indeed, some academics now consider best practice assessment to incorporate assumptions that students will use GenAI (Smolansky et al. 2023).”
Ba, S., Lu, G., Mendoza, N. B., Yang, Y. P., Pan, Z., & Wang, Y. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251396357 · Cited by 3
“As such, traditional outcome-based assessments may not be suf fi cient to capture the full spectrum of learning in GAI-mediated environments (Smolansky et al., 2023).”
Exploring the benefits and challenges of AI-driven lesson planning among preservice science teachers
Chua, K. H., Sathasivam, R. V., Mafarja, N., & Rahim, S. S. A. (2026) · STEM Education · doi:10.3934/steme.2026001 · Cited by 7
AI-driven adaptive stealth assessment for socially regulated learning in collaborative environments
Hadyaoui, A., & Cheniti-Belcadhi, L. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2586501 · Cited by 5
“In parallel, generative AI has improved personalization and feedback quality (Baidoo-Anu & Owusu Ansah, 2023; Chiu, 2024; Smolansky et al., 2023), but most studies optimize content delivery for individuals rather than aligning interventions with collaborative regulation.”
InfluentialRapidly changing attitudes of university students on the use of generative artificial intelligence
Williams, A. E. (2026) · Journal of Further and Higher Education · doi:10.1080/0309877x.2026.2634035 · Cited by 6
“Students tend to emphasise the practical utility and potential for learning enhancement, whereas educators are more concerned about the impact of AI on academic integrity, erosion of cognitive development and institutional readiness (Khlaif et al. 2024; Smolansky et al. 2023).”
Gu, G., & Li, H. (2024) · International Conference on New Media Development and Modernized Education (NMDME) · doi:10.4108/eai.13-10-2023.2341285 · Cited by 3
Amar, S. H., & Benchouk, K. (2024) · Springer eBooks · doi:10.1007/978-3-031-65691-0_3 · Cited by 3
Ethical and Responsible Generative AI Use: Perspectives from STEM and Non-STEM Educational Contexts
Chinedu, C. C., Justin, G., Eriagbondia, J. D.-O., Lopez, A. T., & Osabiya, A. (2024) · Lecture notes in educational technology · doi:10.1007/978-981-97-8752-4_19 · Cited by 4
Dockens, A. L., & Shelton, K. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0502-8.ch005 · Cited by 4
Designing with AI: Integrating Image-Generative AI into Conceptual Design in a CAD Class
Zhu, W., Guo, R., Wang, Y., Xing, W., Kim, E. M., & Li, C. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--47146 · Cited by 3
Learning Through the Dialogue with NPCs Using Generative AI
Rodrigues, V., & Silva, F. G. M. (2024) · International Conference on Graphics and Interaction (ICGI) · doi:10.1109/icgi64003.2024.10923796 · Cited by 3
Catholic higher education interface with AI: diversions and intersections
Ocampo, L.-M. A. R., & Gozum, I. E. A. (2025) · International Studies in Catholic Education · doi:10.1080/19422539.2025.2464734 · Cited by 2
Coelho, R., Bjune, A. E., Ellingsen, S., Solheim, B. M., Thormodsæter, R. S., Wasson, B., & Cotner, S. H. (2025) · Journal of Science Education and Technology · doi:10.1007/s10956-025-10216-1 · Cited by 4
“Using two different assessment scenarios, Smolansky et al. (2023) found that students expressed concerns about a loss of creativity when given a task to analyze essays produced by ChatGPT and improve their quality.”
EDUCATION CLASSES FOR PRE-SERVICE TEACHERS USING TEXT-VIDEO-BASED AI
Oh, S. (2025) · Journal of Baltic Science Education · doi:10.33225/jbse/25.24.538 · Cited by 4
Mwaniki, S., Araka, E., Kituku, B., & Maina, E. M. (2025) · IST-Africa Conference (IST-Africa) · doi:10.23919/ist-africa67297.2025.11060553 · Cited by 2
“Furthermore, ideas regarding problem-solving, coding, and research benefits for deploying AI in academic institutions can be used for the expansion of the applied usage of AI, thus contributing to the increased market share and recognition of AI’s benefits among academics [35].”
Bridging code and timely feedback: integrating generative AI into a programming platform
Martínez-Araneda, C., Gutiérrez, M., Aranda, J. L. M., Montiel, D. M., Gómez, P., & Segura-Navarrete, A. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.3070 · Cited by 2
Promoting Generative AI Literacy among Students and Teachers
Soltani, M., Zarzour, H., & Ladjailia, A. (2025) · Signals and communication technology · doi:10.1007/978-3-031-96855-6_12 · Cited by 2
Mapping the landscape: generative AI in higher education assessment (2020-2024) - a scoping review
Ng, S. H. S., Chan, H. Y., Wong, J. H. K., Sam, L. C. F., & Privitera, A. J. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2614079 · Cited by 9
“…and McGivern (2024) and Tong et al. (2023) identified that students were generally more positive than educators regarding the use of GAI in assessment, Smolansky et al. (2023) observed the opposite pattern, with students being particularly concerned about the loss of creativity when GAI was used.”
Rai, A. P., Gupta, P. K., & Roy, S. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-7807-5_29 · Cited by 2
Sorour, A. S., & Atkins, A. S. (2024) · Advances in logistics, operations, and management science book series · doi:10.4018/979-8-3693-1198-1.ch003 · Cited by 2
WIP: Impact of Generative AI on Learning: Foci and Parameters for an Assessment Tool
Khan, M. M., Ford, C., Dong, Y., & Afsarimanesh, N. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10893560 · Cited by 3
“This issue would often require establishing the quality and methodological framework of the sources used during the training and modelling stages [38, 39].”
From Chalkboards to ChatGPT: Navigating the Future of Teaching with Generative AI
Graefe, B., Porter, A., Indorf, J. L., Ahn, S., Chuan, C.-H., & Gaines, M. S. (2025) · The Journal of Interactive Learning Research · doi:10.70725/029002jsmbne · Cited by 2
Cultivating self-directed learners through research-based learning in the undergraduate curriculum
Uys, W. F., & Chigona, W. (2025) · South African Journal of Education · doi:10.15700/saje.v45ns1a2678 · Cited by 2
“…is especially true where students are becoming more dependent on large-language models such as ChatGPT, Anthropic, Bard, Bing Chat and Claude AI (Smolansky, Cram, Raduescu, Zeivots, Huber & Kizilcec, 2023) to assist them in research areas such as idea generation, summarising articles, and…”
تطبيقات الذكاء الاصطناعي التوليدي التعليمية
سليمان, أ. م. د. م. و. م., & على, م. م. ف. ا. (2024) · Maǧallaẗ Buḥūṯ fi Al-ʿulūm wa Al-Funūn Al-Nawʿiyyaẗ · doi:10.21608/balexu.2024.352891 · Cited by 1
Usage of Gen AI in Employee Training and Development
Bapat, O. J., Prakash, C., & Paliwal, M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-7693-5.ch004 · Cited by 1
Ethical Integration of Generative AI in Higher Education Assessments
AlMohsen, F. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-7332-3.ch017 · Cited by 1
“It's a Social Practice, and Schools Cannot Ignore It”
Cușnir, C., & Surugiu, R. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-6018-8.ch014 · Cited by 1
NEODGOVORNO KORIŠĆENJE CHATGPT-JA OMETA AKADEMSKI UČINAK
Đurđević, N., Maksimović, M., & Nikolić, T. M. (2025) · Limes plus. · doi:10.69899/limes-plus24212-3125d · Cited by 1
Applications and Challenges of Artificial Intelligence in Educational Course Design and Delivery
Dan, D., Wróblewska, A., Grabek, B., Taczała, M., & Nakayama, M. (2025) · Annals of Computer Science and Information Systems · doi:10.15439/2025f8073 · Cited by 1
Comparison of Generative Artificial Intelligence Tools in the Assessment of Student Assignments
Novak, M., Andročec, D., & Picek, R. (2025) · International Conference on Software, Telecommunications and Computer Networks (SoftCOM) · doi:10.23919/softcom66362.2025.11197413 · Cited by 2
“[2], Almasre [3], and Smolansky [4], have started to investigate this application.”
Not a Swiss Army Knife: Academics' Perceptions of Trade‐Offs around Generative AI Use
Razi, A., Bouzoubaa, L. A., Pessianzadeh, A., Seberger, J. S., & Rezapour, R. (2025) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1277 · Cited by 2
“Recent studies have identified the need for specific frameworks around academic integrity (Smolansky et al., 2023; Vargas-Murillo et al., 2023; J. Yang, 2023) to mitigate harmful content and negative social impact.”
Osunbunmi, I. S., Shih, B. P.-J., Cutler, S. L., & Perez, C. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328161 · Cited by 2
“However, the rapid adoption of AI in education driven by students has been largely disruptive to university faculty and administration, navigating new strategies of teaching and learning that are ever-emerging and available to us [2].”
A Survey on AI-Generated Text Detection: Methods, Challenges, and Future Directions
Ismail, A. A., Ahmed, C., & ElKorany, A. (2025) · Future International Conference on Artificial Intelligence and Cybersecurity (FICAC) · doi:10.1109/ficac65757.2025.11341850 · Cited by 1
“This increasing dependency on generative AI poses a serious risk to academic honesty, as it diminishes students' creativity and impairs their learning abilities (Smolansky et al. 2023)[27].”
Concerns and Ethical Awareness of University Students Towards the Use of Generative AI
Yaacob, Y., Mahmud, M. M., Ahmad, R., A’seri, M. S. M., & Mustamam, N. I. (2025) · International Conference on Education Technology and Computer · doi:10.1109/icetc66579.2025.11387607 · Cited by 1
Generative AI and Ethical Integration in K-12 and Higher Education
Shaikh, S., Maroof, M. A., Kaskar, P., Girhe, P. B., Magar, A. V., & Sudhahar, W. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0101-1.ch004 · Cited by 1
Perceptions and Use of Generative Artificial Intelligence (AI) Among Criminal Justice Students
Nodeland, B., Saber, M., & Wall, R. (2026) · Journal of Criminal Justice Education · doi:10.1080/10511253.2026.2640902 · Cited by 1
Undergraduate mathematics faculty attitudes and experiences with generative AI integration
Joung, E., Brinkerhoff, R., Lee, I., Wong, A., & Ioane, O. (2026) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.29333/ejmste/18126 · Cited by 1
“Despite potential benefits, faculty express significant concerns about GenAI integration, particularly regarding academic integrity and student outcomes (Lim et al., 2023; Michel-Villarreal et al., 2023; Smolansky et al., 2023; Yoon et al., 2024).”
A Systematic Review of Ethical Integration of Generative AI in Higher Education
Yarboi, P. Y., Adu-Manu, K. S., Amponsah, S., Oheneba-Sakyi, Y., & Barimah, A. (2026) · Education Sciences · doi:10.3390/educsci16071016 · Cited by 1
An Ontology-Driven Framework for Adaptive and Transparent AI-Assisted Student Assessment
Hadyaoui, A., & Cheniti‐Belcadhi, L. (2026) · Lecture notes in business information processing · doi:10.1007/978-3-032-25534-1_11 · Cited by 1
Claver, J. M. Z. R., Tajdini, M., & Merino, M. V. (2026) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3786580.3786955 · Cited by 1
Impact of Generative AI in Education 2030
Adhikari, S., Kumbhakar, D., Indra, N., & Karforma, S. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-2440-0.ch025 · Cited by 1
AI-Enhanced Ecological Learning Spaces
Ilic, P., & Sato‐Ilic, M. (2024) · Intelligent systems reference library · doi:10.1007/978-3-031-71232-6_2 · Cited by 1
Sterbini, A., & Temperini, M. (2024) · International Conference on Information Technology Based Higher Education and Training (ITHET) · doi:10.1109/ithet61869.2024.10837616 · Cited by 1
“…the idea that this current turn of time is offering a crucial opportunity for significant innovation in the (automated) support to assessment, in [24] the authors present an ongoing study about the impact of generative AI on assessments, as felt by two main involved stakeholders: teachers and…”
Digital Enhancement: Applying Generative AI in Students Decision Making Process
Cabral, C. A. A., & Pereira, R. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-031-78412-5_7 · Cited by 1
AI-Assisted Educational Design: Academic-GPT Collaboration for Assessment CreationPreprint
Chan, K. C., Lokuge, S., Fahmideh, M., & Lane, M. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4996532 · Cited by 1
Ntumi, S., & Bulala, T. (2025) · Research Square · doi:10.21203/rs.3.rs-5532346/v1 · Cited by 2
EvaluAId: Human-AI Collaborative Evaluation of Open-Ended Student Essays
Zhang, C., Ju, K. P., Lu, X., Yen, Y.-C. G., & Rzeszotarski, J. M. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790814 · Cited by 2
“Despite these recent advances, the use of LLMs in assessment has not resolved long-standing concerns around automation, in-accuracies, and alignment [13, 31, 35, 41, 71].”
Anakok, I., Chew, K. J., Matusovich, H., & Katz, A. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--47829
Reza, R. B., Mahmud, M. R., & Ahmed, S. M. Z. (2024) · Science & Technology Libraries · doi:10.1080/0194262x.2024.2413558
“In contrast, Smolansky et al.’s (2023) study found that although there is fear that reliance on AI tools may lead to a decline in such skills, some academics believed that generative AI tools can enhance critical thinking among students.”
Re-imagining Education Through AI: Students Insights from DigiEduHack
Paludo, G., Vielmo, C., Fiore, F., Zozzo, A. D., Decarli, G., Montresor, A., & Bigatto, M. (2024) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-97-9255-9_30
Efficient Didactic Methods Used in Modern E-Learning and Traditional Environments
Aldea, C. L., Iliescu, D. M. D., Bocu, R., & Vasilescu, A. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-84263-4_22
Generative AI in Higher Education Transforming Assessment and Feedback With Optimization Approach
Bhimavarapu, U. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-8744-3.ch006
The Use of Generative Artificial Intelligence in Higher Education
Miller, T., & Habada, P. (2025) · doi:10.55277/rhj.ql8ttmax
Joshi, O. S. (2025) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3696630.3731469
Generative AI in Business Education Transforming Teaching and Learning
Ellahi, A., Jan, M. F., & Khan, M. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-2150-9.ch003
K, D. V. A. (2025) · International Journal of Innovative Research in Technology · doi:10.64643/ijirtv12i1-181732-459
IRRESPONSIBLE USE OF CHATGPT IMPEDES ACADEMIC PERFORMANCE
Đurđević, N., Maksimović, M., & Nikolić, T. M. (2025) · Limes plus. · doi:10.69899/limes-plus-en-24212-3121d
Penpeña, R. A. P. (2025) · EthAIca · doi:10.56294/ai2025426 · Cited by 2
Merino, M., & Duarte, S. R. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7574-8.ch004
Overview of the Use of AI in Buildings Sustainability Assessment
Ersener, T., & Fokaides, P. A. (2025) · Lecture notes in civil engineering · doi:10.1007/978-3-032-09040-9_4
Defining a Methodology to Cocreate Microlearning Resources Based on GenIA and Social Appropriation
Losada, B. M., Vásquez, S. I. A., Osorio-Sanabria, M. A., & Díaz, J. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-00701-8_8
Assessing the Validity of Generative AI in Practice Content
Trahan, M. H., & Nason, E. E. (2025) · Springer eBooks · doi:10.1007/978-3-031-95060-5_26
An Exploration and Scale Validation on Critical Thinking Engagement in Context of Generative AI
Cornet, A. (2025) · Springer Proceedings in Behavioral & Health Sciences. · doi:10.1007/978-981-95-1936-1_10
Nurhayati, S., Lotfi, F. Z., Taufikin, T., & Hidayat, A. W. (2025) · Information systems engineering and management · doi:10.1007/978-3-032-05306-0_1 · Cited by 3
University student experiences of feedback: timing and credibility are key
Willis, A. S., Sempowicz, T., & Robertson, A. (2025) · Teaching in Higher Education · doi:10.1080/13562517.2025.2605679
“These findings are timely, given the rise of online modes of learning (Naylor & Nyanjom 2021) and artificial intelligence use in assessment (Smolansky et al. 2023).”
Alghamdi, A. (2025) · Lecture notes in educational technology · doi:10.1007/978-981-95-5234-4_15
The Dual Edge of Large Language Models
Boulhrir, T., Hamash, M., & Ghreir, H. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-5017-2.ch009
A Pragmatic Approach to using LLMs
Mays, T. (2025) · Journal of ExoTechnology and Education · doi:10.36615/dr5ynf77
ChatGPT as a Teaching Assistant in a CS1 course: An Experience Report
Gomes, L. N., Fraga, C. F., de Holanda, M. T., & Silva, D. D. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328432 · Cited by 2
“In the post-pandemic period, AI has influenced the development of new assessment methods, highlighting the need for changes in academic practices [6] [7] [1].”
Information et intelligence artificielle
Cușnir, C., Popescu-Jourdy, D., & Surugiu, R. (2025) · De Boeck Supérieur eBooks · doi:10.3917/dbu.broud.2025.01.0213
Kapur, I., Cronley, C. C., & Sharkey, C. N. (2026) · Journal of Social Work Education · doi:10.1080/10437797.2025.2602743
“There has been general research exploring student perspectives in fields and locations, such as U.S. medical students (Park et al., 2021), Canadian healthcare students (Teng et al., 2022), and across disciplines (Smolansky et al., 2023).”
Institutional Analytics for Transformation
Baker, R. S. (2026) · Rastros Rostros · doi:10.16925/2382-4921.2026.01.01
How AI Shaped Students’ Perceptions of Assessment within Online Learning Environments
Kim, S. Y., Bolliger, D. U., & Martin, F. (2026) · American Journal of Distance Education · doi:10.1080/08923647.2026.2622771
Sevnarayan, K. (2026) · Springer eBooks · doi:10.1007/978-3-032-01638-6_7
Konstantinidis, K., Apostolakis, I., Malamateniou, C., & Papagiannis, P. (2025) · European Journal of Engineering and Technology Research · doi:10.24018/ejeng.2025.1.cie.70024
Survey on the Use of Generative AI Tools by Undergraduate Computer Science Students
Pezer, M., Zafar, M. N., Naderi, M., Salem, H., Mazzara, M., & Stanko, T. (2026) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-95-4423-3_47
(2026) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-80686-799-820261016
Harfe, B. D., & Thomas, A. (2026) · TechTrends · doi:10.1007/s11528-026-01182-5 · Cited by 1
“…populations report that 86% of students have used generative AI in their course-work, with 54% admitting to weekly use, and 66% of those employing ChatGPT, the most widely adopted tool for AI-generating text (Adiguzel et al., 2023b; Kizilcec et al., 2024; Rong & Chun, 2024; Smolansky et al., 2023).”
Participatory, not Punitive: Student-Driven AI Policy Recommendations in a Design Classroom
Seki, K., Vijay, M., & Kotturi, Y. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790691 · Cited by 1
“Although not the first technology to disrupt higher education [78], generative AI technologies capable of producing text, images, and other media [110] have gripped administrators, faculty, and students alike, all racing to manage its challenges and opportunities [113].”
Designing a Generative AI Solution for Creating Summative Assessments in Higher Education
Sahli, S., & Gillet, D. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-18888-5_18
Levy‐Nadav, L., Shamir‐Inbal, T., & Blau, I. (2026) · Education Sciences · doi:10.3390/educsci16050744
Metadata
- Authors
- Smolansky, A., Cram, A., Raduescu, C., Zeivots, S., Huber, E., & Kizilcec, R. F.
- Affiliations
- Cornell University (US)
- The University of Sydney (AU)
- Cornell University, Ithaca, NY, USA
- Venue
- Proceedings of the Tenth ACM Conference on Learning @ Scale
- Publisher
- ACM
- Published
- 2023-07-20
- Pages
- 378-382
- OpenAlex
- W4384662087
- Semantic Scholar
- f6943500f55c8b67b2396238ea71d2b18f574323
- Cited by
- 275
- References
- 6
- Citations by year
- 2026: 76 · 2025: 116 · 2024: 79 · 2023: 4
- FWCI
- 63.59
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Conference on Learning @ Scale (L@S) (publishedVersion)
- Funders
- USyd-Cornell Partnership Collaboration Awards (PCA) (1178246719)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Academic integrity and plagiarism
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- generative AI, ChatGPT, higher education assessment, academic integrity, student perceptions, educator perspectives, assessment reform, critical thinking, creativity, higher-order thinking skills, artificial intelligence in education
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 2026-10-23, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-23 (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.
What counts as a claim ›How we measure confidence ›How we check this ›
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