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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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.
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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.
- Not matched
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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Toward Sustainable Learning With AI : A Methodological Agenda for Accountable Coursework
Wang, D., Ahmad, M. N., Alahmari, S., Alawad, W. M., Omar, A. H., Osman, N. A., Shen, Y., & Cheng, W. (2026) · European Journal of Education · doi:10.1111/ejed.70677
Flores, G. T., & Guyo, K. D. (2026) · International Conference on Educational and Information Technology · doi:10.1109/iceit68991.2026.11521109
“Based on this, [21] [22] advocates for the redesign of assessment design to highlight how students employ knowledge, make decisions, and explain their decisions instead of relying on an outcome-driven approach.”
Aplicação de IA generativa no processo de tomada de decisão dos estudantes
Cabral, C. A. A. (2024) · Repositório do ISCTE-IUL
Combatting academic dishonesty in online assessment
Yankova, D. (2026) · English Studies at NBU · doi:10.33919/esnbu.26.1.14
“…should be adapted to answer the requirements of the new environment and encourage cognitive processes that materialize in critical thinking, whereby faculty should engage in assessment reform which highlights more the process of learning rather than the learning output (cf. Smolansky et al., 2023).”
Bergh, C. H., Vassar, A., Banks, N., Xu, J., & Renzella, J. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29773-0_7
Integrating Educator-Designed AI Tools in Classrooms: Teachers’ Practices, Perceptions, and Concerns
Ch, N. A. N., Wong, A. Y., Corcoran, B., Barbot, H., Ahmad, Y., & Mills, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29763-1_27
Razak, N. A., Abidin, M. I. Z., Razak, A. A., Assad, A., & El-Gendi, H. (2026) · Social Sciences · doi:10.3390/socsci15070441
Moral Dilemmas of Using AI in Academia: What Do Students Think?
Drushlyak, M. G., Будянський, Д. В., Шамоня, В. Г., Бобокало, А., Skoropad, H., & Семеніхіна, О. В. (2026) · International Convention on Information and Communication Technology, Electronics and Microelectronics · doi:10.1109/mipro70003.2026.11591977
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Giray, L., Nemeño, J., Jadulos, M. X., Abosejo, M. M., & Fabros, B. G. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-33997-3_11
Ethical integration of generative AI (GAI) in higher education
David, M., Maharaj, D., & Maharaj, N. R. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-36775-5.00018-7
Salamonson, Y., Irwin, P., Kornhaber, R. A., Walker, D., McGough, S., Vakavosaki, K., Ramjan, L. M., Bloomfield, J. G., Matheson, A., & Greenwood, M. (2026) · Journal of Clinical Nursing · doi:10.1111/jocn.70484
Self Reflective and Trust Aware Generative Models for Human Aligned AI
Leburu, N., & Joseph, S. M. (2026) · IEEE Global Symposium on Emerging and Communication Technologies (GSEACT) · doi:10.1109/gseact68539.2026.11620076
“Then, reflective reconstruction is applied to output streams to assess consistency/certainty, and output streams are reconstructed through a series of reflective reconstructions for the system to self-evaluate the certainty of the outputs [18-20].”
Elepaño, M. A. D., Manimtim, L., Buendia, B. D., Pasahol, I. S., Abel, J. V., & Sargento, J. U. (2026) · International Conference on e-Education, e-Business, e-Management and e-Learning · doi:10.1109/ic4e69618.2026.11631602
“[20] and [22] noted an opportunity for innovation in Assessment Practices supporting critical thinking and higher-order skills, while acknowledging AI's potential for student cheating.”
From diffusion to negotiation: generative AI and academic integrity in higher education assessment
Mangubat, F. M., & Mangubat, F. N. (2026) · SN Social Sciences · doi:10.1007/s43545-026-01667-3
Visual and Multimodal Data Analysis for Creativity Detection in Arts and STEM
Ahmad, M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8069-8.ch004
Wang, N., & Lee, K.-Y. (2026) · Journal of Digital Contents Society · doi:10.9728/dcs.2026.27.8.2229
Rai, A. P., & Gupta, P. K. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-31097-2_38
Expanded productivity, contested authority: creativity and AI in high-impact research
Sánchez-López, I., Rojas, H. M., & Cornelio, G. S. (2026) · AI & Society · doi:10.1007/s00146-026-03213-4
“In education and academic writing, AI is framed both as a scaffold for writing, feed-back, and idea generation and as a challenge to assessment, academic integrity, and critical thinking (Fyfe 2023; Smolansky et al. 2023; Malik et al. 2023).”
Dhinakaran, D., & Raja, S. E. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9089-5.ch005
HybridDetect: Detecting Partial AI Contamination in Student Essays via Multi-Class Classification
Dan, D., & Nakayama, M. (2026) · Annals of Computer Science and Information Systems · doi:10.15439/2026f3512
“Examining usage, Smolansky et al. [16] report that educators and students alike perceive generative AI as significantly impacting assessment, while Perkins et al. [17] propose the AI Assessment Scale (AIAS), a five-level framework whose graduated levels of permitted AI assistance detection tools…”
Gusman, D., Aditya, D. S., Nurmalina, & Bujdosó, G. (2026) · IEEE Conference on Information Technology and Data Science (CITDS) · doi:10.1109/citds70571.2026.11706842
“Use acceptable-use tiers, disclosure rules, assessment review support, privacy rules, staff development, student guidance, and integrity-case support [11], [13], [19]. teachers directly or position change as a multi-actor problem [8], [20], [21].”
InfluentialTrending use of Generative Artificial Intelligence (GenAI) tools in K–12 school settings
Shirlaw, N., & Lee, J. (2026) · Technology Pedagogy and Education · doi:10.1080/1475939x.2026.2739390
Lipow, G., & Rowe, N. C. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-28454-9_19
Roberts, P., Vernon, L., Mildenhall, P., & Hall, C. (2026) · Asia-Pacific Journal of Teacher Education · doi:10.1080/1359866x.2026.2750210
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.
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