The DOI matches its Crossref record; 53 of the 56 references it cites were found in a registry or an index.
Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review
Open accessAbstract
The use of Artificial Intelligence or AI is rising in higher education. With this rise, the morality of AI programs is being questioned. There is as such a need to understand how notions of Fairness, Accountability, Transparency, and Ethics or FATE are identified in the AI and higher education studies to date. This systematic review paper aims to understand definitions and studies on FATE and AI in higher education literature. The contribution of this work is to provide a summary of FATE development and the synthesis of the challenges and potentials of each of the reviewed studies. A total of 33 review publications from SCOPUS and Web of Science (WoS) were included in this systematic literature review. We examined definitions of FATE noted in the reviewed articles (may have been multiple in each study) and grouped them into descriptive (understandable by laypeople) and technical (containing jargon) definitions. We also examined the main FATE term studied in detail in each reviewed article and grouped them into qualitative and quantitative studies. Findings show more descriptive definitions exist (especially for fairness) and similarly quantitative definitions mostly emerge for Fairness. Findings also show more quantitative studies exist (especially for fairness) and qualitative definitions mostly emerge for ethics. Generally, though, there are more definitions than relevant studies conducted in the literature. This systematic literature review offers a summary of definitions and studies conducted for FATE terms and AI in higher education literature. Future work may benefit from bridging the gap between laypeople and experts by linking descriptive definitions with technical ones as well as qualitative studies with quantitative ones. Moreover, future work can study accountability and transparency further and make the study of FATE terms more longitudinal, open-access, and reproducible.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Responsible use may promote ethical reflection and conscientious academic behavior (Memarian & Doleck, 2023), yet uncritical reliance can undermine originality, authorship norms, and institutional trust (Chan, 2023;Eaton, 2022;Fowler, 2023;Grassini, 2023;Katsamakas et al., 2024;Malinka et al., 2023;Nazaretsky et al., 2025).”
From Academic Integrity and Students’ Ethical Use of ChatGPT in Higher Education (2026) · cites this paper as Memarian & Doleck, 2023
In the citing paper
“Rights-aware educational research establishes the relevance of learner choice, academic values, legal literacy, and context-specific governance(Berendt et al., 2020;Lukianova et al., 2025;Memarian & Doleck, 2023;Oncioiu & Bularca, 2025;Panagopoulou et al., 2025;Temper et al., 2025).”
From Responsible AI in Polish Higher-Education Administration under the EU AI Act: High-Risk Use Cases, Fundamental-Rights Impact Assessment, and Institutional Accountability (2026) · cites this paper as Memarian & Doleck, 2023
In the citing paper
“The disparities in the access to high-quality tools, digital literacy, and linguistic fluency may be interpreted as digital, cultural, and linguistic capital, which benefits some groups and disfavors others (Memarian and Doleck, 2023).”
From Mapping the impact of generative AI in higher education: A scoping review of psychological and equity dimensions. (2026) · cites this paper as Memarian and Doleck, 2023
In the citing paper
“This can result from biased data, faults in the design of the model used, or societal inequalities where inbuilt into training data sets.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [40]
In the citing paper
“In such a situation, the successes of bias mitigation efforts can be held as an essential metric toward measuring how well an organization aligns its applications of AI with ethical standards38–40.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [40]
In the citing paper
“Bias is a key ethical issue for AI - sometimes, the outcome of a computation can have an unacceptably discriminatory bias.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [40]
In the citing paper
“Artificial intelligence fairness is applied to education technology to ensure equal opportunity for students regardless of their background [273].”
From AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023) · cites this paper as [273]
Citations
Cites
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-019-0171-0 · Cited by 7,242
The global landscape of AI ethics guidelines
Jobin, A., Ienca, M., & Vayena, E. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0088-2 · Cited by 6,220
Artificial Intelligence in Education: A Review
Chen, L., Chen, P., & Lin, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2988510 · Cited by 4,133
Ethics of AI in Education: Towards a Community-Wide Framework
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., et al. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00239-1 · Cited by 1,437
Evolution and Revolution in Artificial Intelligence in Education
Roll, I., & Wylie, R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0110-3 · Cited by 1,229
Baker, R. S., & Hawn, A. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-021-00285-9 · Cited by 993
The Merriam-Webster Dictionary
Merriam-Webster (1983) · CERN Document Server (European Organization for Nuclear Research) · Cited by 893
Explainable Artificial Intelligence in education
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100074 · Cited by 863
General Data Protection Regulation (GDPR)
Deaves, M. (2017) · Cited by 815
Emerging challenges in AI and the need for AI ethics education
Borenstein, J., & Howard, A. (2021) · AI and Ethics · doi:10.1007/s43681-020-00002-7 · Cited by 626
Research works printed but not linked: 1
- Quan, 2023, Vol. 119
Cited by
Sorted by citations
The Ethics of ChatGPT-Exploring the Ethical Issues of an Emerging Technology
Stahl, B. C., & Eke, D. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102700 · Cited by 476
Shahzad, M. F., Xu, S., & Zahid, H. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12949-9 · Cited by 204
Wang, C. (2025) · Technology Knowledge and Learning · doi:10.1007/s10758-024-09744-3 · Cited by 212
“Researchers also note challenges such as the varied level of technological readiness among teachers and students as well as concerns regarding accuracy, biases, accountability, transparency, and ethics (e.g., Kohnke et al., 2023; Memarian & Doleck, 2023; Ranalli, 2021).”
Dabis, A., & Csáki, C. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03526-z · Cited by 318
“It is still debated whether the hype is justi fi ed, yet the question still remains, how to address the issues arising in the wake of the educational application of GAI tools (Ivanov, 2023; Memarian and Doleck, 2023).”
Grájeda, A., Burgos, J., Olivera, P. C., & Sanjinés, A. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2287917 · Cited by 266
AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
Chen, P., Wu, L., & Wang, L. (2023) · Applied Sciences · doi:10.3390/app131810258 · Cited by 155
Sarstedt, M., Adler, S. J., Rau, L., & Schmitt, B. (2024) · Psychology & Marketing · doi:10.1002/mar.21982 · Cited by 149
Investigating L2 writers' critical AI literacy in AI-assisted writing: An APSE model
Wang, C., & Wang, Z. (2025) · Journal of Second Language Writing · doi:10.1016/j.jslw.2025.101187 · Cited by 140
A Comprehensive Survey of Deep Learning Approaches in Image Processing
Τρίγκα, Μ., & Dritsas, E. (2025) · Sensors · doi:10.3390/s25020531 · Cited by 174
Lai, C. Y., Cheung, K. Y., Chan, C. S., & Law, K. K. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100246 · Cited by 122
Rawas, S. (2024) · Discover Artificial Intelligence · doi:10.1007/s44163-024-00118-3 · Cited by 119
Policy advice and best practices on bias and fairness in AI
Álvarez, J. M., Colmenarejo, A. B., Elobaid, A., Fabbrizzi, S., Fahimi, M., Ferrara, A., Ghodsi, S., Mougan, C., Papageorgiou, I. T., Lobo, P. R., et al. (2024) · Ethics and Information Technology · doi:10.1007/s10676-024-09746-w · Cited by 147
From Guidelines to Governance: A Study of AI Policies in Education
Ghimire, A., & Edwards, J. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64312-5_36 · Cited by 164
Li, B., Bonk, C. J., Wang, C., & Kou, X. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3386098 · Cited by 109
AI literacy for ethical use of chatbot: Will students accept AI ethics?
Kajiwara, Y., & Kawabata, K. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100251 · Cited by 116
Standards, frameworks, and legislation for artificial intelligence (AI) transparency
Lund, B. D., Orhan, Z., Mannuru, N. R., Bevara, R. V. K., Porter, B., Vinaih, M. K., & Bhaskara, P. (2025) · AI and Ethics · doi:10.1007/s43681-025-00661-4 · Cited by 101
Jiang, Y., Hao, J., Fauss, M., & Li, C. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105070 · Cited by 68
Chen, A., Zhang, Y., Jia, J., Liang, M., Cha, Y., & Lim, C. P. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13064 · Cited by 67
Shi, J., Liu, W., & Hu, K. (2025) · Behavioral Sciences · doi:10.3390/bs15050705 · Cited by 77
O’Dea, X., Tsz Kit Ng, D., O’Dea, M., & Shkuratskyy, V. (2026) · Policy Futures in Education · doi:10.1177/14782103241287401 · Cited by 69
Buele, J., & Llerena-Aguirre, L. A. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1603763 · Cited by 104
A Systematic Review of AI Ethics in Education
Yan, Y.-Y., Liu, H., & Chau, T. (2025) · Journal of Global Information Management · doi:10.4018/jgim.386381 · Cited by 39
Generative Artificial Intelligence for Software Engineering—A Research Agenda
Nguyen‐Duc, A., Cabrero‐Daniel, B., Przybylek, A., Arora, C., Khanna, D., Herda, T., Rafiq, U., Melegati, J., Guerra, E., Kemell, K., et al. (2025) · Software: Practice and Experience · doi:10.1002/spe.70005 · Cited by 60
Göktaş, P. (2024) · Journal of Decision System · doi:10.1080/12460125.2024.2410042 · Cited by 69
Yaroson, E. V., Abadie, A., & Roux, M. (2025) · Annals of Operations Research · doi:10.1007/s10479-025-06534-7 · Cited by 82
Stone, B. W. (2025) · Teaching of Psychology · doi:10.1177/00986283241305398 · Cited by 54
A Social Perspective on AI in the Higher Education System: A Semisystematic Literature Review
Alshahrani, B. T., Pileggi, S. F., & Karimi, F. (2024) · Electronics · doi:10.3390/electronics13081572 · Cited by 82
Hashmi, E., Yamin, M. M., & Yayilgan, S. Y. (2024) · AI and Ethics · doi:10.1007/s43681-024-00529-z · Cited by 68
AI In Higher Education: Risks and Opportunities From the Academician Perspective
Doğan, M., Celik, A., & Arslan, H. (2024) · European Journal of Education · doi:10.1111/ejed.12863 · Cited by 65
Seven HCI Grand Challenges Revisited: Five-Year Progress
Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., Konomi, S., Nah, F. F., Ntoa, S., Rau, P. P., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2450411 · Cited by 60
Lin, M. P.-C., Liu, A. L., Poitras, E., Chang, M., & Chang, D. (2024) · Sustainability · doi:10.3390/su16208992 · Cited by 72
Avances y discusiones sobre el uso de inteligencia artificial (IA) en educación
Tramallino, C. P., & Zeni, A. M. (2024) · Educación · doi:10.18800/educacion.202401.m002 · Cited by 95
Aljabr, F. S., & Al-Ahdal, A. A. M. H. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104605 · Cited by 92
Giray, L., Sevnarayan, K., & Ranjbaran, F. (2025) · Internet Reference Services Quarterly · doi:10.1080/10875301.2024.2437174 · Cited by 62
AI for chemistry teaching: responsible AI and ethical considerations
Blonder, R., & Feldman-Maggor, Y. (2024) · Chemistry Teacher International · doi:10.1515/cti-2024-0014 · Cited by 61
From human-centered to symbiotic artificial intelligence: a focus on medical applications
Desolda, G., Esposito, A., Lanzilotti, R., Piccinno, A., & Costabile, M. F. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20414-5 · Cited by 62
Kim, J., Detrick, R., Yu, S., Song, Y., Bol, L., & Li, N. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13187-9 · Cited by 53
Assessing the quality of automatic-generated short answers using GPT-4
Rodrigues, L., Pereira, F. D., Cabral, L., Gašević, D., Ramalho, G. L., & Mello, R. F. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100248 · Cited by 47
Quttainah, M. A., Mishra, V., Madakam, S., Lurie, Y., & Mark, S. (2024) · JMIR AI · doi:10.2196/51834 · Cited by 38
Grájeda, A., Olivera, P. C., Córdova, J. P., Laguna-Tapia, A., Burgos, J., Rodríguez, L., Arandia, M., & Sanjinés, A. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2378271 · Cited by 67
The Digital Transformation of Higher Education in the Context of an AI-Driven Future
Nazyrova, A., Miłosz, M., Bekmanova, G., Omarbekova, A., Aimicheva, G., & Kadyr, Y. (2025) · Sustainability · doi:10.3390/su17229927 · Cited by 86
The Role of Artificial Intelligence in Shaping the Future of Education: Opportunities and Challenges
Іванашко, О., Козак, А., Knysh, T., & Honchar, K. (2024) · Futurity Education · doi:10.57125/fed.2024.03.25.08 · Cited by 60
Mienye, I. D., & Swart, T. G. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.02.077 · Cited by 54
Yu, J. H., Chauhan, D., Iqbal, R. A., & Yeoh, E. (2024) · Educational Technology Research and Development · doi:10.1007/s11423-024-10425-2 · Cited by 43
Ruwe, T., & Mayweg-Paus, E. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1461362 · Cited by 40
Rabbani, M. R. (2024) · Journal of Accounting & Organizational Change · doi:10.1108/jaoc-01-2024-0028 · Cited by 32
Mosly, I. (2024) · Societies · doi:10.3390/soc14060089 · Cited by 48
Undergraduate students’ perspectives of generative AI ethics
Yang, T., Cheon, J., Cho, M., Huang, M., & Cusson, N. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00533-1 · Cited by 44
Fairness for machine learning software in education: A systematic mapping study
Pham, N., Ngoc, H. P., & Nguyen‐Duc, A. (2024) · Journal of Systems and Software · doi:10.1016/j.jss.2024.112244 · Cited by 48
The impact of AI perceived transparency on trust in AI recommendations in healthcare applications
Shabankareh, M., Sahne, S. S. K., Nazarian, A., & Foroudi, P. (2025) · Asia-Pacific Journal of Business Administration · doi:10.1108/apjba-12-2024-0690 · Cited by 37
Aljohani, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-09569-9 · Cited by 30
Crossing Boundaries: The Ethics of AI and Geographic Information Technologies
Oluoch, I. (2024) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi13030087 · Cited by 29
Chiu, M.-L. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13612-7 · Cited by 29
From Shadow It to Shadow AI–Threats, Risks and Opportunities for Organizations
Silić, M., Silić, D., & Kind-Trueller, K. (2025) · Strategic Change · doi:10.1002/jsc.2682 · Cited by 50
Alghamdi, L. H., & Alghizzi, T. M. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1704820 · Cited by 39
Bullshit universities: the future of automated education
Sparrow, R., & Flenady, G. (2025) · AI & Society · doi:10.1007/s00146-025-02340-8 · Cited by 36
Fair and Transparent Student Admission Prediction Using Machine Learning Models
Raftopoulos, G., Davrazos, G., & Kotsiantis, S. B. (2024) · Algorithms · doi:10.3390/a17120572 · Cited by 32
TeachTune: Reviewing Pedagogical Agents Against Diverse Student Profiles with Simulated Students
Jin, H., Yoo, M., Park, J., Lee, Y., Wang, X., & Kim, J. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714054 · Cited by 47
Itani, A., Gronseth, S. L., Musaad, S. M. A., Nguyen, T. T., Mirabile, Y. Z., & Beech, B. M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00563-9 · Cited by 36
Artificial Intelligence for Education and Research: Pilot Study on Perception of Academic Staff
Titko, J., Steinbergs, K., Achieng, M. S., & Užule, K. (2023) · Virtual Economics · doi:10.34021/ve.2023.06.03(1 · Cited by 36
McCarthy, K. S., & Yan, E. F. (2023) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/23727322231218891 · Cited by 31
Lünich, M., Keller, B., & Marcinkowski, F. (2024) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100305 · Cited by 36
Muringa, T. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1628019 · Cited by 24
AI Technologies in Modern Taxation: Applications, Challenges, and Strategic Directions
Wang, M. (2024) · International Journal of Finance and Investment · doi:10.54097/v2kgty49 · Cited by 22
Wang, S. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13359-1 · Cited by 22
Unpacking the ethics of using AI in primary and secondary education: a systematic literature review
Wieczorek, M., Hosseini, M., & Gordijn, B. (2025) · AI and Ethics · doi:10.1007/s43681-025-00770-0 · Cited by 40
Shannaq, B. (2025) · Journal of Information & Knowledge Management · doi:10.1142/s0219649225500704 · Cited by 22
Alfaleh, M. (2026) · Sustainability · doi:10.3390/su18020785 · Cited by 47
Teaching in the Age of AI/ChatGPT in Mental-Health-Related Fields
Rajaei, A. (2023) · The Family Journal · doi:10.1177/10664807231209721 · Cited by 22
Li, B., Wang, C., Bonk, C. J., & Kou, X. (2024) · TechTrends · doi:10.1007/s11528-024-00960-3 · Cited by 29
Ethical Use of Generative Artificial Intelligence Among Ecuadorian University Students
Buele, J., Sabando-García, Á. R., Sabando-García, B. J., & Yánez-Rueda, H. (2025) · Sustainability · doi:10.3390/su17104435 · Cited by 20
Navigating ChatGPT in ASEAN Higher Education: Ethical and Pedagogical Perspectives
Buragohain, D., & Chaudhary, S. (2025) · Computer Applications in Engineering Education · doi:10.1002/cae.70062 · Cited by 32
Using Explainable AI to Rank Educational Success Factors Driving the Job Market
Shannaq, B. (2025) · Journal of Information & Knowledge Management · doi:10.1142/s0219649225500649 · Cited by 21
Behera, R. K., Janssen, M., Rana, N. P., Bala, P. K., & Chakraborty, D. (2024) · Decision Support Systems · doi:10.1016/j.dss.2024.114337 · Cited by 24
Palmer, E., Lee, D., Arnold, M., Lekkas, D., Plastow, K., Ploeckl, F., Srivastav, A., & Strelan, P. (2023) · ASCILITE Publications · doi:10.14742/apubs.2023.537 · Cited by 21
Jayasinghe, S., Gamage, K. A. A., Yang, D., Cheng, C., Disanayake, C., & Apeji, U. D. (2026) · Education Sciences · doi:10.3390/educsci16010137 · Cited by 23
Lim, T., Gottipati, S., & Cheong, M. L. F. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00556-8 · Cited by 29
To err is human: Bias salience can help overcome resistance to medical AI
Isaac, M. S., Wang, R. J.-H., Napper, L. E., & Marsh, J. K. (2024) · Computers in Human Behavior · doi:10.1016/j.chb.2024.108402 · Cited by 22
Lonsdale, H., Burns, M. L., Epstein, R. H., Hofer, I. S., Tighe, P. J., Delgado, J. A. G., Kor, D. J., MacKay, E. J., Rashidi, P., Wanderer, J. P., et al. (2025) · Anesthesiology · doi:10.1097/aln.0000000000005326 · Cited by 19
Developing a Social Support Framework: Understanding the Reciprocity in Human-Chatbot Relationship
Pan, S., & de Graaf, M. M. A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713503 · Cited by 22
Abulibdeh, A. O. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101033 · Cited by 39
A new framework for ethical artificial intelligence: keeping HRD in the loop
Wang, J., & Pashmforoosh, R. (2024) · Human Resource Development International · doi:10.1080/13678868.2024.2346492 · Cited by 37
Ethics of Artificial Intelligence and Robotics: Key Issues and Modern Ways to Solve Them
Yadav, N. (2023) · Journal of Digital Technologies and Law · doi:10.21202/jdtl.2023.41 · Cited by 20
Lünich, M., & Keller, B. (2024) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3630106.3658953 · Cited by 27
AI Ethics in the Fields of Education and Research: A Systematic Literature Review
Contreras, M. R., & JAIMES, J. O. P. (2024) · International Symposium on Accreditation of Engineering and Computing Education (ICACIT) · doi:10.1109/icacit62963.2024.10788651 · Cited by 24
Clorion, F. D. D., Alieto, E. O., Fuentes, J. O., Suicano, D. J. B., Natividad, E.-R. R., Miñoza, M. V., Pil, A. I. O., Aidil-Karanain, F., & Vallejo, R. G. (2024) · Springer eBooks · doi:10.1007/978-3-031-65691-0_16 · Cited by 18
Wang, Y., Li, H., & Savaş, H. (2025) · Journal of Education for Students Placed at Risk (JESPAR) · doi:10.1080/10824669.2025.2599161 · Cited by 19
Storozhyk, M. (2024) · Futurity Philosophy. · doi:10.57125/fp.2024.03.30.02 · Cited by 17
Smit, M., Wagner, R. F., & Bond-Barnard, T. J. (2025) · Project Leadership and Society · doi:10.1016/j.plas.2025.100187 · Cited by 19
Artificial Intelligence Tools Applied to Education: A Systematic Literature Review
Torres, C. F. Y., Cabezas, A. V. V., Torres, A. R. Y., & Torres, N. A. M. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i24.50055 · Cited by 33
Formation of Ethical Competences for AI Use in English Foreign Language Teachings
Abisheva, C., Aykenova, R., Idrissova, M., Umirzakova, L., Irgebaeva, N., Koldasbaeva, Z., Nossiyeva, N., Aipova, А., Doldinova, S., & Smoilov, S. (2024) · Qubahan Academic Journal · doi:10.48161/qaj.v4n4a1256 · Cited by 15
AI and Epistemic Risk for Democracy: A Coming Crisis of Public Knowledge?Preprint
Wihbey, J. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4805026 · Cited by 16
Reyes, R. L., & Regala, J. D. (2025) · Science & Education · doi:10.1007/s11191-025-00667-8 · Cited by 16
AI, Personalized Education, and Challenges
Mimoudi, A. (2024) · Proceedings of the International Conference on AI Research. · doi:10.34190/icair.4.1.3133 · Cited by 14
Pachava, V., Lasekan, O. A., Alarcón, C. M. M., Pena, M. T. G., & Golla, S. K. (2025) · Journal of Lifestyle and SDGs Review · doi:10.47172/2965-730x.sdgsreview.v5.n02.pe03774 · Cited by 22
Jorolan, J., Cabillo, F., Batucan, R. R., Camansi, C. M., Etoquilla, A., Gapo, J., Hallarte, D. K., Milano, M. L., Gonzales, R. R., & Gonzales, G. G. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105346 · Cited by 14
Yapay genel zekâ çağında öğretmen rolünün yeniden tanımlanması: öngörüler
Yolcu, H. H. (2024) · Açıköğretim Uygulamaları ve Araştırmaları Dergisi · doi:10.51948/auad.1383166 · Cited by 13
The Challenges of The Artificial Intelligence of Law in The Context of Technological Development
Khalifa, M., & Sabry, M. (2024) · ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) · doi:10.1109/icetsis61505.2024.10459547 · Cited by 13
Jiang, Y., Zhang, M., Hao, J., Deane, P., & Li, C. (2024) · Journal of Educational Measurement · doi:10.1111/jedm.12416 · Cited by 13
Fan, L., Kim, J., Detrick, R., & Li, N. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-7332-3.ch024 · Cited by 15
Metadata
- Authors
- Memarian, B., & Doleck, T.
- Affiliations
- Simon Fraser University (CA)
- Corresponding author
- Memarian, Bahar
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 5
- Pages
- 100152
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4382133845
- Semantic Scholar
- 77018f7f53c3c524c88994ea69d528411595b250
- Cited by
- 416
- References
- 56
- Citations by year
- 2026: 138 · 2025: 173 · 2024: 93 · 2023: 12
- FWCI
- 16.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Canada Research Chairs
- Simon Fraser University
- Canada Foundation for Innovation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- fairness, accountability, transparency, ethics, artificial intelligence in higher education, AI ethics
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.
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 ›
Are you an author, or do you see a problem with this page? Request a review
