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Exploring the impact of generative AI-based technologies on learning performance through self-efficacy, fairness & ethics, creativity, and trust in higher education
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“Improved AI literacy and sustainable integration can foster creativity and self-efficacy, thereby enhancing learning performance and academic achievements [6].”
From Generative artificial intelligence in physiotherapy education: great potential amidst challenges- a qualitative interview study (2025) · cites this paper as [6]
In the citing paper
“Empirical studies suggest that when AI-enhanced learning environments are grounded in principles of fairness, transparency, and trust, they can positively influence learning performance while developing students' ethical sensitivity (Shahzad et al., 2025).”
From Managing Artificial Intelligence Ethics in Higher Education: A Systematic Framework for Issues and Policy Recommendations (2025) · cites this paper as Shahzad et al., 2025
In the citing paper
“To ensure content validity, the questionnaire items were adapted from established scales validated by prior studies [56].”
From From Perception to Practice: Artificial Intelligence as a Pathway to Enhancing Digital Literacy in Higher Education Teaching (2025) · cites this paper as [56]
In the citing paper
“The analysis yielded consistently positive Q 2 values across all endogenous constructs, surpassing the null threshold and confirming the model's predictive relevance (Shahzad et al., 2024).”
From From Perception to Practice: Artificial Intelligence as a Pathway to Enhancing Digital Literacy in Higher Education Teaching (2025) · cites this paper as Shahzad et al., 2024
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“The teachers and administrators in HE should consider the utilization of generative AI technologies to enhance student learning (Baidoo-Anu & Owusu Ansah, 2023 ; Shaofeng et al., 2023 ).”
GPT-3: Its Nature, Scope, Limits, and Consequences
Floridi, L., & Chiriatti, M. (2020) · Minds and Machines · doi:10.1007/s11023-020-09548-1 · Cited by 2,519
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- Hartati, R., & Manullang, E. B. (2024). Implementation of Telegram Chatbot AI with Natural Language Processing (NLP) in learning creative entrepreneurship to develop students’ creative and innovative competence. TALENTA Conference Series, 7(2654–7066), 73–79. https://doi.org/10.32734/lwsa.v7i2.2055 · DOI
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Al‐Emran, M., Al-Sharafi, M. A., Foroughi, B., Al-Qaysi, N., Leung, N. K. Y., Yaseen, Z. M., & Ali, N. B. (2026) · Journal of Educational Computing Research · doi:10.1177/07356331261463140 · Cited by 2
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Leba, S. M. R., Nggaruaka, T., & Butarbutar, R. (2025) · EthAIca · doi:10.56294/ai2025419 · Cited by 2
Chang, T., Hsu, H.-Y., & Lei, Z. (2025) · The International Journal of Management Education · doi:10.1016/j.ijme.2025.101305 · Cited by 2
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“This allows students to explore various approaches and perspectives in problem-solving, thereby encouraging them to think more creatively (Arizona et al., 2025; Shahzad et al., 2025).”
Bridging the engagement gap in B2B marketing education: Integrating storytelling and AI
Malhan, M. (2025) · The International Journal of Management Education · doi:10.1016/j.ijme.2025.101279 · Cited by 1
Cheng, X., Wang, T., Ou, Y., & Chen, Y. (2025) · Internet Research · doi:10.1108/intr-08-2024-1237 · Cited by 1
Ethical Judgments in GenAI Environments: A Study of ChatGPT Users
Gupta, P., Hooda, A., Jeyaraj, A., & Dwivedi, Y. K. (2026) · Journal of Computer Information Systems · doi:10.1080/08874417.2025.2610300 · Cited by 1
Hou, S. (2026) · Frontiers in Education · doi:10.3389/feduc.2025.1681007 · Cited by 1
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Delina, G., & Kumar, R. M. (2026) · Management and Labour Studies · doi:10.1177/0258042x261419180 · Cited by 2
“Shahzad et al. (2025) found that generative AI tools like ChatGPT can enhance students’ learning performance and academic achievement.”
Sultana, A., Latheef, N. A., Siby, N., Sellami, A., Abbasi, S. A., & Ahmad, Z. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2625448 · Cited by 1
Muneer, S., Singh, A., Choudhary, M. H., & Anum, S. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-026-07532-1 · Cited by 1
“This correlation can be explained by the feelings of mastery and independence that technological competence conveys to students, equipping them to deal with challenging academic tasks (Shahzad et al., 2024).”
Yang, F., & Tang, Y. (2026) · International Conference on Educational and Information Technology · doi:10.1109/iceit68991.2026.11521541 · Cited by 1
“In turn, self-efficacy is a robust predictor of academic success because it promotes greater effort, persistence, and adaptive strategy use, which collectively improve learning performance [8, 9].”
InfluentialTessarolo, F. M., Whitelock, D. M., Edwards, C. B., & Bektik, D. (2026) · European Journal of Open Distance and E-Learning · doi:10.65043/eurodl.186 · Cited by 1
Hu, W. W. (2026) · Studies in Higher Education · doi:10.1080/03075079.2026.2658738 · Cited by 1
“…of GenAI uptake – including academic self-efficacy, trust, motivation, and anxiety (Chai et al. 2024; Choung, David, and Ross 2023; Ma 2025; Shahzad, Xu, and Zahid 2025; Wang et al. 2025; Wang, Sun, and Chen 2023) – providing useful baseline insights into user acceptance and system design.”
Ashraf, M. A., Aftab, M., Mohsin, M., Maqbool, S., & Hanif, M. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1807322 · Cited by 3
“The chatbot-based learning system aims to achieve motivational and instructional objectives by offering a conversational interface, clear learning outcomes, and enabling students to learn flexibly on their own schedule (26).”
Prianto, C., Komaro, M., & Saripudin (2026) · Language, Technology, and Social Media. · doi:10.70211/ltsm.3026-7196.403 · Cited by 1
“When users increasingly rely on AI systems for explanation, writing, decision-making, and evaluation, the authority to interpret and produce knowledge may gradually shift from humans to algorithmic systems [5], [7], [9], [13].”
InfluentialAl-Sharafi, M. A., Elgendy, I. A., Helal, M. Y., Alahmad, R., Chae, I., & Dwivedi, Y. K. (2026) · International Journal of Innovation Management · doi:10.1142/s1363919626500210 · Cited by 1
Liu, G., & Zhang, X. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1829753 · Cited by 1
“Collaborative and inquiry-based learning models combined with AIGC tools enhance creativity and critical thinking (Kumar, 2021; Shahzad et al., 2025).”
Yang, C. H., Li, R. F., & Feng, D. (2026) · The Asia-Pacific Education Researcher · doi:10.1007/s40299-026-01132-y · Cited by 1
Jafari, A., Alemohammad, S. M. A., & Chahardeh, N. M. (2026) · International Interdisciplinary Conference on Artificial Intelligence: Engineering, Health, Finance and Humanities (IICAI) · doi:10.1109/iicai70155.2026.11620992 · Cited by 1
“The study highlights the growing role of LLM-based systems in supporting student performance within modern educational environments [7].”
Measuring the Effect of GenAI Chatbots in CSCL environments: A Study with PyramidApp
Sánchez-Reina, J. R., Gutiérrez-Ferré, A., & Hernández‐Leo, D. (2025) · Computer-supported collaborative learning/The Computer-Supported Collaborative Learning Conference · doi:10.22318/cscl2025.114109 · Cited by 1
Ren, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1926110
“On the positive side, generative AI may support individualized tutoring, rapid feedback, language learning, and access to explanations for students with diverse learning needs (Kasneci et al., 2023; Tlili et al., 2023; Shahzad et al., 2025).”
Toward Partnership Ethics for Generative Artificial Intelligence in Higher Education
Gillette, M., Wackenhut, A., & Olsson, E. (2026) · Journal of University Teaching and Learning Practice · doi:10.53761/yf2gt848 · Cited by 1
“Many scholars studying genAI in higher education raise the subject of ethics (e.g., Bearman et al., 2025; Bozkurt, 2024; Dabis & Csáki, 2024; Fitzgerald et al., 2025; Rudolph et al., 2024; Shahzad et al., 2025).”
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Poole, A. H., Ahmed, A., & Mentis, H. M. (2025) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1339 · Cited by 2
“…(Anuyahong et al., 2023; Baidoo-Anu & Owusu Ansah, 2023; Chan & Hu, 2023; Chang & Kidman, 2023; Chen et al., 2025; Gunawan & Wiputra, 2024; National Academies of Sciences, Engineering, and Medicine, 2024; Nguyen et al., 2024; Saúde et al., 2024; Shahzad et al., 2025; Simkute et al., 2025).”
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대학운동선수의 생성형 AI 활용도와 학업적 자기효능감, 학업스트레스 및 학업지연행동, 학업성취도 간의 구조적 관계*
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“By submerging learners in communicating virtual environments, VR endorses mental skills such as spatial reasoning and memory holding, as well as abstract thought, which are vital for creative thinking and artistic manufacture [39].”
ChatGPT in Political Education
Song, H. (2025) · Education as Change · doi:10.25159/1947-9417/19336
Wu, B., & Chen, Y. (2025) · International Workshop on Artificial Intelligence and Education (WAIE) · doi:10.1109/waie67422.2025.11381034
“Furthermore, Shahzad et al. stated that whether educators receive and trust AI is based on their perceptions of fairness and ethics [13].”
Li, J., Meng, W., & Flores-Hurtado, R. (2025) · International Workshop on Artificial Intelligence and Education (WAIE) · doi:10.1109/waie67422.2025.11381135
“The impact of this transformation extends beyond its technical utility; it deeply intersects with human emotion, cultural identity, and the ethical frameworks that govern creative expression [5, 6, 7] .”
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How and when does artificial intelligence augment management student creativity?
Leong, A. M. W., Li, X., Lee, J. C.-K., Ji, L., & Bai, J. (2026) · The International Journal of Management Education · doi:10.1016/j.ijme.2026.101391
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“Several studies have reported significant improvements in academic achievement facilitated by AI technologies (Fidan & Gencel, 2022; Mollick & Mollick, 2022; Shahzad et al., 2024; Urban et al., 2024; Wu & Yu, 2024).”
Activity theory as a lens on teachers’ adoption of AI technologies: A structural equation modeling
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Zhang, S., Zhang, S., & Liang, W. (2025) · IEEE Integrated STEM Education Conference (ISEC) · doi:10.1109/isec64801.2025.11460250
“While these studies examine the effects of GenAI on self-efficacy [3], learning performance [4], and motivation [5], they often overlook vocational school students, who also use GenAI for assignments, projects, and course studies.”
Ethics and Learning: Impact of Generative Artificial Intelligence on Higher Secondary Education
Luévano, J. A., Lozano, P. M., & Ruvalcaba, F. R. A. (2026) · SAP Social AI · doi:10.62486/sai202656
Sustainability of AI Use in Higher Education: The Role of Perceived Usefulness and Self-Efficacy
Hassan, S. A., & Yassine, N. (2025) · International Conference on Recent Advances in Mathematics and Informatics (ICRAMI) · doi:10.1109/icrami64946.2025.11472670
“Prior literature has examined the importance of AI intelligence skills on users’ self-efficacy [34,35].”
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“Recently, students ’ AI adoption was studied while extending TAM to include subjective norms, ethics, and trust, finding that each of these factors had an crucial moderating effect on PU and the outcome of attitude and usage [10], [11].”
Yapay Zekâ Kullanım Algısının Bireysel Belirleyicileri: Akademik Motivasyon ve Öz-Yeterliğin Rolü
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A Study on the Adoption Mechanism of AI-Supported Learning Based on TAM and Social Cognitive Theory
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“Similarly, when learners perceive AI tools as beneficial and effective, their sense of competence and motivation improves, strengthening their AI learning self-efficacy [ 35 ] .”
Two Pathways at Once: How Reactance and Ethical Engagement Shape Student Learning with AIPreprint
Hyde, S. J., Hanna, A. A., & Kaupins, G. E. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6665242
Deni̇z, Ü. (2026) · Journal of College Reading and Learning · doi:10.1080/10790195.2026.2667284
“Additionally, research is needed to understand how AI writing tools influence students’ writing self-efficacy, academic identity formation, and ethical reasoning (Bin-Nashwan et al., 2023; Shahzad et al., 2025).”
Generative AI Ethics in Open Distance Learning
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Fan, J., Huang, M., Zhao, X., Fang, Y., Zhang, H., & Lu, J. (2026) · TechTrends · doi:10.1007/s11528-026-01188-z · Cited by 1
“For instance, Shahzad et al., (2024) explored the role of trust in mediating the effects of generative AI on academic performance and self-efficacy.”
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“By analyzing students’ learning data, AI systems can generate personalized learning pathways, relevant instructional materials, and customized exercises that address individual needs and learning paces [22,23].”
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“Consistent with research on technology accep - tance and organizational behavior, users are more likely to engage with AI systems when they perceive them as fair, transparent, and aligned with professional values (Dahri et al., 2024; Shahzad et al., 2024).”
InfluentialAI as a thinking partner: rethinking human cognitive processes in the age of generative AI
Zhong, T., & Zhu, G. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2680598
Jin, H., Baby, M., Das, R. P., Moratti, T., Pagan, M. B., & Morkos, B. W. (2026) · Proceedings of the Design Society · doi:10.1017/pds.2026.10658
Redefining Integrity: Academic Standards and Ethical Communication in the Age of AI
Williams, F., & Williams, A. K. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-31418-5_24
Alubthane, F. O. (2026) · Education Sciences · doi:10.3390/educsci16071118
“…moderators of trust transfer magnitude (Nazaretsky et al., 2022a; Herdiani et al., 2024; Deric et al., 2025; Goldshtein et al., 2025; Song, 2024; Shahzad et al., 2024; Rana et al., 2024; Shen et al., 2025; Qin et al., 2020; Ayanwale et al., 2024; Viberg et al., 2024; Aladi, 2024), as summarized…”
GenAI Usage in Higher Education: The Evolution of Students’ Perceptions
Aparício, M., Schroll, K., & Bernardo, D. F. D. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-32035-3_31
Shatila, K., Aránega, A. Y., & Sánchez, M. P. S. (2026) · Measurement Interdisciplinary Research and Perspectives · doi:10.1080/15366367.2026.2704208
Critical Thinking and Artificial Intelligence
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Zhang, H., Tang, Q., Wang, J., Yang, L., & Deng, W. (2026) · SAGE Open · doi:10.1177/21582440261462203
Artificial Intelligence in Fashion Design Education: Implications for Sustainable Design Practices
Alajaji, T. N., & Al-Qudairi, T. A. (2026) · Sustainability · doi:10.3390/su18157520
Shi, Y., Chen, J., Wei, Y., Wu, M., Ji, X., & 珂, 朱. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1861220
“Specifically, environmental factors usually include social environment, climate, learning environment, and interpersonal relationships (Bandura, 2001; Cai and Shi, 2022; Leiter and Maslach, 1988; Shahzad et al., 2025).”
Wang, H., Fu, F., Li, L., & Liu, M. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1861541 · Cited by 1
“Recent studies in higher education and generative AI contexts have treated AI trust as an important moderating factor that shapes how AI-related experiences translate into educational outcomes (Chiu, 2025; Shahzad et al., 2025).”
Brătianu, C., & Bejinaru, R. (2026) · Proceedings of the ... International Conference on Business Excellence · doi:10.2478/picbe-2026-0305
“The presence of “educational technology” ( 18 ; 70 ) reinforces the idea that AI is analyzed as part of a wider edtech ecosystem, where policy, pedagogy, and tools co-evolve (Shahzad et al., 2025).”
Capability Reconfiguration, AI-Enabled HR, and the Political Economy of Academic Performance
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Enhancing student creative thinking: a new approach based on generative artificial intelligence a
Morán, F.-E., Peña, F. L. M., & Parrales, E. P. B. (2026) · Prisma social · doi:10.65598/rps.6245 · Cited by 1
Luo, Y., Fan, Y., Wang, T., Xu, Q., & Zhao, W. (2026) · Behavioral Sciences · doi:10.3390/bs16081313
Wu, F., Xiao, H., & Lin, X. (2026) · SAGE Open · doi:10.1177/21582440261477182
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Jia, C., Li, H., Wu, L., Xu, Z., Shen, L., Liu, Y., & Wang, D. (2026) · BMC Psychology · doi:10.1186/s40359-026-05339-y
“When students regard GenAI as trustworthy, they are more likely to believe that it contributes to fairness in educational resources [58].”
Modelling Human Generative AI Interaction in Higher Education: Evaluation Among Ghanaian Students
Wahab, A. W., Asabere, T. M., & Chakurah, I. (2026) · Review of Artificial Intelligence in Education · doi:10.37497/rev.artif.intell.educ.v7ii.1381
Liao, J., Wei, X., Fang, X., Sun, X., Li, F., & Lei, L. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14116-8
“Although numerous recent studies have demonstrated that Gen AI use can enhance individuals’ self-efficacy (Urban et al., 2024 ; Shahzad et al., 2025 ), Gen AI dependency differs from Gen AI use in that it is considered a form of problematic use (Zhang et al., 2024 ), which may exert adverse effects…”
Ren, Y., & Khan, S. U. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.107648 · Cited by 1
Wang, S., Zhong, Y., & Li, W. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01985-8
“Representative studies test the effects of AI-assisted learning on learning performance, higher-order thinking, self-regulation, knowledge construction, academic achievement, and language ability [47, 66, 93].”
The Impact of AI-Assisted Learning Tools on Students’ Academic Writing Performance
Ishtiaq, M., Naseem, A., & Akbar, G. (2026) · The regional tribune. · doi:10.55737/trt/v-vii.336
Riswari, S. D. (2026) · Indonesian Journal of Innovation Multidisipliner Research · doi:10.69693/ijim.v4i3.1816 · Cited by 1
“…dan faktor utilitarian melalui kerangka Technology Acceptance Model (TAM) dan Unified Theory of Acceptance and Use of Technology (UTAUT), yang lebih menyoroti manfaat dan kemudahan penggunaan secara praktis, bukan dorongan psikologis dari dalam diri pengguna (Al-kfairy, 2024; Shahzad et al., 2025).”
Singh, M. I., Pradhan, S., Naveen, S., & Vinod, L. (2026) · Discover Education · doi:10.1007/s44217-026-02090-9
“…suggest that students' engagement with generative AI depends heavily on motivational orientation, perceptions of fairness, and the credibility of AI-supported learning systems, highlighting the importance of trust calibration and responsible AI integration within higher education [48, 53, 55, 60].”
Zhou, Y., & Yang, S. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2726358
Hu, P., Rahman, M. K., Hossain, D., Piprani, A. Z., Feng, X., & Bhuiyan, M. A. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2721389
Exploring the Double-Edged Effects of Artificial Intelligence Dependence on Student Creativity
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Social influence and academic performance: a serial mediation model in AI-enhanced learning
Bhunia, A. K., & Alzahrani, S. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1928799
“This is possible because SI enables students to implement AI technology effectively (Soodan et al., 2024; Li et al., 2024), and ASE positively affects students’ academic performance (Shahzad et al., 2025; Singh et al., 2025).”
A Comparative Case Study of Evolving Identities
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The access–conversion gap across countries: how generative AI adoption exceeds learning use
Achuthan, K. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1946943
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Metadata
- Authors
- Shahzad, M. F., Xu, S., & Zahid, H.
- Affiliations
- Beijing University of Technology (CN)
- University of the Punjab (PK)
- Corresponding author
- Shahzad, Muhammad Farrukh
- Venue
- Education and Information Technologies
- Published
- 2024-08-24
- Volume
- 30
- Issue
- 3
- Pages
- 3691-3716
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4401846772
- Semantic Scholar
- 752710bda78d91ff3a5a9f1c9a9cc5440a605673
- Cited by
- 204
- References
- 88
- Citations by year
- 2026: 112 · 2025: 83 · 2024: 9
- FWCI
- 76.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Education and Information Technologies (publishedVersion)
- Funders
- National Natural Science Foundation of China (72074014)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI in education, learning performance, self-efficacy, creativity, trust, large language models, ChatGPT, chatbots, social cognitive theory, university students, moderating effect, Chinese universities
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