Do AI chatbots improve students learning outcomes? Evidence from a meta‐analysis
Open accessAbstract
Artificial intelligence (AI) chatbots are gaining increasing popularity in education. Due to their increasing popularity, many empirical studies have been devoted to exploring the effects of AI chatbots on students' learning outcomes. The proliferation of experimental studies has highlighted the need to summarize and synthesize the inconsistent findings about the effects of AI chatbots on students' learning outcomes. However, few reviews focused on the meta‐analysis of the effects of AI chatbots on students' learning outcomes. The present study performed a meta‐analysis of 24 randomized studies utilizing Stata software (version 14). The main goal of the current study was to meta‐analytically examine the effects of AI chatbots on students' learning outcomes and the moderating effects of educational levels and intervention duration. The results indicated that AI chatbots had a large effect on students' learning outcomes. Moreover, AI chatbots had a greater effect on students in higher education, compared to those in primary education and secondary education. In addition, short interventions were found to have a stronger effect on students' learning outcomes than long interventions. It could be explained by the argument that the novelty effects of AI chatbots could improve learning outcomes in short interventions, but it has worn off in the long interventions. Future designers and educators should make attempt to increase students' learning outcomes by equipping AI chatbots with human‐like avatars, gamification elements and emotional intelligence. Practitioner notes: What is already known about this topic: In recent years, artificial intelligence (AI) chatbots have been gaining increasing popularity in education. Studies undertaken so far have provided conflicting evidence concerning the effects of AI chatbots on students' learning outcomes. There has remained a paucity of meta‐analyses synthesizing the contradictory findings about the effects of AI chatbots on students' learning outcomes. What this paper adds: This study, through meta‐analysis, synthesized these recent findings about the effects of AI chatbots on students' learning outcomes. This study found that AI chatbots could have a large effect on students' learning outcomes. This study found that the effects of AI chatbots were moderated by educational levels and intervention duration. Implications for practice and/or policy: AI chatbot designers could make AI chatbots better by equipping AI chatbots with human‐like avatars, gamification elements and emotional intelligence Practitioners and/or teachers should draw attention to the positive and negative effects of AI chatbots on students. Considering the importance of ChatGPT, more research is required to develop a better understanding of the effects of ChatGPT in education. More research is needed to examine the mechanisms underlying the effects of AI chatbots on students' learning outcomes.
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There is a dearth of RCTs conducted in authentic K-12 school settings, with most studies taking place in higher education contexts.
“There is also a dearth of RCTs conducted in authentic K-12 school settings, with most studies taking place in higher education contexts (Wu & Yu, 2024 ).”
From Enhancing School Students' Self-Regulated Learning through Generative AI Support: A Randomized Controlled Trial (2026) · cites this paper as Wu & Yu, 2024
The Additional information table (page unavailable) lists 19 of 24 included studies in higher education and five in primary or secondary education, supporting the claim that most were in higher education. The eligibility criteria allow both randomized controlled and quasi-experimental designs, while the Limitations section says learning locations could not be examined. The paper therefore does not establish a dearth specifically of RCTs in authentic K–12 school settings. (LLM, conf=0.87)
Experimental — accuracy not yet measuredInterventions lasting less than 1 week generally failed to statistically significantly affect student learning or motivation.
“Wu and Yu ( 2024) found that interventions lasting less than 1 week generally failed to statistically significantly affect student learning or motivation.”
From Enhancing School Students' Self-Regulated Learning through Generative AI Support: A Randomized Controlled Trial (2026) · cites this paper as Wu and Yu (2024)
The Study coding section divides interventions at 10 weeks, and the results report a significant effect for the under-10-week group. The paper does not report a separate analysis of interventions lasting less than one week, so that result cannot establish whether such interventions generally failed to significantly affect learning or motivation. I searched for a one-week subgroup and its significance results. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
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Teachers and AI: Understanding the factors influencing AI integration in K-12 education
Filiz, O., Kaya, M. H., & Adıgüzel, T. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13463-2 · Cited by 199 · see citing works
“AI has demonstrated substantial potential in supporting students’ self-learning, enhancing literacy development, and improving learning outcomes through technologies like chatbots and predictive models (Ouyang et al., 2023; Wu & Yu, 2023; Xia et al., 2023).”
Wijaya, T. T., Yu, Q., Cao, Y., He, Y., & Leung, F. K. S. (2024) · Behavioral Sciences · doi:10.3390/bs14111008 · Cited by 103 · see citing works
“For example, the ANOVA for AI dependency shows significant effects (F [3, 357] = 91.8, η 2 = 0.442, p 0.001), indicating that as profiles increase in AI dependency, the proficiency in skills such as critical thinking declines significantly (F [3, 357] = 84.941, η 2 = 0.423, p 0.001).”
InfluentialAli, F., Choy, D., Divaharan, S., Tay, H. Y., & Chen, W. (2023) · Learning Research and Practice · doi:10.1080/23735082.2023.2258886 · Cited by 122 · see citing works
“A recent meta-analysis highlighted the significant benefits of chatbots in education (Wu & Yu, 2023).”
BackgroundMethodAI-based avatars are changing the way we learn and teach: benefits and challenges
Fink, M. C., Robinson, S. A., & Ertl, B. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1416307 · Cited by 99 · see citing works
Karataş, F., & Ataç, B. A. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13164-2 · Cited by 124 · see citing works
“While these findings align with broader trends in educational technology research (Wu & Yu, 2023; Yue et al., 2024), they also highlight potential systemic biases in technology access and attitudes that require further investigation (Jafari, 2023).”
AI in the classroom: Exploring students’ interaction with ChatGPT in programming learning
Güner, H., & Er, E. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13337-7 · Cited by 116 · see citing works
“Besides, ChatGPT can adapt to individual learning styles and provide contextually relevant assistance (Kooli, 2023; Wu & Yu, 2024; Zhang & Tur, 2024), which can be particularly effective in programming education, where timely and specific feedback is crucial for mastering coding skills (Yilmaz &…”
Yang, T.-C., Hsu, Y.-C., & Wu, J.-Y. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2450659 · Cited by 80 · see citing works
“As previous studies suggest, real-time feedback can help students quickly identify their errors and adjust their strategies, thus improving learning efficiency and promoting self-correction that in turn boosts their self-efficacy (Wu & Yu, 2023).”
Generative AI detection in higher education assessments
Ardito, C. G. (2025) · New Directions for Teaching and Learning · doi:10.1002/tl.20624 · Cited by 86 · see citing works
Yan, D., & Zhang, S. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03543-y · Cited by 90 · see citing works
Personalized learning through AI: Pedagogical approaches and critical insights
Vorobyeva, K. I., Belous, S. V., Savchenko, N. V., Smirnova, L. M., Nikitina, S. A., & Zhdanov, S. P. (2025) · Contemporary Educational Technology · doi:10.30935/cedtech/16108 · Cited by 121 · see citing works
“These tools increase students’ problem-solving skills and self-efficacy by providing timely feedback and support (Bahroun et al., 2023; Wu & Yu, 2024).”
Zhu, Y., Liu, Q., & Zhao, L. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13420-z · Cited by 92 · see citing works
Jing, Y., Wang, H., Chen, X.-J., & Wang, C.-L. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-02751-w · Cited by 74 · see citing works
“Moreover, learners ’ cognitive level and intention to use new technologies are often considered key factors in fl uencing the effectiveness of technology utilization (Chai et al., 2021; Yu et al., 2023; Wang et al., 2023).”
Yin, J., Goh, T., & Hu, Y. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00480-3 · Cited by 95 · see citing works
“Further research could investigate other factors and different feedback types such as affective feedback, corrective feedback or delayed feedback to better understand the dynamics of emotion and learning in the educational chatbot environment (Wu & Yu, 2023).”
BackgroundDong, L., Tang, X., & Wang, X. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100400 · Cited by 75 · see citing works
Intelligent educational technologies in individual learning: a systematic literature review
Kerimbayev, N., Akramova, А., Shadiev, R., & Altınay, Z. (2025) · Smart Learning Environments · doi:10.1186/s40561-024-00360-3 · Cited by 73 · see citing works
Exploring the impact of language models, such as ChatGPT , on student learning and assessment
Zirar, A. (2023) · Review of Education · doi:10.1002/rev3.3433 · Cited by 83 · see citing works
Guizani, S., Mazhar, T., Shahzad, T., Ahmad, W., Bibi, A., & Hamam, H. (2025) · Discover Education · doi:10.1007/s44217-025-00424-7 · Cited by 62 · see citing works
“When creating lesson plans for the classroom, Chatbots like ChatGPT can be pretty helpful [92, 93].”
Yu-peng, L., & Yu, Z. (2024) · Behaviour and Information Technology · doi:10.1080/0144929x.2024.2332458 · Cited by 66 · see citing works
“This fi nding re fl ects a prevailing trend in technology-enhanced education research that e ff ectiveness evaluation is a central topic, although it is measured by various indicators (e.g. Wu and Yu 2023).”
Self-citationPrilop, C. N., Mah, D.-K., Jacobsen, L. J., Hansen, R. R., Weber, K. E., & Hoya, F. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100471 · Cited by 95 · see citing works
Tlili, A., Saqer, K., Salha, S. H., & Huang, R. (2025) · Information Development · doi:10.1177/02666669241304407 · Cited by 91 · see citing works
“This could be attributed to the several interactive features provided by AI applications that make teaching and learning strategies more creative (Hwang & Chen, 2023) and consequently support students ’ achievement (Wu & Yu, 2023).”
Xu, Y., Zhu, J., Wang, M., Qian, F., Yang, Y., & Zhang, J. (2024) · Applied Sciences · doi:10.3390/app14156418 · Cited by 60 · see citing works
Han, X., Peng, H., & Liu, M. (2025) · Educational Research Review · doi:10.1016/j.edurev.2025.100714 · Cited by 70 · see citing works
Kong, X., Fang, H., Chen, W., Xiao, J., & Zhang, M. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-05097-z · Cited by 72 · see citing works
“Wu and Yu (2023) suggested that educators could increase students ’ learning outcomes by equipping AI chatbots with humans, like avatars, gami fi cation elements, and emotional intelligence.”
Chen, S., & Cheung, A. (2025) · Educational Research Review · doi:10.1016/j.edurev.2025.100737 · Cited by 117 · see citing works
Innovative Early Childhood STEM Education with ChatGPT: Teacher Perspectives
Uğraş, H., Uğraş, M., Papadakis, S., & Kalogiannakis, M. (2024) · Technology Knowledge and Learning · doi:10.1007/s10758-024-09804-8 · Cited by 52 · see citing works
A systematic review of artificial intelligence in mathematics education: The emergence of 4IR
Opesemowo, O. A. G., & Adewuyi, H. O. (2024) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.29333/ejmste/14762 · Cited by 51 · see citing works
“However, several studies (Adiguzel et al., 2023; Deng & Yu, 2023; Lee & Yeo, 2022; Wu & Yu, 2023) have explored using ChatGPT, such as ChatGPT, in teaching mathematics.”
BackgroundLiu, L. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13296-5 · Cited by 75 · see citing works
Baltà‐Salvador, R., Madafri, I. E., Brasó‐Vives, E., & Peña, M. (2025) · Computer Applications in Engineering Education · doi:10.1002/cae.22817 · Cited by 52 · see citing works
Alejandro, I. M. V., Sanchez, J. M. P., Sumalinog, G. G., Mananay, J. A., Goles, C. E., & Fernandez, C. B. (2024) · STEM Education · doi:10.3934/steme.2024024 · Cited by 64 · see citing works
“Possible explanations could involve the strong influence of social norms and perceived benefits, according to Wu and Yu [44], which may overshadow the perceived voluntariness of adopting AI applications.”
Liu, X., Guo, B., He, W., & Hu, X. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251329185 · Cited by 78 · see citing works
“Existing research indicates that GenAI may impact learners at different educational levels (Wu & Yu, 2023).”
InfluentialKiuchi, K., Otsu, K., & Hayashi, Y. (2023) · Behaviour and Information Technology · doi:10.1080/0144929x.2023.2286528 · Cited by 50 · see citing works
“Meta-analysis showed a positive impact of chatbots on learning outcomes, especially in higher education for short periods of time (Wu and Yu 2023).”
Labrague, L. J., & Sabei, S. A. (2025) · Teaching and Learning in Nursing · doi:10.1016/j.teln.2024.11.010 · Cited by 48 · see citing works
Lademann, J., Henze, J., & Becker, S. (2025) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.21.010147 · Cited by 61 · see citing works
Chatbots and student motivation: a scoping review
Huang, W., Jiang, J., King, R. B., & Fryer, L. K. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00524-2 · Cited by 69 · see citing works
“Furthermore, the reference lists of previous related reviews (Ansari et al., 2024; Hwang & Chang, 2023; Kuhail et al., 2023; Wollny et al., 2021; Wu & Yu, 2024) were examined to identify additional primary studies.”
InfluentialFacilitating Student Learning With a Chatbot in an Online Math Learning Platform
Cheng, L., Croteau, E. A., Baral, S., Heffernan, C., & Heffernan, N. T. (2024) · Journal of Educational Computing Research · doi:10.1177/07356331241226592 · Cited by 57 · see citing works
“A meta-analysis of 24 randomized studies found chatbots had a large overall effect on students ’ learning outcomes including learning performance, learning motivation, learning self-ef fi cacy, learning interest, and perceived value of learning (Wu & Yu, 2023).”
MethodOfosu‐Ampong, K., Acheampong, B., Kevor, M.-O., & Amankwah-Sarfo, F. (2023) · doi:10.7176/ikm/13-4-03 · Cited by 45 · see citing works
Effectiveness of Chatbots in Improving Language Learning: A Meta‐Analysis of Comparative Studies
Lyu, B., Lai, C., & Guo, J. (2024) · International Journal of Applied Linguistics · doi:10.1111/ijal.12668 · Cited by 45 · see citing works
Xia, Q., Li, W., Yang, Y., Weng, X., & Chiu, T. K. F. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2025.100455 · Cited by 45 · see citing works
Martin, F., Long, S., Haywood, K., & Xie, K. (2025) · Educational Technology Research and Development · doi:10.1007/s11423-025-10550-6 · Cited by 46 · see citing works
“While such AI tools hold potential for enhancing personalized learning (Zawacki-Richter et al., 2019), they complicate the boundary between tools for enhancement and sources of distraction (Birenbaum, 2023; Huang et al., 2022; Wu & Yu, 2024).”
The Impact of <scp>ChatGPT</scp> on Students' Academic Achievement: A Meta‐Analysis
Liu, Z., Zuo, H., & Lu, Y. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70096 · Cited by 44 · see citing works
Sun, D., Cheng, G., Yu, P. L. H., Jia, J., Zheng, Z., & Chen, A. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2462156 · Cited by 44 · see citing works
“These applications include personalized learning experiences and intelligent tutoring systems (Wu & Yu, 2023), which support the development of essential skills such as problem-solving, decision-making, critical thinking, and creativity (Ouyang et al., 2023; Sun et al., 2024b).”
The AI Motivation Scale (AIMS): a self-determination theory perspective
Li, J., King, R. B., Chai, C. S., Zhai, X., & Lee, V. W. Y. (2025) · Journal of Research on Technology in Education · doi:10.1080/15391523.2025.2478424 · Cited by 59 · see citing works
“Students from various cultural backgrounds may interact with AI differently (Ge et al., 2024; Wu & Yu, 2024).”
Enough of the chit-chat: A comparative analysis of four AI chatbots for calculus and statistics
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.22 · Cited by 50 · see citing works
Giray, L., Sevnarayan, K., & Ranjbaran, F. (2025) · Internet Reference Services Quarterly · doi:10.1080/10875301.2024.2437174 · Cited by 62 · see citing works
“Wu and Yu (2024) found that AI chatbots improved learning outcomes by providing timely support.”
Weber, F., Wambsganss, T., & Söllner, M. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13529 · Cited by 42 · see citing works
Revesai, Z. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2549787 · Cited by 56 · see citing works
“Wu and Yu (2024) conducted a meta-analysis and found that AI chatbots can be effective in enhancing student learning outcomes, with moderately significant positive effects, if these tools are incorporated into well-designed learning activities that are integrated into suitable pedagogical practices.”
Wang, Y. J., Wei, Z., Wijaya, T. T., Cao, Y., & Ning, Y. (2025) · BMC Psychology · doi:10.1186/s40359-025-02781-2 · Cited by 59 · see citing works
“It offers targeted learning resources that bridge abstract mathematical concepts and real-world applications, and provides personalized diagnostics and formative assessments that support timely learning adjustments [2, 24].”
Lepp, M., & Kaimre, J. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100642 · Cited by 40 · see citing works
Lyu, W., & Salam, Z. A. (2025) · Learning and Motivation · doi:10.1016/j.lmot.2025.102129 · Cited by 52 · see citing works
A Meta‐Analysis of the Impact of Generative Artificial Intelligence on Learning Outcomes
Ma, N., & Zhong, Z. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70117 · Cited by 57 · see citing works
“Better than my professor?” How to develop artificial intelligence tools for higher education
Triberti, S., Fuccio, R. D., Scuotto, C., Marsico, E., & Limone, P. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1329605 · Cited by 50 · see citing works
“Previous studies have demonstrated the positive impact of chatbot applications on learning outcomes, although these effects may vary depending on instructional levels and the duration of intervention in the learning application (Wu and Yu, 2023).”
BackgroundScherr, S., Cao, B., Jiang, L., & Kobayashi, T. (2025) · Computers in Human Behavior · doi:10.1016/j.chb.2025.108738 · Cited by 42 · see citing works
A Bibliometric Analysis of Research on ChatGPT in Education
Polat, H., Topuz, A. C., Yıldız, M., Taşlıbeyaz, E., & Kurşun, E. (2024) · International Journal of Technology in Education · doi:10.46328/ijte.606 · Cited by 47 · see citing works
“Consequently, there is a clear need for further studies that concentrate on these emerging themes, with a specific emphasis on exploring the role of ChatGPT in educational contexts (Huang et al., 2023; Kuhail et al., 2023; Wu & Yu, 2023; Zhang et al., 2023).”
BackgroundThe 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 51 · see citing works
“According to Wu and Yu (2024) AI-based chatbots had a greater effect on students in higher education, compared to those in primary education and secondary education.”
BackgroundMethodPirzado, F. A., Ahmed, A., Mendoza-Urdiales, R. A., & Terashima‐Marín, H. (2024) · IEEE Access · doi:10.1109/access.2024.3443621 · Cited by 37 · see citing works
A bibliometric analysis of publications on ChatGPT in education: Research patterns and topics
ZHELTUKHINA, M. R., Sergeeva, O. V., Masalimova, A. R., Budkevich, R. L., Kosarenko, N. N., & Nesterov, G. V. (2024) · Online Journal of Communication and Media Technologies · doi:10.30935/ojcmt/14103 · Cited by 36 · see citing works
Zhu, Y., Zhu, C., Wu, T., Wang, S., Zhou, Y., Chen, J., Wu, F., & Li, Y. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12898-3 · Cited by 33 · see citing works
Liu, J., Zhang, Y., Wei, L., Wang, Q., Niu, P., & Zhang, X. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105473 · Cited by 40 · see citing works
Analysis of artificial intelligence chatbots and satisfaction for learning in mathematics education
Moral-Sánchez, S. N., Rey, F. J. R., & de la Serna, M. C. (2023) · IJERI International Journal of Educational Research and Innovation · doi:10.46661/ijeri.8196 · Cited by 32 · see citing works
Liu, Z., Zhang, W., & Yang, P. (2025) · Computer Assisted Language Learning · doi:10.1080/09588221.2025.2456512 · Cited by 39 · see citing works
“Fourth, regarding self-efficacy, the results are consistent with Wu and Yu (2024) and Huang et al. (2022), indicating that AI chatbots significantly boost learners’ self-efficacy.”
InfluentialYu-peng, L., Niu, R., & Yu, Z. (2023) · Language Teaching Research · doi:10.1177/13621688231216201 · Cited by 35 · see citing works
“With the advancements in educational technologies, learning effectiveness was adopted to evaluate the benefits of various technologies, such as artificial intelligence chatbots and augmented reality (Wu & Yu, 2023; Z.G. Yu, 2023).”
Self-citationExploring student and teacher perspectives on ChatGPT’s impact in higher education
Žáková, K., Urbano, D., Cruz-Correia, R. J., Guzmán, J. L., & Matišák, J. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13184-y · Cited by 32 · see citing works
“Inthemeta-analysis(Wu&Yu,2023),themainconclusionabouttheeffectsofAI chatbots in students learning outcomes is that higher education students are the ones benefiting the most and the gains are more visible if the pedagogical interventions have a duration of less than 10 weeks.”
A Meta-analysis Evaluating the Effectiveness of Instructional Video Technologies
Yu-peng, L., & Yu, Z. (2023) · Technology Knowledge and Learning · doi:10.1007/s10758-023-09669-3 · Cited by 38 · see citing works
“Learning styles might determine how educational technologies could influence individual learning effectiveness, considering different technological features, learning content, educational levels, and genders (e.g., Li, 2023; Wu & Yu, 2023).”
InfluentialSelf-citationBubaš, G., Čižmešija, A., & Kovačić, A. (2023) · Future Internet · doi:10.3390/fi16010004 · Cited by 30 · see citing works
Short-term learning effect of ChatGPT on pharmacy students' learning
Svendsen, K., Askar, M., Umer, D., & Halvorsen, K. H. (2024) · Exploratory Research in Clinical and Social Pharmacy · doi:10.1016/j.rcsop.2024.100478 · Cited by 30 · see citing works
“It has been shown that chatbots can have a positive effect on teaching some types of topics such as communication skills 1,2 , but our study is the first to look at the general effects of ChatGPT on learning more widely for pharmacy students.”
BackgroundEffects of GenAI Interventions on Student Academic Performance: A Meta-Analysis
Gu, J., & Yan, Z. (2025) · Journal of Educational Computing Research · doi:10.1177/07356331251349620 · Cited by 30 · see citing works
“Researchers argued that GenAI could promote student learning by providing students with timely feedback from various perspectives (Xia et al., 2024) and facilitating student self-directed learning (Yu, 2024).”
Technology Acceptance Model in Artificial Intelligence in Education: A Meta-Analysis
Xue, L., Mahat, J., & Ghazali, N. (2026) · SAGE Open · doi:10.1177/21582440251409441 · Cited by 61 · see citing works
Younas, M. S., Ismayil, I., El‐Dakhs, D. A. S., & Anwar, B. (2025) · Open Praxis · doi:10.55982/openpraxis.17.3.842 · Cited by 35 · see citing works
Potentials and Challenges of Chatbot-Supported Thesis Writing: An Autoethnography
Schwenke, N., Söbke, H., & Kraft, E. (2023) · Trends in Higher Education · doi:10.3390/higheredu2040037 · Cited by 32 · see citing works
Beyond the “Wow” Factor: Using Generative AI for Increasing Generative Sense-Making
Makransky, G., Shiwalia, B. M., Herlau, T., & Blurton, S. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10039-x · Cited by 27 · see citing works
Salminen, J. O., Jung, S., Medina, J., Aldous, K. K., Azem, J. Y., Akhtar, W., & Jansen, B. J. J. (2024) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3657604.3664690 · Cited by 27 · see citing works
Lee, D., Son, T., & Yeo, S. (2024) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13091 · Cited by 27 · see citing works
AI4Design: A generative AI-based system to improve creativity in design–A field evaluation
Abrusci, L., Dabaghi, K., D’Urso, S., & Sciarrone, F. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100401 · Cited by 27 · see citing works
Morell‐Mengual, V., Fernández‐García, O., Berenguer, C., Ortega-Barón, J., Gil‐Llario, M. D., & Estruch‐García, V. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13650-1 · Cited by 27 · see citing works
AI support in self‐regulated learning: A decade of technological evolution and meta‐analysis
Xu, J. H., Luo, Y., Wang, C., Wang, M., & Wu, Y. (2026) · British Journal of Educational Technology · doi:10.1111/bjet.70058 · Cited by 26 · see citing works
Xia, Q., Zhang, P., Huang, W., & Chiu, T. K. F. (2025) · Asia Pacific Journal of Education · doi:10.1080/02188791.2025.2530503 · Cited by 31 · see citing works
Students Experience on Self-Study through AI
Namjoo, F., Liaghat, E., Shabaziasl, S., Modabernejad, Z., & Morshedi, H. (2023) · AI and Tech in Behavioral and Social Sciences · doi:10.61838/kman.aitech.1.3.6 · Cited by 31 · see citing works
Can rule-based educational chatbots be an acceptable alternative for students in higher education?
Güldal, H., & Dinçer, E. O. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12977-5 · Cited by 27 · see citing works
“According to Wu and Yu (2024), chatbots have a great impact on students’ learning outcomes, and have a more significant effect on students in higher education than in primary and secondary education.”
Empowering Student Learning Through Artificial Intelligence: A Bibliometric Analysis
Yun, G., Lee, K. M., & Choi, H. H. (2024) · Journal of Educational Computing Research · doi:10.1177/07356331241278636 · Cited by 26 · see citing works
“Indeed, current research primarily focuses on AI ’ s instructional methods and pedagogical applications, highlighting its positive implications on student learning processes and outcomes (Wu & Yu, 2024).”
Han, I., Ji, H., Jin, S., & Choi, K. (2026) · Journal of Computing in Higher Education · doi:10.1007/s12528-025-09434-8 · Cited by 24 · see citing works
“Many studies have explored the use of AI chatbots in education and identified a positive impact that is attributed to their adaptability, flexibility, and natural interactions (Essel et al., 2022; Wu & Yu, 2023).”
Zhang, Q., Siraj, S. B., & Razak, R. A. (2025) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2025.2515111 · Cited by 24 · see citing works
“Powered by natural language processing and machine learning, these intelligent conversational systems engage learners in real-time, interactive dialogues that simulate human conversations (Wu & Yu, 2024).”
- Authors
- Wu, R., & Yu, Z.
- Affiliations
- Beijing Language and Culture University (CN)
- Corresponding author
- Yu, Zhonggen
- ORCID
- Venue
- British Journal of Educational Technology
- Publisher
- Wiley
- Published
- 2023-05-03
- Volume
- 55
- Issue
- 1
- Pages
- 10-33
- ISSN
- 0007-1013 (ISSN-L)
- 1467-8535
- OpenAlex
- W4367849331
- Cited by
- 576
- References
- 76
- Citations by year
- 2026: 198 · 2025: 245 · 2024: 113 · 2023: 20
- FWCI
- 134.94
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- British Journal of Educational Technology (publishedVersion)
- Funders
- Beijing Language and Culture University (202010032003, MOOC201902)
- Fundamental Research Funds for the Central Universities (MOOC201902, 202010032003)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- AI chatbots, learning outcomes, educational technology, higher education, primary education, secondary education, intervention duration, novelty effect, gamification, emotional intelligence
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