The scarcity of experimental studies demonstrating the concrete effects of AI-assisted applications on learning outcomes

The gap

Evidence profile

Sourced from the limitations and recommendations and stated research gap of the source papers, classified as general, spanning 2 journals.

Supporting evidence — 3 representative gaps

• Artificial Intelligence in Health Professions Education: Qualitative Study of Student Experiences (2026) · Journal of Medical Internet Research · doi

  Therefore, future research could address these limitations by conducting larger-scale studies with more diverse samples and using objective measures of AI usage, such as usage logs or performance data. Additionally, future research could explore how AI is used in other fields of study and whether the patterns observed in this study are generalizable to different educational contexts. One of the limitations of this study is the small sample size and the use of self-reported data, and the fact that the data were collected within a single establishment, which limits the generalization of the results to other institu- tions.

  generallimitations
  Keywords: future limitations usage address conducting larger scale diverse samples using objective measures logs performance additionally
• ACADEMIC PERMISSIBILITY IN LLM-ASSISTED EFL WRITING: HOW CONTEXTUAL JUSTIFICATIONS SHAPE STUDENTS' MORAL JUDGMENTS IN A WITHIN-SUBJECTS VIGNETTE SURVEY (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  https://doi.org/10.1186/s41077-025-00350-6 Cho, M.-H., Park, E. G., Lim, S., & Yu, H. (2026). Learning with AI: Student intentions for academic use and broader perspectives on AI. Technology, Knowledge and Learning. Advance online publication. https://doi.org/10.1007/s10758-026-09982-7 Cleland, J., Driessen, E., Masters, K., Lingard, L., & Maggio, L. A. (2026). When and how to disclose AI use in academic publishing: AMEE Guide No. 192. Medical Teacher, 48(4), 542–553. https://doi.org/10.1080/0142159X.2025.2607513 Cohen, J. (2009). Statistical power analysis for the behavioral sciences (2nd ed.). Psychology Press. Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148 Cui, Y. (2025). What influences college students using AI for academic writing? A quantitative analysis based on HISAM and TRI theory. Computers & Education: Artificial Intelligence, 8, Article 100391. https://doi.org/10.1016/j.caeai.2025.100391 Danyaro, K. U., Abdullahi, S., Abdallah, A. S., & Chiroma, H. (2025). Hallucinations in large language models for education: Challenges and mitigation. International Journal of Teaching, Learning and Education, 4(6), 13–19. https://doi.org/10.22161/ijtle.4.6.2 Digital Education Council. (2024). Digital Education Council global AI student survey 2024. https://www.digitaleducationcouncil.com/resource-library-items/digital-education-council- global-ai-student-survey-2024 Fathi, J., & Rahimi, M. (2026). Utilising artificial intelligence-enhanced writing mediation to develop academic writing skills in EFL learners: A qualitative study. Computer Assisted Language Learning, 39(1–2), 263–302. https://doi.org/10.1080/09588221.2024.2374772 George, D., & Mallery, P. (2016). IBM SPSS Statistics 23 step by step: A simple guide and reference (14th ed.). Routledge. Gonsalves, C. (2025). Addressing student non-compliance in AI use declarations: Implications for academic integrity and assessment in higher education. Assessment & Evaluation in Higher Education, 50(4), 592–606. https://doi.org/10.1080/02602938.2024.2415654 Haireche, N. E. H., & Lamri, C. (2025). Language and strategic challenges in EFL essay writing: A case study of master’s students at the University of Sidi Bel Abbes, Algeria. Journal Faslo El Khitab, 14(1), 515–526. Hammond, K. M., Lucas, P., Hassouna, A., & Brown, S. (2023). A wolf in sheep’s clothing? Critical discourse analysis of five online automated paraphrasing sites. Journal of University Teaching & Learning Practice, 20(7), Article 08. https://doi.org/10.53761/1.20.7.08 Seddiki & Korichi / International Journal of Education, Technology and Science 6(3) (2026) 267–290 287 Jin, Y., Yan, L., Echeverria, V., Gašević, D., & Martinez-Maldonado, R. (2025). Generative AI in higher education: A global perspective of institutional adoption policies and guidelines.

  generalrecommendations
  Keywords: education https academic learning student writing journal teaching international language digital council global higher technology
• Trends in Research on the Use of Artificial Intelligence Applications in Turkish Language Teaching (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  The study identifies a gap in the literature regarding the scarcity of experimental studies demonstrating the concrete effects of AI-assisted applications on learning outcomes. The study highlights the need for studies examining the effectiveness of AI-based materials. The study identifies a gap in the literature regarding the development of instruments to measure secondary school students' attitudes toward AI.

  generalstated research gapevidence 5/5
  Keywords: study identifies gap literature regarding scarcity experimental studies

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