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ע 9 Montathar Faraon מאיה אושר , מקורות Banihashem, S.K., Kerman, N.T., Noroozi, O., Moon, J., & Drachsler, H. (2024). Feedback sources in essay writing: Peer-generated or AI-generated feedback? International Journal of Educational Technology in Higher Education 21(23). https://doi.org/10.1186/s41239-024-00455-4 Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43 .https://doi.org/10.1186/s41239-023-00411-8 Double, K.S., McGrane, J.A., & Hopfenbeck, T.N. (2020). The impact of peer assessment on academic performance: A meta-analysis of control group studies. Educational Psychology Review 32(2), 481-509. https://doi.org/10.1007/s10648-019-09510-3 Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students' learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(57). https://doi.org/10.1186/s41239-022-00362-6 Falchikov, N., & J. Goldfinch. (2000). Student peer assessment in higher education: A meta-analysis comparing peer and teacher marks. Review of Educational Research 70(3), 287-322. Flodén, J. (2025). Grading exams using large language models: A comparison between human and AI grading of exams in higher education using ChatGPT. British Educational Research Journal 51(1), 201-224. https://doi.org/10.1002/berj.4069 Gorgun, G. & Yildirim‐Erbasli, S.N. (2024). Algorithmic bias in BERT for response accuracy prediction: A case study for investigating population validity. Journal of Educational Measurement. https://doi.org/10.1111/jedm.12420 Gurin S., Klebanov, B., & Alexandron, G. (2025). Uncovering measurement biases in LLM Embedding spaces: The Anna Karenina Principle and its implications for automated feedback. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-025-00485-7 Haudek, K.C. & Zhai, X. (2023). Examining the effect of assessment construct characteristics on machine learning scoring of scientific argumentation. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00385-8 Labadze, L., Grigolia, M. & Machaidze, L. (2023). Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education, 20(56). https://doi.org/10.1186/s41239-023-00426-1 Li, H., Xiong, Y., Hunter, C.V., Guo, X., & Tywoniw, R. (2020) Does peer assessment promote student learning? A meta-analysis, Assessment & Evaluation in Higher Education, 45(2), 193-211. https://doi.org/10.1080/02602938.2019.1620679 Lu, Q., Yao, Y., Xiao, L., Yuan, M., Wang, J., & Zhu, X. (2024) Can ChatGPT effectively complement teacher assessment of undergraduate students' academic writing? Assessment & Evaluation in Higher Education, 49(5), 616-633. DOI: 10.1080/02602938.2024.2301722 Morris, W., Holmes, L., Choi, J.S. & Crossley, S. (2024). Automated Scoring of Constructed Response Items in Math Assessment Using Large Language Models. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00418-w Ocampo, J.C., Panadero, E., Zamorano, D., Sánchez-Iglesias, I., & Ruiz, F.D. (2024) The effects of gender and training on peer feedback characteristics. Assessment & Evaluation in Higher Education, 49(4), 539-555, DOI: 10.1080/02602938.2023.2286432 Okonkwo, C. W., & Ade-Ibijola, A. O. (2021). Chatbots applications in education: A systematic review. Computers & Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033 Pinto, G., Cardoso-Pereira, I., Monteiro, D., Lucena, D., Souza, A., & Gama, K. (2023). Large language models for education: Grading open-ended questions using ChatGPT. In 37th Brazilian Symposium on Software Engineering, edited by Edna Dias Canedo, 293-302. New York, NY, USA: ACM. https://doi.org/10.1145/3613372.3614197

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