Instructions for Participants in the E-course "Assessment Supported by Digital Technology"

11. Literature

Each topic contains learning materials in Croatian, as well as a list of recommended literature for further study. Below is an overview of the key references used in the course.

AAC&U VALUE Rubrics – internationally recognized rubrics for 16 key areas of learning.

Andrade, H. & Du, Y. (2007). Student responses to criteria-referenced self-assessment. Assessment and Evaluation in Higher Education, 32(2), 159–181.

Assessment Design and Strategies for Student Learning (Cambridge CCTL)

Assessment Design Framework

Bacchus, R., Colvin, E., Knight, E. B., & Ritter, L. (2020). When rubrics aren’t enough: Exploring exemplars and student rubric co-construction. Journal of Curriculum and Pedagogy, 17(1), 48–61.

Bandura, A. (1999). Moral disengagement in the perpetration of inhumanities. Personality and Social Psychology Review, 3(3), 193–209.

Biggs, J. & Tang, C. (2011). Teaching for Quality Learning at University (4th ed.). McGraw-Hill.

Bretag, T., Harper, R., Burton, M., Ellis, C., Newton, P., Rozenberg, P., Saddiqui, S., & van Haeringen, K. (2019). Contract cheating: A survey of Australian university students. Studies in Higher Education, 44(11), 1837–1856.

Chen, I.-C., Hwang, G.-J., Lai, C.-L., & Wang, W.-C. (2020). From design to reflection: Effects of peer-scoring and comments on students’ behavioural patterns and learning outcomes in musical theater performance. Computers and Education, 150, 103856.

Clark, I. (2012). Formative assessment: Assessment is for self-regulated learning. Educational Psychology Review, 24(2), 205–249.

Divjak, B. (2014). Provjera konzistentnosti i postizanja ishoda učenja. UNIQInfo, 5, 10–13.

Divjak, B., Svetec, B., Horvat, D. (2025). Generative AI in Mathematics Education: Analysing Student Performance and Perceptions over Three Academic Years. International Journal of Technology Enhanced Learning.

Divjak, B., Svetec, B., Horvat, D., & Kadoić, N. (2023). Assessment validity and learning analytics as prerequisites for ensuring student-centred learning design. British Journal of Educational Technology, 54, 313–334.

Divjak, B., Žugec, B., & Pažur Aničić, K. (2022). E-assessment in mathematics in higher education: A student perspective. International Journal of Mathematical Education in Science and Technology.

Fernández-Sánchez, A., Lorenzo-Castiñeiras, J. J., & Sánchez-Bello, A. (2025). Navigating the Future of Pedagogy: The Integration of AI Tools in Developing Educational Assessment Rubrics. European Journal in Education, Research, Development and Policy, 60(1).

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.

Ifenthaler, D. (2023). Investigating self-assessment use in higher education with learning analytics. Journal of Computer Assisted Learning, 39(1), 222–233.

Ifenthaler, D. & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990.

Khasawneh, M. A. S., Aladini, R., Assi, N., & Rawashdeh, H. (2025). The effect of using artificial intelligence-based feedback in electronic portfolios on EFL students’ academic emotion regulation and mindfulness. Language Testing in Asia, 15(1), 10.

Kumar, H., Xiao, R., Lawson, B., Musabirov, I., Shi, J., Wang, X., Luo, H., Williams, J., Rafferty, A., Stamper, J., & Liut, M. (2024). Supporting self-reflection at scale with large language models: Insights from randomized field experiments in classrooms. arXiv preprint.

Lancaster, T. (2021). Contract cheating in higher education: Global perspectives, policy, and prevention. Routledge.

Noorbehbahani, F., Mohammadi, A., & Aminazadeh, M. (2022). A systematic review of research on cheating in online exams from 2010 to 2021. Education and Information Technologies, 27, 8413–8460.

Oravec, J. A. (2022). AI, biometric analysis, and emerging cheating detection systems: The engineering of academic integrity?. Education Policy Analysis Archives, 30, 175.

Panadero, E., Brown, G. T. L., & Courtney, M. (2022). Students’ strategies during self-assessment: Feedback and rubrics effects. Assessment in Education, 29(1), 23–43.

Panadero, E. & Jonsson, A. (2013). The use of scoring rubrics for formative assessment purposes revisited: A review. Educational Research Review, 9, 129–144.

Panadero, E., Jonsson, A., Pinedo, L., et al. (2023). Effects of Rubrics on Academic Performance, Self-Regulated Learning, and Self-Efficacy: A Meta-analytic Review. Educational Psychology Review, 35, 113.

Ramesh, D. & Sanampudi, S. K. (2021). An automated essay scoring systems: A systematic literature review. Artificial Intelligence Review, 55, 2495–2527.

Rüth, M., Jansen, M., & Kaspar, K. (2024). Cheating behaviour in online exams: On the role of needs, conceptions and reasons of university students. Journal of Computer Assisted Learning, 40(5), 1987–2008.

Sevnarayan, K. & Maphoto, M. (2024). Academic dishonesty in a first-year English module in open distance e-learning (ODeL). Journal of Academic Ethics, 22(2), 357–374.

Siemens, G. & Long, P. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 30–40.

Slade, S. & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1510–1529.

Valızadeh, M. (2022). Cheating in online learning programs: Learners’ perceptions and solutions. Turkish Online Journal of Distance Education, 23(1), 195–209.