Automating student assessment using digital data to improve education management effectiveness in higher education institutions

Author:

Liu Chun

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Education

Reference38 articles.

1. Alrashidi, H., Almujally, N., Ullmann, T. D., & Joy, M. (2022). Evaluating an automated analysis using machine learning and natural language processing approaches to classify computer science students’ reflective writing. In Second International Conference on Pervasive Computing and Social Networking, 3–4 Mar 2022 (pp. 1–20). Salem, India.

2. Arndt, T., & Guercio, A. (2013). Evaluating student attitudes on ubiquitous e-learning. In Proceedings of the 7th International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (pp. 98–101). Cleveland State University.

3. Ball, S., Goodson, I., & Maguire, M. (2013). Education, Globalisation and New Times. Abingdon and New York: Routledge.

4. Borg, M., Olsson, T., Franke, U., & Assar, S. (2018). Digitalization of Swedish government agencies-a perspective through the lens of a software development census. In 2018 IEEE/ACM 40th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) (pp. 37–46). IEEE. https://doi.org/10.1145/3183428.3183434

5. Brown, S., & Glasner, A. (1999). Assessment matters in higher education: Choosing and using diverse approaches. McGraw-Hill Education (UK).

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