Process mining for self-regulated learning assessment in e-learning

Author:

Cerezo RebecaORCID,Bogarín AlejandroORCID,Esteban María,Romero CristóbalORCID

Funder

Ministerio de Ciencia e Innovación

European Regional Development Fund

Publisher

Springer Science and Business Media LLC

Subject

Education

Reference53 articles.

1. Aljawarneh, S., Muhsin, Z., Nsour, A., Alkhateeb, F., & AlMaghayreh, E. (2010). E-learning tools and technologies in education: A perspective. In The fifth international conference of learning international networks consortium (LINC). Cambridge, MA: MIT. Retrieved from http://people.math.sfu.ca/~vjungic/shadi.pdf . Accessed 5 Jan 2019.

2. Azevedo, R., & Aleven, V. (Eds.). (2013). International handbook of metacognition and learning technologies. Amsterdam: Springer.

3. Azevedo, R., & Feyzi-Behnagh, R. (2011). Dysregulated learning with advanced learning technologies. Journal of e-Learning and Knowledge Society,7(2), e9–e18.

4. Azevedo, R., Harley, J., Trevors, G., Duffy, M., Feyzi-Behnagh, R., Bouchet, F., et al. (2013). Using trace data to examine the complex roles of cognitive, metacognitive, and emotional self-regulatory processes during learning with multi-agent systems. In R. Azevedo & V. Aleven (Eds.), International handbook of metacognition and learning technologies (pp. 427–449). New York: Springer.

5. Bannert, M., Reimann, P., & Sonnenberg, C. (2014). Process mining techniques for analysing patterns and strategies in students’ self-regulated learning. Metacognition and Learning,9(2), 161–185. https://doi.org/10.1007/s11409-013-9107-6 .

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