Putting to Test a Model of Self-evaluation of the Learning Method in an e-Learning Environment

  • Jonathan KaplanEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 993)


This paper describes the process and results of a study that put to test a model of self-evaluation of the learning processes which had emerged from a previous study. As in the previous study, this study examined self- and co-regulation strategies, in particular learners’ assessment strategies that learners perceived to have used during a university course within an e-learning environment. In the previous study [13], collective evaluation of the targeted learning content—a co-regulation strategy—, and to a lesser extent, individual environmental control, both predicted individual self-evaluation of the study method. Using the same research method, the study presented in this paper aimed at examining learners’ self-evaluation of their study method to test if a similar explicative model emerged. Furthermore, the present research studied two student groups, learning within the same course but with separate instructors. Studying two groups enabled to compare perceived regulation of learning strategies used. Subjects were postgraduate students in Educational Sciences studying on a digital campus in a French university during the academic year 2017–18. Data was collected using the ERICA scale [15]. The study found that the same explicative model applied, though the explicative power of the model was weaker. It also revealed that the two groups of learners did not differ significantly. These findings are discussed followed by suggestions for the design of e-learning environments.


Self-regulation Co-regulation Learning strategies Assessment Self-evaluation 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institut des Sciences et Pratiques d’Éducation et de Formation, Laboratoire Éducation, Cultures and Politiques (EA 4571)Université Lumière Lyon 2LyonFrance
  2. 2.Laboratoire Cognitions Humaine et ArtificielleUniversité Paris Nanterre (EA 4004)NanterreFrance

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