Notice to Authors

Due to the overwhelming number of submissions to IRRODL, the journal has already met its publication quota for 2019. As a result, for a period that will not exceed six months, IRRODL will no longer be accepting submissions after May 1, 2019. In order to improve our service to the academic community, and to ensure a six month review to publication cycle, IRRODL will be moving to a regularized publication schedule in 2020. More information will be provided later this year.

We thank our authors, reviewers, and readers for their unwavering and exceptional support in making our journal one of the world’s most successful, open access journals in the field of open and distributed learning.

The PERLA Framework: Blending Personalization and Learning Analytics

  • Mohamed Amine Chatti University of Duisburg-Essen
  • Arham Muslim University of Duisburg-Essen
Keywords: personalization, self-regulated learning, user-centered learning analytics, learning analytics reference model, goal-oriented learning analytics

Abstract

Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing insights and understanding into how learners learn and supporting customized learning experiences that meet their goals and needs. This paper discusses the Personalization and Learning Analytics (PERLA) framework which represents the convergence of personalization and learning analytics and provides a theoretical foundation for effective analytics-enhanced personalized learning. The main aim of the PERLA framework is to guide the systematic design and development of effective indicators for personalized learning.

Published
2019-02-28
How to Cite
Chatti, M. A., & Muslim, A. (2019). The PERLA Framework: Blending Personalization and Learning Analytics. The International Review of Research in Open and Distributed Learning, 20(1). Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/3936
Section
Research Articles