Predavanje: "Learning analytics – a multiple perspectives analysis of student data"

Sažetak predavanja:

Learning analytics (LA) is a growing research area, which aims at selecting, analyzing and reporting student data (in their interaction with the online learning environment), finding patterns in student behavior, displaying relevant information in suggestive formats; the end goal is the prediction of student performance, the optimization of the educational platform and the implementation of personalized interventions. The topic is highly interdisciplinary, including machine learning techniques, educational data mining, statistical analysis, social network analysis, natural language processing, but also knowledge from learning sciences, pedagogy and sociology.

Despite its increasing popularity, LA has been applied less in the context of social media-based environments; hence in this talk we focus especially on research in social learning analytics area. In particular, we explore academic performance predictors and the relationships between students’ learning styles and their social media use; we also investigate students’ collaboration patterns and the community of inquiry supported by social media tools. Four research directions are tackled: analytics dashboards, predictive analytics, social network analytics and discourse analytics. As far as analysis techniques are concerned, we apply various approaches, such as: classification, regression, clustering and PCA algorithms, textual complexity analysis, social network analysis techniques, content analysis based on Community of Inquiry. We thus address the “trinity” of methodological approaches: i) network analysis (representing actor-actor / social relations); ii) process-oriented analysis (based on action logs and pattern detection); iii) content-oriented analysis (based on learner created artefacts); hence a more comprehensive learning analytics perspective is provided.

O predavačici:

Elvira Popescu is a full professor at the Computers and Information Technology Department, University of Craiova, Romania. She received the Ph.D. degree in information and systems technologies from the University of Technology of Compiègne, France, and the University of Craiova, Romania, in 2009. Her research interests include technology-enhanced learning, adaptation and personalization in Web-based systems, learner modeling, computer-supported collaborative learning, learning analytics, and intelligent and distributed computing. Dr. Popescu has authored and co-authored over 100 publications, including two books, journal articles, book chapters, and conference papers, which have received over 1400 citations. In addition, she has co-edited six journal special issues, as well as 15 international conference proceedings published by Springer and one published by IEEE. She has also given several invited and panel talks at various international conferences. She has participated in over 15 national and international research projects, three of which as a principal investigator (grant director).
Prof. Popescu also serves as the Vice Chair for the IEEE Women in Engineering Romania Section Affinity Group and is an Executive Board Member for the IEEE Technical Committee on Learning Technology and the International Association of Smart Learning Environments. She received several scholarships and awards, including five best paper distinctions (IEEE EUROCON 2007, IEEE ICALT 2013, ICWL 2015, ICWL 2018, IEETeL 2019). She is actively involved in the academic community by serving as associate editor for two journals (IEEE Transactions on Learning Technologies, Smart Learning Environments), member of five other journal editorial boards, organizing a series of international workshops in the area of social and personal computing for e-learning (SPeL 2008–2020), serving as a conference chair, program committee chair, and track chair for 18 conferences.