Open AccessSupporting teaching staff through data Analytics: A Systematic Review
Author(s) -
Dirk Ifenthaler,
Jane Yin-Kim Yau
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.14742/ascilite2021.0105
Subject(s) - learning analytics , leverage (statistics) , computer science , pace , context (archaeology) , analytics , data science , educational data mining , knowledge management , medical education , mathematics education , psychology , medicine , paleontology , geodesy , machine learning , biology , geography
Higher education institutions and its stakeholders are just about to catch up with the rapid pace at which educational data are being generated. While recent learning analytics research and applications are mainly focused on learning, there is an increased awareness that data analytics may provide teaching staff with evidence-based insights for enhancing teaching processes. The aim of this systematic review is to gain a deeper understanding on how data analytics in the educational context may play a role in helping teaching staff to leverage their own teaching A total of N = 18,723 articles were located and screened resulting in a final sample N = 35 key publications. Findings indicate that empowering teachers with data from educational contexts may support pre-active, interactive, and post-active reflection phases of teaching. However, teaching staff are required to further develop their educational data literacy in order to avoid biased pedagogical decision-making.