توضیحات
ABSTRACT
This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic planning. We examined the literature on experimental case studies conducted in the domain during the past six years (2008-2013). Search terms identified 209 mature pieces of research work, but inclusion criteria limited the key studies to 40. We analyzed the research questions, methodology and findings of these published papers and categorized them accordingly. We used non-statistical methods to evaluate and interpret findings of the collected studies. The results have highlighted four distinct major directions of the LA/EDM empirical research. We discuss on the emerged added value of LA/EDM research and highlight the significance of further implications. Finally, we set our thoughts on possible uncharted key questions to investigate both from pedagogical and technical considerations.
INTRODUCTION
The information overload, originating from the growing quantity of “Big Data” during the past decade, requires the introduction and integration of new processing approaches into everyday objects and activities (“ubiquitous and pervasive computing”) (Cook & Das, 2012; Kwon & Sim, 2013). Handling large amounts of data manually is prohibitive. Several computational methods have been proposed in the literature to do this analysis.
In commercial fields, business and organizations are deploying sophisticated analytic techniques to evaluate rich data sources, identify patterns within the data and exploit these patterns in decision making (Chaudhuri, Dayal & Narasayya, 2011). These techniques combine strategic planning procedures with informational technology instruments, summarized under the term “Business Intelligence” (Eckerson, 2006; Jourdan, Rainer & Marshall, 2008). They constitute a well-established process that allows for synthesizing “vast amount of data into powerful decision making capabilities” (Baker, 2007, p. 2).
Recently researchers and developers from the educational community started exploring the potential adoption of analogous techniques for gaining insight into online learners’ activities. Two areas under development oriented towards the inclusion and exploration of big data capabilities in education are Educational Data Mining (EDM) and Learning Analytics (LA) and their respective communities.
Year : 2014
Publisher : article of the Journal of Educational Technology & Society
By : Zacharoula Papamitsiou and Anastasios A. Economides
File Information : English Language / 16 Page / Size : 306 KB
Download : click
سال : 2014
ناشر : article of the Journal of Educational Technology & Society
کاری از : Zacharoula Papamitsiou and Anastasios A. Economides
اطلاعات فایل : زبان انگلیسی / 16 صفحه / حجم : 306 KB
لینک دانلود : روی همین لینک کلیک کنید
نقد و بررسیها
هنوز بررسیای ثبت نشده است.