Title
Using a learning analytics tool for evaluation in self-regulated learning
Abstract
In self-regulated learning, evaluation is a complex task of the teaching process, but even more if students have social media that allow them to build their personal learning environment in different ways. In these kind of virtual environments a large amount of data that needs to be assessed by teachers is generated, and therefore they require tools that facilitate the assessment task. In this paper, we present an experiment with a process mining-based learning analytics tool, called SoftLearn, that helps teachers to assess the student's activity in self-regulated learning. The subject of this experiment is taught in blended learning mode with weekly classroom sessions, and the students use a social network software, called ELGG, as an e-portfolio in which they reflect their individual knowledge process construction. The results show that the use of this tool reduces significantly the assessment time and helps teachers to understand the learning process of the students.
Year
DOI
Venue
2014
10.1109/FIE.2014.7044400
FIE
Keywords
Field
DocType
computer aided instruction,data mining,social networking (online),elgg,softlearn,blended learning mode,e-portfolio,individual knowledge process construction,learning analytics tool,personal learning environments,process mining-based learning analytics tool,self-regulated learning,social media,social network software,teaching process,weekly classroom sessions,process control,clustering algorithms
Experiential learning,Educational technology,Learning sciences,Active learning,Learning analytics,Computer science,Knowledge management,Synchronous learning,Blended learning,Cooperative learning,Multimedia
Conference
ISSN
Citations 
PageRank 
0190-5848
7
0.64
References 
Authors
13
5
Name
Order
Citations
PageRank
ana rodriguez groba170.64
Borja Vázquez-Barreiros2495.82
Manuel Lama338334.84
adriana gewerc4101.04
Manuel Mucientes537835.05