Assessing the suitability of student interactions from Moodle data logs as predictors of cross-curricular competencies. (June 2015) - Iglesias-Pradas, Santiago; Ruiz-de-Azcárate, Carmen; Agudo-Peregrina, Ángel F.
Highlights: Suitability of learning analytics to predict competency acquisition is assessed. Focus on two cross-curricular competencies: teamwork and commitment. Three types of student interactions are extracted from Moodle logs. No relation is found between interactions and competency levels. Recommendations for further research on this topic are offered. Abstract: In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics. This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master's Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.