Is the LMS access frequency a sign of students' success in face-to-face higher education?

Reshaping the educational system dynamics by incorporating Learning Analytics concepts along the learning cycle is a great challenge. With the progressively inclusion of online learning in Higher Education, blended learning is a reality which makes easier the inclusion of learning analysis with less human effort. This paper describes an exploratory analysis of the online activity in the official Learning Management System of 2nd-year students in a course at the Telecommunication Engineering Degree at the University of Vigo for three consecutive academic years. We conclude there is a correlation between the interaction of the students in the LMS and their final marks. Besides, we have obtained temporal behaviour patterns for successful and unsuccessful students. Thus, it is possible the early detection of students who are not interacting as they are supposed to do when following the course and, consequently, to trigger alarms for both students and professors. Besides, professors would have a good feedback system to improve the course design in short-term.

[1]  Shane Dawson,et al.  SNAPP: a bird's-eye view of temporal participant interaction , 2011, LAK.

[2]  Rebecca Ferguson,et al.  Social Learning Analytics , 2012, J. Educ. Technol. Soc..

[3]  Donald J. Berndt,et al.  Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.

[4]  Roope Raisamo,et al.  A Model for Assessing Learning Management System Success in Higher Education in Sub‐Saharan Countries , 2014, Electron. J. Inf. Syst. Dev. Ctries..

[5]  Ulrik Schroeder,et al.  A reference model for learning analytics , 2012 .

[6]  Estela Bee Dagum.  Time Series Modelling and Decomposition , 2010 .

[7]  Matthew D. Pistilli,et al.  Course signals at Purdue: using learning analytics to increase student success , 2012, LAK.

[8]  Henda Chorfi Ouertani,et al.  Learning Analytics: definitions, applications and related fields , 2013, DaEng.

[9]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[10]  Sabine Graf,et al.  AAT: a tool for accessing and analysing students' behaviour data in learning systems , 2011, LAK.

[11]  Anil K. Jain,et al.  Algorithms for Clustering Data , 1988 .

[12]  Sebastián Ventura,et al.  Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[13]  George Siemens,et al.  Learning analytics and educational data mining: towards communication and collaboration , 2012, LAK.

[14]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[15]  E. Dagum.  TIME SERIES MODELING AND DECOMPOSITION , 2010 .

[16]  Delbert Dueck,et al.  Clustering by Passing Messages Between Data Points , 2007, Science.

[17]  D. Weaver,et al.  Academic and student use of a learning management system: Implications for quality , 2008 .

[18]  Jan Hauke,et al.  Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data , 2011 .