Using Video Visualizations in Open edX to Understand Learning Interactions of Students
The emergence of Massive Open Online Courses (MOOCs) has caused a high disrupting effect on online education. One of the most extended MOOC platforms is Open edX. There is a demanding necessity by the instructors and students of these courses to provide t
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niversidad Carlos III de Madrid, Madrid, Spain {100075697,100060449}@alumnos.uc3m.es, {jruipere,pedmume,cdk}@it.uc3m.es 2 Oulun yliopisto, Oulu, Finland 3 IMDEA Networks Institute, Madrid, Spain
Abstract. The emergence of Massive Open Online Courses (MOOCs) has caused a high disrupting effect on online education. One of the most extended MOOC platforms is Open edX. There is a demanding necessity by the instructors and students of these courses to provide timely analytics tools that can help understand the learning process at any moment. In this direction we have devel‐ oped the Add-on of learNing AnaLYtics Support for open Edx (ANALYSE), which is our learning analytics contribution for Open edX. In this demonstration paper we will provide guidelines on how to use some of the ANALYSE video visualizations in order to detect problems in video resources, so that the learning process can be improved. Keywords: Moocs · Open edx · Learning analytics · Visualizations
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Introduction
MOOCs have had quite an important impact on education in the last years. These courses usually have thousands of students, which makes them particularly difficult to control and have a feeling about what is actually happening. Learning analytics functionality is a key factor in these virtual environments for allowing students self-reflection and facil‐ itating teachers to make decisions based on data. However, most of the MOOC platforms are not providing yet the learning analytics functionalities to support these courses. Therefore, as an example, instructors might feel a little bit lost about how their students are progressing in the course or whether some learning resources are causing problems due to a bad design. The use of visualizations with the objective of transmitting infor‐ mation is a common tool in learning analytics. We can find several learning analytics developments for different platforms such as ALAS-KA [1] for Khan Academy which also include visualizations for video activity. Currently our efforts are focused on Open edX platform. Most of the MOOC data analyses in the literature are performed over the static data after course completion. As
© Springer International Publishing Switzerland 2015 G. Conole et al. (Eds.): EC-TEL 2015, LNCS 9307, pp. 522–525, 2015. DOI: 10.1007/978-3-319-24258-3_51
Using Video Visualizations in Open edX
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an example we can find several post-hoc analysis papers1 by the MIT Office of Digital Learning. However, there is not much work developed in Open edX aimed at providing timely information for both students and instructors while taking and teaching a course respectively. The current support for learning analytics in Open edX is at an early stage providing a single visualization about the progress in problems. In this direction we have developed ANALYSE, which currently incorporates 12 brand new visualizations that were not present previously in Open edX. In this paper we provide guidelines on how to use some of the video visualizations included in ANALYSE to detect problems in educational video resour
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