Improving learner engagement in MOOCs using a learning intervention system: A research study in engineering education

Abstract

The development of web applications is an essential and critical skill for Computer Science Engineers. Nowadays, this is a core subject in the Computer Science Engineering Studies and an increasingly demanded subject in other Engineering Studies. With the aim to facilitate introductory know-how in this area, the University Autónoma of Madrid offers at edX Platform the Massive Open Online Course (MOOC): "Introduction to Development of Web Applications". Several studies have emphasised the positive impact of methods, such as the use of continuous feedback, to improve and promote learning persistence and engagement in online courses. We propose a system for periodically providing MOOC learners information about their progress and suggestions about how can they can improve their learner performance based on their achievements and interactions in MOOCs. This system is called Learning Intervention System for edX MOOCs (edX-LIS). To test the intervention strategy on learners' behaviour supported by edX-LIS, a research study was conducted with the learners of the mentioned MOOC. The results obtained from this study have demonstrated that the intervention strategy supported by the edX-LIS has a positive impact on the motivation, persistence and engagement of the learners in the MOOC.

Grade Prediction in Blended Learning Using Multisource Data

“…It includes four-link maps: projection views of learner-identifying groups, pattern views showing the overall sequence patterns within the selected group, sequence views describing transformations between ongoing events, and individual views with an extended sequence chain. Cobo and Ruiz-Garcia presented the edX-LIS Learning Intervention System, which provides intervention strategies to improve learning performance, positively affecting learning motivation, persistence, and participation [27]. García-Molina et al presented an automatic scoring algorithm based on the data dimension and correlation of learners' contributions [28].…”

Predicting Learning Behavior Using Log Data in Blended Teaching

“…e results provided a scientific basis for MOOC instructional design and instructional resources allocation. Cobos and Ruiz-Garcia proposed a learning intervention system called edX-LIS for providing MOOC learners with information about their progress regularly and making suggestions by their performance [23]. Contrast experiments had shown that the intervention strategies provided by this system had a positive impact on learners' motivation, persistence, and engagement.…”

Guest editorial: Distance learning, MOOCs and globalisation of engineering education

“…This could be due to the expertise of the guest editorial team, but it is also true that MOOCs continue to receive a lot of attention in the Computer-Assisted Education research community, as Yousef and Summer [1] point out in this volume. Nevertheless, the use of MOOCs in the specific domain of Engineering Education was somewhat under-researched when the call was launched, which is reflected in this special issue with a number of relevant contributions such as Sahin's [14] analysis of optics software teaching tools, the studies on how learners interact in discussion forums [9,11], learners' behaviour and performance when watching online lecture videos [8], technologyenhanced interventions to increase engineering learners' engagement [2,12], including the best approaches to feedback for those with difficulties [16] and those whose English is not their first language [13].…”