Learning Analytics: Requirements for Enhanced Learner-Content Interactions in an Online Environment

During face to face classroom interactions, learning is facilitated through the dissemination of course materials by subject specialists, in a pedagogical manner, suiting the pace of the learners. It is known that proper interactions with contents, tutors and peers encourage learning to take place. However, the learner-content process is known to be challenging for online learners who struggle alone to overcome learning difficulties, and which may lead them to drop out from the course. In absence of face to face interactions, the content, being the prime source of knowledge for distant learners, has to be up to date and comprehensive while catering for different learning styles of students. Therefore, this paper aims at investigating whether learners meet the cognitive level as required by the course's learning objectives. Through a questionnaire, 18 online learners were requested to identify their learning activities done in both asynchronous and synchronous modes as part of their learning process. Furthermore, content analysis, using both Activity Theory and the Jaillet & Panchoo grid, was done on four online tutorials to identify if learners study their course materials as desired and if their interactions are of cognitive level. A total of 761 lines of logged textual interactions was coded twice. Results show that learners go through different learning activities as imposed by the module but less emphasis is put on ensuring that learners study the course content before embarking on the assignment. Acquiring the relevant knowledge from the course materials prior to online discussions, will encourage better interactions and learning to take place in this socio-constructivism set up.