Designing Massive Open Online Learning Processes: The importance of the social element

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Recommending peers for learning: Matching on dissimilarity in interpretations to provoke breakdown

People recommenders are a widespread feature of social networking sites and educational social learning platforms alike. However, when these systems are used to extend learners’ Personal Learning Networks, they often fall short of providing recommendations of learning value to their users. This paper proposes a design of a people recommender based on content-based user profiles, and a matching method based on dissimilarity therein. It presents the results of an experiment conducted with curators of the content curation site Scoop.it!, where curators rated personalized recommendations for contacts. The study showed that matching dissimilarity of interpretations of shared interests is more successful in providing positive experiences of breakdown for the curator than is matching on similarity. The main conclusion of this paper is that people recommenders should aim to trigger constructive experiences of breakdown for their users, as the prospect and potential of such experiences encourage learners to connect to their recommended peers.

Students’ Use of Knowledge Resources in Environmental Interaction on an Outdoor Learning Trail

This study examined how students leveraged different types of knowledge resources on an outdoor learning trail. We positioned the learning trail as an integral part of the curriculum with a pre- and post-trail phase to scaffold and to support students’ meaning-making process. The study was conducted with two classes of secondary two students. We coded two groups’ discourse to examine the use of knowledge resource types in the meaning-making process in an outdoor learning setting: contextual resource, new conceptual resource, prior knowledge resource, as well as the relationship among these knowledge resource types. Next, we also examined environmental interaction and integration in the students’ use of these knowledge resource types. Analysis showed that contextual resources are chiefly instrumental in fostering students’ capacity to harness new conceptual resource and to activate prior knowledge resource in interacting with and integrating the outdoor learning environment in the meaning-making process.

Predicting Student Performance and Differences in Learning Styles based on Textual Complexity Indices applied on Blog and Microblog Posts

Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.