Centrality Metrics from Students' Discussion Fora at Distance Education | IEEE Conference Publication | IEEE Xplore

Centrality Metrics from Students' Discussion Fora at Distance Education


Abstract:

In this study, we applied the HITS algorithm, an advanced network-based algorithm that produces the metrics “Authority” and “Hub” to indicate the importance of the nodes ...Show More

Abstract:

In this study, we applied the HITS algorithm, an advanced network-based algorithm that produces the metrics “Authority” and “Hub” to indicate the importance of the nodes (tutors and students) in a discussion forum network. By using this algorithm, we evaluated the tutors' and the students' authority and hub scores, as a result of their participation in the fora at an Open University Moodle platform. Through a graph representation and the use of the HITS algorithm, we located those students with the highest authority and hub scores, in an attempt to find correlations between those metrics and the students' performance and role, in the learning process. Our study intends to offer useful knowledge, especially in distance learning settings, where there is a lack of physical interaction between tutors and learners. Additionally, as the plethora of the existing data does not allow tutors to identify early and before the mid and final evaluations, the active students, the HITS algorithm spots those students for them. Our aim is to empower the forum community role in Distance Education by giving it a more student-centered profile, as the most active student could cooperate with their tutors and be the leaders to support their peers' effort for a more self-directed learning.
Date of Conference: 10-12 July 2023
Date Added to IEEE Xplore: 15 December 2023
ISBN Information:
Conference Location: Volos, Greece

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