Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University) · 2018 · 54 citations · 19 references
Open access
Nowadays, most of e-learning systems embody online discussion forums as a medium for collaborative learning that supports knowledge sharing and information exchanging between learners. The exponential growth of the available shared information in e-learning online discussion forums has caused a difficulty for \nlearners in discovering interesting information. This paper introduces a novel recommendation architecture that is able to recommend interesting post messages to the learners in an e-learning online discussion forum based on a semantic content-based filtering and learners’ negative ratings. We evaluated the proposed elearning recommender system against exiting e-learning recommender systems that use similar filtering \ntechniques in terms of recommendation accuracy and learners’ performance. The obtained experimental results show that the proposed e-learning recommender system outperforms other similar e-learning recommender systems that use non-semantic content-based filtering technique (CB), non-semantic contentbased filtering technique with learners’ negative ratings (CB-NR), semantic content-based filtering technique (SCB), with respect to system accuracy of about 57%, 28%, and 25%, respectively. Furthermore, the obtained results also show that the learning performance has been increased by at least 9.84% for the \nlearners whom are supported by recommendations based on the proposed technique as compared to other similar recommendation techniques.
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