Toward Enhancing Collaborative Learning Groups Formation in Q&A Website Using Tag-based Next Questions Predictor

Autor:	Mohammad Sadegh Rezaei, Hossein Bobarshad, Kambiz Badie
Rok vydání:	2018
Předmět:	World Wide Web Naive Bayes classifier Computer science Lifelong learning Collaborative filtering Collaborative learning Informal learning Social learning Online community Computer Science Applications Education Domain (software engineering)
Zdroj:	International Journal of Technology Enhanced Learning. 1:1
ISSN:	1753-5263 1753-5255
DOI:	10.1504/ijtel.2018.10018196
Popis:	The advent of informal social learning environment has provided the necessary platform for realising of lifelong learning. The basic platform of learning in an informal environment is the learning groups called online Community of Practice (oCoP). This study proposes a predictor for predicting the topics most suitable for the formation of oCoPs for the users adopting the roles of co-learner and mentor in a shared domain perspective. Proposed predictor operates based on Naive Bayes prediction and collaborative filtering and uses educational social tags for realising the learners' roles and behaviour. The predictor is evaluated with the dataset of the website StackOverflow. The results show that the proposed predictor can predict the next question of learners with high accuracy. Therefore, the system can facilitate the formation of suitable learning groups around the predicted users' interest topics.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1ecb9b9e64561c733625dcfa812db44 https://doi.org/10.1504/ijtel.2018.10018196 Zobrazit plný text záznamu