The effect of recommendation systems on Internet-based learning for different learners: A data mining analysis

Chen Chung Liu, Chia Jung Chang, Jui Min Tseng

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


A general challenge facing Internet-based learners is how to identify information objects which are helpful in expanding their understanding of important information in a domain. Recommendation systems may assist learners in identifying potentially helpful information objects. However, the recent literature mainly focuses on the technical performance, rather than on how recommendations support searching in educational contexts. This study thus investigates how recommendation systems may influence the searching behaviors and strategies of different learners, when they are used with a mind map. The results suggested two main different searching behavioral patterns, namely focused searchers and broad searchers. It is found that the recommendations may influence the searching behaviors of the two types of searchers in different ways. For the focused searchers, the recommendations may support these searchers to expand their keywords to explore the domain. Regarding the broad searchers, they did not rely on the computer recommendations. However, the mind map interface applied along with the recommendations may support them in monitoring their searching processes. Online Information Searching Strategies Inventory (OISSI) was applied to examine the participants' perceptions of how students applied information searching strategies. The results of OISSI support that both types of searchers perceived a higher level of searching strategies when they search with the recommendation system and mind maps.

Original languageEnglish
Pages (from-to)758-773
Number of pages16
JournalBritish Journal of Educational Technology
Issue number5
StatePublished - Sep 2013


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