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Mining learners’ Data to Perceive the Need for German for Academic Purposes
Published in Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Volume: 8
Issue: 2
Pages: 5491 - 5494
Learning a foreign language at the tertiary level opens up many opportunities for the learners and is indeed an essential requirement for those aspiring to continue their education abroad. With Germany becoming one of the most preferred destinations for higher studies, along with the general German language skills, the academic skills that would be needed is an aspect worth analyzing in the given context of growing demands. Educational data mining is an emerging field and analysis using data mining techniques in educational settings aid in better understanding of the learners, their learning environment and their learning needs. Through this study, by applying one of the data mining techniques called “Clustering”, we explored the German learners’ perception of which academic skill they deem important to be learned in German at the tertiary level. A significant difference in the perception of German learners when it comes to learning academic skills in German was found between the two clusters that were formed. This divide in perceptions among learners indicates the awareness of the learners about studying in German universities or the lack thereof. Educational data mining and its techniques aid in significant decision making that could enhance the teachinglearning process of German. These findings are discussed in this paper in light of augmenting the German curriculum at the tertiary sector.
About the journal
JournalInternational Journal of Recent Technology and Engineering 2
PublisherBlue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Open Access0