Mining learners’ Data to Perceive the Need for German for Academic Purposes
Subhasri Vijayakumar1, Syed Ibrahim S P2
1Subhasri Vijayakumar, VIT Chennai, Vandalur-Kelambakkam Road, Chennai, Tamil Nadu, India.
2Syed Ibrahim S P, VIT Chennai, Vandalur-Kelambakkam Road, Chennai, Tamil Nadu, India.
Manuscript received on 12 March 2019 | Revised Manuscript received on 17 March 2019 | Manuscript published on 30 July 2019 | PP: 5491-5494 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3777078219/2019©BEIESP | DOI: 10.35940/ijrte.B3777.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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 teaching-learning process of German. These findings are discussed in this paper in light of augmenting the German curriculum at the tertiary sector.
Keywords: Educational Data Mining, Foreign Language learning, K-Means Clustering, Needs Analyses, German for Academic Purposes
Scope of the Article: Data Mining