Effect of Academic Interest and Emotional Happiness on Academic Performance in Learning Environment
Amala Jayanthi.M1, Lakshmana Kumar.R2

1M. Amala Jayanthi, Assistant Professor, Department of Computer Applications, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India.
2Dr. R. Lakshmana Kumar, Assistant Professor & Technical Lead, Department of Computer Applications, Hindusthan College of Engineering and Technology, Coimbatore, Tamil Nadu, India.

Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 2486-2489 | Volume-9 Issue-1, May 2020. | Retrieval Number: A3043059120/2020©BEIESP | DOI: 10.35940/ijrte.A3043.059120
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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: According to Bloom’s Taxonomy, the motto of education is to groom the students’ as a better personality in knowledge, skill set and emotions under the supervision of academicians. Development of information technology paves the way to analyse the data from the educational environment and make decisions which help to be in track to achieve the motto. i.e. Educational Data mining. Education Data mining is one of the research domains of data mining which convert the data from the educational sector as insights for decision making. This paper is to analyse the effect of student’s academic interest on emotional happiness and academic performance by applying supervised and unsupervised learning techniques. Students’ Emotional Happiness and students’ academic performance is evaluated by the Oxford Happiness Inventory and criterion reference model. Academic interest is received as yes or no responses from the students. Naive Bayes classification algorithm and K Means clustering algorithm is applied to categorise the student participants based on their happiness scale, academic interest and academic performance. The association between academic interest and performance is determined using predictive and descriptive mining. By this research, it is witnessed the positive association between academic interest, happiness and performance. The insights of this investigation will allow the teachers’ to understand the students in a better way and do the needful to enhance academic efficiency. 
Keywords: Education, Bloom’s Taxonomy, Academic Interest, Happiness, K-Means clustering, Navie Bayes Classification, Apriori Association.
Scope of the Article: Classification