Sachin Ahuja

Work place: Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

E-mail: sachin.ahuja@chitkara.edu.in

Website: https://scholar.google.com/citations?user=BEDrP7cAAAAJ&hl=en

Research Interests: Big data and learning analytics, Database Management System, Data Mining, Innovation of language teaching

Biography

Dr. Sachin Ahuja holds a PhD in Data mining. His primary research interests are in the field of educational data mining. Specifically, under data mining he is interested in predictions, designing of survey questionnaires, measuring and comparing the academic performance of students and comparison of traditional teaching with flipped and blended learning models. Apart from data mining, his teaching interests include big data, relation database and procedural languages. In addition to this, he is heading the Office of Patent Facilitation where he has facilitated inventors from Chitkara University in filing patents by guiding them in licensing & consultancy. Sachin in his free time practices yoga and explores the city for good vegetarian cuisine.

Author Articles
Identification of Influencing Factors for Enhancing Online Learning Usage Model: Evidence from an Indian University

By Sachin Ahuja Puninder Kaur S N Panda

DOI: https://doi.org/10.5815/ijeme.2019.02.02, Pub. Date: 8 Mar. 2019

With advent of technology online education has become the core of educational settings worldwide. This paper aims to identify the factors that contribute in enhancing the online learning usage model in context of India, an emerging leader in Educational settings across the globe. In this study, data mining techniques were applied on the data collected from the log files of online courses. The initial investigations supported the use of custom build framework for teaching online courses. Data Structure course was taught using online platform and the data was collected using the log files. The data collected was further analysed using data mining techniques using Rapid miner tool. Although the results from three different data mining techniques showed some variations but the inferences from the results identified few common factors that have influence on enhancing the online learning usage model. Clustering techniques revealed that factors related to timely checking of online contents and posting have positive impact on online learning however decision trees supported that timely completing the online assignments along with checking of online contents and posting of messages played an important role in terms of enhancing the academic performance. This paper identifies three factors for teachers teaching online courses to improve overall performance of the students by learning from Indian University Success.

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