Learning Pathway: Analytical Framework to Predict Learner’s Learning Effectiveness and Performance
Vinayak Hegde1, Sahana Patil2, Smruthi G3 

1Vinayak Hegde, Department of Computer Science, Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham, Mysuru, India.
2Sahana Patil, Department of Computer Science, Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham, Mysuru, India.
3Smruthi G, Department of Computer Science, Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham, Mysuru, India.

Manuscript received on 15 March 2019 | Revised Manuscript received on 21 March 2019 | Manuscript published on 30 July 2019 | PP: 1751-1755 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1043078219/19©BEIESP| DOI: 10.35940/ijrte.B1043.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In recent years, computerized online tests play a significant role to judge the learning of the students in their academics. The conventional process of examining students for academic performance take a long time and thus, identifying and understanding the learning behaviors at that time is very crucial and difficult. The pen and pencil tests that are used to assess the student’s learning way by the teachers take a lot of time. Thus, a computerized test can serve as an early mechanism for testing the students wherein the evaluation results are produced immediately and thus, reducing the time for the teachers for further assessment. The students learning and understanding behaviors are reflected through their scores and performances in these tests. The present model helps the teachers to predict the weak learners and their area of weakness in studies so that special coaching and interests can be given on such students to improve their academics strength. In recent years, the JAVA programming language is extensively used for several kinds of examinations. This web-based testing environment is a JAVA based application through which the results are analyzed and are visualized to students and the reports are provided as feedback to the teachers. The analysis uses regression to predict the performance based on the y value calculated. The correlation coefficient between the average score and average time spent on chapters was found to be 0.474, which indicates the moderate correlation between them. This kind of examination helps students to self-evaluate their learning results and thus, can improvise on weaker areas.
Index Terms: Correlation, Education Data Mining, Online Test, Performance Prediction, Regression

Scope of the Article: Data Mining