Open Access Open Access  Restricted Access Subscription or Fee Access

Role of Effectual Predictors of Academic Achievement: An Analytical Study on Select Course Adopted

Mudasir Ashraf, Dr. Majid Zaman, Dr. Muheet Ahmed

Abstract


The contemporary challenges in higher education that are positioned under limelight include academic achievement, teaching, learning activities and the overall development of students. The intend of this investigation is to discover imperative facets within a precise course (Bachelors of Arts)  that may designate which variables/predictors are possibly to effect and optimize academic performance. Therefore, quantitative and statistical techniques such as discriminant and analysis of variance (ANOVA) were utilized to explore imperative characteristics of students responsible for their success. Furthermore, these techniques were deployed in the realm of academic mining keeping in view their novel nature in discovering valid patterns from educational settings. In this study, association among various individual variables of the course and students overall performance were put under examination, to get an insight which elements are accountable for the student’s performance. Moreover, real dataset that was acquired from university of Kashmir was put under investigation, and it was examined that economics as a subject played a predominant role in the overall performance of the students.


Keywords


Knowledge Discovery, Educational Data Mining, Discriminant, ANOVA, Correlation, Structure Matrix.

Full Text:

PDF

References


BakerRSJd, Yacef K. The state of educational data mining in 2009. A review and future visions. J EduData Min 2009.

Romero C, Ventura S, Pechenizky M, Baker R. Handbook of educational data mining. Data Mining and Knowledge Discovery Series. Boca Raton, FL: Chapman and Hall/CRCpress; 2010.

J. Han and M. Kamber, Data mining: Concepts and Techniques. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2000.

Klecka, W.R. 1980. Discriminant analysis. Sage, Beverley Hills.

X.chen, M.Vorvoreanu, K.Madhavan, Mining Social Media Data for Understanding Student’s Learning Experiences, Ieeexplore.Ieee.Org, 7(3), 2014, 246–259.

Sheikh, L., Tanveer, B. and Hamdani, S. 2004. Interesting measures for mining association rules. IEEE-NMIC Conference. held at Lahore (Pakistan), 24−26 Dec. 2004.

Romero, C. and Ventura, S. (2007) ‘Educational data Mining: A Survey from 1995 to 2005’, Expert Systems pp. 135-146.with Applications (33),

El-Halees, A. 2009. Mining students data to analyze learning behavior: a case study. https://uqu.edu.sa/fi les2/tiny_mce/plugins/fi lemanager/fi les/30/papers/f158.pdf.

Kifaya. 2009. Mining student evaluation using associative classification and clustering. Communications of the IBIMA. 11, IISN 1943−7765.

Ayesha, S., Mustafa, T., Sattar, A.R. and Khan, M.I. 2010. Data mining model for higher education system. European Journal of Scientific Research. 43(1): pp. 24−29.

Sunil Kumar, P., Panda, A.K. and Jena, D.2013. “Mining the factors affecting the high school dropouts in rural areas”, International Journal of Advance Computer Engineering and Communication Technology (IJACECT), 2(1); pp. 1−6.

Sembiring, S., Zarlis, M., Hartama, D., Ramliana, S., & Wani, E. (2011, April). Prediction of student academic performance by an application of data mining techniques. In International Conference on Management and Artificial Intelligence IPEDR (Vol. 6, No. 1, pp. 110-114).

Sahedani, K., and B. Reddy. "A Review: Mining Educational Data to Forecast Failure of Engineering Students." International Journal of Advanced Research in Computer Science and Software Engineering 3.12 (2013).

Alaskar, K. M., Prashant G. Tandale, and A. A. Basade. "Data Mining Applications in Higher Education." Proceedings of National Conference on Emerging Trends: Innovations and Challenges in IT. Vol. 19. 2013.

Prabha, S. Lakshmi, and AR Mohamed Shanavas. "Educational data mining applications." Operations Research and Applications: An International Journal (ORAJ) 1.1 (2014): 1-6.

Fatima, D., Sameen Fatima, and AV Krishna Prasad. "A survey on research work in educational data mining." IOSR Journal of Computer Engineering (IOSR-JCE) 17.2 (2015): 43-49.


Refbacks

  • There are currently no refbacks.