Predictive Learning Analytics for Student Success towards Outcome Based Education Perspective

  IJCTT-book-cover
 
         
 
© 2021 by IJCTT Journal
Volume-69 Issue-9
Year of Publication : 2021
Authors : Dr. Vijayakumar V
DOI :  10.14445/22312803/IJCTT-V69I9P102

How to Cite?

Dr. Vijayakumar V, "Predictive Learning Analytics for Student Success towards Outcome Based Education Perspective," International Journal of Computer Trends and Technology, vol. 69, no. 9, pp. 7-11, 2021. Crossref, https://doi.org/10.14445/22312803/IJCTT-V69I9P102

Abstract
Learning analytics is useful technology in examining students’ learning performance, skill and attitude in learning environment. It also takes to the next level i.e. rather than focusing on the past issues, it helps to predict learners’ future success. The key accountability of most of the education systems is student success. It may be measured as graduating from college, qualifying for a job or further education, acquiring a specified set of skills, or achieving needed credentials. Outcome Based Education is a learnercentered approach that focuses on measuring students` attainment and achievement based on activities and assessments. By leveraging predictive analytics in OBE, faculty members and mentors can identify the nonattainment of the graduate outcomes of a student and intervene earlier with higher impact. Personalized learning style which focuses on the needs of each student and a practice. The proposed approach assists faculty to measure the attainment status of a student with respect to OBE assessment and also predicts the academic performance of students towards Outcome Based Education perspective.

Keywords
Learning Analytics, Outcome Based Education, Outcome Based Attainment, Education Analytics, Student Success, Outcome Based Analytics.

Reference

[1] Myint Swe Khine, Learning Analytics for Student Success: Future of Education in Digital Era, Proceedings of the European Conference on Education, (2018).
[2] D. Buenaño Fernández, S. Luján-Mora, Exploring approaches to educational data mining and learning analytics, to measure the level of acquisition of student`s learning outcome, Proceedings of EDULEARN16, (2016) 1845-1850.
[3] Eduardo Fernandesa,b,, Maristela Holandaa, Marcio Victorinoa, Vinicius Borgesa, Rommel Carvalhoa, Gustavo Van Ervena,c, Educational data mining: Predictive analysis of academic performance of public school students in the capital of Brazil, Journal of Business Research, 94 (2019) 335–343.
[4] Viet Anh Nguyen, Quang Bach Nguyen, Vuong Thinh Nguyen, A model to forecast learning outcomes for students in blended learning courses based on learning analytics, Proceedings of the 2nd International Conference on E-Society, E-Education and ETechnology, (2018) 35–41.
[5] Amirah Mohamed Shahiria, Wahidah Husaina, Nur’aini Abdul Rashida, A Review on Predicting Student’s Performance using Data Mining Techniques, Proceedings of the Third Information Systems International Conference, Procedia Computer Science, 72 (2015) 414 – 422.
[6] Asiah Mat, Nik Zulkarnaen Khidzir , Safaai Deris , Nik Nurul Hafzan Mat Yaacob, Mohd Saberi Mohamad, and Siti Syuhaida Safaai, A Review on Predictive Modeling Technique for Student Academic Performance Monitoring, Proceedings of MATEC Web of Conferences, EAAI Conference, (2019).
[7] Beth Dietz-Uhler, Janet E. Hurn, Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective, Journal of Interactive Online Learning, 12(1) (2013) 17-274.
[8] Christothea Herodotou, Bart Rienties, Avinash Boroowa, Zdenek Zdrahal, Martin Hlosta, A large-scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective, Education Tech Research Dev., 67 (2019) 1273–1306.
[9] Manuel Fernandez-Delgado, Manuel Mucientes, Borja VazquezBarreiros and Manuel Lama, Learning Analytics for the Prediction of the Educational Objectives Achievement, Proceedings of the IEEE Frontiers in Education Conference, (2014) 2500-2504.
[10] IBM. Analytics for achievement: Understand success and boost performance in primary and secondary education., Retrieved from http://public.dhe.ibm.com/common /ssi/ecm/ en/ ytw03149caen /YTW03149CAEN.PDF. (2001).
[11] Pooja Chaturvedi, A. K. Daniel, Application of Learning Analytics Model in Outcome-Based Education, Chapter 6, Role of ICT in Higher Education: Trends, Problems, and Prospects, 59(2020).
[12] Sahar Yassine, Seifedine Kadry, Miguel-Angel Sicilia, A Framework for Learning Analytics in Moodle for Assessing Course Outcomes, Proceedings of IEEE Global Engineering Education Conference (EDUCON), Abu Dhabi, UAE, (2016) 261-267.
[13] http://edudownloads.azureedge.net/msdownloads/MicrosoftEducati onAnalytics.pdf