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Reseach Article

Dynamic Workflow Enabled Advanced Predictive model in Outcome based Education

by Shweta Dumbre, Sahil Karkhanis
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 160 - Number 7
Year of Publication: 2017
Authors: Shweta Dumbre, Sahil Karkhanis

Shweta Dumbre, Sahil Karkhanis . Dynamic Workflow Enabled Advanced Predictive model in Outcome based Education. International Journal of Computer Applications. 160, 7 ( Feb 2017), 16-21. DOI=10.5120/ijca2017913084

@article{ 10.5120/ijca2017913084,
author = { Shweta Dumbre, Sahil Karkhanis },
title = { Dynamic Workflow Enabled Advanced Predictive model in Outcome based Education },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2017 },
volume = { 160 },
number = { 7 },
month = { Feb },
year = { 2017 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2017913084 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:06:02.744247+05:30
%A Shweta Dumbre
%A Sahil Karkhanis
%T Dynamic Workflow Enabled Advanced Predictive model in Outcome based Education
%J International Journal of Computer Applications
%@ 0975-8887
%V 160
%N 7
%P 16-21
%D 2017
%I Foundation of Computer Science (FCS), NY, USA

Research in the field of Academic Analytics has led to the development of various models which aim at analyzing the performance of students. The different objectives of these models include prediction of student’s performance, providing feedback for supporting Instructors, student modelling, designing course curriculum and timetable scheduling. This research paper proposes an intervention model based on the existing NBA outcome based education system. The existing model includes the usage of parameters like the Program Educational Objectives (PEO’s), Program Outcomes (PO’s) and Course Outcomes (CO’s). The paper also includes a case study which shows the application of the intervention model on educational data for 40 students of the B.Tech in Computer Science program. The intervention model uses the direct assessment performance of students as input and predicts the students who fail to attain the CO’s. The intervention model results help in identifying the students who are in need of extra coaching and help the institution in focusing on these students in order to enhance the overall performance of the class. The automation of this model using artificial intelligent agents based model (iAERWS) further helps in improving the performance of the system significantly.

  1. Anna Alderson and Marie Martin, Outcome based education: Where has it come from and where is it going. Issues in Educational Research, 17(2) 2007, pp. 161-182.
  2. Dr ACR Tavner Outcomes-based education in a University setting Australasian Journal of Engineering Education, Copyright AAEE, 2005, ISSN 1324-5821 pp. 1-14
  3. T. A. Janardhan Reddy, P. Srinivas Reddy. Outcome Based Education—Some Initiatives Open Journal of Social Sciences, October 2014, 2, 7-11 pp. 7-11.
  4. Gladie Lui and Connie Shum. Outcome-based education and student learning in managerial accounting in Hong Kong Journal of Case Studies in Accreditation and Assessment pp. 1-13
  5. Sreekanth N V, Arjun CC and Dr. K Guruprasad. Outcome Based Education: Strategies and tools for Indian scenario Journal of Engineering Education Transformations, Special Issue: Jan. 2015, eISSN 2394-1707 pp. 348-352.
  6. Zamri Mohamed, Mohd Yusof Taib, M.S. Reza Assessment Method for Course Outcome and Program Outcome in Outcome Based Education (OBE) Proceedings of MUCET2010 Malaysian Technical Universities Conference on Engineering and Technology June 28-29, 2010 pp. 1-4.
  7. Eitel J.M. Lauría, Joshua D. Baron, Mallika Devireddy,Venniraiselvi Sundararaju, Sandeep M. Jayaprakash, Mining academic data to improve college student retention: An open source perspective LAK’12, 29 April – 2 May 2012, Vancouver, BC, Canada Copyright 2012 ACM 978-1-4503-1111-3/12/04
  8. Eitel J.M. Lauría, Erik W. Moody, Sandeep M. Jayaprakash, Nagamani Jonnalagadda, Joshua D. Baron, Open Academic Analytics Initiative: Initial Research Findings LAK '13, April 08 - 12 2013, Leuven, Belgium Copyright 2013 ACM 978-1-4503-1785-6/13/04
  9. Sandeep M. Jayaprakash, Erik W. Moody, Eitel J.M.Lauría, James R. Regan, and Joshua D. Baron, Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative Journal of Learning Analytics, 1(1), pp 6-47
  10. Sahil P. Karkhanis, Shweta S. Dumbre A Study of Application of Data Mining and Analytics in Education Domain 10.5120/21393-4436
  11. Shweta Tayade, Vinay Chavan, Flexibility Analysis in Business Process Reengineering with Theory of Constraint using Intelligent Dynamic Workflow System. 10.5120/13915-1821, International Journal of Computer Applications, Volume 80 - Number 12
Index Terms

Computer Science
Information Sciences


Outcome based Education (OBE) performance prediction model workflow management academic analytics dynamic change education.