Rana Hammad Hassan

Work place: School of Systems and Technology, University of Management and Technology, Lahore – Pakistan

E-mail: rana_hammad@live.com


Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Data Structures and Algorithms


Rana Hammad Hassan is student of Ph.D. Computer Sciences in University of Management & Technology, Lahore Pakistan. His research focus includes Big Data, Data Analytics and Machine Learnings. He has 15+ years industry experience and currently working as Manager Management Information Systems with Punjab Vocational Training Council, Lahore Paksitan. He is the winner of Intel Education Award 2010-2011 for Punjab – Pakistan initaives. He is member of Technical Advisory Group (TAG) of National Skills Information System (NSIS) of Pakistan. He is certified as Oracle Certified Expert Consultant, Microsoft Certified Solution Developer, LRQA Quality Management System Internal Auditor. He is trained for PMP, CCNA, OCP-DBA and JAVA applications

Author Articles
Identification of Trainees Enrollment Behavior and Course Selection Variables in Technical and Vocational Education Training (TVET) Program Using Education Data Mining

By Rana Hammad Hassan Shahid Mahmood Awan

DOI: https://doi.org/10.5815/ijmecs.2019.10.02, Pub. Date: 8 Oct. 2019

Producing skilled workforce according to industry required skills is quite challenging. Knowledge of trainee’s enrollment behavior and trainee’s course selection variables can help to address this issue. Prior knowledge of both can help to plan and target right geographic locations and right audience to produce industry required skilled workforce. Globally Technical and Vocational Education Training (TVET) is used to provide skilled workforce for the industry. TVET is an educational stream which focus learning through more practicing with less theory knowledge.
In this article, we have analyzed TVET actual enrollment data of 2017 – 2018 session from a TVET training provider organization of Punjab, Pakistan. The purpose of this analysis is to understand trainee’s enrollment behavior and course selection variables which plays an important role in TVET course selection by the trainees. This enrollment behavior and course selection variables can be used to monitor and control industry required and produced skilled TVET workforce. We developed a framework which contain series of steps to perform this analysis to extract knowledge. We used educational data mining techniques of association, clustering and classification to extract knowledge. The analysis reveals that central Punjab youth is getting more TVET education as compare to south and north Punjab, Pakistan. Similarly, trainee’s ‘age group’, ‘qualification’, ‘gender’, ‘religion’ and ‘marital status’ are potential variables which can play important role in TVET course selection. By controlling these variables and integrating TVET training provider institutes, funding agencies and industry, we can smartly produce TVET skilled workforce required for industry nationally and internationally.

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