Outcome-Based Quality Assessment Framework for Higher Education
📝 Abstract
This research paper proposes a quality framework for higher education that evaluates the performance of institutions on the basis of performance of outgoing students. Literature was surveyed to evaluate existing quality frameworks and develop a framework that provides insights on an unexplored dimension of quality. In order to implement and test the framework, cloud-based big data technology, BigQuery, was used with R to perform analytics. It was found that how the students fair after passing out of a course is the outcome of educational process. This aspect can also be used as a quality metric for performance evaluation and management of educational organizations. However, it has not been taken into account in existing research. The lack of an integrated data collection system and rich datasets for educational intelligence applications, are some of the limitations that plague this area of research. Educational organizations are responsible for the performance of their students even after they complete their course. The inclusion of this dimension to quality assessment shall allow evaluation of educational institutions on these grounds. Assurance of this quality dimension shall boost enrolments in postgraduate and research degrees. Moreover, educational institutions will be motivated to groom students for placements or higher studies.
💡 Analysis
This research paper proposes a quality framework for higher education that evaluates the performance of institutions on the basis of performance of outgoing students. Literature was surveyed to evaluate existing quality frameworks and develop a framework that provides insights on an unexplored dimension of quality. In order to implement and test the framework, cloud-based big data technology, BigQuery, was used with R to perform analytics. It was found that how the students fair after passing out of a course is the outcome of educational process. This aspect can also be used as a quality metric for performance evaluation and management of educational organizations. However, it has not been taken into account in existing research. The lack of an integrated data collection system and rich datasets for educational intelligence applications, are some of the limitations that plague this area of research. Educational organizations are responsible for the performance of their students even after they complete their course. The inclusion of this dimension to quality assessment shall allow evaluation of educational institutions on these grounds. Assurance of this quality dimension shall boost enrolments in postgraduate and research degrees. Moreover, educational institutions will be motivated to groom students for placements or higher studies.
📄 Content
Outcome-Based Quality Assessment Framework for Higher Education
Samiya Khan1, Mansaf Alam2
Department of Computer Science, Jamia Millia Islamia, New Delhi
1samiyashaukat@yahoo.com, 2malam2@jmi.ac.in
Samiya Khan has received her Bachelor’s degree in Electronics and a Master’s degree in
Informatics from Delhi University. She is currently pursuing her doctoral studies in Computer
Science from Jamia Millia Islamia (A Central University). Her area of interest includes cloud-
based big data analytics, virtualization and data-intensive computing.
Mansaf Alam received his doctoral degree in Computer Science from Jamia Millia Islamia,
New Delhi in 2009. He is currently working as an Assistant Professor at the Department of
Computer Science, Jamia Millia Islamia. He is the Editor-in-Chief, Journal of Applied
Information Science. He is in Editorial Board of reputed International Journals in Computer
Sciences and has published several research papers. He has also authored two books entitled
“Concepts of Multimedia” and “Digital Logic design”. His areas of research include Cloud
database management system (CDBMS), Object Oriented Database System (OODBMS),
Genetic Programming, Bioinformatics, Image Processing, Information Retrieval and Data
Mining.
Outcome-Based Quality Assessment Framework for Higher Education
This research paper proposes a quality framework for higher education that
evaluates the performance of institutions on the basis of performance of outgoing
students. Literature was surveyed to evaluate existing quality frameworks and
develop a framework that provides insights on an unexplored dimension of
quality. In order to implement and test the framework, cloud-based big data
technology (BigQuery) was used with R to perform analytics. It was found that
how the students fair after passing out of a course is the ‘outcome’ of educational
process. This aspect can also be used as a quality metric for performance
evaluation and management of educational organizations. However, it has not
been taken into account in existing research. The lack of an integrated data
collection system and rich datasets for educational intelligence applications, are
some of the limitations that plague this area of research. Educational
organizations are responsible for the performance of their students even after they
complete their course. The inclusion of this dimension to quality assessment shall
allow evaluation of educational institutions on these grounds. Assurance of this
quality dimension shall boost enrolments in postgraduate and research degrees.
Moreover, educational institutions will be motivated to groom students for
placements or higher studies.
Keywords: Quality in education; Educational intelligence; Higher education
Introduction
Higher education is the backbone of the education system of any country. Effective
management and quality assessment of the higher education system is not just
important, but it is also necessary. However, quality assurance is usually not achieved in
higher education systems because of several obstacles (Cardoso et al. 2015). The
concept of quality in higher education has found varied definitions and descriptions in
literature. The most recent and widely accepted definition of quality describes it as
conformance of standards and meeting the set objectives. None of the dimensions
covered the outcomes-based perspective of the education system.
The proposed framework evaluates quality from the perspective of how a student who
passes out of an organization fairs after completion of the degree. This is assessed using
the information about the university or company that student joins after course
completion. Quality score is computed using this information and analytics are
generated on the basis of the cumulative study of these quality scores.
The analytical framework proposed in this paper can be used for evaluating the
performance of an educational organization on the basis of the cumulative quality
scores’ analysis of the students who pass out in a year. Moreover, predictive analysis
can also be generated to monitor progress and make interventions as and when required,
to maintain quality of the educational organizations and system, at large.
There are several ways in which such a quality metric may be relevant. Quality
improvement approaches must be oriented with accountability (Boyle and Bowden
2006). Most quality metrics assume that the responsibility of an educational institution
for a student’s performance is restricted to the time that the student concerned spends
enrolled in the institution. However, the responsibility of the student’s performance on
his or her alma mater extends beyond this timeframe. This is perhaps the reason why
organizations take pride in their alumni networks and achievers who hail from their
institutes. Therefore, a quality evaluation basis that assesses the organization’s
performance on the basi
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