Smart Rubric-based Systematic Model for Evaluating and Prioritizing Academic Practices to Enhance the Education Outcomes

Abstract

Recently, the impact of free-market economy, globalization, and knowledge economy has become a challenging and focal to higher educational institutions, which resulted in radical change. Therefore, it became mandatory for the academic programs to prepare highly qualified graduates to meet the new challenges, through the implementation of well-defined academic standards. For this reason, the National Center for Academic Accreditation & Evaluation (NCAAA) in Kingdom of Saudi Arabia (KSA) defined a set of standards to ensure that quality of education in KSA is equivalent to the highest international standards. NCAAA standards contains of good criterions to guide the universities in evaluating their quality performance for improvement and obtain NCAAA accreditation. However, implementing NCAAA standards without supportive systems has been found to be a very complex task due to the existence of a large number of standard criterions, evaluation process occurs according to personal opinions, the lack of quality evaluation expertise, and manual calculation. This, in turn, leads to inaccurate evaluation, develops inaccurate improvement plans, and difficulty in obtaining NCAAA accreditation. Therefore, this paper introduces a systematic model that contain smart-rubrics that has been designed based on NCAAA quality performance evaluation elements supported with algorithms and mathematical models to reduce personal opinions, provide an accurate auto-evaluation, and auto-prioritization action plans for NCAAA standards. The proposed model will support academics and administrative by facilitating their NCAAA quality tasks with ease, an authenticate self-assessment, accurate action plans and simplifying accreditation tasks. Finally, the implementation of the model proved to have very efficient and effective results in supporting KSA education institution in accreditation tasks that will lead to enhance the quality of education and to obtain NCAAA accreditation.

Authors and Affiliations

Mohammed Al-Shargabi

Keywords

Related Articles

 Annotations, Collaborative Tagging, and Searching Mathematics in E-Learning

 This paper presents a new framework for adding semantics into e-learning system. The proposed approach relies on two principles. The first principle is the automatic addition of semantic information when creating t...

Performance Measurement Model of Mobile User Connectivity in Femtocell/Macrocell Networks using Fractional Frequency Re-use Scheme

Technologies are traversing to its new dimensions every day. As part of this progression, mobile cellular system is at the summit of its constant advancement. The usage of Femtocells in mobile cellular system has created...

Model Driven Development Transformations using Inductive Logic Programming

Model transformation by example is a novel approach in model-driven software engineering. The rationale behind the approach is to derive transformation rules from an initial set of interrelated source and target models;...

Design and Modeling of RF Power Amplifiers with Radial Basis Function Artificial Neural Networks

A radial basis function (RBF) artificial neural network model for a designed high efficiency radio frequency class-F power amplifier (PA) is presented in this paper. The presented amplifier is designed at 1.8 GHz operati...

Detecting and Classifying Crimes from Arabic Twitter Posts using Text Mining Techniques

Crime analysis has become a critical area for helping law enforcement agencies to protect civilians. As a result of a rapidly increasing population, crime rates have increased dramatically, and appropriate analysis has b...

Download PDF file
  • EP ID EP626588
  • DOI 10.14569/IJACSA.2019.0100818
  • Views 93
  • Downloads 0

How To Cite

Mohammed Al-Shargabi (2019). Smart Rubric-based Systematic Model for Evaluating and Prioritizing Academic Practices to Enhance the Education Outcomes. International Journal of Advanced Computer Science & Applications, 10(8), 133-141. https://europub.co.uk/articles/-A-626588