A Framework for Evaluating Distance Learning of Environmental Science in Higher Education using Multi-Criteria Group Decision Making - Kabassi, Katerina (Informatica, 2023)
Purpose: Due to Covid-19, big changes took place in Universities around the world. Universities were asked in March 2020 within a short while to provide the whole of the available lessons using e-Learning methods. Since the health crisis continues, e-learning has expanded on a variety of contexts and simultaneously has created an urgent need for designing, developing, and implementing a valid and reliable distance learning procedure. The validity and efficiency of the aforementioned procedure is a major issue that has to be tested at the end of the semester. Therefore, developing a valid framework to evaluate the e-learning process has become more important now than in the past due to the ongoing pandemic. Design/methodology/approach: The evaluation of the educational process is a multi-criteria problem that is based on the points of view of both instructors and students. In order to solve this multi-criteria problem of e-learning evaluation, a new framework for evaluating e-Learning in Higher Education has been developed. This framework uses group decision making with multiple criteria and is called ENVEL. This paper defines the set of evaluation criteria and uses the Fuzzy Analytic Hierarchy Process to prioritize criteria and help the decision-makers draw conclusions on the effectiveness and success of e-learning. Findings: The framework takes into account heterogeneous groups of students and professors, makes different calculations for these groups, and can extract useful conclusions by comparing the results of the different groups. The framework has been applied in the Department of Environmental Science at the Ionian University and conclusions have been made on its effectiveness and usage. Originality: Trying to focus on the evaluation of e-learning in a whole study program in Higher Education, and not only on single courses, the paper describes a novel framework for e-learning evaluation using multi-criteria decision making with heterogeneous groups of users. This framework provides a formal way of combining different aspects of the evaluation of e-learning and collect summative results.