Abstract:

Distance education is a challenging endeavor. The last few years especially with the COVID pandemic, distance education became the norm. The following years, returning to the everyday life, distance education remained as an established methodology and approach for teaching and learning. It is also true that this online approach is based on various aspects and parameters that need to be considered and evaluated in order to increase its efficiency. In the core of the specific e-learning process are located students and instructors. One of the challenges associated with this online teaching and learning experience is to create optimum groups of students and assign them to the proper instructors. The goal is to maximize the educational performance and satisfy both students and instructors. There are many techniques originating from various fields of studies and operations to match people. The current paper provides an extensive literature review focusing on matching techniques with emphasis on distance education. Investigation on relevant tools and approaches has covered all years until 2023. A number of papers were identified and a corresponding relevant database was organized in Mendeley. This database included 167 documents. The findings reveal that a plethora of mathematical models and techniques have been widely implemented in order to facilitate organizational issues in education in general and in distance education with emphasis in matching students togethers, or assigning students to courses and instructors. Furthermore, a bibliometric analysis has taken place, through the use of VOS-viewer, and identified fundamentals concepts that are associated with the development and evolution of matching techniques with emphasis in education. Terms that were identified during the analysis included but were not limited to Heuristics, Decision Support Systems and Set Partitioning.

Keywords:

Matching Approaches, Education, Distance Education, Teaching, Learning.