Recommender System for Low Achievers in Higher Education

Abstract

Digital education platforms like learning management systems (LMS) have made the virtual teaching-learning process very much handy. The LMS must include additional features to track and review the learner’s behavior in the teaching-learning process. This study aims to identify the low achievers with the assessment marks which let the course instructors understand the learner’s cognitive level and enables the facilitators to recognize the student’s perspective of the course based on their reviews collected from the questionnaire. In the outcome, recommender systems are incorporated with the learning analytics by using the K-Means clustering algorithm. This algorithm has helped the facilitators to segregate and identify the set of low achievers based on their assessment scores and also to predict the appropriate reason behind such slow performance. Apart from this, the results of this study have also suggested that facilitators incorporate the use of various emerging pedagogical methods in the teaching-learning process to maximize the learner’s performance and accentuate the level of virtual classrooms.

Developing Canva-Based Learning Media on Maps and Class Layout for Third Graders of Elementary School

“…Canva for Education is a highly interactive and user-friendly digital tool designed to enhance the learning experience for primary students (Wilkinson et al, 2019). It provides a platform where educators can create engaging and visually appealing educational content, such as presentations, infographics, worksheets, and more, tailored specifically to younger students' needs and learning styles (Maiti & Priyaadharshini, 2022). This tool is particularly effective in primary education due to its simplicity and emphasis on visual learning, which aligns well with the developmental stage of primary-aged learners (Frumkina et al, 2020).…”