Exploring Factors and Indicators for Measuring Students’ Performance in Moodle Learning Environment

Iman Rashid Al-Kindi,Zuhoor Al-Khanjari

doi:10.3991/ijet.v16i12.22049

Abstract

One of the most important pillars of smart cities is the smart learning environ-ment. This environment should be well prepared and managed to improve the in-struction process for instructors from one side and the learning process for stu-dents from the other side. This paper presents the student’s Engagement, Behav-ior and Personality (EBP) predictive model. This model uses Moodle log data to investigate the influence and the effect of the students’ EBP factors on their per-formance. For this purpose, this paper uses the data log files of the "Search Strat-egies on the Internet" online course in Fall 2019 at Sultan Qaboos University (SQU) extracted from Moodle database. The intention of conducting this kind of experiments is of three-facets: 1. to assist in gaining a holistic understanding of online learning environments by focusing on student EBP and performance with-in the course activities, 2. to explore whether the student’s EBP can be considered as indicators for predicting student’s performance in online courses, and 3. to support instructors with insights to develop better learning strategies and tailor instructions for personal learning of individual students. Moreover, this paper takes a step forward in identifying effective methods to measure student’s EBP during the learning process. This may contribute to proposing a framework for the smart learning behavior environment that would guide the instructors to ob-serve students’ performance in a more creative way. All the 38 students who participated in this experiment had compatible statistics and results as the relationship between their Engagement, Behavior, Personality was symmetric with their Performance. This relationship was presented using a group of condition rules (If-then). The extracted rules gave us a straightforward and visual picture of the rela-tionship between the factors mentioned in this paper.

Highlights

Successful learning involves motivation for the students to achieve the learning objectives they want [1]
Dividing the numerical data into categories in this work is based on the percentiles approach. It is based on dividing the data into unequal intervals, but each interval points to a specific category
Building a smart learning environment is the basis for reforming instruction and learning practices

Summary

Introduction

Successful learning involves motivation for the students to achieve the learning objectives they want [1]. Through the provision of information on engagement, behaviors of learning, personality and performance of every student would assist the instructors in adjusting instruction techniques and taking any necessary precautions to enhance learning environments. There is no doubt that students are considered as a significant factor in all processes of learning. In the current Moodle environment, no enough attention given to the student's engagement, behavior and personality, together with their performance. The acronym "Modular Object-Oriented Dynamic Learning Environment" stands for Moodle. Sultan Qaboos University (SQU) uses Moodle in the teaching and learning process besides face to face learning. Both students and instructors can access Moodle using their login credentials (SQU username and password)

Objectives

Methods

Discussion

Conclusion