Predicting Student Performance in Higher Educational Institutions Using Video Learning Analytics and Data Mining Techniques

Raza Hasan,Kamal Uddin Sarker,Mian Usman Sattar,Sellappan Palaniappan,Ali Abbas,Salman Mahmood

doi:10.3390/app10113894

Abstract

Technology and innovation empower higher educational institutions (HEI) to use different types of learning systems—video learning is one such system. Analyzing the footprints left behind from these online interactions is useful for understanding the effectiveness of this kind of learning. Video-based learning with flipped teaching can help improve student’s academic performance. This study was carried out with 772 examples of students registered in e-commerce and e-commerce technologies modules at an HEI. The study aimed to predict student’s overall performance at the end of the semester using video learning analytics and data mining techniques. Data from the student information system, learning management system and mobile applications were analyzed using eight different classification algorithms. Furthermore, data transformation and preprocessing techniques were carried out to reduce the features. Moreover, genetic search and principle component analysis were carried out to further reduce the features. Additionally, the CN2 Rule Inducer and multivariate projection can be used to assist faculty in interpreting the rules to gain insights into student interactions. The results showed that Random Forest accurately predicted successful students at the end of the class with an accuracy of 88.3% with an equal width and information gain ratio.

Highlights

Digitalization has infiltrated into every aspect of life
A supervised data classification technique was used to determine the best prediction model that fit the requirements for giving an optimal result
A supervised data classification model is proposed with the aim of predicting student academic performance at the end of the semester

Summary

Introduction

Digitalization has infiltrated into every aspect of life. Emerging new technologies have an impact on our lives and change the way we do our daily work, raising our performance to a new height. The technology used in education has allowed educators to implement new theories to enhance the teaching and learning process. This shift from “traditional learning” has led to a model in which learning can take place outside the classroom, facilitating different learner attributes such as visual, verbal, aural and solitary learning within the “blended learning” approach [1]. Educators use innovative technologies to cater to different learners with blended learning, and learners can use these technologies to improve their cognitive abilities to excel in the courses being taught [2]. Webinars, links, simulations or any other online mechanism to deliver the information [3]

Results

Discussion

Conclusion