Predicting the Academic Performance of Students Using Utility-Based Data Mining

Data mining in education has become an important topic in the sphere of influence of data mining. Mining educational data encompasses developing models, plotting data, and utilizing machine learning algorithms to derive patterns on educational data by attempting to uncover hidden patterns, create information for hidden relationships using educational statistics, and perform many more operations that are unfeasible using traditional computational tools. This research aims to identify the main factors that influence the academic performance of learners in tertiary education system in Sri Lanka. A conceptual framework and an analytical framework on factors affecting the academic performance was constructed with this aim. The analytical framework was then validated with the data collected from technology learners in a tertiary educational institute.

Towards Increasing the Efficiency of E-Learning Systems Using Recommendation System Approach

Data mining approaches have been tried in e-learning systems for information optimization and knowledge extraction to make decisions. In recent years, the recommendation system has gained popularity in every field be it e-commerce, entertainment, sports, healthcare, news, etc. However, in e-learning system, the recommender systems were not effectively utilized in comparison to other domains and thus emerged as a bottleneck for almost all e-learning systems for not offering flexible delivery of the learning resources. Current e-learning systems lack personalization features, and the information is presented in a static way despite their varying learning objectives and needs. The aim of recommender system is to personalize the information with respect to learner interest. The objective of this study is to highlight various algorithmic techniques that can be used to improve information retrieval process to provide effective recommendations to learners for improving their performance and satisfaction level.

Intelligent Tutoring System

With digitization, a rapid growth is seen in educational technology. Different formal and informal learning contents are available on the internet. Intelligent tutoring system provides personalized e-learning to the learners. Different attributes like historical data, real-time data, behavioral, and cognitive are usually used for personalization. Based on the personalization, the intelligent tutoring system aims to provide easy and effective understanding. Recent research highlights the effect of learner's behavior and emotions on effective teaching-learning process. This chapter provides a brief description of the intelligent tutoring system, current developments, instructional techniques, proposed solution, and future recommendations. The emphasis of the study is to provide insights on self-regulated learning.

Improvement of the Transmission of Information for ICT Techniques Through CBEDE Methodology

There is no single and universal definition for ICT (information and communication technology). The term is normally adopted to all devices, networking components, applications, and systems that allow combined people, companies, and organizations (i.e., businesses, nonprofit agencies, governments, and enterprises) to interact in the digital world, the modern era. In this digitally globalized world, we deal with a huge set of data all the time. Data refers to facts, events, actions, activities, and transactions which have been and can be recorded (i.e., the raw material from which information is produced), nurturing the infrastructure and components that enable modern computing. Based on this, the present study aims to implement a discrete events-based model with advanced modulation format DQPSK in a simulation environment, the Simulink of MATLAB software, aiming to improve the transmission of information in communication systems. The results show better computational performance related to memory utilization related to compression of the information, showing an improvement of up to 92.6%.

Role of Information and Communication Technologies in Transforming Teaching and Learning Environments

No aspect of human life has remained untouched by information and communication technologies (ICT) at present. Various forms of media like radio, computers, televisions, computers, etc. keep on surrounding us right from the moment we wake up in the morning till we go to bed at night. The electronic media, which have become an inseparable part of our daily lives, fall under the umbrella of a single entity known as ICT. As the society has moved one step ahead from being information society to acquiring the status of knowledge society, the knowledge and use of ICT tools has become even more important. ICT has a deep impact on every sphere of human life and education is no exception. Use of information communication technologies has promoted drastic changes in work environment, transformed the ways of handling and exchanging information, and has an everlasting impact on teaching-learning pedagogy. This chapter presents the role of ICT transforming the teaching and learning environments. The limitation of ICT and the challenges in implementation have also been discussed.

Data Mining in Global Higher Education

Historically, educators in higher education have searched for reliable means and methods to increase student learning. Many techniques and strategies have been used and even some have taken the form of laws to incorporate certain approaches to learning. However, there has not been one method proved effective in all situations for all students. One of the biggest challenges that global educational institutions face is the explosive growth of educational data and how to use this data to improve the quality of instructional and managerial decisions. Global higher education leaders embraced data-driven practices as an opportunity to improve efficiency, objectivity, transparency, and innovation. As a result, global higher education institutions are producing a large amount of student related data every year. Technology has given educators in higher education access to methods for assessing learning and engagement. Educational data mining is a relatively new process in global higher education that provides a tool to analyze this data and extract valuable information.