The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

A course-level early final study status prediction task is to predict as soon as possible the final success of each student after studying a course. It is significant because each successful course accomplishment is required for a degree. Further, early predictions provide enough time to make necessary changes for ultimate success. This article…

Governments and educational authorities around the world are emphasizing performance evaluation of educational systems. Opinion Mining (OM) has gained acceptance among experts in various regions, including the preparation space. The proposed model involves Two modules: the data preprocessing module and the opinion mining module. The main objective…

The recently increased importance of practicing precision education has attracted much attention. To better understand students' learning and the relationship between their individual differences and learning outcomes, the bird-eye view possible for educational policymakers and stakeholders from educational data mining and institutional research…

The flow experience (i.e., challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration, sense of control, loss of self-consciousness, transformation of time, and "autotelic" experience) is an experience highly related to the learning experience. One of the current challenges is to identify whether…

Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…

Workforce planning is prevalent and recognized as a good strategic practice in many organizations. However, business students may have little experience with workforce planning or workforce analytics. The purpose of this article is to present a workforce planning exercise for use in a face-to-face or online classroom setting. In this exercise,…

In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we…

As we become increasingly acquainted with the rich opportunities that analytics systems can provide, there is a commensurate need to consider the extent to which analytics tools are effectively integrated, with proper training, into the day-to-day functioning of higher education professionals. This chapter explores the extent to which predictive…

Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in prior courses), the task of student's performance prediction is to predict a student's grades in future…

Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…

The academic performance of a student in a university is determined by a number of factors, both academic and non-academic. Student that previously excelled at the secondary school level may lose focus due to peer pressure and social lifestyle while those who previously struggled due to family distractions may be able to focus away from home, and…

In the world of technology, tools and gadgets, a huge amount of data is produced every second in applications ranging from medical science, education, business, agriculture, economics, retail and telecom. Higher education institutes play an important role in the overall development of any nation. For the successful operation of these institutions,…

In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…