Student academic performance prediction is a significant area of study in the realm of education that has drawn the interest and investigation of numerous scholars. The current approaches for student academic performance prediction mainly rely on the educational information provided by educational system, ignoring the information on students'…

The COVID-19 pandemic induced a digital transformation of education and inspired both instructors and learners to adopt and leverage technology for learning. This led to online learning becoming an important component of the new normal, with home-based virtual learning an essential aspect for learners on various levels. This, in turn, has caused…

Identifying students facing difficulties and providing them with timely support is one of the educator's key responsibilities. Yet, this task is becoming increasingly challenging as the complexity of physical learning spaces grows, along with the emergence of novel educational technologies and classroom designs. There has been substantial research…

Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the…

The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to…

In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…

Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…

Schools have poor reputation among creativity researchers. Teachers' biases and implicit theories, disruptive behaviors among creative students, and the equivocal pattern of the relationship between creativity and school achievement all contribute to this fact. This chapter presents a new typological model of creativity and demonstrate how this…

The increasing use of the Learning Management Systems (LMSs) is making available an ever-growing, volume of data from interactions between teachers and students. This study aimed to develop a model capable of predicting students' academic performance based on indicators of their self-regulated behavior in LMSs. To accomplish this goal, the authors…

Researchers are concerned that English language learners (ELL) may remain classified too long and, therefore, may not receive appropriate mainstream educational services. In this study, we investigate the effects of language classification on student outcomes in one California school district. Our ordinary least squares regression estimates…

The present study used the 2009-2010 sample of the Health Behavior in School-Aged Children Survey (N = 12,642) to investigate the incremental validity of four competing bullying involvement classification schemas, which differ as a function of relative rates of endorsing victimization and perpetration behaviors at school: the standard four-group…

To describe and facilitate the identification of child school behavior patterns, we developed a typology of child school behavior (ages 6-11 years) using the norming data (N = 2,338) for the second edition of the Behavior Assessment System for Children Teacher Rating-Child form). Latent profile analysis was conducted with the entire data set,…

The problem of student final grade prediction in a particular course has recently been addressed using data mining techniques. In this paper, we present two different approaches solving this task. Both approaches are validated on 138 courses which were offered to students of the Faculty of Informatics of Masaryk University between the years of…

Classification changes are common in special education. Using the first four years of the Pre-elementary Education Longitudinal Study data set (N = 3000), we investigated national trends in classification changes among young children with disabilities, the relationship between classification changes and children's demographic information, and the…

In recent years there has been a proliferation of massive open online courses (MOOCs), which provide unprecedented opportunities for lifelong learning. Registrants approach these courses with a variety of motivations for participation. Characterizing the different types of participation in MOOCs is fundamental in order to be able to better…