In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides space and makes time for online learning; though teachers cannot control the learners accurately, the state of education calculates learners' learning situation. This paper explains that the discourse…

E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…

Since MOOC is suffering high dropout rate, researchers try to explore the reasons and mitigate it. Focusing on this task, we employ a composite model to infer behaviors of learners in the coming weeks based on his/her history log of learning activities, including interaction with video lectures, participation in discussion forum, and performance…

Cyber-bullying has become increasingly problematic in academic settings including universities and colleges. The bullying literature has been expanding investigation of the bully behaviors and has identified four bully types to include pure offender, pure victim, offender and victim, neither-offender-nor-victim. The majority of research has…

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…

This article describes the ICAP framework that defines cognitive engagement activities on the basis of students' overt behaviors and proposes that engagement behaviors can be categorized and differentiated into one of four modes: "Interactive," "Constructive," "Active," and "Passive." The ICAP hypothesis…

In this study, through the observation of mathematically promising students in regular classrooms, relevant learning environments and the learning needs of promising students, teacher approaches and teaching methods, and the differences between the promising students and their normal ability peers in the same classroom were investigated.…

Background: Youth diagnosed with autism spectrum disorders (ASD) often show deficits in cognitive control processes, potentially contributing to characteristic difficulties monitoring and regulating behavior. Modification of performance following conflict can be measured by examining conflict adaptation, the adjustment of cognitive resources based…

Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…

The purpose of this study was to examine the behavioral and demographic characteristics of deaf males enrolled at state school for the Deaf. An analysis of student, family, and educational variables was conducted in order to provide a composite description of both the type and frequency of the offenses and of the offender. Participants were 90…

A modern clustering technique was applied to age-10 and age-13 sociometric data with the purpose of identifying longitudinally stable peer status clusters. The study included 445 girls from a Swedish longitudinal study. The identified temporally stable clusters of rejected, popular, and average girls were essentially larger than corresponding…

Emergent reading attempts of 24 children at the beginning of their kindergarten year are content analyzed in light of theoretical considerations about general and language development. In addition, the reading attempts of two-, three-, and four-year olds are examined. Comparison of data reveal a developmental progress across age-levels. (HOD)

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…