This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…

The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…

Federal regulations indicate that the achievement gap must be closed between subgroups, including the gap between special education and non-special education students. We explored the ways in which achievement trends are influenced by three methods of reporting (cross-sectional, cohort-static, and cohort-dynamic). We also investigated (a) the ways…

In this study we set out to investigate the errors made by students in logarithms. A test with 16 items was administered to 89 Secondary three students (Year 9). The errors made by the students were categorized using four categories from a framework by Movshovitz-Hadar, Zaslavsky, and Inbar (1987). It was found that students in the top third were…

Researchers often presume that it is better to use administrative data from grades 4 and 5 than data from grades 6 through 8 for conducting research on teacher effectiveness that uses value-added models because (1) elementary school teachers teach all subjects to their students in self-contained classrooms and (2) classrooms are more homogenous at…

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 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

This article describes a qualitative research study that explored how a middle school case-study class read and responded to "culturally conscious" African American children's books (Sims, 1982, p. 49). First, I relied on literary analyses conducted mainly by Sims (1982) and Harris (1995) to identify African American textual features contained in…

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…