Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

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…

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…

Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

This paper presents the empirical basis for the phenomena known as stimulus overselectivity. Stimulus overselectivity involves responding on the basis of a restricted range of elements or features that are discriminative for reinforcement. The manner in which such a response pattern impedes the skill acquisition in children is identified. A…

The purpose of this study was to assess the role of common motor responses as the "speaker" behavior on stimulus class formation,and the emergence of functional classes. Experiment 1 examined whether training one motor response to a set of three stimuli and a second motor response to another set of three stimuli would result in correct…

Despite the recent technical and theoretical advances in the investigation of children's social relations, the inherent complexity of these methods may prevent their easy integration into the classroom. A simple and effective tool can be valuable for teachers who wish to investigate students' social realities in the classroom. Therefore, the…

Using an experimenter-developed system, articles from four school psychology journals for the years 2000-2005 (n = 929) were classified. Results showed that 40% of the articles were narrative, 29% correlational, 16% descriptive, 8% causal-experimental, 4% causal-comparative, and 2% were meta-analytic. Further analysis of the causal-experimental…

Generally recognized as the standard work in its field, "Behavioral, Social, and Emotional Assessment of Children and Adolescents" provides a comprehensive foundation and guide for conducting conceptually sound, culturally responsive, and ecologically oriented assessments of student social and emotional behavior. It is aimed at graduate…

This study explored the ability of Systematically Progressive Assessment (SPA), a multiple gating approach for assessing students with attention-deficit/hyperactivity disorder (ADHD), to discriminate between subtypes of ADHD. A total of 48 students with ADHD (ages 6-11) were evaluated with three "gates" of assessment. Logistic regression analysis…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

Describes the SOLO Taxonomy, a five-level hierarchy designed to help teachers evaluate the quality of students' thinking. Illustrates how the taxonomy may be used to construct questions and score responses to test questions. Concludes that the taxonomy has broad curriculum applicability and can make a substantial contribution to improved teaching…

This explorative data mining project used distance based clustering algorithm to study 3 indicators, called OIndex, of student behavioral data and stabilized at a 6-cluster scenario following an exhaustive explorative study of 4, 5, and 6 cluster scenarios produced by K-Means and TwoStep algorithms. Using principles in data mining, the study…