Successful computer-based assessments for learning greatly rely on an effective learner modeling approach to analyze learner data and evaluate learner behaviors. In addition to explicit learning performance (i.e., product data), the process data logged by computer-based assessments provide a treasure trove of information about how learners solve…

Valid and reliable teacher ratings serve as the foundation for screening and assessment of youth with behavioral disorders and twin studies offer an opportunity to study those ratings. We conducted a meta-analysis of 15 empirical investigations of aggressive and rule-breaking behavior using teacher ratings in the context of a twin research design.…

The purpose of the present study is to investigate the initial psychometric properties and cultural adaptation of the School Belongingness Scale (SBS) in a sample of Iranian adolescents. Participants included 324 students, ranging in age between 12 and 18 years (M = 14.68, SD = 1.39). Confirmatory factor analysis indicated that responses to the…

Traditionally, students' various educational characteristics are evaluated according to the grades they get or the results of their answers to the scales. There are some limitations in making an evaluation based on the results. The fuzzy logic approach, which tries to eliminate these limitations, has recently been used in the field of education.…

A neurological disorder, along with several behavioral issues, may be to blame for a child's subpar performance in the academic journey (such as anxiety, depression, learning disorders, and irritability). These symptoms can be used to diagnose children with ASD, and supervised machine learning models can help differentiate between ASD traits and…

Background: Relational victimization (RV) is a significant threat to adolescent mental health and social adaptation in China. However, its developmental characteristics during the school transition period are poorly understood. Finkelhor's developmental victimology framework provides a comprehensive lens to explore factors influencing RV's…

There is a collective agreement about the necessity of content knowledge (CK) as a prerequisite for pedagogical content knowledge (PCK). However, most PCK models lack explanatory power because of the missing link between CK and PCK. Thus, the study firstly attempts to develop a theoretical model that consists of knowledge of students' learning…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

This study aimed to enhance understanding of team creativity by investigating the type of team mental models that team members develop during their work on a creative problem solving task. We hypothesized that teams that develop dissimilar team mental models, compared to similar and complementary team mental models, will achieve a higher…

The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…

This article describes how to teach fraction and percentage word problems using a model-drawing strategy. This cognitive strategy places emphasis on explicitly teaching students how to draw a schematic diagram to represent the qualitative relations described in the problem, and how to formulate the solution based on the schematic diagram. The…

The important role that metacognition plays as a predictor for student mathematical learning and for mathematical problem-solving, has been extensively documented. But only recently has attention turned to primary grades, and more research is needed at this level. The goals of this paper are threefold: (1) to present metacognitive framework during…

Metacognition is a powerful predictor for learning performance, and for problem-solving. But how metacognition works for cognitive strategies and learning performance is not clear. The present study was designed to explore how metacognition affected the cognition (learning strategies and problem solving strategies) and different kinds of learning…

This paper discusses investigations in science education addressing the nonlinear dynamical hypothesis. Learning science is a suitable field for applying interdisciplinary research and predominately for testing psychological theories. It was demonstrated that in this area the paradigm of complexity and nonlinear dynamics have offered theoretical…

Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…