Because of the need to provide fine-grained longitudinal diagnostic feedback, longitudinal cognitive diagnosis is an emerging approach that integrates cross-sectional cognitive diagnosis models (CDM) with longitudinal data analysis techniques. By adopting the generalized longitudinal higher-order log-linear CDM, this study attempted to track the…

The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, especially in mathematics, is a well-established and proven approach in learning analytics. In this work, we report on our analysis examining the generalizability of BKT models across academic years attributed to "detector rot." We compare the…

In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…

Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes:…

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…

Research suggests that students put more effort into language learning when they feel that it is a voluntary and self-relevant activity or they enjoy the process of mastering that language (i.e., they have a more self-determined orientation). This orientation is fostered when learners feel autonomous, competent, and related to others in their…

Achievement goal orientations are important for students' ongoing motivation. Students with a mastery goal orientation show the most advantageous achievement and motivational patterns. Much research has been conducted to identify classroom structures which promote students' mastery goal orientation. The TARGET framework is one example of these…

Background/Context: Despite decades of research, the persistence of the gap in student achievement between disadvantaged minority students and their middle-class peers remains unexplained. Purpose/Objective: The purpose of the current article is to propose a new model of the achievement gap. Research Design: Data were analyzed from three…

Research suggests that motivated students and those with high academic self-concepts perform better academically. Although substantial evidence supports a reciprocal relation between academic self-concept and achievement, there is less evidence supporting a similar relation between achievement goal orientations and achievement. There is also a…

Background: Research has shown that both achievement goal theory and self-determination theory (SDT) are quite useful in explaining student motivation and success in academic contexts. However, little is known about how the two theories relate to each other. Aim: The current research used SDT as a framework to understand why students enter classes…

Adopts a longitudinal design to track mother-child developmental change in infant task-related mastery and concomitant maternal behavior. Finds that, as infants gain more mastery across time, mothers gradually withdraw support in terms of concrete, specific and nonverbal means of instruction. Results support a one-step-ahead model for maternal…