Fostering creative performance in art and design education via self-regulated learning

Instructional Science - There is a lack of research and practice focused on how to foster higher-order processing, such as creative performance, within higher education settings. To address this...     

A Model for the Behavioural Assessment of Developmentally Handicapped Children

This paper describes a model for assessing young children who have developmental handicaps. The design and implementation of instructional programs are presented as integral components of assessment. The involvement of parents and teachers in all aspects of assessment is a feature of the model, which also stresses evaluation of the physical and social contexts of child behaviour, and suggests long term evaluation of both the intended and unanticipated effects of intervention.     

Structural Equations and Causal Explanations: Some Challenges for Causal SEM

One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete explanations or partial explanations. Moreover, it remains unclear what sorts of things researchers can best take as causes and effects. Finally, the meaning of causal assertions itself remains poorly understood. Attempting to clarify the use of structural equations as causal explanations by addressing these issues has implications for behavioral science methodology because applications of SEM typically remain vague about causation and thus about their substantive conclusions. Research aimed at clarifying these issues can lead to a sharper and more refined use of SEM for causal explanation, and by extension, clarify behavioral science methodology more generally.     

Is Peer Interaction Necessary for Optimal Active Learning?

Meta-analyses of active-learning research consistently show that active-learning techniques result in greater student performance than traditional lecture-based courses. However, some individual studies show no effect of active-learning interventions. This may be due to inexperienced implementation of active learning. To minimize the effect of inexperience, we should try to provide more explicit implementation recommendations based on research into the key components of effective active learning. We investigated the optimal implementation of active-learning exercises within a “lecture” course. Two sections of nonmajors biology were taught by the same instructor, in the same semester, using the same instructional materials and assessments. Students in one section completed in-class active-learning exercises in cooperative groups, while students in the other section completed the same activities individually. Performance on low-level, multiple-choice assessments was not significantly different between sections. However, students who worked in cooperative groups on the in-class activities significantly outperformed students who completed the activities individually on the higher-level, extended-response questions. Our results provide additional evidence that group processing of activities should be the recommended mode of implementation for in-class active-learning exercises.