TASK ANALYSIS: BULIDING MODELS OF CHANGE PROCESSES IN GIFTED EDUCATION

Researchers in the field of gifted education are becoming increasingly aware that a variety of research approaches can make contributions to research on giftedness. This paper describes task analysis, a research methodology derived from counseling process research. Task analysis appears to be a useful research approach for building theoretical models of how therapeutic and educational interventions can facilitate positive changes in gifted children. The paper traces the historical development of task analysis methodology, describes the steps involved in conducting a rational‐empirical task analysis of change processes, and provides an example of how task analysis methodology might be applied to investigations of change processes in the field of gifted education.     

Holographic perspective

Although the principle of holography was conceived as long ago as 1947, interest was limited until the advent of the laser in 1960 made possible the off-axis holography widely used today. Since then holography has found many applications and become so well known outside the laboratory as to be a recognized art form. Within the last few years considerable progress has also been made in acoustic holography.     

Concurrent and predictive validity of the WISC-R,McCarthy Scales,Woodcock-Johnson,and academic achievement

Twenty-six normal first-grade children (M = 7.0 years) were administered the WISC-R, the McCarthy Scales, and the Woodcock-Johnson Scales of Cognitive Ability. Two years later, their levels of academic achievement were determined by way of the WRAT and global teacher ratings of classroom performance. Pearson intercorrelations among the summary indices of the three intellectual measures were significant and uniformly high (rang. 77-.95). Correlations between first-grade ability scores and third-grade achievement measures also were significant (range .64-.90), suggesting strong predictive validity for each of the cognitive instruments. Though not significantly so, the correlations between the Woodcock-Johnson and achievement tended to be the highest. The results indicate that all three intellectual measures are appropriate for predicting later academic achievement in young school-aged children.     

Advanced,Analytic, Automated (AAA) Measurement of Engagement During Learning

It is generally acknowledged that engagement plays a critical role in learning. Unfortunately, the study of engagement has been stymied by a lack of valid and efficient measures. We introduce the advanced, analytic, and automated (AAA) approach to measure engagement at fine-grained temporal resolutions. The AAA measurement approach is grounded in embodied theories of cognition and affect, which advocate a close coupling between thought and action. It uses machine-learned computational models to automatically infer mental states associated with engagement (e.g., interest, flow) from machine-readable behavioral and physiological signals (e.g., facial expressions, eye tracking, click-stream data) and from aspects of the environmental context. We present 15 case studies that illustrate the potential of the AAA approach for measuring ensgagement in digital learning environments. We discuss strengths and weaknesses of the AAA approach, concluding that it has significant promise to catalyze engagement research.