Daniel Stanhope

Core self-evaluations and training effectiveness: : Prediction through motivational intervening mechanisms.

Understanding the processes through which trainee characteristics influence learning is important for identifying mechanisms that drive training effectiveness. We examine the direct and indirect paths through which core self-evaluations (CSE) impact learning. We also include general cognitive ability (GCA) to explore whether CSEs paths to effectiveness differ from those of a well-documented predictor of learning. We proposed a model in which CSE contributes to training effectiveness through its influence on motivational intervening mechanisms, and we tested this model empirically with military personnel (N = 638) who participated in job-required training. The data supported a partially mediated model. Irrespective of inclusion of GCA as a control variable, motivation and effort allocation (MEA) process variables (i.e., training motivation, midtraining self-efficacy, and midtraining goal setting) mediated (or partially mediated) the relationship between CSE and training outcomes that included affective (e.g., intentions to transfer), cognitive (e.g., declarative knowledge), and skill-based (e.g., proficiency) learning. Conversely, GCA had neither direct nor indirect effects on affective learning but did demonstrate direct effects on cognitive and skill-based learning. Results support the utility of including CSE in training research and practice, suggest that MEA serves as an explanatory mechanism for CSEs relation to learning outcomes, and demonstrate that CSE and GCA differentially influence training effectiveness and do so through different explanatory mechanisms.

The Development and Validation of a Measure of Student Attitudes Toward Science, Technology, Engineering, and Math (S-STEM)

Using an iterative design along with multiple methodological approaches and a large representative sample, this study presents reliability, validity, and fairness evidence for two surveys measuring student attitudes toward science, technology, engineering, and math (S-STEM) and interest in STEM careers for (a) 4th- through 5th-grade students (Upper Elementary S-STEM) and (b) 6th- through 12th-grade students (Middle/High S-STEM). Findings from exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) suggested the use of a four-factor structure to measure student attitudes toward science, math, engineering/technology, and 21st century skills. Subject matter experts and literature reviews provided evidence of content validity. Reliability levels were high for both versions. Furthermore, both the Upper Elementary S-STEM and Middle/High S-STEM Surveys demonstrated evidence of configural, metric, and scalar invariance across grade levels, races/ethnicities, and genders. The findings support the validity of interpretations and inferences made from scores on the instruments’ items and subscales.

Acquiring Teacher Commitment to 1:1 Initiatives: The Role of the Technology Facilitator.

Abstract Using mixed methods, we examined the impact of technology facilitators (TFs) on teacher commitment to 1:1 initiatives. Findings from quantitative analysis complemented by qualitative analyses suggest teachers benefitted from having TFs assist with the technological integration. Teachers from schools with a TF endorsed attitudes that were significantly more positive toward teaching and student learning with technology. Further, they reported greater use of technology for planning, reported the school infrastructure was of higher quality, and shared normative perceptions toward the school infrastructure. Results suggest that as ubiquitous technology-related initiatives continue to proliferate, schools should consider employing qualified TFs to assist the transition.