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Training reactions are the most common criteria used for training evaluation, and reaction measures often include opportunities for trainees to provide qualitative responses. Despite being widely used, qualitative training reactions are poorly understood. Recent trends suggest commenting is ubiquitous (e.g., tweets, texting, Facebook posts) and points to a currently untapped resource for understanding training reactions. In order to enhance the interpretation and use of this rich data source, this study explored commenting behavior and investigated 3 broad questions: who comments, under what conditions, and how do trainees comment? We explore both individual difference and contextual influences on commenting and characteristics of comments in 3 studies. Using multilevel modeling, we identified significant class-level variance in commenting in each of the 3 samples of trainees. Because commenting has only been considered at the individual level, our findings provide an important contribution to the literature. The shared experience of being in the same class appears to influence commenting in addition to individual differences, such as interest in the topic (Studies 1 and 2), satisfaction (Studies 2 and 3), and entity beliefs (Study 3). Furthermore, we demonstrated that item wording may have an impact on commenting (Study 3) and should be considered as a potential lever for training professionals to influence commenting behavior from trainees. Training professionals, particularly those who regularly administer training evaluation surveys, should be aware of nonresponse to open-ended items and how that may impact the information they collect, use, and present within their organizations., ((c) 2015 APA, all rights reserved.)

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 CSE's 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 CSE's relation to learning outcomes, and demonstrate that CSE and GCA differentially influence training effectiveness and do so through different explanatory mechanisms., (PsycINFO Database Record (c) 2013 APA, all rights reserved)

Empirical evidence supporting frame-of-reference (FOR) training as an effective intervention for calibrating raters is convincing. Yet very little is known about who does better or worse in FOR training. We conducted a field study of how motivational factors influence affective, cognitive, and behavioral learning outcomes, as well as near transfer indexed by achieving professional certification. Relying on goal orientation theory, we hypothesized effects for 3 goal orientations: learning, prove performance, and avoid performance. Results were generally supportive across learning outcomes and transfer. Findings further supported a hypothesized interaction between learning self-efficacy and avoid performance goal orientation, such that higher levels of learning self-efficacy mitigated the negative effects of higher performance avoid tendencies., ((c) 2010 APA, all rights reserved.)