Validation of Assessment for Learning Questionnaires for teachers and students

Background. Assessment can be a powerful force in promoting student learning. Still, few measures exist to gauge Assessment for Learning (AFL) in the classroom. Literature on AFL suggests that it encompasses both a monitor to track student progress as well as a scaffold to show or help students recognize in what areas they need to improve. Aims. Based on a review of recent attempts to measure the AFL, we constructed Assessment for Learning Questionnaires for Teachers (TAFL‐Q) and for students (SAFL‐Q) for evaluating perceptions regarding AFL practices in classrooms using matching items. Sample. The total sample included 1,422 students (49% girls, 51% boys) and 237 teachers (43% females, 57% males) in lower vocational secondary education. Methods. The 28‐item questionnaires were examined by means of confirmatory factor analysis (CFA) using EQS on one random half of the sample. The CFA was cross‐validated on the second half. Measurement invariance tests were conducted to compare the students and teacher versions of the questionnaires. Results. CFA revealed a stable second‐order two‐factor structure that was cross‐validated: perceived monitoring, and perceived scaffolding subsumed under a common factor: AFL. Tests for measurement invariance showed that the parallel constructs were measured similarly for both students and teachers. Conclusion. The TAFL‐Q and SAFL‐Q capture the construct AFL in two subscales: Monitoring and Scaffolding, and allows for comparisons between teacher and student perceptions. The instruments can be useful tools for teachers and students alike to identify and scrutinize assessment practices in classroom.     

Establishing team knowledge coordination from a learning perspective

Research has identified the importance of knowledge coordination in high-performing teams. However, little is known on the processes through which these cognitive structures are developed, more specifically on the learning occurring as teams communicate and interact to build new team knowledge. In a multiple-measures experiment, 33 teams with no prior experience in flight simulations were assigned to newly formed dyads to complete 4 successive performance episodes of a flight simulation task, modeling a complex, fast-paced, and high workload task context. The study showed how team learning processes (i.e., team learning behaviors and team reflexivity), driven by task cohesion, and group potency supported coordination development, which in turn predicted team performance.     

Measuring adaptive expertise: development and validation of an instrument

Individuals with adaptive expertise possess the skills to deal with novel problems. Whereas this concept has been around since the mid-1980s, no instrument exists that provides a good operationalization of the theoretical construct. This inhibits the further development of research on adaptive expertise and the evaluation of employees’ adaptive expertise levels. Adaptive expertise has been unanimously described as a composition of domain-specific and innovative skills. Some researchers argue that metacognitive skills are also crucial. This study aimed to establish whether an instrument measuring adaptive expertise is composed of these three dimensions. In addition, it was tested whether such an instrument is influenced by task variety and work experience, as previously reported in literature. A sample of 383 professionals and graduates were used to test the Adaptive Expertise Inventory. Through exploratory factor analysis (EFA), (E/CFA), and confirmatory factor analysis (CFA), the quality of the instrument was evaluated. Good model fit was achieved. The final instrument consisted of two dimensions—i.e., domain-specific and innovative skills—with five items each. Regression analysis showed that not work experience, but task variety is related to level of adaptive expertise. The Adaptive Expertise Inventory proved to be a valid instrument for measuring adaptive expertise.     

Where to seat the applicant? How spatial distance influences the effect of self‐promotion on interviewer evaluations

In high‐stakes contexts such as job interviews, people seek to be evaluated favorably by others and they attempt to accomplish such favorable judgments particularly through self‐promotional behaviors. We sought to examine the persuasiveness of job candidates’ self‐promotion by examining job applicants’ subjective hireability from the perspective of construal‐level theory. Construal‐level theory states that perceptions occur from different levels of psychological distance (i.e., distal vs. proximal). This distance is created by other dimensions of distance (e.g., spatial or social distance) and affects how individuals construe incoming information. From a large distance, people more readily process abstract information, whereas from a close distance, people more readily process concrete information. Specifically, construal compatibility occurs when abstract versus concrete features of a stimulus match the psychological distance experienced by message‐recipients. Construal compatibility (vs. incompatibility) makes evaluations (e.g., of messages) more favorable. To apply this principle to self‐promotion, we created self‐promotional videos of a job interview, in which the applicant sat either far away from or close to the hiring manager (manipulating psychological distance); the applicant, then, used either direct or indirect self‐promotion (manipulating message construal level). The results showed participants reported stronger intention to hire the applicant when distance matched (vs. did not match) the type of self‐promotion the applicant used.     

Factors in teachers' ratings of schoolchildren: Heymans' data reconstructed by modern standards

In this article we re-analyse the data that Heymans and Wiersma collected on pupils from secondary schools, about 80 years ago. The main interest is in the structure of the adolescence data set in terms of modern standards and understood against the background of recent findings. More specifically, one question is whether the Heymans data can be understood in terms of the framework of the Big Five structure of personality traits. To that end, principal components analysis and multiple group analysis were performed. The general conclusion from these analyses is that the adolescence data are best described by a two-dimensional structure. Another more specific research question is to what extent Heymans' own three dimensions can be detected in the data set. With emphasis on a small number of criterion items, used by Heymans to identify the three dimensions, a three-factor solution was inspected for this purpose. The conclusion from this analysis is that the three Heymans dimensions cannot unequivocally be identified in the adolescence data set.