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The present study will be conducted in the first-year undergraduate course “materials science 1”, which is part of the mechanical engineering program at Avans University of Applied Sciences. All students form the cohort 2017-2018 will take part in the field experiment, and each of them will take three cumulative assessments before the final course exam. For a random half of the students, the performance on these cumulative assessments will add to the final course exam grade, i.e., the summative cumulative assessment condition, whereas for the other half of the students the performance will not add to the final course grade, i.e., the formative cumulative assessment condition. All participants will be tested immediately after the course, i.e., the final course exam, and after a 10-week delay prior to the start of “materials science 2”, which follows up on “materials science 1”. We decided to include a delayed test as Kerdijk and colleagues (2015) suggest that the effect of summative cumulative assessment may only lead to better achievement in the long term. The treatment effect, which is defined as the mean performance difference between the summative cumulative assessment condition and the formative cumulative assessment condition is the primary outcome in the present field experiment and we will examine the treatment effect at the two already mentioned retention intervals. Furthermore, the nature of the cumulative assessment (formative vs. summative assessment) may influence study effort, self-efficacy and perceived competence. Therefore, as a secondary outcome, we will compare the two conditions on these measures.

Presenting novices with examples and problems is an effective and efficient way to acquire new problem-solving skills. Nowadays, examples and problems are increasingly presented in computer-based learning environments, in which learners often have to self-regulate their learning (i.e., choose what type of task to work on and when). Yet, it is questionable how novices self-regulate their learning from examples and problems, and to what extent their choices match with effective principles from instructional design research. In this study, 147 higher education students had to learn how to solve problems on the trapezoidal rule. During self-regulated learning, they were free to select six tasks from a database of 45 tasks that varied in task format (video examples, worked examples, practice problems), complexity level (level 1, 2, 3), and cover story. Almost all students started with (video) example study at the lowest complexity level. The number of examples selected gradually decreased and task complexity gradually increased during the learning phase. However, examples and lowest level tasks remained relatively popular throughout the entire learning phase. There was no relation between students' total score on how well their behavior matched with the instructional design principles and learning outcomes, mental effort, and motivational variables.

The Actively Open-minded Thinking scale (AOT; Stanovich & West, 2007) is a questionnaire that is used to measure the disposition towards rational thinking as a single psychological trait. Yet, despite its frequent use, also in abbreviated form, it is still unclear whether sumscores of the AOT can actually be used to order individuals on their disposition towards actively open-minded thinking and whether the questionnaire can be validly shortened. The present study aimed to obtain a valid and shorter AOT. We conducted Mokken scale analyses on the (Dutch) AOT using two samples of higher education students (N = 930; N = 509). Our analyses showed that none of the 41 items could discriminate sufficiently between respondents with varying latent trait levels. Furthermore, no item-set of the AOT could be obtained to validly order individuals on the assumed latent trait, which is a crucial assumption when using it in research. Consequently, it is questionable whether scores on the AOT provide insights into the concept it aims to measure. published

The aim of this study was to identify characteristics that are related to higher education teachers' (N ¼ 263) Cognitive Reflection Test (CRT) performance, which assesses an important aspect of critical thinking (CT), and their attitudes towards teaching CT more generally. Results of a structural equation model showed that a stronger disposition towards effortful thinking, teaching in a more technological domain, and a higher level of education were related to a better CRT performance. Thinking dispositions were also related to teachers’ perceived relevance of teaching CT. Confidence in CRT performance rather than actual performance was related to perceived competence in teaching CT.

Teachers play a crucial role in attaining a major objective of higher education: fostering students’ critical thinking (CT). Yet, little is known about how to foster teachers’ own CT-skills and attitudes towards teaching CT. In a quasi-experimental study (N = 54), we investigated whether a three-session teacher training on (teaching) CT (n = 32) positively affected higher education teachers’ CT-skills and their attitudes towards teaching CT compared to a control condition (n = 22). The training consisted of explicit instruction on common reasoning biases combined with assignments focused on the teaching practice. Results showed that the training improved teachers’ performance on trained but not on novel CT-tasks. Also teachers’ ability to detect biases in a written student product improved; however, despite a small improvement, they still had difficulties in correctly explaining those biases. Possibly due to ceiling effects the training did not affect perceived relevance of teaching CT. Finally, perceived competence in teaching CT decreased temporarily after the first training session but this negative effect disappeared after the final third session. Future research should investigate ways to promote teachers’ ability to transfer trained skills to other CT-tasks, their ability provide feedback on students’ reasoning (i.e., bias explanation), and their attitudes towards teaching CT.

Critical thinking is considered to be an important competence for students and graduates of higher education. Yet, it is largely unclear which teaching methods are most effective in supporting the acquisition of critical thinking skills, especially regarding one important aspect of critical thinking: avoiding biased reasoning. The present study examined whether creating desirable difficulties in instruction by prompting students to generate explanations of a problem-solution to themselves (i.e., self-explaining) is effective for fostering learning and transfer of unbiased reasoning. Seventy-nine first-year students of a Dutch Applied University of Sciences were first instructed on two categories of “heuristics and biases” tasks (syllogism and base-rate or Wason and conjunction). Thereafter, they practiced these either with (self-explaining condition) or without (no self-explaining condition) self-explanation prompts that asked them to motivate their answers. Performance was measured on a pretest, immediate posttest, and delayed (2 weeks later) posttest on all four task categories, to examine effects on learning (performance on practiced tasks) and transfer (performance on non-practiced tasks). Participants’ learning and transfer performance improved to a comparable degree from pretest to immediate posttest in both conditions, and this higher level of performance was retained on the delayed posttest. Surprisingly, self-explanation prompts had a negative effect on posttest performance on practiced tasks when those were Wason and conjunction tasks, and self-explaining had no effect on transfer performance. These findings suggest that the benefits of explicit instruction and practice on learning and transfer of unbiased reasoning cannot be enhanced by increasing the difficulty of the practice tasks through self-explaining.

Four experiments investigated whether the testing effect also applies to the acquisition of problem-solving skills from worked examples. Experiment 1 (n = 120) showed no beneficial effects of testing consisting of isomorphic problem solving or example recall on final test performance, which consisted of isomorphic problem solving, compared to continued study of isomorphic examples. Experiment 2 (n = 124) showed no beneficial effects of testing consisting of identical problem solving compared to restudying an identical example. Interestingly, participants who took both an immediate and a delayed final test outperformed those taking only a delayed test. This finding suggested that testing might become beneficial for retention but only after a certain level of schema acquisition has taken place through restudying several examples. However, experiment 2 had no control condition restudying examples instead of taking the immediate test. Experiment 3 (n = 129) included such a restudy condition, and there was no evidence that testing after studying four examples was more effective for final delayed test performance than restudying, regardless of whether restudied/tested problems were isomorphic or identical. Experiment 4 (n = 75) used a similar design as experiment 3 (i.e., testing/restudy after four examples), but with examples on a different topic and with a different participant population. Again, no evidence of a testing effect was found. Thus, across four experiments, with different types of initial tests, different problem-solving domains, and different participant populations, we found no evidence that testing enhanced delayed test performance compared to restudy. These findings suggest that the testing effect might not apply to acquiring problem-solving skills from worked examples.