Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…

Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…

Functional fixedness involves difficulty with conceptualizing creative object uses. When it obstructs problem-solving, individuals must reframe their approach. We examined how different training techniques--chunk decomposition (i.e., considering an object's basic parts and physical properties) and constraint relaxation (i.e., considering an…

This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…

Purpose: The National Academy of Medicine has called for "identifying opportunities to improve the diagnostic process". We studied the association between problem representation and diagnostic accuracy during an objective structured clinical exam (OSCE). Materials and methods: We conducted a non-randomized controlled trial during a…

The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to…

Undergraduate students tend to struggle with probability in their introductory statistics course. Probability problem solving requires several steps. First, students must make sense of the probability scenario, then determine the appropriate probability rules, and finally, execute the procedures to solve the problem. With no previous exposure to…

In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate…

Providing test questions after an initial study phase is a common instructional technique. In theory, questions that require higher-level (deep) processing should be more beneficial than those that require lower-level (shallow) processing. However, empirical evidence on the matter is inconsistent. To shed light on two potential reasons for these…

Problem solving is an integral part of doing science, yet it is challenging for students in many disciplines to learn. We explored student success in solving genetics problems in several genetics content areas using sets of three consecutive questions for each content area. To promote improvement, we provided students the choice to take a…

The present study aims at fostering undergraduate medical students' clinical reasoning by learning from errors. By fostering the acquisition of "negative knowledge" about typical cognitive errors in the medical reasoning process, we support learners in avoiding future erroneous decisions and actions in similar situations. Since learning…

Process-oriented dynamic testing aims to investigate the processes children use to solve cognitive tasks, and evaluate changes in these processes as a result of training. For the current study, a dynamic complex figure task was constructed, using the graduated prompts approach, to investigate the processes involved in solving a complex figure task…

This research aimed to develop a computer detective game for science education to provide students in experiencing real-world problem-solving after learning electricity-related knowledge, and to explore the effects of designing the guidance of process constraints and prompts into this game. To explore the effects of guidance, two different game…

While the general planning advice offered to mathematics teachers seems to be to start with simple examples and build complexity progressively, the research reported in this article is a contribution to the body of literature that argues the reverse. That is, posing of appropriately complex tasks may actually prompt the use of more sophisticated…

Research on the seductive details effect on reading expository texts in multimedia learning environments has grown over the past few decades. However, less is known when seductive details are encountered in learning through worked-examples to solve problems. Thus, it is necessary to examine the seductive details effect when solving problems in a…