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Previous research has shown that explaining is an effective activity to enhance learning. In prior studies, students were instructed to explain the contents after completing an entire learning phase. Explaining at the end of a learning phase, however, may be less apt to support comprehension monitoring and subsequent regulation activities. In 2 experiments, we investigated whether explaining in earlier phases of studying (i.e., in-between explaining) would foster learning more than explaining after the entire study phase (i.e., afterstudy explaining). In Experiment 1, university students (N = 91) read a text about combustion engines and either explained the contents between the study phases or at the end of the entire study phase. A third group recalled the learning contents aloud at the end of the study phase to control for retrieval-processes that may also be involved in explaining. Results showed no overall effect of explaining in comparison to retrieval practice. However, in-between explaining enhanced students' conceptual knowledge as compared with afterstudy explaining. Verbal protocol analyses showed that this effect was due to students' increased monitoring. Experiment 2 (N = 126), had a 2 × 2-factorial design with between-subjects factors timing (in-between vs. afterstudy) and learning activity (explaining vs. written retrieval practice). We found a cascaded trend: In-between learning activities were more effective than afterstudy learning activities, whereas explaining was more effective than written retrieval practice. These findings suggest that the timing of learning activities is crucial to improve learning. Additionally, our findings reveal that explaining is not simply a result of retrieval practice.

Example-based learning often uses a design in which learners first receive basic instructional explanations of new principles and concepts and then examples thereof. In this sequence, it is crucial that learners self-explain by using the content of the basic instructional explanations to elaborate on the examples. Typically, learners are not provided with access to the basic instructional explanations while they engage in self-explaining. However, it is reasonable to assume that this established design is suboptimal to some extent. When learners cannot retrieve the required knowledge components of the instructional explanations from memory, they can hardly generate the crucial self-explanations. Against this background, we analyzed the effects of a potential remedy for this suboptimality. Specifically, in 2 experiments with high school students we tested the effects of providing learners with constrained access to the basic instructional explanations while they engaged in self-explaining. The constraints were that learners were instructed to review the instructional explanations only when they could not remember certain required knowledge components or when they needed to check their self-explanations. We found that the effects of the constrained review option depended on learners' academic self-concept. Learners with low academic self-concepts benefitted from the review option, whereas learners with high academic self-concepts were even hindered by it. We conclude that the constrained review option should not be provided to learners with high academic self-concepts. On a more general level, we furthermore conclude that a high academic self-concept can be an obstacle rather than a beneficial resource in certain learning settings.

A rising number of (online) learning scenarios feature video-based worked examples. We analyzed the effects of the presentation mode of worked examples on their effectiveness and efficiency in two experiments with university students (N[subscript 1] = 57; N[subscript 2] = 43). The students acquired argumentation knowledge by self-explaining different types of worked examples. In Experiment 1, we compared video-based examples with written examples, and in Experiment 2, we compared video-based examples with graphic novel-based examples. Regardless of the examples' presentation mode, we observed similar learning processes (i.e., invested mental effort and self-explanation quality) as well as a large effect on learning outcomes (i.e., conceptual knowledge about argumentative principles). Although they appear similarly effective, we found learning by self-explaining written examples and by self-explaining graphic novels to be less time consuming and, thus, more efficient than learning by self-explaining video examples.

Recent findings show that after studying a text, teaching the learned content on video to a fictitious peer student improves learning more than restudying the content. This benefit may be in part due to increased arousal associated with the teaching activity. The present experiment investigated whether teaching on video is also effective for acquiring problem-solving skills from worked examples, and explored the role of cognitive load, worry, and arousal. Participants (N = 61 university students) first studied two worked examples on electrical circuits troubleshooting and completed a practice problem. Then they either taught the content of a worked example of the practice problem on video (teaching condition) or studied that worked example (control condition) for the same amount of time. Self-reported cognitive load was measured after each task and self-reported worry after the final task. Effects on arousal were explored via the Empatica wristband measuring electrodermal activity (EDA; i.e., galvanic skin response). Teaching the content of the worked example on video was not associated with more worry, but did result in higher perceived cognitive load, more arousal, and better performance on isomorphic and transfer problems on the posttest. Although this finding has to be interpreted with caution, teaching also seemed to moderate the effect of prior knowledge on transfer that was present in the study condition. This suggests that teaching is particularly effective for students who initially have low prior knowledge.

Recently, there have been efforts to rethink assessment. Instead of informing about (relatively stable) learner characteristics, assessment should assist instruction by looking at the learning process, facilitating feedback about what students' next step in learning could be. Similarly, new forms of strategy assessment aim at capturing self-regulated learning as it happens. One potential method for such assessment is the learning journal. We analyzed whether (a) quantity and (b) quality of learning strategies assessed by learning journals predict learning outcomes, and (c) whether differently successful combinations of strategies can be identified. In Study 1, 9th graders of medium-track high schools (N = 236) wrote learning journals in mathematics during 6 weeks. Foremost, quality and quantity of cognitive strategies predicted learning outcomes, controlling for prior knowledge. Learners who combined cognitive plus metacognitive strategies were particularly successful. Learners who mainly used 1 type of strategy performed similarly poorly as did learners who hardly used strategies. Study 2 in the domain of biology learning (N = 144) essentially replicated these findings. In summary, learning journals are a useful and innovative method for assessing learning strategies. (Contains 4 figures and 9 tables.)

The main goals of this study were to test whether multiple representations, such as diagrams and equations, per se help to acquire conceptual understanding in probability, and to investigate whether learners need instructional support to utilize the potentials of multiple representations. The authors conducted an experimental study with 8 conditions in which high school students (N = 170) studied worked examples from probability. The authors varied the type and number of representations and the availability of 2 support procedures: (a) a relating aid that used color codes and flashing to help learners see which elements in different representations corresponded to each other on a surface level and (b) self-explanations prompts to ensure that learners integrate corresponding parts in different representations on a structural level. The authors found that multiple representations per se did not foster conceptual understanding, however, both support procedures enhanced it. Yet, the self-explanation prompts did not only foster conceptual understanding by eliciting elaborations directed to domains principles but also incorrect elaborations that hindered the acquisition of procedural knowledge. Hence, self-explanation prompts are an instructional support procedure that can have conflicting effects on learning outcomes. (Contains 3 figures and 7 tables.)

Learning with self-explaining examples is an effective method in well-structured domains. The authors analyzed this method in teaching the complex skill of argumentation, experimentally comparing 4 conditions (N = 71 student teachers) that differed with respect to whether and how the processing of the examples was supported by self-explanation prompts. They found that examples of argumentation could be successfully used to teach declarative knowledge about argumentation. However, when the skill of argumentation is to be fostered, prompts that direct the learners' attention to the principles of argumentation should be used. The authors demonstrate that learning with self-explaining examples is also a promising method of enhancing skills in ill-structured domains such as argumentation.

Tutors often make use of explanations that do not promote learning. One reason for the ineffectiveness of explanations might lie in tutors' failure to take into account a tutee's understanding in order to individualize instruction. To test whether tutors provide more effective explanations when they are assisted in assessing a tutee's understanding, we conducted an experiment (N = 30 dyads of tutors and tutees) and varied whether tutors received information about a tutee's individual knowledge level. Results showed that only tutors provided with information about the tutee were able to customize instruction. As a consequence, the individualized explanations lowered the incidence of clarifying questions on the part of the tutees, deepened their understanding, and reduced the number of false beliefs about newly learned concepts. The findings suggest that a diagnosis-based approach to support tutors in developing a model of the tutee effectively contributes to the individualization of instruction in tutoring. Keywords: assessment, instructional explanations, pedagogical strategies, tutoring DOI: 10.1037/a0016727