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In recent years, COVID-19 policy measures massively affected university teaching. Seeking an effective and viable way to transform their lecture material into asynchronous online settings, many lecturers relied on prerecorded video lectures. Whereas researchers in fact recommend implementing prompts to ensure students process those video lectures sufficiently, open questions about the types of prompts and role of students' engagement remain. We thus conducted an online field experiment with teacher students at a German university (N = 124; 73 female, 49 male). According to the randomly assigned experimental conditions, the online video lecture on topic "Cognitive Apprenticeship" was supplemented by (A) notes prompts (n = 31), (B) principle-based self-explanation prompts (n = 36), (C) elaboration-based self-explanation prompts (n = 29), and (D) both principle- and elaboration-based self-explanation prompts (n = 28). We found that the lecture fostered learning outcomes about its content regardless of the type of prompt. The type of prompt did induce different types of self-explanations, but had no significant effect on learning outcomes. What indeed positively and significantly affected learning outcomes were the students' self-explanation quality and their persistence (i.e., actual participation in a delayed posttest). Finally, the self-reported number of perceived interruptions negatively affected learning outcomes. Our findings thus provide ecologically valid empirical support for how fruitful it is for students to engage themselves in self-explaining and to avoid interruptions when learning from asynchronous online video lectures.

In two experiments with German secondary school students (N[subscript 1] = 43; N[subscript 2] = 41), we aimed to analyze and optimize an effective learning environment. We sought further active ingredients and crucial factors for deep processing during an example-based training intervention, which consisted mainly of video examples and self-explanation prompts. In Experiment 1, we analyzed whether presenting learning goals influenced learning processes (i.e. mental effort and self-explanation quality) and learning outcomes (i.e. declarative knowledge about argumentation). In Experiment 2, we examined the role of the ratio between the number of self-explanation and practice tasks. Both experiments revealed that learners highly improved their declarative knowledge on argumentation. These effects remained stable after 2 and 3 weeks--regardless of whether learning goals had been presented or the ratio between self-explanation and practice tasks. Furthermore, mental effort and the Need for Cognition (NFC) were identified and discussed as crucial factors for deep processing the given examples and for the knowledge gain from pretest to delayed posttests. Presenting learning goals reduced mental effort, albeit at the expense of beneficial cognitive processing of the given examples. Finally, NFC contributed to learners' mental engagement not only during but also after the training intervention.

Future teachers face the challenge of whether and how to address their students' misconceptions--naïve concepts that often conflict with the correct scientific concepts taught at school. We developed a short-term digital training intervention on instructional knowledge about strategies for addressing students' misconceptions in physics. It comprised cognitive modelling of three instructional strategies (i.e. ignoring, refuting, and integrating) and self-explanation prompts. In a web experiment with 58 teacher students, we found that our digital intervention fostered learning processes (self-explanation quality) and learning outcomes (knowledge about three instructional strategies). It can thus help teacher students to acquire initial knowledge about how to tackle their future students' misconceptions. Self-explanation quality mediated the intervention's effect on instructional knowledge both immediately and 3 weeks later. These mediation effects emphasise the impact of self-explanations while learning from complex cognitive models. Finally, the intervention's positive side effect of reducing participants' own misconceptions is an additional practical advantage.

The main goal of this study was to test whether feedback from a lecturer and tutor on an initial reflective journal entry fosters reflection quality in a subsequent journal entry and reflection skills in student teachers. To address these questions, we, a team of educators and psychologists, conducted a field experiment during the practical semester. Student teachers (N = 54; 40 female) wrote two reflective journals about their own classroom teachings on an online-platform and were randomly assigned to one of two conditions: (a) reflective journaling with feedback (experimental condition, n = 27) or (b) reflective journaling without feedback (control condition, n = 27). Feedback in reflective journaling fostered reflection quality in the subsequent journal entry and conceptual knowledge about reflection. These findings indicate that feedback in reflective journal-keeping exerts a powerful influence in fostering reflection in student teachers during their practical semester.

In learning from examples, students are often first provided with basic instructional explanations of new principles and concepts and second with examples thereof. In this sequence, it is important that learners self-explain by generating links between the basic instructional explanations' content and the examples. Therefore, it is well established that learners receive self-explanation prompts. However, there is hardly any research on whether these prompts should be provided in a closed-book format--in which learners cannot access the basic instructional explanations during self-explaining and thus have to retrieve the main content of the instructional explanations that is needed to explain the examples from memory (i.e., retrieval practice)--or in an open-book format in which learners can access the instructional explanations during self-explaining. In two experiments, we varied whether learners received closed- or open-book self-explanation prompts. We also varied whether learners were prompted to actively process the main content of the basic instructional explanations before they proceeded to the self-explanation prompts. When the learners were not prompted to actively process the basic instructional explanations, closed-book prompts yielded detrimental effects on immediate and delayed (1 week) posttest performance. When the learners were prompted to actively process the basic instructional explanations beforehand, closed-book self-explanation prompts were not less beneficial than open-book prompts regarding performance on a delayed posttest. We conclude that at least when the retention interval does not exceed 1 week, closed-book self-explanation prompts do not entail an added value and can even be harmful in comparison to open-book ones.

Worked examples support learning. However, if they introduce easy-to-confuse concepts or principles, specific ways of providing worked examples may influence their effectiveness. Multiple worked examples can be introduced blocked (i.e., several for the same principle) or interleaved (i.e., switching between principles), and can be sequentially or simultaneously presented. Crossing these two factors provides four ways of presenting worked examples: blocked/sequential, interleaved/sequential, blocked/simultaneous, and interleaved/simultaneous. In an experiment with university students (N = 174), we investigated how these two factors influence the acquisition of procedural and conceptual knowledge about different, but closely related (thus, easy-to-confuse) stochastic principles. Additionally, we assessed the ability of students to discriminate between principles with verification tasks. Simultaneous presentation benefitted procedural knowledge whereas, interleaved presentation benefitted conceptual knowledge. No significant differences were found for verification tasks. The results suggest that it is worthwhile to adapt the presentation of the worked examples to the learning goals.

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.

The ability to comprehend informal arguments is essential for scientific literacy but students often lack structural knowledge about these arguments, especially when the arguments are more complex. This study used a pre-post-test design with a follow-up 4 weeks later to investigate whether a computerised training in identifying structural components of informal arguments can improve university students' competences to understand complex arguments. The training was embedded in a constructivist learning environment and contents were based on the Toulmin model of argument structure, according to which arguments can be deconstructed into several functional components: Claim, datum, warrant, backing evidence, and rebuttal. Being able to identify the warrant is central for scientific literacy, as the warrant determines whether a conclusion is justified given the data. Results indicate that training in argument structure did not generally improve performance for all students and argument types, but that it was particularly helpful for identifying more complex arguments with a less typical structure and relational aspects between key components (i.e. warrants). High achieving students profited the most from this intervention, and the intervention was also helpful for students with high pretest accuracy scores. Our results suggest that interventions to foster argumentation skills should be included into the curriculum and these interventions should be designed to match learners' ability level.

Numerous effective digital learning environments have evolved over the last few years built around video examples that follow an introduction phase and are often supplemented by prompts. The learning mechanisms behind these components remain subject to open questions, though. We thus conducted an online experiment with university students (N = 138) and compared four conditions: (A) training intervention with an introduction, video examples, and self-explanation prompts (training condition, n = 34), (B) condition A without self-explanation prompts (no prompt condition, n = 35), (C) condition B without video examples (introduction condition, n = 35), and (D) no training intervention (control condition, n = 34). We applied a-priori contrasts to test assumed effects of video examples and self-explanation prompts on learning processes and learning outcomes. Referring to learning processes, video examples already fostered self-explanation quality, but additional self-explanation prompts provided an extra boost. Referring to learning outcomes, the introduction alone already fostered knowledge, but only the additional video examples provided an extra boost in knowledge gain. Finally, self-explanation quality mediated the video examples' effect on knowledge gain. Our findings provide further empirical support how a fruitful combination of video examples and self-explanation prompts promote learning processes and outcomes—despite the asynchronous and unsupervised online setting with potential diversions and off-task behavior. [ABSTRACT FROM AUTHOR]

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 inconsistencies, we conducted an experiment (N = 81) to analyze the role of (a) the share of information to which test questions direct learners and (b) the learning activities performed in the initial study phase with respect to the effects between higher- and lower-level test questions. We found that both the share of focused information and the initial learning activities moderated the effects between higher- and lower-level test questions.

Argumentative thinking requires not only the "skill" to apply argumentative strategies such as supporting theories with evidence but also the "will" to apply these strategies by considering argumentative thinking to be both reasonable and worthwhile. Focusing on direct instruction for the initial acquisition of both skill and will, we developed a new short-term computer-based training intervention. We tested its effects on learning processes and learning outcomes in an experimental study with 147 German high school students. Our intervention fostered facets of both skill (i.e. a declarative knowledge about argumentation) and will (i.e., epistemic orientation, intellectual values, and epistemic knowledge). We gained additional insights into learning mechanisms, such as the mediating effects of the learners' self-explanation activities and the advantage of addressing will before skill.

Adjunct questions are a common means to foster learning from instructional explanations. As the benefit of adjunct questions is mitigated if learner performance on them is low, it is also common to provide feedback as an add-on if learners fail to correctly respond to them. However, if adjunct questions are highly demanding, feedback might not only beneficially affect learning because it helps learners revise their comprehension difficulties; at the same time, it could also detrimentally affect learning by causing learners to invest less time in responding to subsequent adjunct questions, which lowers learner performance on these questions. This, in turn, could reduce learning outcomes. To address these potential detrimental effects of feedback, we experimentally varied whether N = 59 students received immediate feedback after they responded to highly demanding adjunct questions. We found that the feedback did indeed have detrimental effects: At least for the learners who perceived the task of responding to the adjunct questions as highly demanding, the feedback decreased both the time the learners invested in responding to the adjunct questions and their performance on them. This detrimental effect on the performance on the adjunct questions, in turn, entailed a detrimental effect on learning outcomes. We conclude that immediate feedback is not necessarily a beneficial add-on to adjunct questions in all situations.

Learners often insufficiently monitor their comprehension, which results in overconfident judgments of learning and underachievement. In the 3 present experiments, we investigated whether insufficient comprehension monitoring is due in part to the fact that learners are not sufficiently aware of the benefit of comprehension monitoring and thus scarcely engage in this process. As an intervention, we informed learners about the likely negative consequences of failing to monitor their comprehension. Specifically, we informed them about the high frequency of and the detrimental consequences that result from making overconfident judgments of learning. In Experiment 1 we found that for university students, this intervention increased their engagement in comprehension monitoring, led to more cautious judgments of learning, and fostered the acquisition of conceptual knowledge in a subsequent learning phase in which they received instructional explanations relating to a new topic. By contrast, this intervention was less beneficial for 13- to 15-year-old high school students: Although the intervention increased their comprehension monitoring and led to more cautious judgments of learning, it did not foster the acquisition of conceptual knowledge from the subsequent explanations (Experiment 2). In Experiment 3, we varied whether 13- to 15-year-old high school students received (a) information about the frequency of and the detrimental consequences that result from making overconfident judgments of learning and (b) information about effective regulation strategies. The results of this experiment suggest that the limited beneficial effect found in Experiment 2 could be attributed to a lack of knowledge regarding effective regulation strategies for this age group.

Comparing contrasting cases is a promising means to prepare learners for future learning from related direct instruction. The most prevalent type of preparation intervention used in this "case comparison approach" is providing contrasting cases together with comparison prompts. However, if the contrasting cases are complex learners might need more guidance than mere prompts in order to detect their relevant similarities and differences and thus exploit their full potential. The "inventing approach" entails having learners invent explanations that deal with the detected similarities and differences in addition to comparing contrasting cases. In this approach, however, it is unclear whether the generation of inventions per se has an added value to the concomitant detection of similarities and differences. Against this background, in a 2 × 2 factorial experiment with N = 80 eighth-grade students we varied the preparation intervention the learners received before they processed some instructional explanations according to: (a) "type of task while comparing contrasting cases" (responding to a comparison prompt vs. verifying provided comparisons), and (b) "inventing task after comparing contrasting cases" (with vs. without). We found that if there was no invention task, the learners who verified the provided comparisons learned more from the instructional explanations than those who received a comparison prompt. Requiring learners to generate inventions only after comparing the cases yielded differential results. The learners who detected only one similarity or difference among the cases benefitted from the inventing task, whereas the learners who detected all of the relevant features were hindered by it, albeit marginally.

In 2 experiments we examined the role of (a) specificity, (b) the type of targeted learning activities, and (c) learners' prior knowledge for the effects of relevance instructions on learning from instructional explanations. In Experiment 1, we recruited novices regarding the topic of atomic structure (N = 80) and found that "specific" relevance instructions designed to focus learners' attention on basic contents (i.e., focused processing prompts) were more effective than "general" relevance instructions that merely told learners to process the explanations for study purposes. This "specificity effect" was mediated by lower extraneous load that was due to having to identify the relevant information. Furthermore, regarding the role of the type of targeted learning activities, we found that focused processing prompts were more effective when they were combined with reduced explanations without explicit answers to the focused processing prompts, rather than with complete explanations that included them. This effect was mediated by a higher amount of generative learning activities on the part of the learners who received reduced explanations. To explore the role of learners' prior knowledge, in Experiment 2 we recruited a sample with greater diversity in prior knowledge (N = 77). As in Experiment 1, we found that reduced explanations and focused processing prompts were more effective than complete explanations and general purpose instructions for novice learners. However, learners with a higher degree of prior knowledge benefited more from complete explanations and general purpose instructions than from reduced explanations and focused processing prompts.

In an experiment, prior to processing instructional explanations N = 75 students received either (a) contrasting cases plus comparison prompts, (b) contrasting cases plus provided comparisons (i.e., model answers to the comparison prompts), or (c) no preparation intervention. We found that the learners with preparation intervention learned more and with a higher degree of efficiency, perceived less extraneous load, and experienced a higher feeling of smooth automatic running while they processed the explanations than the learners without a preparation intervention. These findings suggest that comparing contrasting cases serves a focusing function. Furthermore, we found that the learners in the provided comparisons condition acquired more conceptual knowledge from the explanations than the learners in the prompted comparisons condition. This result indicates that providing high amounts of instructional guidance while learners compare contrasting cases can have an added value in comparison to providing comparison prompts concerning the resulting preparation for future learning.

Argumentation skills play a crucial role in science education and in preparing school students to act as informed citizens. While processing conflicting scientific positions regarding topics such as sustainable development in the domain of ecology, argumentation skills such as evaluating arguments or supporting theories with evidence are beneficial for developing deep understanding and well-grounded conclusions. We developed a 50-min training intervention to foster argumentation skills in the domain of ecology on topics related to sustainable development and analyzed its effects in a control-group design: (a) training intervention to foster argumentation skills (n = 41), (b) no such training intervention (n = 42). Results showed that this short-term training intervention successfully fostered three components of argumentation skills (i.e., evaluative knowledge, generative knowledge, and argument quality) and declarative knowledge about argumentation. The positive effect on declarative knowledge was stable 1 week after the training and it was mediated by learning processes during the training intervention: self-explaining the principles of argumentation underlying the video-based examples mediated the effect on declarative knowledge 1 week after the training. In short, the training intervention is an effective instructional method to enhance argumentation skills as well as declarative knowledge about argumentation.

Although instructional explanations are commonly used to introduce learners to new learning content, previous studies have often shown that their effects on learning outcomes are minimal. This failure might partly be due to mental passivity of the learners while processing introductory explanations and to a lack of opportunity to revise potential misunderstandings after working on introductory explanations. Against this background, we provided learners with two instructional support measures to optimise the introduction of new principles and concepts by providing instructional explanations in the domain of management theory: (a) prompts designed to induce inferences that are focused on the central content of the explanations, and (b) remedial explanations that are adapted to the learners' knowledge gaps. We tested their effects in a 2 × 2 factorial experimental design with the following factors: (a) prompts designed to induce focused processing (with vs. without), and (b) remedial explanations (adapted vs. random). The participants consisted of 80 psychology students. We found that the prompts fostered both the share of deep-oriented processing and the acquisition of conceptual knowledge. The beneficial effect of prompts on conceptual knowledge was mediated by the number of inferences that learners generated in response to the prompts. In addition, we found that prompts also fostered the instructional efficiency of providing instructional explanations. The provision of adapted remedial explanations, however, fostered neither deep-oriented processing nor the acquisition of conceptual knowledge. We conclude that prompts designed to induce focused processing can foster deep-oriented processing as well as both the effectiveness and efficiency of learning from instructional explanations.

Providing prompts to induce focused processing of the central contents of instructional explanations is a promising instructional means to support novice learners in learning from instructional explanations. However, within research on the expertise reversal effect it has been shown that instructional means that are beneficial for novices can be detrimental for learners with more expertise if the instructional means provide guidance that overlaps with the internal guidance provided by the prior knowledge of learners with more expertise. Under such circumstances, prompts to induce focused processing might even be detrimental for learners with expertise whose prior knowledge already provides internal guidance to learn from explanations. On this basis, we aimed at experimentally varying expertise by developing prior knowledge. Specifically, we used a preparation intervention with contrasting cases to enhance learners' prior knowledge (expertise). Against this background, we tested 71 university students in a 2 × 2 factorial experimental design: (a) "Factor of expertise." Working with contrasting cases to develop prior knowledge and expertise to provide internal guidance to learn from instructional explanations (with vs. without), (b) "Factor of prompts." Prompts to induce focused processing of the explanations (with vs. without). The results showed that prompts to induce focused processing fostered conceptual knowledge for novice learners whereas prompts hindered the acquisition of conceptual knowledge for learners with expertise that was developed by working with contrasting cases beforehand. Moreover, measures of subjective cognitive load and learning processes suggest that the instructional guidance provided by prompts compensated for the low internal guidance of novice learners and overlapped with the internal guidance of learners with expertise.

In instructional communication settings, instructional explanations play an important role. Despite the very common use of instructional explanations, empirical studies show that very often, they have no positive effects on learning outcomes. This ineffectiveness might be due to mental passivity of the recipient learners that leads to shallow processing of the explanations. Against this background, we introduce several types of instructional assistance to foster active processing of written instructional explanations in asynchronous computer-mediated instructional communication settings. The findings of three experiments showed that prompts or training for "focused processing" regarding the central principles and concepts of the explanation are especially effective with respect to fostering learning outcomes.

Learning with multiple representations is usually employed in order to foster understanding. However, it also imposes high demands on the learners and often does not lead to the expected results, especially because the learners do not integrate the different representations. Thus, it is necessary to support the learners' self-explanation activity, which concerns the integration and understanding of multiple representations. In the present experiment, we employed multi-representational worked-out examples and tested the effects of two types of self-explanation prompts as help procedures for integrating and understanding multiple representations. The participants (N = 62) learned about probability theory under three conditions: (a) open self-explanation prompts, (b) self-explanation prompts in an assistance-giving-assistance-withholding procedure (assisting self-explanation prompts), or (c) no prompts (control group). Both types of self-explanation prompts fostered procedural knowledge. This effect was mediated by self-explanations directed to domain principles. Conceptual knowledge was particularly fostered by assisting self-explanation prompts which was mediated by self-explanations on the rationale of a principle. Thus, for enhancing high-quality self-explanations and both procedural knowledge and conceptual understanding, we conclude that assisting self-explanation prompts should be provided. We call this the "assisting self-explanation prompt effect" which refers to the elicitation of high-quality self-explanations and the acquisition of deep understanding.

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.)

In this study, the authors compared four multimedia learning arrangements differing in instructional approach on effectiveness and efficiency for learning: (a) hypermedia learning, (b) observational learning, (c) self-explanation-based learning, and (d) inquiry learning. The approaches all advocate learners' active attitude toward the learning material but show differences in the specific learning processes they intend to foster. Learning results were measured on different types of knowledge: conceptual, intuitive, procedural, and situational. The outcomes show that the two approaches asking learners to generate (parts of) the subject matter (either by self-explanations or by conducting experiments) led to better performance on all types of knowledge. However, results also show that emphasis on generating subject matter by the learner resulted in less efficient learning. (Contains 12 tables and 2 figures.)

Although writing learning protocols is an effective follow-up course work activity, many learners tend to do it in a rather suboptimal way. Hence, we analyzed the effects of instructional support in the form of prompts. The effects of different types of prompts were investigated in an experiment with four conditions: cognitive prompts, metacognitive prompts, a combination of cognitive and metacognitive prompts, or no prompts (N=84 undergraduate psychology students). We found that the prompts stimulated the elicitation of cognitive and metacognitive learning strategies. The provision of purely metacognitive prompts did not, however, improve learning outcomes. Only the groups who had received cognitive, or a combination of cognitive and metacognitive, prompts learned more than the control group. This effect was mediated by cognitive learning strategies. The learners in the successful groups did not perceive the prompted learning strategies as more helpful than the learners of the group without prompts. It can be concluded that cognitive prompts--alone or in combination with metacognitive prompts--are an effective means to foster learning. However, additional means should be employed in order to convince the learner of the usefulness of such prompts.

Learning diaries--as we employ them--are students' written reflections of their learning experiences and outcomes over the course of university seminars. The writing of such diaries is 'tutored' by a computer program: eHELp supports the writing of sophisticated learning diaries through a modelling and scaffolding of the phases of planning, production and revision. In addition, the learning diaries get published--by uploading them in a cooperation platform--so that the learners can read and discuss their peers' diaries. The main function of such public learning diaries is to enrich traditional university courses (Blended Learning) with additional elaborative, organisational, critical reasoning, and metacognitive activities in order to foster a deeper processing and better retention of the contents to be learnt. We would like to present the educational rationale of our approach and report the findings of corresponding empirical studies.

Learning from instructional explanations is one of the most established, prevalent, and obvious ways of learning--but it carries the risk of shallow processing. Unlike previous research that focused on providing digital just-in-time support measures for learning with explanations, we strived to prepare learners on how to make the most of upcoming explanations. We thus developed a short-term computer-based training intervention on the focused processing of instructional explanations. In two experiments (N1 = 47, N2 = 42), we tested its effects on learning processes and outcomes of a subsequent learning phase. Our results revealed that the training intervention fostered domain-general knowledge about explanations. Furthermore, it enabled learners to benefit from future instructional explanations in other domains (inter-domain transfer for university students, Experiment 1) or at least on other topics (intra-domain transfer for primary school fourth graders, Experiment 2). The digital training intervention did not trigger more cognitive load in the subsequent learning phase. All in all, we describe an initial promising step toward a generic training effect that has the potential advantage of enhancing learning from explanations without altering the actual learning material. [ABSTRACT FROM AUTHOR]