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Background: Students often show unfavourable attribution: they attribute poor school performance to stable factors such as lack of ability and good school performance to variable factors such as effort. However, attribution can be influenced by individualized digital re‐attributional feedback leading to positive motivational effects and higher learning outcomes. This is very promising, but it still is unclear, whether this digital re‐attributional feedback can also be successfully integrated in everyday classroom activities. Objectives: The present field experiment investigated how integrating digital re‐attributional feedback into classroom instruction affects student attribution, motivation and learning outcomes. Methods: In the experiment, 8th–10th grade high school students (N = 322) worked with a digital mathematics learning program which was integrated in a three‐week teaching unit. Half the students in each classroom received only standard feedback after each practice task (SF group); the other half received additionally an individual re‐attributional feedback (RF group) after every third task. Attribution, mathematics self‐concept, and self‐efficacy were measured by an online questionnaire twice a week; learning outcomes in mathematics were measured weekly. Results and Conclusion: Hierarchical analyses showed that re‐attributional feedback led to a more favourable attribution in case of success on stable factors. Especially low‐performing students benefited from this feedback. No effects on attribution in case of failure, self‐efficacy or learning outcomes could be found. Further research could investigate if certain adaptations to the digital re‐attributional feedback is more effective in a real classroom setting and has a broader impact on different students. Lay Description: What is already known about this topic: Working with computers in the classroom and at home is becoming more common.Re‐attributional feedback can increase student's motivation when given directly after solving a task and at a high density.Digital re‐attributive feedback can be given in a high density.Re‐attributional training sessions have been shown to be effective in individual training sessions or outside the students' classroom. What this paper adds: The study took place within a real teaching environment during mathematics class for 4 weeks.Digital re‐attributional feedback sessions were directly integrated into the students' online learning which was part of the teaching plan. The implications of study findings for practitioners: Computer‐based re‐attributional training show some limited effects in regular classroom instruction and could be well integrated in student online learning—when adapted accordingly.Low‐performing students show less favourable attribution than better‐performing students in case of success and benefit the most from re‐attributional training. [ABSTRACT FROM AUTHOR]

Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task and requires the application of natural language processing methodology. In this article, we implement and evaluate multiple machine learning models for coding energy knowledge in free‐text responses of German K‐12 students to items in formative science assessments which were conducted during synchronous online learning sessions. Dataset: The dataset we collected for this purpose consists of German constructed responses from 38 different items dealing with aspects of energy such as manifestation and transformation. The units and items were implemented with the help of project‐based pedagogy and evidence‐centered design, and the responses were coded for seven core ideas concerning the manifestation and transformation of energy. The data was collected from students in seventh, eighth and ninth grade. Methodology: We train various transformer‐ and feature‐based models and compare their ability to recognize the respective ideas in students' writing. Moreover, as domain knowledge and its development can be formally modeled through knowledge networks, we evaluate how well the detection of the ideas within responses translated into accurate co‐occurrence‐based knowledge networks. Finally, in terms of the descriptive accuracy of our models, we inspect what features played a role for which prediction outcome and if the models pick up on undesired shortcuts. In addition to this, we analyze how much the models match human coders in what evidence within responses they consider important for their coding decisions. Results: A model based on a modified GBERT‐large can achieve the overall most promising results, although descriptive accuracy varies much more than predictive accuracy for the different ideas assessed. For reasons of comparability, we also evaluate the same machine learning architecture using the SciEntsBank 3‐Way benchmark with an English RoBERTa‐large model, where it achieves state‐of‐the‐art results in two out of three evaluation categories. Lay Description: What is already known about this topic?: Formative assessments are needed to test and monitor the development of learners' knowledge throughout a unit to provide them with appropriate automated feedback.Constructed response items which require learners to formulate their own free‐text responses are well suited for testing their active knowledge.Assessing constructed responses in an automated fashion is a widely researched topic, but the problem is far from solved and most of the work focuses on predicting holistic scores or grades.To allow for a more fine‐grained and analytic assessment of learners' knowledge, systems which go beyond predicting simple grades are required.To guarantee that models are stable and make their predictions for the correct reasons, methods for explaining the models are required. What this papers adds?: A core topic in physics education is the concept of energy.We implement and evaluate multiple systems based on natural language processing technology for assessing learners' conceptual knowledge about energy physics using transformer language models as well as feature‐based approaches.The systems assess students' knowledge about various forms of energy, indicators for the same and the transformation of energy from form into another.As our systems are based on machine learning methodology, we introduce a novel German short answer dataset for training them to detect the respective knowledge elements within students' free‐text responses.We evaluate the performance of these systems using this dataset as well as the well‐established SciEntsBand‐3‐Way dataset and manage to achieve, to our best knowledge, new state‐of‐the‐art results for the latter.Moreover, we apply methodology for explaining model predictions to assess whether predictions are carried out for the correct reasons. Implications for practice and/or policy: It is indeed possible to assess constructed responses for the demonstrated knowledge about energy physics in an analytic fashion using natural language processing.Transformer language models can outperform more specialized feature‐based approaches for this task in terms of predictive and descriptive accuracy.Co‐occurrences of different concepts within the same responses can lead models to learn undesired shortcuts which make them unstable. [ABSTRACT FROM AUTHOR]

Background: Although research on mathematics learning programs has taken off in recent years, little is known about how different person characteristics are related to practice behaviour with such programs. When implementing a mathematics learning program in the classroom, it might be important to know whether students with specific characteristics need more encouragement to make use of this learning opportunity. Objectives: Using a supply‐use model, we analysed the predictive power of students' cognitive characteristics (prior mathematics knowledge), personality traits (conscientiousness), motivational‐affective characteristics (mathematics self‐concept and mathematics anxiety), and family background characteristics (socioeconomic status and migration background) for practising with an adaptive arithmetic learning program. Methods: We used longitudinal data from 203 fifth graders from seven non‐academic‐track schools in Germany. Practice behaviour, measured by completed tasks in the learning program, was recorded weekly for every student over a period of 22 weeks. Results and Conclusions: The results of our multilevel analyses showed that mathematics anxious students practised less with the program. We did not find any relationship with the other characteristics. Takeaways: Our results suggest that mathematics anxious students need more encouragement when practising with a mathematics learning program; otherwise, they do not get the chance to benefit from the use. Lay Description: What is already known about this topic: The use of mathematics learning programmes in mathematics education has recently intensified.It is important that students practice with such learning programmes regularly over a longer period of time in order for them to achieve learning success.Students differ in their mathematics learning behaviour. What this paper adds: Little is known about how person characteristics are related to practice behaviour with mathematics learning programmes.Students may differ in their use of a mathematics learning programme, which is why cognitive characteristics, personality traits, motivational‐affective characteristics, and family background characteristics may affect students' practice behaviour. Implications for practice: Mathematics anxious students practiced less with a mathematics learning program, and need more encouragement to benefit equally from the implementation in school.Teachers should keep in mind that after the initial enthusiasm, practice with a programme may decrease over time, especially after school holidays. [ABSTRACT FROM AUTHOR]

Background: Computer‐based assessment allows for the monitoring of reader behaviour. The identification of patterns in this behaviour can provide insights that may be useful in informing educational interventions. Objectives: Our study aims to explore what different patterns of reading activity exist, and investigates their interpretation and consistency across different task sets (units), countries, and languages. Three patterns were expected: on‐task, exploring and disengaged. Methods: Using log data from the PISA 2012 digital reading assessment (9226 students from seven countries), we conducted hierarchical cluster analyses with typical process indicators of digital reading assessments. We identified different patterns and explored whether they remained consistent across different units. To validate the interpretation of the identified patterns, we examined their relationship to performance and student characteristics (gender, socio‐economic status, print reading skills). Results and Conclusions: The results indicate a small number of transnational clusters, with unit‐specific differences. Cluster interpretation is supported by associations with student characteristics—for example, students with low print reading skills were more likely to show a disengaged pattern than proficient readers. Exploring behaviour tended to be exhibited only once across the three units: It occurred in the first unit for proficient readers and in later units for less skilled readers. Major Takeaways: Behavioural patterns can be identified in digital reading tasks that may prove useful for educational monitoring and intervention. Although task situations are designed to evoke certain behaviours, the interpretation of observed behavioural patterns requires validation based on task requirements, assessment context and relationships to other available information. Lay Description: What is already known about the subject matter?: Students differ in how they read, comprehend and use digital information.Indicators from process data provide insight about how students engage with digital reading tasks. What does this paper add to the subject matter?: Based on multiple process indicators, a small number of clusters indicating different behavioural activity can be distinguished.These clusters can be described as on‐task, passive, hasty, exploring, disengaged, persistent and lost interest.A meaningful interpretation of the clusters must consider the requirements of the underlying tasks. Implications for practice and/or policy: Knowledge of how students engage with digital resources may provide useful feedback for teachers to guide students' learning or intervene when they struggle.Educational monitoring: The high comparability of country‐specific results suggests an invariant set of solution strategies in the digital reading assessment. [ABSTRACT FROM AUTHOR]

Background: The professional knowledge of pre‐service teachers is highly important for effective and successful teaching. In recent years, many research groups have been engaged in developing simulated classroom environments to capture especially the pedagogical knowledge (PK) of pre‐service teachers, neglecting the content‐related facets of professional knowledge such as pedagogical content knowledge (PCK). Objectives: In the present study, we describe the development of a simulated classroom environment—the Simulated Classroom Biology (SCRBio)—and provide evidence regarding its validity to assess pre‐service biology teachers' action‐oriented PCK in the area of evolution. Methods: This study examined the evidence supporting the validity of using the SCRBio to investigate action‐oriented PCK of pre‐service biology teachers. The (1) evidence based on test content (expert ratings) and the (2) evidence based on relation to other variables (known‐groups comparison) was obtained. We tested the SCRBio with N = 76 German pre‐service biology teachers. Results and Conclusions: Our results show the successfully operationalized PCK in the SCRBio through explicit allocation of specific misconceptions to each virtual student's answer and the valid measurement of pre‐service biology teachers' action‐oriented PCK. This results in a validated simulated classroom environment for pre‐service but also in‐service teachers. In the future, the SCRBio will be developed from an assessment instrument to a training tool to simulate explicit teaching situations. This allows to complement the predominantly theoretical components of university‐based teacher education with practice‐based simulated classroom environments. Lay Description: What is already known about this topic: The professional knowledge of pre‐service teachers is a prerequisite for quality teaching in the future, as well as student achievement.Simulated classroom environments are already being used, primarily to examine and train the pedagogical knowledge of pre‐service teachers.The action‐oriented character of simulated classroom environments can bridge the theory‐practice gap of university‐based education programs. What this paper adds: Description of an innovative simulated classroom environment—the Simulated Classroom Biology.Ability to capture several domains of professional knowledge in an action‐oriented setting.Validation of the Simulated Classroom Biology using various validity aspects.Implications of study findings for practitioners.Description of validation steps for developing simulated classroom environments.A validated simulated classroom environment is provided to capture various knowledge domains of professional knowledge in an actionable setting.The Simulated Classroom Biology can be adapted to new subjects and teaching topics by changing the content. [ABSTRACT FROM AUTHOR]

Background: Previous research has shown that teachers hold misconceptions about multimedia learning (e.g., multimedia instruction needs to be adapted to students' learning styles), which may be at odds with evidence‐based teaching. Objectives: Refutation texts are a classical method to reduce misconceptions and thus to stimulate conceptual change. We wanted to know whether making use of a computer algorithm to personalize refutation texts would best initiate teachers' conceptual change. Methods: We designed an online experiment, in which N = 129 in‐service teachers read either (1) expository texts (without direct refutation), (2) common refutation texts, or (3) personalized refutation texts. The teachers filled in a misconception questionnaire pre and post to assess their conceptual change. Results and Conclusions: Statistical analyses revealed that personalized refutation texts initiated the strongest conceptual change, which was driven by increased feelings of guilt and shame. Common refutation texts did not foster teachers' conceptual change as compared to expository texts. These findings indicate that refutation texts should be personalized for experienced practitioners such as teachers. Takeaways: Personalized refutation seems to be promising in the context of online teacher training programs. Further research should test to which extent the present findings also apply to other groups of experienced learners or practitioners. Lay Description: What is already known about this topic?: Teachers hold misconceptions about multimedia learning (e.g., learning materials should be adapted to students' individual learning styles, such as visualizers or verbalizers).Refutation texts, naming a commonly held misconception, disproving it and introducing a scientific explanation, are a common means to reduce misconceptions.Personalization fosters learning by drawing the learner's attention toward the discrepancy between their own beliefs and the learning material, further creating an impasse experience.Said impasse experience may trigger teachers' conceptual change, as, for teachers' conceptual change, a certain degree of discomfort is required. Yet, anger, caused by lessoning teachers on their topic may cause repulse and hamper learning. What this paper adds?: With a computer algorithm, we can efficiently personalize refutation texts by automatically matching them to teachers' answers in a pre‐test. Such a personalized refutation instruction may especially foster conceptual change.Within a randomized experiment, the personalized refutation instruction worked best compared to common refutation texts and expository texts.Feelings of guilt and shame moderated the effect of a personalized refutation, as teachers felt more addressed in their misconceptions and thus experienced the required impasse experience.Feelings of anger did not play an important role within our experiment. The implications of study findings for practitioners: Computer algorithms enable efficient personalization of instruction to better deal with heterogeneous groups of learners (e.g., with big differences in prior knowledge or experience, such as in the case of in‐service teachers).Refutation texts work better for teachers when they are personalized. Common refutation texts do not work better than expository texts.An advantage of digital instruction is the use of algorithms to efficiently personalize instructions even for larger groups. [ABSTRACT FROM AUTHOR]

The study presented in this paper aimed to examine the effect of visual and verbal cognitive style on learning from different types of visualization and modalities of explanatory text. Learning materials in the form of either computer‐based animation or a series of static pictures with written or spoken explanations were presented to 197 students. We found that a more developed visual cognitive style was related to a better learning outcome, when learning from a combination of static pictures and written text. Higher developed visualizers achieved poorer learning outcomes when learning with an animation and written text. The results are partially in line with an ability‐as‐compensator effect and the expertise reversal effect. Additionally, we found a modality effect as the versions with spoken text provided better results on learning outcome than the versions with written text regardless of the prominence of visual cognitive style. No significant interaction effects were found regarding verbal cognitive style. Lay Description: What is already known about this topic: Combining text and pictures supports learning and deepens understanding.Learning differs with respect to individual differences and the type of visualization.Visualizers profit from pictorial information more than verbalizers.Unclear what type of visualization and modality is beneficial to visualizers. What this paper adds: Influence of cognitive style on learning differs with regard to text modality.Visual cognitive style moderates multimedia learning with written text.Higher visual cognitive style leads to better learning with pictures and written text.Higher visual cognitive style leads to poorer learning with animations and written text. Implications for practice and/or policy: Contributes to empirical findings on how people learn from text and visuals.Broadens discussion on cognitive style and its impact on the learning process.Modality of the explanatory text has an impact on the learning outcome.Implement the written modality with caution during multimedia learning. [ABSTRACT FROM AUTHOR]

According to the personalization principle, addressing learners by means of a personalized compared to a nonpersonalized message can foster learning. Interestingly, though, a recent study found that the personalization principle can invert for aversive contents. The present study investigated whether the negative effect of a personalized message for an aversive content can be compensated when learners are in a happy mood. It was hypothesized that the negative effect of a personalized compared to a nonpersonalized message would only be observable for participants in a sad mood, while for participants in a happy mood a personalized message should be beneficial. A 2 × 2 between‐subject design with mood (happy vs. sad) and personalization (personalized vs. nonpersonalized message) was used (N = 125 University students). Mood was experimentally varied prior to learning. Learning outcomes were measured by a retention and a transfer test. Results were essentially in line with the assumption: For participants in the sad mood condition, a negative effect of a personalized message was observable for retention and transfer. For participants in the happy mood condition, a positive effect of personalized message was observable for retention, but no effect for transfer. Note that the manipulation check measure for the mood induction procedure did not detect differences between conditions; this may be due to a shortcoming of the used measure (as indicated by an additional evaluation study). The study emphasizes the importance to consider the inherent emotional content of a topic, such as its aversive nature, since the emotional content of a topic can be a boundary condition for design principles in multimedia learning. The study also highlights the complex interplay of externally induced and inherently arising emotions. Lay Description: What is already known about this topic?: Multimedia learning is usually fostered by a personalized message (e.g., using personal pronouns) compared to a nonpersonalized message.A personalized message can be harmful when the topic is about a serious disease.Little is known about boundary conditions for when a personalized message can be harmful. What this paper adds?: A happy mood can help processing a personalized message about a serious disease.For learners in a happy mood, such a personalized message was beneficial.For learners in a sad mood, such a personalized message was harmful. Implications for practice and/or policy: The emotional content of a topic should be considered when applying design principles.Unpleasant contents may reverse well‐established multimedia design principles.A positive mood is promising to counteract the reversing impact of unpleasant contents. [ABSTRACT FROM AUTHOR]

Background: Past research has shown that seductive details (i.e., interesting, but irrelevant adjuncts in learning materials) hamper learning in short, instructor‐paced learning sessions through impaired cognitive processing. Objectives: We integrate theory and research on multimedia learning and self‐control to test whether detrimental effects of seductive details also apply to longer and strenuous learning sessions (e.g., online lectures), in which there is greater need for self‐control. Methods: A total of N = 194 students studied five chapters in a digital learning unit about chemistry either (1) without seductive details, or (2) with seductive details but without being informed about their irrelevance for the learning goal, or (3) with seductive details while being informed about their irrelevance. To assess learning outcomes, all students completed the same posttests for recall and transfer of knowledge. Results and conclusions: For students who were uninformed about the details' irrelevance, the seductive details impeded learning outcomes not just overall, but also in the final phase of prolonged studying (i.e., when the willingness to self‐control is reduced). The latter effect was mediated through a reduced positive affect. Implications: The seductive details effect seems to generalize to prolonged learning sessions, where students may start to dislike the seductive details. Lay Description: What is already known about this topic?: Seductive details (i.e., interesting, but irrelevant adjuncts) hamper learning in short instructor‐paced learning sessions through impaired cognitive processing.However, they also have beneficial effects on affective factors.These benefits did not translate to better learning outcomes in past research.It is unknown whether the affective benefits could translate to better learning outcomes in longer, more self‐paced learning sessions (e.g., digital learning sessions), with higher self‐control demands. What this paper adds?: The harmful effect of seductive details on learning also appears in extended and self‐paced digital learning sessions.However, seductive details hampered learning only when students perceived them as relevant. The implications of study findings for practitioners: Seductive details should be used very cautiously or even be excluded from instructional material.If it is impossible to dismiss the seductive details in actual learning materials, students should be informed about the details' irrelevance for learning to avoid their potential negative effects. [ABSTRACT FROM AUTHOR]

Metacomprehension as reflected in judgements of one's learning is crucial for self-regulated study, yet their accuracy is often low. We investigated text difficulty as a constraint on metacomprehension accuracy in text learning. A total of 235 participants studied a 10-section expository text and afterwards took a knowledge test. They made judgements of learning after each section. Sections were of high, medium or low difficulty; we manipulated between participants the order of difficulty levels across sections. In blocked orders, texts in each block (sections 1-4; sections 5-6; sections 7-10) were of the same difficulty level. In mixed orders, difficulty varied throughout the learning unit either from easy to difficult or from difficult to easy. Our general tenet was that orders would trigger different extents of experience-based processing and thus influence metacomprehension accuracy to different degrees. As hypothesized, accuracy was higher for blocked difficulty orders. Late-section judgement magnitude decreased more strongly in the blocked groups. At the same time, late-section judgement accuracy was higher in the blocked group. We discuss implications and limitations of the influence of fluctuations in text difficulty on judgements of learning accuracy together with some avenues for further research. Lay Description What is already known about this topic? Metacomprehension as reflected in judgements of one's learning (JOL) is crucial for effective self-regulated study., JOL accuracy is often low., Text difficulty appears to bias metacomprehension in topically non-coherent series of texts., What this paper adds? This paper establishes text difficulty as a constraint on metacomprehension accuracy in topically coherent texts., This paper explains text difficulty effects as different relative weights of experience-based and theory-based processing, respectively., Implications for practice and/or policy: Taking systematic text difficulty effects into account may help avoid unintended adverse effects of difficulty order on metacomprehension accuracy., Arranging difficulty levels block-wise may enhance experience-based processing and thus judgement accuracy., Additionally, with topically coherent texts, increasing difficulty across texts benefits performance in a later knowledge text. [ABSTRACT FROM AUTHOR]

The current study validated the proposed structure of relationships among outcome‐related achievement emotions (pride and anxiety), their cognitive predictors (appraisals und online‐learning‐related self‐efficacy), and learning outcomes (competence gain and satisfaction) in the context of online learning in higher education. On the basis of a sample of 220 university students, we applied structural equation modeling. We found that high self‐efficacy was related to greater perceived control, which was positively associated with interest in online learning. Self‐efficacy showed positive relations with pride and negative relations with anxiety. Interest was positively associated with pride, competence gain, and satisfaction. Both outcomes also showed direct positive relations with pride, whereas anxiety was negatively associated with satisfaction only. Furthermore, three substantial indirect effects of self‐efficacy on the two outcomes were revealed. The findings supported the role of anxiety and pride as mediators between cognitions and learning outcomes although also direct relationships between interest and learning outcomes were observed. Lay Description: What is currently known about the subject matter? achievement emotions are mediators between learner's appraisals and learning outcomeshowever, little research on emotions as antecedents of achievement in academic online learningfew studies differentiated effects of dispositional and contextual appraisalsregarding emotions, pride as affective antagonist of anxiety remains underresearched What does the paper add to the topic? The manuscript examines antecedents and outcomes of pride and anxiety as antagonistic emotionsdifferentiates the interplay among three kinds of appraisals on emotionsinvestigates differential effects of emotions on affective and competence‐based outcomesexamines direct and indirect associations between the study variables using latent modeling Implications for practitioners? Lecturers should address rather students' positive emotions like pride than anxiety in online learning settingsfoster learners' interest to enhance pride, as well as outcomes like satisfaction and competence gainstrengthen students' self‐efficacy to decrease anxiety that is linked to lower satisfaction [ABSTRACT FROM AUTHOR]

Self‐generated learning (SGL) activities are characterized as an active learning strategy that functions as a support for deeper comprehension. However, the question arises which factors could be essential to fully exploit the effectiveness of SGL activities. One possible factor may be the emotional state of learners during learning. Because different emotional states are associated with different styles of information processing, in turn, they may support learning with SGL activities. Consequently, this study addresses learning with a type of SGL activities, answering elaborative interrogations, and the impact of learners' emotional states. German students (N = 123) were assigned to one of four conditions, resulting from a 2 × 2 design with instructional material (elaborative interrogations vs. no elaborative interrogations) and emotional state (positive vs. negative) as independent variables. Results showed that learners learning with elaborative interrogations experienced the instructional material as more difficult than without elaborative interrogations. Learning with them led to a better transfer learning outcome of concepts that had to be generated by interrogations (not for concepts that were already readable in the text) and had no effect for retention. Unexpectedly, neither an influence of the learners' emotional state nor an interaction of both independent variables could be shown. Lay Description: What is currently known about this topic: So‐called SGL activities force the learner to deal with instructional material more actively, which in turn should result in better comprehension of the content.Answering elaborative interrogations, one type of SGL activity, prompt learners to elaborate on information that are essential to understand the learning issue.Different emotional states are associated with varied information processing: positive enhances flexible thinking and motivation to learn; negative supports rather rigid learning strategies with just enough effort to learn the issue. What this paper adds: The combination of this both possibly influencing factors: the effectiveness of answering elaborative interrogations might be affected by learners' emotional state.Learners with a positive emotional state should profit from learning with the additional challenging task (assessed by knowledge tests).Learners with a negative emotional state should not profit from this learning strategy to the same extent than the learners with the positive but would rather benefit through the use of text‐only.Motivation of learners could play a mediating role. Implications for practice and/or policy: It is important to know under which conditions the effectiveness of SGL activities is enhanced or even not.Accordingly, other SGL activities have to be investigated, too.In school context, teachers could get a better idea under which conditions which learning strategy is effectiveLearners can profit from knowing which learning strategy best suits according to the learning issue [ABSTRACT FROM AUTHOR]

If learning materials are presented in either a conversational or formal language style, people will process them differently. This study reports an experiment in which 64 high school students watched an educational video in a massive open online course scenario in which the instructions were phrased either conversationally or formally. The video demonstrated and explained the psychological McGurk effect. After watching the video, participants performed a transfer task. Learning outcomes were assessed and answers were analysed by using Linguistic Inquiry and Word Count. Results showed better learning outcomes for participants in the conversational (vs. formal) condition. Participants in the formal (vs. conversational) condition referred more to others in their answers. Implications for the design of massive open online courses are discussed. Lay Description: What is currently known about the subject matter: Language styles can affect individual dealing with learning materials.Addressing learners directly in the learning material can support transfer performance.Massive open online courses (MOOCs) have become the most prominent form of online learning in higher education.High school students (future students) are a new group of MOOC users. What this paper adds: MOOCs contain a social dimension, which might be crucial for individual learning.Most MOOCs do not ask for transferring knowledge of just learned materials.Conversational language in the instruction led to better transfer performance and more self‐directedness.Instructional language styles affect individual dealing with learning materials in a MOOC scenario. Implications of study findings for practitioners: MOOCs should apply conversational language style instructions for deeper learning.Conversational language style instructions and transfer tasks are easy to implement in already existing MOOCs.Being personally addressed in a MOOC might be a key for enhancing learners' involvement. [ABSTRACT FROM AUTHOR]

Abstract: In organizations, the assessment of mental abilities is a common way to predict learning success. This paper analyses the effect of general mental ability on skill retention and examines the relationship between refresher interventions and general mental ability in terms of skill retention. Two hundred sixty‐six adult participants were trained to perform a complex cognitive skill in a simulated chemical processing plant (Week 1). After 1 week, 158 participants received intermediate computer‐assisted refresher intervention training in which the skill was applied (Week 2; 108 received no intervention). Finally, participants had to recall (perform) the learned skill after 2 weeks (Week 3). Results show that general mental ability alone affects skill retention with small effect sizes and that refresher interventions affect skill retention positively for low and high general mental ability levels. The findings suggest that persons with low and high general mental abilities benefit equally from refresher interventions in order to maintain complex cognitive skills. [ABSTRACT FROM AUTHOR]

The Cognitive-Affective Theory of Learning with Media postulates that affective factors as well as individual learner characteristics impact multimedia learning. The present study investigated how experimentally induced positive and negative emotions influence multimedia learning and how learner characteristics moderated this impact. Results showed that the group with the negative emotion induction outperformed the group with the positive emotion induction with regard to learning outcome. Cognitive resources (working memory capacity, prior knowledge) and openness to experience were significant predictors for learning. In addition, learners with highest prior knowledge or working memory capacity could compensate the emotional impact on learning. Neuroticism enhanced the emotional impact on learning outcome as a moderator. Lay description What is already known about this topic: Emotions and learner characteristics are assumed to influence multimedia learning., There are inconsistent results on emotional impact on multimedia learning., Cognitive resources were shown to be predictors of learning outcomes., There are inconsistent results on how much learners' personality predicts learning., What this paper adds: Negative emotions can lead to higher learning outcomes than positive emotions., Cognitive resources are significant predictors for learning outcomes., Openness to experience predicts learning outcomes., Neuroticism enhances the emotional impact on multimedia learning., Implications for practice and/or policy: Learner characteristics and emotions influence multimedia learning., A very positive emotional state can be harmful to learning., Learners' personality can enhance emotional impact on multimedia learning., Learning environments should be designed to attract learners' curiosity. [ABSTRACT FROM AUTHOR]

This paper presents an original approach to designing social media that support informal learning in the digital workplace. It adapts design-based research to take into account the embeddedness of interactions within digitally mediated work-based contexts. The approach is demonstrated through the design, implementation, and evaluation of software tools supporting a particular type of informal learning called knowledge maturing. The paper: introduces and presents the rationale for, and concept of, knowledge maturing; presents a new design methodology for developing social media that support informal learning and knowledge maturing; focuses on one prototype, for 'people tagging for organisational development', that was produced by the methodology (and concisely describes two others); presents the formative evaluation of the highlighted prototype; and finally, discusses the implications and insights arising from this work. [ABSTRACT FROM AUTHOR]

A brief, problem-oriented phase such as an inventing activity is one potential instructional method for preparing learners not only cognitively but also motivationally for learning. Student teachers often need to overcome motivational barriers in order to use computer-based learning opportunities. In a preliminary experiment, we found that student teachers who were given paper-based course material spent more time on follow-up coursework than teachers who were given a well-developed computer-based learning environment (CBLE), leading to higher learning outcomes. Thus, we tested inventing as an instructional method that may help overcome motivational barriers of teachers' use of computer-supported tools or learning environments in our main experimental study (N = 44). As a computer-based environment, we used the 'Assessment of Learning strategies in Learning journals'. The inventing group produced ideas about criteria to evaluate learning strategies based on student cases prior to the learning phase. The control condition read a text containing possible answers to the inventing problem. The inventing activity enhanced motivation prior to the learning phase and assessment skills as assessed by transfer problems. Hence, the inventing activity prepared student teachers to learn from a CBLE in a motivational as well as cognitive way. [ABSTRACT FROM AUTHOR]

Abstract The Second Information Technology in Education Study — Module 2 (SITES-M2) in Germany investigated 12 cases of innovative pedagogical practice using technology (IPPUT) in primary, lower and upper secondary schools. One theme that emerged from the analysis of these cases was students' cooperation. It seems that the co-occurrence of ICT-use and students' cooperation and collaboration is not accidental. The focus of this paper is an analysis and classification of the students' cooperation identified in the IPPUTs. [ABSTRACT FROM AUTHOR]