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Paper-and-pencil learning and testing are gradually shifting to computerized environments. Cognitive and metacognitive researchers find screen inferiority compared to paper in effort regulation, test performance, and extent of overconfidence, in some cases, with unknown differentiating factors. Notably, these studies used reading comprehension tasks involving lengthy texts, which confound technology-related and cognitive factors. We hypothesized that the medium provides a contextual cue which leads to shallower processing on screen regardless of text length, particularly when task characteristics hint that shallow processing is legitimate. To test this hypothesis, we used briefly phrased yet challenging problems for solving on screen or on paper. In Experiment 1, the time frame for solving the problems was manipulated. As with lengthy texts, only time pressure resulted in screen inferiority. In Experiment 2, under a loose time frame, the same problems were now framed as a preliminary task performed before a main problem-solving task. Only the initial task, with reduced perceived importance, revealed screen inferiority similarly to time pressure. In Experiment 3, we replicated Experiment 1's time frame manipulation, using a problem-solving task which involved reading only three isolated words. Screen inferiority in overconfidence was found again only under time pressure. The results suggest that metacognitive processes are sensitive to contextual cues that hint at the expected depth of processing, regardless of the reading burden involved. [ABSTRACT FROM AUTHOR]

This commentary describes the contribution of each individual paper to our understanding of engagement, as well as evaluating whether together these papers achieve the editor's goal of developing an emerging consensus on the meaning and measurement of this construct. Individually these papers extend our understanding of specific aspects of engagement and contextual effects on engagement in important ways, but together have fallen short of the ambitious goal of bringing the different conceptualizations, measurements, and methods into closer alignment. The commentary concludes with a discussion of three issues that need to be addressed in future research on engagement including: 1) examining the degree of overlap between engagement and self-regulation, 2) more clearly articulating the role of affect in engagement, and 3) describing the crucial role of goals in engagement and learning. [ABSTRACT FROM AUTHOR]

This paper investigates whether prompting students to draw their own visual representations enhances students’ learning from technology-based instructional activities with visual representations. Seventy-two undergraduate students were randomly assigned to receive an educational technology with (1) drawing prompts throughout instruction, (2) drawing prompts before and after instruction, or (3) no drawing prompts. We assessed learning outcomes with respect to instructional effectiveness and efficiency using immediate and delayed posttests. Results on instructional efficiency showed a significant advantage for drawing prompts. Results on instructional effectiveness showed an advantage at the delayed posttest for drawing prompts provided throughout instruction, compared to prompts before and after. Qualitative analyses suggest that adding drawing prompts throughout instruction promotes drawing quality. In sum, our findings expand theory by suggesting that drawing prompts facilitate visual sense making of concepts shown in visual representations. Furthermore, we provide practical recommendations on how best to implement drawing prompts with technology-based instructional activities. [ABSTRACT FROM AUTHOR]

This paper reports on a study in which students used agent-based computer models to learn about complex systems ideas of relevance to understanding climate change. The experimental condition used a Productive Failure (PF) learning design in which ninth grade students initially worked with agent-based computer models to solve challenge problems followed by teacher instruction about targeted climate and complexity ideas. In contrast, the comparison condition employed a Direct Instruction (DI) learning design in which the teacher instruction was provided initially, followed by the students working on the same computer models and challenge problems as the experimental group. The students in the PF group scored significantly higher on the post-test on measures of climate and complex systems explanatory knowledge and near and far knowledge transfer. Theoretical and practical implications of these findings are considered. [ABSTRACT FROM AUTHOR]

In this commentary, the articles of the special issue will be discussed in relation to how they address classroom dialogue to promote new forms of education. The articles present possibilities to rethink learning and education through the analysis of classroom dialogue. The commentary will address how the outcomes of the included papers lead to reflections about how practitioners and researchers may rethink school and society in a more emancipating, revolutionary, and transformative way. [ABSTRACT FROM AUTHOR]

The article offers information on the European Association for Research on Learning and Instruction (EARLI). Topics include promoting an active educational research culture; encouraging systematic exchange and discussion on diverse instructional and educational research; and also mentions importance to education such as state-of-the-art papers, meta-analytic research reviews, narrative reviews, best-evidence syntheses, research critiques, forum papers and methodological and thematic reviews.

In my commentary, I discuss the historical origins of the Fredricks et al. 3 dimensions of engagement, provide some critical assessment of the individual papers in this special issue, and lay out the argument for renewed theoretical analysis of the concept of engagement. Specifically, the importance of theoretical work related to the definitions of engagement, dimensionality questions, and origins of, and influences, on engagement are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a theoretical framework on how school policy can promote student learning. School policy is considered to have an indirect effect on student achievement by changing school stakeholders' actions toward improving the School Learning Environment (SLE) and teaching practice. A reciprocal relationship between school policy and stakeholders' actions is also considered. A longitudinal study was conducted to test the framework's main assumptions. A stratified sample of 64 primary schools was selected and students' achievement in Mathematics at the beginning of Grade 4 and at the end of the next three consecutive school years was measured, alongside the school policy and teachers' actions with regards to issues associated with teaching and the SLE. The results of multilevel structural equation modelling analyses supported the main assumptions of the framework. Implications for the development of school policy are drawn and suggestions for further research are provided. [ABSTRACT FROM AUTHOR]

Recent developments in educational technologies have provided a viable solution to the challenges associated with scaling personalised feedback to students. However, there is currently little empirical evidence about the impact such scaled feedback has on student learning progress and study behaviour. This paper presents the findings of a study that looked at the impact of a learning analytics (LA)-based feedback system on students' self-regulated learning and academic achievement in a large, first-year undergraduate course. Using the COPES model of self-regulated learning (SRL), we analysed the learning operations of students, by way of log data from the learning management system and e-book, as well as the products of SRL, namely, performance on course assessments, from three years of course offerings. The latest course offering involved an intervention condition that made use of an educational technology to provide LA-based process feedback. Propensity score matching was employed to match a control group to the student cohort enrolled in the latest course offering, creating two equal-sized groups of students who received the feedback (the experimental group) and those who did not (the control group). Growth mixture modelling and mixed between-within ANOVA were also employed to identify differences in the patterns of online self-regulated learning operations over the course of the semester. The results showed that the experimental group showed significantly different patterns in their learning operations and performed better in terms of final grades. Moreover, there was no difference in the effect of feedback on final grades among students with different prior academic achievement scores, indicating that the LA-based feedback deployed in this course is able to support students' learning, regardless of prior academic standing. • A learning analytics-based system was used to deliver process feedback to students in a course. • The learning-analytics feedback employed multimodal data, such as log data from the learning management system and e-book. • The pattern of self-regulated learning differed between students who had received the feedback, and those who had not. • Final course marks were significantly higher for students who had received the feedback, compared to those who had not. • There was no difference in impact of the LA-based, process feedback among students with different program entry scores. [ABSTRACT FROM AUTHOR]

This article comments on the five papers published in this special issue on understanding and measuring emotions in technology-rich learning environments. The articles identify a number of emotions that frequently occur in digital learning environments across different tasks, goals, populations, and subject matters. The Control Value Theory of achievement emotions unifies the research reported in the articles, whereas social emotions surface in contexts where there are significant social interactions, such as group learning or the training of medical students. The emotions that were detected and tracked in the reported studies rely on self-reports of learners and judges who observe them. This commentary identifies a number of limitations of the studies that will hopefully stimulate future research. Researchers are encouraged to collect (1) larger sample sizes, (2) longer interventions with learning technologies, (3) physiological, multimodal, and behavioral signatures of emotions to complement the subjective judgments, (4) more precise timing and transitions between emotions to uncover emotion dynamics, (5) assessments of nonlinear relations between variables, and (6) interventions designed to regulate and productively respond to learner emotions. • This article comments on the articles in this special issue on emotions in technology-rich learning environments. • There are emotions that frequently occur across different tasks, goals, populations, and subject matters. • The Control Value Theory of achievement emotions unifies the research but social emotions sometimes surface. • This article recommends six directions for future research on emotions in technology rich environments. [ABSTRACT FROM AUTHOR]

What is the affective quality of specific design features of game characters? The Integrative Model of Emotion in Game-based Learning (EmoGBL) describes common mechanisms of how emotion and learning processes interact to foster specific learning outcomes. In the present paper, we asked how color, shape, expression, and dimensionality of game characters induce emotions in digital games for learning. We investigated learners' perception of the affective quality of these four different visual design features for adults and adolescents using a forced choice paradigm (studies 1–3), as well as the PANAS-X and qualitative measures (study 4). Participants were shown a series of game characters and were asked to report their emotional response. Results show the relative contribution of the four visual attributes on players' perception of affective quality, with the visual design features of expression and dimensionality having the strongest effect, color a medium-sized effect, and shape a small to medium-sized effect. • The affective quality of design features of characters for learning games was investigated. • Immersion (Immersive 3D vs. Desktop 2D) had a large effect on affective arousal. • Expression (sad v. neutral v. happy) had a large effect on affective arousal. • Color (cold v. warm) had a medium-sized effect on affective arousal. • Shape (square v. round) had a small to medium-sized effect on affective arousal. [ABSTRACT FROM AUTHOR]