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Background: Game‐based learning can frame problem‐solving as a sense‐making experience with domain‐specific tasks for school students. However, multiple challenges arise when trying to support learners in such a complex, problem‐oriented learning environment. Objectives and Methods: With an architecture‐themed mathematics learning game, we conducted two mixed‐method studies to explore the impact and design of game‐based mathematical experience on the math problem‐solving performance of middle school students. Results and Conclusions: The study findings suggested a positive impact of game‐based math experience on math problem‐solving for middle school students. Problematization‐oriented game‐based math tasks with structuring features enhanced students' reasoning with problems and channelled it to doing mathematics. Takeaways: The current research findings support the initiative to frame learning as a sense‐making experience with domain‐specific tasks and inform the design of game‐based mathematical experience and learning support. Lay Description: What is already known about this topic: Realistic mathematical practices frame learning as a sense‐making experience.Challenges arise when involving learners in realistic mathematical experiences driven by domain‐specific tasks. What this paper adds: Game‐based simulation of math tasks framed learning as sense‐making experience.Game‐based math experiencing promoted math contextual problem‐solving performance.Structuring features enhanced problematized experiencing with math tasks. Implications for practice and/or policy: Teachers can integrate and facilitate game‐based math experiencing in class.Efforts should be made to make game‐based math tasks meaningful for students. [ABSTRACT FROM AUTHOR]

Background: Even though monitoring and control enactment are key aspects of self‐regulated learning (SRL), Adaptive learning technologies (ALTs) may reduce the need for learners to monitor and control their learning. Personalized dashboards are effective in supporting learners' monitoring and can potentially support control behaviour. Allowing learners to enact control over their learning process, seems to hold potential for increasing their motivation. Objectives: Therefore, this study's aim was to investigate the relation between control enactment and motivation. We examined how learners enacted control while learning with an ALT with personalized dashboards and examined the relation between learners' enactment of control and their motivation. Methods: Seventy‐eight primary school learners (Grade 5) participated. During the lesson, learners worked on mathematics in the ALT and concurrently were shown personalized visualizations that supported monitoring and enacting control over their learning process. Learners could enact control to change problems' difficulty to easy, medium, or hard. Motivation was measured before and after learning. Results: The SEM analyses showed that how learners enacted control was related to their motivation. Choosing difficult problems was related to more enjoyment and competence while choosing easy problems related to more pressure and tension. Learners who complied with the suggested difficulty level experienced less choice, but also less pressure/tension and more enjoyment and competence. Conclusions: These results provide avenues to account for broader learner characteristics like SRL and motivation to optimize learning. This way, hybrid systems in which control enactment is a shared responsibility of the system and learner, can be improved to support SRL development. Lay Description: What is currently known: Monitor and control enactment are key aspects of self‐regulated learning (SRL).Adaptive learning technologies may reduce the need for learners to monitor and control their learning.Personalized dashboards support learners' monitoring behaviour and can potentially also support control enactment.Enactment of control could positively affect learners' motivation. What does this paper add: There is a large variation in how learners enact control and whether they comply with the scaffold.Learners who chose more difficult problems experienced more enjoyment, while learners choosing easy problems, experienced more pressure.Learners complied with the scaffold, experienced less choice, but also less pressure and more enjoyment.This study provides avenues to account for broader learner characteristics like SRL and motivation to optimize learning. Practical implications: Support control enactment by actively involve learners in choice during the learning process.Offer monitor and enactment in conjunction, as learners can only make well‐founded choices if they can monitor their learning process.Intrinsically and extrinsically motivated learners showed different choice patterns and learning experience.It is important to have an understanding and monitoring of learners' motivation. [ABSTRACT FROM AUTHOR]

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: Measurement of students' self‐regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and need careful interpretation. Precise and interpretable evaluation of self‐regulation skills in a normal K‐12 classroom thus poses a challenge. Objectives: The present study proposes and explores a learning analytics method of combining aptitude and event measures to evaluate student's self‐regulation skills. Methods: An explorative learning analytics study was conducted in a junior high school mathematics class (N=20 students), using a three‐lesson intervention with digital learning materials. Students first assessed their self‐regulation skills with a self‐report questionnaire, after which trace logs and observations of student behaviour were collected. Learning sessions were extracted from trace logs, clustered, and linked to learning strategies. Students were clustered by the self‐report results and learning behaviour profiles. Session clusters, student behaviour clusters and assignment grades were also tested for association. Results and Conclusions: The detected session and student behaviour types were linked to learning tactics and strategies found in prior studies. Additionally, association was found between self‐reported self‐regulation skills and the student behaviour obtained from trace logs. Implications: The results demonstrate the feasibility of concurrently using aptitude and event measures on a classroom scale, providing teachers with a tool to evaluate and support self‐regulated learning. Combined with further measures like predictive learning analytics, teachers can obtain an early and highly interpretable picture of at‐risk students in their classes. Lay Description: What is already known about this topic: Active monitoring of self‐regulated learning skills is primarily standard in large courses and MOOCs.Aptitude measures for self‐regulated learning are commonplace but considered subjective.Event measures for self‐regulated learning are precise but require additional interpretation to link behaviour to learning.Prior studies demonstrated approaches to analysing student behaviour from trace logs. What this paper adds: Both measure types can be used to monitor student behaviour in a classroom actively over a low number of sessions.Event and aptitude measures complement each other by exposing discrepancies between students' behaviours and actions.Measuring self‐regulated learning actively in class can yield valuable information to select appropriate interventions. Implications for practice: Integrating aptitude and event measures in digital learning materials gives teachers quickly actionable information about student behaviour.Approaches to integrating learning analytics for self‐regulated learning in digital learning materials should be further developed.Data‐informed choice of self‐regulated learning interventions should be explored further. [ABSTRACT FROM AUTHOR]

One of the golden rules in instructional design methods is to optimize the use of working memory capacity and avoid cognitive overload. The study of cognitive load has historically relied on one's introspection. However, it is difficult to capture changes in cognitive load levels during learning sensitively. This paper suggests an approach to investigating dynamic changes in cognitive load by using a pupillometry. With the method, this study explores the effects of learners' prior knowledge and task complexity on cognitive load. An experiment was conducted on two groups of students (N = 19) with distinct levels of prior knowledge. In the experimental session, participants watched a video lecture on a mathematics proposition, while being eye‐tracked. The lecture consists of sections, which can be either a high task complexity or a low task complexity based on elements they have. Pupil dilations acquired in each section were used to explore the time course of cognitive load. To formulate cognitive load patterns, a time‐series clustering was used. The research conducted a chi‐square analysis to test differences in cognitive load patterns by prior knowledge and task complexity. Results show that pupil dilation patterns can be applied to monitor changes in cognitive load during learning. What is already known about this topic? Cognitive load is a dynamic construct so that it can be changed during learning.Pupil dilation is a valid indicator of showing changes in cognitive load during learning. What this paper adds? The study proposes a novel method to capture dynamic changes in cognitive load in video‐based learning by using a time‐series clustering.The proposed approach detected the changes in cognitive load as a function of learner's level of prior knowledge and task complexity in learning.The proposed approach found seven different types of cognitive load patterns during learning. Implications for practice and/or policy: The use of temporal approach can be a technique to capture dynamics of cognitive load learners are experiencing during learning. [ABSTRACT FROM AUTHOR]

With facilitation of advanced technologies, design and application of smart become promising research issues in education. Although it is potential for students to learn geometric in authentic contexts, there were still lack of studies addressing smart learning issue in authentic context for geometry. This study aim to propose an app, called SmartUG, to support students smartly to consolidate geometry understanding and learning through enriching experience of exploring and applying related geometry surrounding. There were four smart mechanisms proposed in SmartUG (direction guidance, learning progress, object recognition and answer feedback) to guide students' measuring and applying geometry smartly and meaningfully in authentic contexts. A total of 83 fifth‐grade students participated in this experiment and were divided into three groups, an experimental group that learned with smart mechanisms, a control group that learned without smart mechanisms and a traditional control group that learning with traditional teaching approach. Basically, experimental group outperformed control group and traditional teaching group in term of geometry ability and estimation ability, which means students benefited from proposed SmartUG. Moreover, students showed positive attitude and high intention to use toward SmartUG. Students should be provided more chances to learn geometry smartly in authentic contexts with SmartUG. It is potential to future studies to implement more smart mechanisms to support students learning in authentic contexts. Moreover, the learning system can get smarter and smarter when the learning system gets more and more input data from students' use. Lay Description: What is already known about this topic: Geometry is important and strongly related to our surroundings.Students have few chances to learn Geometry through practicing in authentic contexts.Innovative technologies are potential to be utilized to facilitate smart learning. What this paper adds: Proposed a framework of smart mechanisms to support learning Geometry in authentic context.Utilized innovative technologies to facilitate smart learning in authentic context. Implications for practice and/or policy: Smart learning in authentic context helped improving students' motivation and achievements.The proposed smart mechanisms are effective to support smart learning.The smart mechanisms can be implemented not only for Geometry but also other subjects. [ABSTRACT FROM AUTHOR]

The overarching goal of this research project is to develop a set of theoretical and empirical based design principles to support student engagement in flipped mathematics learning. We used a design‐based research approach in which a series of studies was conducted in a secondary school. First, an analysis of practical problems was performed via exploratory studies (Studies 1A and 1B), randomized experiments (Studies 2A and 2B), and a literature review (Study 3). Second, a basic flipped lesson prototype was developed based on our empirical findings and relevant theoretical work of student engagement and self‐determination theory. Third, we refined and evaluated our practice with two empirical studies (Studies 4 and 5). Finally, we reflected on each stage of our research project to produce a set of design principles for future practice. This study thus contributes to our knowledge of methods to support student engagement in flipped mathematics learning. Lay Description: What is already known about this topic: Flipped learning can increase student achievement in mathematics education.After flipping, studies reported non‐significant or even negative results in terms of student engagement.Little work has been done to support student engagement in flipped learning. What this paper adds: This study investigated methods to support student engagement in flipped mathematics learning.A 2‐year design‐based research was conducted consisting of a series of five studies.Theoretical work of student engagement and self‐determination theory were drawn. Implications for practice and/or policy: The use of group competitions increased student engagement in flipped mathematics learning.Peer interaction inside the classroom fostered students' cognitive engagement.Design principles are proposed to support student engagement in future practice.The principles cover five major instructional activities of flipped learning. [ABSTRACT FROM AUTHOR]

This study investigates the effect of E‐learning (EL), blended learning (BL) and flipped learning (FL) approaches on the mathematics achievement, self‐regulation and mathematics self‐efficacy. Participants consist of 163 first‐year students attending an associate degree program (a 2‐year program) of a state university. The EL, BL and FL settings in the research were designed based on Merrill's 'First Principles of Instruction Design Theory'. In the research in which a quasi‐experimental pre‐test–post‐test research design was used, the data were obtained by means of mathematics achievement test, self‐regulation and self‐efficacy questionnaires. The experimental results showed that the mathematics achievement post‐test scores of FL students were significantly higher than those of the students of EL and BL. No significant difference was found between BL and EL settings. In addition, FL students showed significantly higher self‐regulation and mathematics self‐efficacy than the other groups' students. According to these results, it can be said that the usage of FL approach in mathematics courses has a positive effect on the learning process of students. It is expected that the findings will be helpful in the future design and implementation of mathematics courses at vocational colleges. Lay Description: What is already known about this topic?: The flipped learning approach has the potential to develop mathematics teachingThe ability of student's own learning regulation becomes one of the key concepts of flipped learning setting.Little is known about the design and implementation of flipped learning settings in mathematics courses. What this paper adds: This study investigates the effect of E‐Learning (EL), Blended Learning (BL) and Flipped Learning (FL) approaches on the mathematics achievement, self‐regulation and mathematics self‐efficacy.The EL, BL and FL settings in the research were designed based on Merrill's 'First Principles of Instruction Design Theory'.The usage of FL approach, developed in line with Merrill's First Principles of Instruction design theory, improves the mathematics achievement, self‐regulation and mathematics self‐efficacy levels of students. Implications for practice and/or policy: This research provided evidences for effects of Merrill's "First Principles of Instruction Design Theory" on online learners.The FL approach, developed in line with Merrill's First Principles of Instruction design theory, may serve as a reference for improving students' learning performance.It is expected that the findings will be helpful in the future design and implementation of mathematics courses at vocational colleges. [ABSTRACT FROM AUTHOR]

Task solving processes and changes in these processes have long been expected to provide valuable information about children's performance in school. This article used electronic tangibles (concrete materials that can be physically manipulated) and a dynamic testing format (pretest, training, and posttest) to investigate children's task solving processes and changes in these processes as a result of training. We also evaluated the value of process information for the prediction of school results. Participants were N = 253 children with a mean age of 7.8 years. Half of them received a graduated prompts training; the other half received repeated practice only. Three process measures were used: grouping behaviour, verbalized strategies, and completion time. Different measures showed different effects of training, with verbalized strategies showing the largest difference on the posttest between trained and untrained children. Although process measures were related to performance on our dynamic task and to math and reading performance in school, the amount of help provided during training provided the most predictive value to school results. We concluded that children's task solving processes provide valuable information, but the interpretation requires more research. Lay Description: What is already known about this topic: Dynamic testing provides information on a child's ability to learn.Solving process information provides indications for intervention.Computerized testing can be of great help in recording process information. What this paper adds: Process‐oriented dynamic testing provides explanatory information beyond traditional tests.The use of a tangible user interface (TUI) console uncovers valuable information on solving processes.Process measures are related to series completion performance, math, and reading.Need for instruction is the best predictor of math and reading ability.Implications for practice and/or policy: A framework for interpreting process information is necessary in dynamic testing.Process‐oriented dynamic testing may be more suitable to inform education.TUIs provide a more natural testing environment. [ABSTRACT FROM AUTHOR]