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Background: Digital game‐based learning is gaining increased attention from both researchers and educators for improving mathematics instruction. However, the evidence for game‐based learning is mixed and research with rigorous research design and analyses are limited. Objective: Here, in a pre‐registered randomized controlled study, we investigated whether a fraction game designed collaboratively by educational experts and professional game developers may serve as a useful tool to enhance students' fraction knowledge. Methods: We assigned French fifth graders to either an experimental group who used the game (n = 110) or a control group (n = 78) who received traditional instruction on fractions. Fraction knowledge was assessed pre‐ and post‐intervention. Results: Results show that students in the active control group had superior overall fraction performance than students in the experimental group at the end of intervention. However, the game had a positive effect on decimal learning. We also found a positive relation between game performance and overall fraction knowledge scores at post‐test. Contribution: The study highlights the importance of game metrics as indicators of personalized assessment tools. Given the increased usage of games in learning mathematics and the equivocal results on the effectiveness of these games, our study also highlights the importance of pre‐registration and randomized controlled studies. Lay Description: What is already known about this topic: Digital game‐based learning (DGBL) is gaining popularity in mathematics teaching.DGBL shows potential for teaching difficult abstract concepts such as fractions.However, research evaluating DGBL for fractions is limited. What this paper adds: The study examines a fraction game designed by education experts and game designers.Students fraction knowledge is assessed using paper‐based test.Challenges associated with DGBL in the classroom are discussed in the paper. Implications for practice: The results will guide educators in designing effective fraction instruction in classroom.The study highlights the critical role of instructional support in DGBL for fractions.Game based metrics can be used to individualize instruction in the classroom. [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: As educational digital technologies are increasingly being used in schools, past research left unanswered the question of these technologies' impact on the socioeconomic achievement gap even when equal access is guaranteed. Objectives: The objectives of the present study are to examine whether and how the socioeconomic achievement gap can be reduced through the use of computer‐assisted instruction (CAI). Methods: We addressed this issue experimentally by comparing CAI to conventional teacher‐led classroom instruction with more than 800 middle and high school students from disadvantaged and highly privileged socioeconomic backgrounds in a range of topics. Results and Conclusions: Both disadvantaged and highly privileged students taught with CAI outperformed those taught with conventional instruction, thus maintaining the socioeconomic achievement gap constant. However, we also found that disadvantaged students receiving CAI performed as well as highly privileged students receiving conventional teacher‐led instruction. Takeaways: The positive effects associated with CAI may therefore help compensate the difficulties of students with a disadvantaged background, a still neglected possibility. Lay Description: What is already known about this topic?: Socioeconomic status affects academic achievement especially in students from disadvantaged backgrounds.Inequal access to digital learning is a by‐product of socioeconomic status.Computer‐assisted instruction is known to yield positive effects on learning. What this paper adds?: It examines the effectiveness of computer‐assisted instruction on reducing the socioeconomic achievement gap when equal access to digital education is guaranteed at the school level.It shows that computer‐assisted instruction (relative to teacher‐led conventional instruction) benefited disadvantaged students and their highly privileged counterparts equally, shifting the socioeconomic achievement gap upward.However, disadvantaged students receiving CAI may reach similar performance level as their highly privileged counterparts receiving conventional instruction, thus compensating the socioeconomic achievement gap. Implications for practice and/or policy: This finding strengthens the importance of targeting teaching methods depending on students' socioeconomic characteristics to allow disadvantaged students to maximize their learning potential and chances to access to higher education. [ABSTRACT FROM AUTHOR]

Many studies have demonstrated the crucial role of vocabulary in predicting reading performance in general. More recent work has indicated that one particular facet of vocabulary (its depth) is more closely related to language comprehension, especially inferential comprehension. On this basis, we developed a training application to specifically improve vocabulary depth. The objective of this study was to test the effectiveness of a mobile application designed to improve vocabulary depth. The effectiveness of this training was examined on 3rd and 4th grade children's vocabulary (breadth and depth), decoding and comprehension performances. A randomized waiting‐list control paradigm was used in which an experimental group first received the intervention during the first 4 weeks (between pretest and post‐test1), thereafter, a waiting control group received the training for the next 4 weeks (between postest1 and posttest2). Results showed that the developed application led to significant improvements in terms of vocabulary depth performance, as well as a significant transfer effect to reading comprehension. However, we did not observe such a beneficial effect on either vocabulary breadth or written word identification. These results are discussed in terms of the links between vocabulary depth and comprehension, and the opportunities the app presents for remedying language comprehension deficits in children. Lay Description: What is already known about this topic:Vocabulary is a powerful predictor of both word identification and text comprehensionVocabulary depth rather than breadth is more closely related to language comprehensionDepth of vocabulary is particularly predictive of inferencing skills What this paper adds:We develop a new training application specifically targeting vocabulary depthThe training led to significant gain in children's knowledge for the taught wordsWe also observe a transfer effect with significant improvements in reading comprehension Implications for practice and/or policy:Vocabulary depth trainings represent a good way for remedying language comprehension deficits [ABSTRACT FROM AUTHOR]