Keep DRAGging ON: Is solving more problems in DragonBox 12+ associated with higher mathematical performance during the COVID-19 pandemic?

Prior research has shown that game-based learning tools, such as DragonBox 12+, support algebraic understanding and that students' in-game progress positively predicts their later performance. Using data from 253 seventh-graders (12–13 years old) who played DragonBox as a part of technology intervention, we examined (a) the relations between students' progress within DragonBox and their algebraic knowledge and general mathematics achievement, (b) the moderating effects of students' prior performance on these relations and (c) the potential factors associated with students' in-game progress. Among students with higher prior algebraic knowledge, higher in-game progress was related to higher algebraic knowledge after the intervention. Higher in-game progress was also associated with higher end-of-year mathematics achievement, and this association was stronger among students with lower prior mathematics achievement. Students' demographic characteristics, prior knowledge and prior achievement did not significantly predict in-game progress beyond the number of intervention sessions students completed. These findings advance research on how, for whom and in what contexts game-based interventions, such as DragonBox, support mathematical learning and have implications for practice using game-based technologies to supplement instruction. Practitioner notes What is already known about this topic DragonBox 12+ may support students' understanding of algebra but the findings are mixed. Students who solve more problems within math games tend to show higher performance after gameplay. Students' engagement with mathematics is often related to their prior math performance. What this paper adds For students with higher prior algebraic knowledge, solving more problems in DragonBox 12+ is related to higher algebraic performance after gameplay. Students who make more in-game progress also have higher mathematics achievement, especially for students with lower prior achievement. Students who spend more time playing DragonBox 12+ make more in-game progress;their demographic, prior knowledge and prior achievement are not related to in-game progress. Implications for practice and/or policy DragonBox 12+ can be beneficial as a supplement to algebra instruction for students with some understanding of algebra. DragonBox 12+ can engage students with mathematics across achievement levels. Dedicating time and encouraging students to play DragonBox 12+ may help them make more in-game progress, and in turn, support math learning. © 2023 The Authors. British Journal of Educational Technology published by John Wiley & Sons Ltd on behalf of British Educational Research Association.

Using Deep Learning Algorithms in Chest X-ray Image COVID-19 Diagnosis

We are experiencing heavy COVID-19 outbroke globally since January 2020. In Taiwan, because its low infection rate (< 0.01%), there was not enough evidence for diagnosis through medical imaging. At present, chest X-ray is widely used in lung infection diagnoses. This study uses deep learning methods to assist doctors in classifying COVID-19 disease from chest X-ray images. After pre-processing, the images were put into the VGG16 model to automaticallyclassify into three categories to assist the radiologist in the treatment of the disease. The results show that the classification accuracy was 78%. Detail analyses disclosed that this accuracy can be improved by rectifying the unbalanced images problem. In addition, choosing proper image pre-processing algorithms has a high tendency to generate better results. © 2021 ECBIOS 2021. All rights reserved.