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Gamified learning is an instructional strategy that motivates students to learn, and the use of multiple representations assists learning by promoting students' thinking and advanced mathematical problem-solving skills. In particular, emergency distance learning caused by the COVID-19 pandemic may result in a lack of motivation and effectiveness in learning. This study designed an online gamified learning activity incorporating multi-representational scaffolding and compared the differences in the learning achievement and motivation for the gamified activity and general synchronous distance learning. In addition, for the group that conducted the gamified learning activity, we measured the participants' flow, anxiety, and emotion during the activity. A total of 36 high school students participated in the experiment. The results indicated that the gamified learning activity was not significantly effective in terms of enhancing learning achievement. In terms of learning motivation, a significant decrease in motivation was found for the group using general synchronous learning, while a significant increase in motivation was found for the group using synchronous gamified learning. This indicates that despite the negative impact of the pandemic on learning, gamified learning still enhances students' learning motivation. The results of flow, anxiety, and emotion showed that the participants had a positive and engaged experience. Participants provided feedback that the multi-representational scaffolding facilitates learning.

Pattern recognition is an important skill in computational thinking. In this study, an equation puzzle game was developed by combining pattern recognition with algebraic reasoning, and scaffolding was designed to support learners' learning. Sixty participants were enrolled in this study, divided into a control group and an experimental group to compare the results and differences in game achievement, flow, anxiety, and motivation of participants with and without algebraic reasoning scaffolding. The results of the study showed that the participants in both groups had positive flow and motivation during the game, did not feel over-anxious, and there was no significant difference in the game achievement of the two groups. In addition, the game with the scaffolding may have the potential to make a positive correlation between game achievement and psychological status. The results of this study indicated that the game did not cause too much anxiety to the participants. The scaffolding-based design achieves the intended effect on the participants' assistance and facilitates the participants' engagement in pattern recognition problem solving. And as learners became more focused and engaged, they could also perform better in the game. This game mechanism can be used as a reference for designing pattern recognition games.

BackgroundChronic kidney disease (CKD) is a global health problem with a high economic burden, which is particularly prevalent in Taiwan. Mobile health apps have been widely used to maintain continuity of patient care for various chronic diseases. To slow the progression of CKD, continuity of care is vital for patients’ self-management and cooperation with health care professionals. However, the literature provides a limited understanding of the use of mobile health apps to maintain continuity of patient-centered care for CKD. ObjectiveThis study identified apps related to the continuity of patient-centered care for CKD on the App Store, Google Play, and 360 Mobile Assistant, and explored the information and frequency of changes in these apps available to the public on different platforms. App functionalities, like patient self-management and patient management support for health care professionals, were also examined. MethodsWe used the CKD-related keywords “kidney,” “renal,” “nephro,” “chronic kidney disease,” “CKD,” and “kidney disease” in traditional Chinese, simplified Chinese, and English to search 3 app platforms: App Store, Google Play, and 360 Mobile Assistant. A total of 2 reviewers reached consensus on coding guidelines and coded the contents and functionalities of the apps through content analysis. After coding, Microsoft Office Excel 2016 was used to calculate Cohen kappa coefficients and analyze the contents and functionalities of the apps. ResultsA total of 177 apps related to patient-centered care for CKD in any language were included. On the basis of their functionality and content, 67 apps were recommended for patients. Among them, the most common functionalities were CKD information and CKD self-management (38/67, 57%), e-consultation (17/67, 25%), CKD nutrition education (16/67, 24%), and estimated glomerular filtration rate (eGFR) calculators (13/67, 19%). In addition, 67 apps were recommended for health care professionals. The most common functionalities of these apps were comprehensive clinical calculators (including eGFR; 30/67; 45%), CKD medical professional information (16/67, 24%), stand-alone eGFR calculators (14/67, 21%), and CKD clinical decision support (14/67, 21%). A total of 43 apps with single- or multiple-indicator calculators were found to be suitable for health care professionals and patients. The aspects of patient care apps intended to support self-management of CKD patients were encouraging patients to actively participate in health care (92/110, 83.6%), recognizing and effectively responding to symptoms (56/110, 50.9%), and disease-specific knowledge (53/110, 48.2%). Only 13 apps contained consulting management functions, patient management functions or teleconsultation functions designed to support health care professionals in CKD patient management. ConclusionsThis study revealed that the continuity of patient-centered care for CKD provided by mobile health apps is inadequate for both CKD self-management by patients and patient care support for health care professionals. More comprehensive solutions are required to enhance the continuity of patient-centered care for CKD.

A scaffolding-based mind tool was designed to allow teachers to easily create lesson plans for in-class gamified activities and to embed various scaffoldings in the lesson plan design. The purpose of this study was to investigate the learning outcomes of a scaffolding-based mind tool integrated with gamified learning activities applied to a science course. The study was conducted to investigate students' learning outcomes, flow, and qualitative feedback on the scaffolding-based mind tool. A total of 134 high school students participated in the experiment. The results showed that the gamified activity with the scaffolding-based mindtool significantly improved students' learning effectiveness, but the learning effectiveness did not differ significantly from that of the students in the lecture-based instruction. In addition, the study found that the learners' flow was high, the students were engaged in the activity. The qualitative feedback analysis also revealed high positive evaluations of the usefulness of the gamified activity, mind tool, and scaffolds. In addition, students with low prior knowledge or low learning effectiveness had significantly higher active engagement in flow than those with high prior knowledge/learning effectiveness.

The purpose of this study is to explore the classroom management effectiveness enhancement by using social networking apps through electronic devices such as smartphones, tablet computers, and personal computers, as well as the role of parental involvement. Quantitative research was conducted, and the Structural Equation Modelling (SEM) statistical technique applied. From 15 different Changhua County primary schools in Taiwan, 411 teachers were chosen using stratified random sampling in proportion to the size and location of schools. Each teacher was invited to fill out a questionnaire. A total of 403 (98.05%) questionnaires were returned, with 382 (92.94%) considered valid. In order to confirm the statistical results, a focused group interview was also conducted. The effects of the behaviour intention of using Line, parental involvement, and classroom management effectiveness were all found to be positively associated with one another. Moreover, the mediating role of parents in the relationship between the behaviour intention of using Line and classroom management effectiveness enhancement was also supported and confirmed.

Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non‐motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI‐based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

In a smart city, IoT devices are required to support monitoring of normal operations such as traffic, infrastructure, and the crowd of people. IoT‐enabled systems offered by many IoT devices are expected to achieve sustainable developments from the information collected by the smart city. Indeed, artificial intelligence (AI) and machine learning (ML) are well‐known methods for achieving this goal as long as the system framework and problem statement are well prepared. However, to better use AI/ML, the training data should be as global as possible, which can prevent the model from working only on local data. Such data can be obtained from different sources, but this induces the privacy issue where at least one party collects all data in the plain. The main focus of this article is on support vector machines (SVM). We aim to present a solution to the privacy issue and provide confidentiality to protect the data. We build a privacy‐preserving scheme for SVM (SecretSVM) based on the framework of federated learning and distributed consensus. In this scheme, data providers self‐organize and obtain training parameters of SVM without revealing their own models. Finally, experiments with real data analysis show the feasibility of potential applications in smart cities. This article is the extended version of that of Hsu et al. (Proceedings of the 15th ACM Asia Conference on Computer and Communications Security. ACM; 2020:904‐906). [ABSTRACT FROM AUTHOR]