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Mapping the public understanding of computational thinking education: Insights from social Q&A platform discussions
No full textWith the growing popularity of computational thinking (CT) classes in K-12 schools, it is important to investigate public perceptions of these initiatives. Analyzing public discussions and opinions provides valuable insights that can inform future educational policies and reforms. In this paper, we collected questions and answers related to CT education on the Quora platform. Next, we applied a topic modeling approach to find out major topics in online discussions. Through analysis, we identified 6 topics in questions and 14 topics in answers. Our findings revealed that people showed great interests but also uncertainty about CT education learning outcomes. Many people asked for suggestions on CT learning tools and platforms, but they struggled to identify appropriate information to support their learning needs. Among their answers, while people held positive attitudes toward CT education, they were concerned about the difficulties their children faced in the learning process and the problem of educational equity. Moreover, since CT practices cultivate information literacy skills for children in the 21st century, the benefits of CT education might be overestimated. These findings deepen our understanding of CT education, which could inform education policies and future research directions.Published versio
Associations between parents’ and teachers’ autonomy support and the bifactor model of academic motivation: A short-term cross-lagged analysis
No full textThis study investigated the bidirectional associations between teacher and parent autonomy support and adolescents’ academic motivation in mathematics. A total of 2317 secondary students (49.10% female; Mage = 14.07 years) completed the same survey twice within a year. Using bifactor exploratory structural equation modelling to specify the global and specific motivational types in self-determination theory, a cross-lagged analysis revealed that (a) T1 teacher autonomy support did not significantly predict any T2 student motivation types, though the effect sizes of the cross-lagged paths were small-to-medium in magnitude, (b) T1 parent autonomy support significantly predicted T2 external regulation, (c) T2 teacher autonomy support was significantly predicted by T1 parent autonomy support and identified regulation, and (d) T2 parent autonomy support was significantly predicted by T1 global self-determined motivation. These results emphasise the role of autonomy support in shaping students’ motivation and highlight the interdependencies of students, parents, and teachers in the process.Accepted versionOER 09/22 GADLOER 34/22 PKL
Dietary nitrate supplementation and exercise performance: An umbrella review of 20 published systematic reviews with meta-analyses
No full textThe open access publication is available at https://doi.org/10.1007/s40279-025-02194-6Background
Dietary nitrate (NO3−) supplementation is purported to benefit exercise performance. However, previous studies have evaluated this nutritional strategy with various performance outcomes, exercise tasks, and dosing regimens, often yielding inconsistent results that limit the generalizability of the findings.ObjectiveWe aimed to synthesize the available evidence regarding the effect of NO3− supplementation on 11 domains of exercise performance.MethodsAn umbrella review was reported in accordance with the Preferred Reporting Items for Overviews of Reviews guideline. Seven databases (MEDLINE, EMBASE, Cochrane Database, CINAHL, Scopus, SPORTDiscus, and Web of Science) were searched from inception until July 2024. Systematic reviews with meta-analyses comparing NO3− supplementation and placebo-controlled conditions were included. Literature search, data extraction, and methodological quality assessment (A Measurement Tool to Assess Systematic Reviews Assessing the Methodological quality of SysTemAtic Review [AMSTAR-2]) were conducted independently by two reviewers.ResultsTwenty systematic reviews with meta-analyses, representing 180 primary studies and 2672 unique participants, met the inclusion criteria. Our meta-analyses revealed mixed effects of NO3− supplementation. It improved time-to-exhaustion tasks [standardized mean difference (SMD): 0.33; 95% confidence interval (CI) 0.19–0.47] with subgroup analyses indicating more pronounced improvements when a minimum dose of 6 mmoL/day (372 mg/day) and chronic (> 3 days) supplementation protocol was implemented. Additionally, ergogenic effects of NO3− supplementation were observed for total distance covered (SMD: 0.42; 95% CI 0.09–0.76), muscular endurance (SMD: 0.48; 95% CI 0.23–0.74), peak power output (PPO; SMD: 0.25; 95% CI 0.10 to 0.39), and time to PPO (SMD: − 0.76; 95% CI − 1.18, − 0.33). However, no significant improvements were found for other performance outcomes (all p > 0.05). The AMSTAR-2 ratings of most included reviews ranged from low to critically low.ConclusionsThis novel umbrella review with a large-scale meta-analysis provides an updated synthesis of evidence on the effects of NO3− supplementation across various aspects of exercise performance. Our review also highlights significant methodological quality issues that future systematic reviews in this field should address to enhance the reliability of evidence
Supporting social inclusion of refugees: A funds of knowledge approach
No full textIn recent times, the world has seen an unprecedented increase in the number of refugees seeking asylum and refuge from war, conflict, and persecution. This study focuses on five refugee children in Malaysia and how their knowledge, skills, and lived experiences could be harnessed to support their education, well-being, and social inclusion. The study adopts a Funds of Knowledge (FoK) approach, which capitalises on an individual’s knowledge, skills, experiences and practices to support one’s well-being. Data comprised observations of the refugees both in and out of school, interviews with the refugees and their parents/guardians, and artefacts. Collected over an approximately one-year period, the data were coded to identify the FoK that could be used to support the refugees’ learning, well-being, and social inclusion. Five main FoK types centred on Interest, Literacy Practice, Family, Religion and Aspiration were identified. The paper concludes with a discussion of the ways in which FoK can be viewed as a viable approach to facilitate the education and social integration of refugees in Malaysia and beyond.Accepted versio
Implementation mechanisms for AR-based inquiry learning through the lens of motivational design
No full textThe application of Augmented Reality (AR) in science learning has gained widespread recognition for its potential benefits. Existing studies highlight the role of teachers as cognitive and emotional facilitators in AR-enhanced learning environments. However, limited research has explored the specific teaching mechanisms that support the effective implementation of AR-based learning activities. This mixed-methods quasi-experimental study examined the use of a self-developed AR-supported inquiry learning app in primary science classrooms, analysed teachers’ instructional events in terms of the ARCS model and identified four key implementation mechanisms for optimizing AR-supported inquiry learning through case comparisons. The study provides practical recommendations for AR instructional designers and educators to enhance the integration of AR into teaching practices.Accepted versionMOE SSHRF 8/22 W
在教育戏剧实践中发展新加坡中学生华文阅读素养之研究 (Enhancing Chinese language reading literacy among Secondary school students in Singapore with the practice of drama in education)
No full text教育戏剧作为一种教学策略，指学生透过戏剧习式来感知、体验、思考、表达，从而对文本有更深入的理解，对自我、他人和世界有更广泛的认知。在新加坡中小学华文教学中，教育戏剧的应用屈指可数，原因是：对于教育戏剧如何构建学生的认知，缺乏理论阐述；缺乏实践教育戏剧的具体范本。本研究致力于填补以上空白。本研究以质性分析为主要研究方法。研究者在四所不同性质的学校进行了一年的课堂实践，对参与的学生和教师进行了口头访谈或问卷调查。研究者对访谈资料进行了深入分析；同时，研究者创建了“教育戏剧认知模型”，以此为基础，结合对访谈资料的分析，回答了三个问题：1、教育戏剧是能否发展学生的阅读素养？2、如果教育戏剧对发展阅读素养能起到积极作用，这个过程如何实现？3、教育戏剧对于发展学生的阅读素养有哪些具体作用？本研究说明：教育戏剧能够发展新加坡中学生的华文阅读素养。本研究亦产生如下结论：教育戏剧以同理心为核心，对于学生思考的能力、表达的能力、采取行动的能力都有积极影响；教育戏剧促进学生在阅读中反思，同时推动了学生全球素养的发展。本研究的研究成果对于教师在新加坡中学华文教学中运用教育戏剧提供了理论支撑，同时也提供了切实可行的实践范本
A note on Kurzweil-Henstock's anticipating non-stochastic integral
No full textMotivated by the study of anticipating stochastic integrals using Kurzweil-Henstock approach, we use anticipating interval-point pairs (with the tag as the right-end point of the interval) in studying non-stochastic integral, which we call the Kurzweil-Henstock anticipating non-stochastic integral. We prove the integration-by-parts and integration-by-substitution results, the convergence theorems using our new setting. Using the convergence theorems, we show that the Kurzweil-Henstock's anticipating non-stochastic integral is equivalent to the Lebesgue integral.Published versio
Measuring undergraduate students' reliance on generative AI during problem-solving: Scale development and validation
No full textReliance on AI describes the behavioral patterns of when and how individuals depend on AI suggestions, and appropriate reliance patterns are necessary to achieve effective human-AI collaboration. Traditional measures often link reliance to decision-making outcomes, which may not be suitable for complex problem-solving tasks where outcomes are not binary (i.e., correct or incorrect) or immediately clear. Therefore, this study aims to develop a scale to measure undergraduate students' behaviors of using Generative AI during problem-solving tasks without directly linking them to specific outcomes. We conducted an exploratory factor analysis on 800 responses collected after students finished one problem-solving activity, which revealed four distinct factors: reflective use, cautious use, thoughtless use, and collaborative use. The overall scale has reached sufficient internal reliability (Cronbach's alpha = .84). Two confirmatory factor analyses (CFAs) were conducted to validate the factors using the remaining 730 responses from this activity and 1173 responses from another problem-solving activity. CFA indices showed adequate model fit for data from both problem-solving tasks, suggesting that the scale can be applied to various human-AI problem-solving tasks. This study offers a validated scale to measure students' reliance behaviors in different human-AI problem-solving activities and provides implications for educators to responsively integrate Generative AI in higher education.Accepted versionRG 133/24ARC 1/24 Z
Intelligent technology for educational applications: First international conference, ITEA 2024, Kuala Lumpur, Malaysia, July 20–22, 2024, proceedings
No full textTowards an authentic collaborative inquiry model for cultivating data science skills and attitudes: Effects of SPIRE on secondary school students
No full textPreparing the new generation to be data-literate citizens is a pressing challenge, and some explorations have been made to cultivate K-12 students’ data science skills and attitudes. However, there is a lack of instructional models to guide the design of data science programs in K-12 due to its complex and interdisciplinary nature as well as the involvement of diverse communities in its research targeting various audiences. To address this research gap, we proposed an authentic collaborative inquiry model (SPIRE, Stimulate, Practice, Improve and Reflect) that integrates science inquiry procedures (emphasizing students’ hands-on engagement in data science workflow) and the Knowledge Building approach (highlighting students’ continuous and collaborative work on real-world problems and questions). Following the mode, we developed and engaged 67 secondary school students in an out-of-school Data Science program through two cycles. We examined how students’ data science skills, perceived learning and attitudes changed during and after the program. The findings show that the groups of participants could engage in complete data science processes, demonstrating strong skills in identifying variables, aligning data with investigative questions, and interpreting results in their final artifacts. However, they performed relatively poorly in explaining the rationale of the investigation, comprehensive data analysis and considering other factors beyond those included in the investigative questions. Participants perceived learning significantly increased over the inquiry phases, and their perceived data science skills significantly increased after the program. Overall, the results were positive and uncovered skills requiring more support and scaffolding. Future research and practice can further examine how to apply the SPIRE model in K-12 data science education in schools in subjects such as data science, science, and mathematics and study how to enhance the data science skills that students do not perform well.NIE-SUG 4-22 ZG