Programming education has become essential in primary schools, yet students' perceptions vary significantly across different achievement levels. While teacher support is crucial for learning, little is known about how it influences students' attitudes and flow experience across different achievement groups in programming education. This study examined the interrelationships among perceived teacher support, students' attitudes, and flow experience in programming learning across different achievement levels. Data were collected through surveys from 549 students across 43 Hong Kong primary schools. Students were categorised into three groups based on their programming achievement levels: above-average, average, and below-average. A multi-group mediation analysis was conducted to examine the relationships between variables. The above-average group showed significantly more positive perceptions across all variables than other groups. Students’ attitudes mediated the relationship between perceived teacher support and flow experience differently across achievement groups. The findings highlight the importance of differentiated teacher support strategies across achievement tiers and suggest that fostering positive attitudes towards programming is crucial for all achievement levels, particularly through enhancing the perceived usefulness of programming. Copyright © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Empowerment enables students to be psychologically and affectively ready to leverage the benefits of artificial intelligence (AI). However, a theory-driven scale to extend empowerment into the use of AI for problem-solving is lacking. This study developed and validated an 11-item scale of empowerment in using AI for problem-solving (EUAIPS) based on a proposed conceptual framework that synthesises empowerment and AI-related literature. The EUAIPS scale encompasses impact, self-efficacy, and meaningfulness in using AI for problem-solving. We collected data from a diverse sample of Hong Kong senior secondary and university students before (N = 477) and after the course (N = 409). Results demonstrated that the EUAIPS scale with a three-factor structure had good reliability and validity. Students also felt significantly more empowered to use AI for problem-solving after a 14-h course using AI for problem-solving. These findings empirically support the affective dimension of AI literacy and show that psychological control/competence is particularly important for students to harness AI to solve problems at the affective level. This study presents a valid instrument for researchers and practitioners to measure empowerment in using AI for problem-solving and informs AI literacy curriculum designers about including learning activities to help students realise its impact, self-efficacy, and meaningfulness. Copyright © 2025 The Authors. Published by Elsevier Ltd.

This study designed and evaluated a pedagogical innovation which used Scratch coding to foster Grade 4 students to co-develop subject knowledge and computational thinking (CT) in English Language classrooms. A 280-minute teaching in four lessons was arranged for 205 students from ten selected Grade 4 classes in three primary schools at Hong Kong. The Scratch-based pedagogy “To Play and Learn, To Think and Navigate, To Code”–supplementary with four Scratch games and four Scratch activity worksheets–was trialed for engaging students in Scratch coding to explore, think about, apply and consolidate English Language building blocks for talking about locations and directions. The pre-post-test results provide statistically significant evidence that students can advance all three topic-specific knowledge points and all four target CT concepts after learning under the designed pedagogy. The questionnaire survey results reveal the impact of the designed pedagogy on students’ growing awareness of the two target CT practices, and their growing confidence in coding. The focus group interview results reveal students’ confirmation on their success in and satisfaction with the designed pedagogy for developing English Language knowledge and CT competency through coding. This study validates that the pedagogical innovation of learning through coding is potential to foster the co-development of subject knowledge and CT competency in Grade 4 English Language classrooms. Future directions of integrating coding activities into senior primary curriculum are discussed. Copyright © 2022 Asia Pacific Society for Computers in Education.

The rapid development of generative artificial intelligence (GenAI) tools has given rise to a growing discussion of the potential challenges and benefits that the use of these technologies may present in the field of education. This study examines the acceptance of the use of GenAI tools for teaching and learning among primary and secondary school teachers in Hong Kong. It uses an extension of the technology acceptance model (TAM) with a modified framework that incorporates two key factors: self-efficacy and subjective norm. Data were collected from a sample of 367 primary and secondary school teachers in Hong Kong using questionnaires containing items for six constructs: self-efficacy, perceived usefulness, perceived ease of use, attitude towards using, subjective norm, and behavioural intention. The results show that fostering teachers' self-efficacy, perceived usefulness, and attitude is essential for successfully increasing their behavioural intention to use GenAI tools. Subjective norm was also found to influence teachers' behavioural intention. To enhance teachers' effective use of GenAI for teaching, teacher development programmes should focus on equipping teachers with comprehensive conceptual knowledge and skills and an understanding of the application of these tools to teaching and learning. Policy support to create a conducive environment for the use of GenAI in teaching and learning would also be beneficial. The study has theoretical implications in its extension of the TAM model as well as implications for enhancing teachers’ AI literacy and developing pedagogies for the meaningful use of GenAI tools for teaching and learning in K–12 settings. Copyright © 2024 The Authors. Published by Elsevier Ltd.

Recent studies identify Self-Regulated Learning (SRL) as a key factor in enhancing cognitive development, particularly within Computational Thinking (CT) literature. However, research gaps remain in understanding how SRL and CT interact from a developmental perspective. Our study designed a program with tailored animations and worksheets to specifically foster students' learning and cognitive development. Using a mixed-methods approach, we administered surveys among 1235 students from 29 Hong Kong primary schools to investigate a dynamic learning system comprising SRL and CT in a large-scale CT program. Additionally, semi-structured interviews were conducted with 15 students to further probe insights. Quantitative findings revealed a mutually reinforcing relationship in the dynamic system, suggesting that higher SRL skills enhance cognitive CT abilities, and vice versa. Complementing these results, qualitative findings showed that integrating animations and worksheets into the CT program significantly boosted students' SRL and cognitive development. These findings have significant implications for educational practices and curriculum design. Schools should consider implementing SRL strategies, such as proactive goal setting and reflective evaluation, within their curricula to promote students’ cognitive development. Furthermore, strategic investments in educational technology, including collaborations with EdTech developers, are essential to create effective, pedagogically sound tools that enhance learning outcomes. These insights provide valuable guidance for creating a supportive SRL environment that fosters cognitive development in primary school education. Copyright © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

This paper presents the results of an empirical study that aimed to evaluate the effectiveness of using robots to teach machine learning concepts to primary school students and consolidate their reflection on learning-to-learn skills. The pedagogical design of this study was based on the neuroscience-informed Attention-Engagement-Error-feedback-Reflection (AEER) framework. The study involved 87 Grade 5 students from Hong Kong. Data collection included pre- and post-tests on machine learning concepts, as well as pre- and post-questionnaires on learning-to-learn skills based on the AEER framework. The findings suggest that the use of purposely designed robots for understanding machine learning significantly enhanced primary school students’ understanding of machine learning concepts. Further, it can facilitate students’ reflection on their learning-to-learn skills, which have been nurtured over their years of study period, thereby effectively preparing them for the transition to secondary school education. The paper concludes with a discussion of the findings and provides potential directions for future research. Copyright © 2024 CSEDU.

Student-centered pedagogy (SCP) is highly considered for its potential to facilitate cognitive learning in Computational Thinking (CT) education. However, there is a noticeable gap in understanding its influence on students' cognitive development from a multilevel perspective. This study delves into cognitive learning theories and aims to bridge the existing gap by introducing a three-level conceptual model to illustrate how the influence of SCP on students' cognitive CT abilities is mediated through the cognitive learning processes. This multilevel approach simultaneously explores SCP within the intricate school environment where factors at the school, teacher, and student levels are closely intertwined. Data was collected from 82 programming teachers and their 2433 students across 43 Hong Kong primary schools. Using multilevel modeling, results indicate that the adoption of SCP is significantly anchored by school support on teacher professional development (TPD), which in turn enhances students’ cognitive learning (i.e., active, interactive, constructive, and reflective learning) in class, further contributing to their enhanced cognitive CT abilities. The findings underscore the nuances of SCP adoption in school scenarios, advocating for strategic approaches to maximize student achievements in CT education. Recommendations for future research are discussed. Copyright © 2024 Elsevier Ltd. All rights reserved.

Self-regulated learning (SRL) is critical to students' academic success and lifelong learning. Although the benefits of SRL have been examined in many studies, few have explored it in a broader educational context. This study presents an eight-month institutional case study that demonstrates how SRL has been developed as a pedagogy through the collective endeavours of teachers, researchers, and experts at a university in Hong Kong. A case study method protocol was followed. Data were obtained from multiple sources, including surveys of teachers (N = 93) and students (N = 215), interviews with teachers (n = 5) and students (n = 19), archived course documents, videos, and project reports. T-tests, coding, and document analysis were applied to analyse the collected data. The results showed that the teachers had good knowledge of SRL strategies but some students struggled to apply them effectively. Our study's findings have various implications for the effective promotion of SRL at the university level, and include the importance of developing a collective approach involving various members of the university, integrating responsive pedagogy, and adapting SRL strategies to students' individual needs. Future research can follow our methodology to replicate the study in different educational contexts.

Computational thinking (CT) practices is a critical cognitive tool for students to overcome challenges in this technological era. Few studies investigated CT practices from a development perspective. A two-year intervention was implemented in 30 intervention and 22 control schools in Hong Kong to promote CT education (T1baseline: N = 13,056; T2: N = 16,367; and T3: N = 15,269). Senior primary students (grades 4 to 6) around 8–12 years old were targeted. Among them, 34% were girls at T1baseline. Their learning progression of cognitive development was assessed with a CT practices test. Data were analyzed using item response analysis. Learning trajectories of CT practices were modeled to understand how students’ cognitive development differed between schools. Insights of findings were discussed in bringing CT practices to life. Copyright © 2023 Elsevier Ltd. All rights reserved.