In recent years, AI technologies have been developed to promote students' self-regulated learning (SRL) and proactive learning in digital learning environments. This paper discusses a comparative study between generative AI-based (SRLbot) and rule-based AI chatbots (Nemobot) in a 3-week science learning experience with 74 Secondary 4 students in Hong Kong. The experimental group used SRLbot to maintain a regular study habit and facilitate their SRL, while the control group utilized rule-based AI chatbots. Results showed that SRLbot effectively enhanced students' science knowledge, behavioural engagement and motivation. Quantile regression analysis indicated that the number of interactions significantly predicted variations in SRL. Students appreciated the personalized recommendations and flexibility of SRLbot, which adjusted responses based on their specific learning and SRL scenarios. The ChatGPT-enhanced instructional design reduced learning anxiety and promoted learning performance, motivation and sustained learning habits. Students' feedback on learning challenges, psychological support and self-regulation behaviours provided insights into their progress and experience with this technology. SRLbot's adaptability and personalized approach distinguished it from rule-based chatbots. The findings offer valuable evidence for AI developers and educators to consider generative AI settings and chatbot design, facilitating greater success in online science learning. Copyright © 2024 The Authors.

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.

Maker education is regarded as a global initiative. Empowering STEM makers in schools becomes an important task for K-12 educators. Creativity, critical thinking, STEM identity, and STEM interest are all vital attributes of a good STEM maker. While researchers have proposed various pedagogical approaches to supporting the processes of STEM making, rare studies have been carried out to compare the effectiveness of these approaches. To fill the research gap, we have conducted a quasi-experimental study (with 63 secondary school students in Hong Kong) to explore the pedagogical effects of mentoring and authentic problem-solving strategies in supporting STEM making. Implications for the development of maker education and future work are also discussed in this paper. Copyright © 2021 Publication of Asia Pacific Society for Computers in Education.

This study examined the processes that contributed to students’ aspirations for STEM careers and unpacked the relationships between students’ self-concept in science and mathematics learning, perceived parental expectations, perceptions of STEM professionals, career outcome expectations and STEM career aspirations. Structural equation modelling was used to analyse quantitative survey data of 2,477 primary and secondary school students studying in seven Asian regions (Hong Kong, Malaysia, Mainland China, Indonesia, Korea, Taiwan, and Singapore). The results demonstrated that students’ self-concept, perceptions of STEM professionals, and their career outcome expectations all significantly and positively predicted their aspirations for STEM careers. However, this study failed to establish a direct relationship or positive correlation between perceived parental expectations and STEM career aspirations. Students’ self-concept negatively predicted their career outcome expectations related to seeking parental approval. While no significant positive effects of perceived parental expectations on career aspirations were found, an indirect effect of perceived parental expectations on STEM career aspirations via career outcome expectations was observed. Moreover, career outcome expectations mediated the relationships between students’ STEM career aspirations and their perceptions of STEM professionals more strongly than self-concept. The implications of these results for STEM education are discussed. Copyright © 2024 National Institute of Education, Singapore.

In this article, we use the family resemblance approach as a framework to contribute to the debate about the similarities and differences between the constituent disciplines of STEAM (science, technology, engineering, arts and mathematics) and to explore the implications for education. The family resemblance approach has been used in science education in various ways, for instance, in teacher education and undergraduate teaching and as an analytical tool for examining science curricula and assessments. The relevant sense of application of the family resemblance approach for our purposes in this article is that it is a framework that has the potential to differentiate the disciplines underpinning STEAM. We explore the utility of the family resemblance approach for clarifying what is meant by the nature of STEAM and, subsequently, we elaborate on some practical examples drawn from a project conducted in Hong Kong with Year 7 (12–13-year-old) students to illustrate how the use of the family resemblance approach can help articulate a contrast of nature of science and the arts in school activities. Copyright © 2024 Sibel Erduran and Kason Ka Ching Cheung.

Background: Different instructional factors are related to students’ achievement in different cognitive domains. Most research studies on large-scale assessment focus on science achievement as an entire variable, without considering science achievement in different cognitive domains. Purpose: This study investigates the predictive effects of the frequency of teachers’ using practical work and clarity of instruction on students’ achievement in different cognitive domains. Sample: A regional representative sample of 3265 Hong Kong students who took part in Trends in International Mathematics and Science Study (TIMSS) 2019 was used in this study. Design and Method: In order to disentangle the interrelationships between science instructional factors, attitudes toward science and students’ achievement in different cognitive domains, we carried out structural equation modelling to explore the responses by 3265 Hong Kong students to TIMSS 2019 surveys. Results: Frequency of teachers’ use of practical work had a significant positive impact on students’ achievement in the domains of knowing, applying, and reasoning, while clarity of instruction had a significantly negative impact on students’ achievement in the domains of knowing and applying. Enjoyment of science mediates the relationship between the relationships between frequency of practical work and achievement in three cognitive domains. Conclusion: This informs how teachers use practical work to enhance students’ enjoyment of science, intrinsic motivation and self-concept, in order to improve their achievement in knowing, applying and reasoning science. Implications contribute to future research on how best to improve students’ achievement in all three cognitive domains are discussed. Copyright © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Purpose: Using Hong Kong as the context of study, this paper examines the role of education policy, particularly professional standards for teachers (PST) and principals (PSP), in enabling leadership for action on contemporary challenges and crises such as climate change.Design/methodology/approach: This paper utilises critical policy analysis (CPA) and an associated analytical framework to examine key policy texts that are designed with the intent to frame the professional roles, practice and learning of educators and leaders in Hong Kong. The data analysis process involved rounds of descriptive coding, which was then collated into broader themes for discussion.Findings: Policy texts emphasised the scope for educators to exercise leadership and decision-making that supports innovation, improvement and collaboration in the pursuit of a broad social mission for education, emphasising the skills students do and will need to respond to dynamic contemporary challenges. However, how this relates to broader policy goals, and limited articulation of the means through which this is possible, questions remain about the extent to which teachers and leaders are able to exercise leadership for action on climate change.Originality/value: This study has important implications for how those in policymaking, research and practice spaces understand the framing of the role of teachers and school leaders in policy and the influence of this on their capacity to lead action on contemporary challenges and crises, such as climate change. Copyright © 2024, Emerald Publishing Limited.

Many Southeast Asian countries have been promoting the use of EMI in non-language subjects, including science. Content and Language Integrated Learning (CLIL) is a notion which promotes students’ integration of both content and language. This chapter explores the use of a content analysis technique, an epistemic network analysis to explore how classroom interaction facilitates CLIL. We draw on Lin (2012)‘s ‘rainbow diagram’ to analyse how two Hong Kong science teachers used and expanded communicative resources to promote CLIL. These resources are L1 and L2 every day, oral and academic languages, as well as multimodal representations. A coding scheme is developed based on the ‘rainbow diagram’ from Lin (2012). Afterwards, we illustrate an innovative discourse analysis technique, epistemic network analysis, to characterise the frequency of connections between the codes generated. By qualitatively comparing the epistemic networks between teachers and students in a science practical work setting, we propose that epistemic network analysis can be used to compare the practice of CLIL of experienced and non-experienced teachers, as well as before and after professional development programmes. The strengths and weaknesses of this innovative method are then discussed. Copyright © 2023 selection and editorial matter, Samantha M. Curle and Jack K. H. Pun; individual chapters, the contributors.