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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. Practitioner notesWhat is already known about this topic AI technologies have been used to support student self‐regulated learning (SRL) across subjects.SRL has been identified as an important aspect of student learning that can be developed through technological support.Generative AI technologies like ChatGPT have shown potential for enhancing student learning by providing personalized guidance and feedback.What this paper adds This paper reports on a case study that specifically examines the effectiveness of ChatGPT in promoting SRL among secondary students.The study provides evidence that ChatGPT can enhance students' science knowledge, motivation and SRL compared to a rule‐based AI chatbot.The study offers insights into how ChatGPT can be used as a tool to facilitate SRL and promote sustained learning habits.Implications for practice and/or policy The findings of this study suggest that educators should consider the potential of ChatGPT and other generative AI technologies to support student learning and SRL.Educators and students should be aware of the limitations of AI technologies and ensure that they are used appropriately to generate desired responses.It is also important to equip teachers and students with AI competencies to enable them to use AI for learning and teaching. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) literacy is at the top of the agenda for education today in developing learners' AI knowledge, skills, attitudes and values in the 21st century. However, there are few validated research instruments for educators to examine how secondary students develop and perceive their learning outcomes. After reviewing the literature on AI literacy questionnaires, we categorized the identified competencies in four dimensions: (1) affective learning (intrinsic motivation and self‐efficacy/confidence), (2) behavioural learning (behavioural commitment and collaboration), (3) cognitive learning (know and understand; apply, evaluate and create) and (4) ethical learning. Then, a 32‐item self‐reported questionnaire on AI literacy (AILQ) was developed and validated to measure students' literacy development in the four dimensions. The design and validation of AILQ were examined through theoretical review, expert judgement, interview, pilot study and first‐ and second‐order confirmatory factor analysis. This article reports the findings of a pilot study using a preliminary version of the AILQ among 363 secondary school students in Hong Kong to analyse the psychometric properties of the instrument. Results indicated a four‐factor structure of the AILQ and revealed good reliability and validity. The AILQ is recommended as a reliable measurement scale for assessing how secondary students foster their AI literacy and inform better instructional design based on the proposed affective, behavioural, cognitive and ethical (ABCE) learning framework. Practitioner notesWhat is already known about this topic AI literacy has drawn increasing attention in recent years and has been identified as an important digital literacy.Schools and universities around the world started to incorporate AI into their curriculum to foster young learners' AI literacy.Some studies have worked to design suitable measurement tools, especially questionnaires, to examine students' learning outcomes in AI learning programmes.What this paper adds Develops an AI literacy questionnaire (AILQ) to evaluate students' literacy development in terms of affective, behavioural, cognitive and ethical (ABCE) dimensions.Proposes a parsimonious model based on the ABCE framework and addresses a skill set of AI literacy.Implications for practice and/or policy Researchers are able to use the AILQ as a guide to measure students' AI literacy.Practitioners are able to use the AILQ to assess students' AI literacy development. [ABSTRACT FROM AUTHOR]

Research has shown that even though standardized financial education has gained prevalence to promote financial literacy over the past decade, it has had little effect on personal financial planning. The present study used a randomized control trial to examine the effectiveness of a Python‐based personalized financial projection on young working adults in Hong Kong, to examine if and how this approach improves their financial planning. Participants assigned to the experiment group received standardized financial education and Python‐based financial projections, while those in the control group only received standardized financial education. The assessment based on the two‐wave data showed that Python‐based financial projection promoted future time perspectives, reduced temporal discounting, and improved financial planning via the full mediation of promoting financial attitudes. Although numerous applications for personal financial planning exist (such as Wallet, Walnut, Monefy, and Money View), our Python‐based financial projection stands out as the pioneering solution tailored for the hands‐on manipulation of programming code to effectively manage personal finances. Our findings suggest a new track to upgrade personalized financial projection and standardized financial education and contribute generously to the development of personal finance education. Practitioner notesWhat is already known about this topic Standardized financial education promotes objective financial knowledge.Standardized financial education has a limited effect on personal financial planning.Classical personalized financial projection promotes personal financial planning, but the effect is small.What this paper adds Introduction of a novel Python‐based personalized financial projection by manipulating projection code.The evidence that Python‐based personalized financial projection more strongly improves personal financial planning, compared to the classical personalized financial projection.The evidence why Python‐based personalized financial projection can improve personal financial planning.Implications for practice and/or policy Facilitating engagement of young working adults with personalized finance planning through the use of a Python‐based intervention.Integrating Python‐based personalized financial projection into standardized financial education in the school setting.Using Python as the platform to design more topic‐specific financial education module. [ABSTRACT FROM AUTHOR]

A lack of evidence bridging the chasm between professional learning practices and commonly used, publicly available resources such as YouTube videos, remains a long‐term challenge in both research and practice. The study introduced a YouTube video club for female early childhood teachers in Hong Kong (N = 29) to view, analyse and discuss STEM teaching videos. The participants wrote reflections and discussed with peers to exchange views on teaching content and strategies. All participants completed pre‐ and post‐intervention surveys reporting their teaching beliefs, and five participants from the experimental group were invited for individual interviews. The questionnaire survey data were analysed using statistical analysis, while the interview data were analysed through inductive thematic analysis. The study, which was pre‐post quasi‐experimental, showed that the video club enhanced teachers' beliefs and attitudes towards professional practices in early childhood education. Qualitative analysis of teacher interviews revealed benefits and constraints of using YouTube videos for professional learning. The study transformed video clubs into a web‐mediated mode using YouTube, Google Classroom and Zoom. The results have implications for the design and implementation of video clubs in teacher learning programmes. Practitioner notesWhat is already known about this topic As the largest and most popular video‐sharing service, YouTube hosts a wide range of freely accessible video types that can be used for professional education in various disciplines.There are worldwide efforts to improve early childhood teachers' ability to teach STEM.Video recordings of classroom observations have been used in the context of video clubs since the 1990s to support teacher learning.What this paper adds We introduced the design of a YouTube video club focusing on STEM teaching, in which the participants were asked to view and analyse video excerpts, write reflection as guided by the facilitator and discuss with peers in groups to exchange views on the teaching content and strategies demonstrated in the video excerpts.We extended prior research on video clubs by transforming video clubs into a fully web‐mediated mode using the technologies of YouTube, Google Classroom and Zoom.This design‐based study evaluated the design of YouTube video club in terms of affording and constraining teachers' professional learning in STEM education.Implications for practice and/or policy Results of this study can inform the design of teacher learning programmes using YouTube videos.YouTube videos can be used in web‐mediated video clubs to enhance teachers' professional beliefs, as well as the pedagogical content knowledge in specific learning domains (eg, STEM).More enhancements should be made to optimize the design of YouTube video club. [ABSTRACT FROM AUTHOR]