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. Copyright © 2023 The Authors.

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.

Artificial intelligence (AI) literacy is widely recognized as a new set of competencies that people use AI effectively and ethically in everyday life. In K-12 education, educators have started to employ different pedagogical strategies to foster students' AI literacy. Using digital story writing (DSW) in the classroom is an effective inquiry-based pedagogical approach to address literacy development by improving language and technological abilities across disciplines. This study recruited 82 primary students in Hong Kong to attend a three-month DSW journey to learn AI and completed a knowledge test at the end of the program. Among the students, 16 best-achieving students were further invited to participate in artefact-based interviews, and we further analysed their work to understand how they formulate AI understandings. It is found that the participating students were able to propose an authentic scenario, apply their new knowledge of AI and think up meaningful AI-driven solutions in their digital stories. Furthermore, we examined students' DSW process in terms of inquiry-based pedagogical cycle (orientation, conceptualization, investigation, conclusion, discussion) to demonstrate how they learn AI. Overall, DSW as an inquiry could effectively foster students' AI literacy in using and applying AI knowledge to solve real-life problems, far beyond merely knowing and understanding related concepts. We suggest that using DSW as a pedagogy has the potential to support students to scaffold students’ AI understanding, particularly for young children. Copyright © 2022 The Authors. Published by Elsevier Ltd.

In recent years, schools started to incorporate artificial intelligence (AI) into computer science/STEAM curricula. However, few validated measurements have been designed to examine how secondary students develop AI literacy and perceive their learning outcomes. AI literacy has been measured from students' knowledge and skill acquisition, and behavior and attitudes. This research aims to develop and validate an instrument to assess AI literacy for secondary students. A questionnaire with 25 items measured in a 5-point Likert scale was created. In a pilot study, the questionnaire was administered to a sample of 363 secondary school students from two different schools in Hong Kong. Confirmatory factor analysis was conducted and grouped into six factors: (1) intrinsic motivation, (2) self-efficacy, (3) behavioral intention, (4) behavioral engagement, (5) know and understand, and (6) use and apply AI. The questionnaire showed a good fit model to support internal consistency reliability in most of the factors, with Cronbach's Alpha levels ranging from.58 to.88. A less-parsimonious model was proposed that help educators measure a wider AI literacy skill set with an acceptable model fit, with Cronbach's Alpha levels ranging from.91 to.94 based on affective, behavorial, cognitive and ethical (ABCE) learning framework. Further studies are needed to confirm the factor structure. Copyright © 2023 IEEE.

COVID-19 virus outbreak started in Hong Kong in January 2020. All schools in Hong Kong were suspended from January 2020 to December 2022. Many secondary schools in Hong Kong would like to catch up with the learning schedule during the pandemic and e-learning became the possible solution. There were different forms of e-learning method. Some common examples were online lecture, e-learning platform and e-learning education technology tools. The use of e-learning tools became popular and common during the pandemic. Because of the sudden shift to e-learning lecture, teachers might not have enough time to realize students’ e-learning needs. As a result, teachers may not be able to provide sufficient needs-satisfying support to students when they are using e-learning tools in the lesson. This study would like to apply an experimental approach to investigate the influence of needs-satisfying teaching approaches on the motivation of using e-learning tool based on Self-determination Theory (Deci & Ryan, 1986). Hong Kong secondary school students would be intrinsically motivated to e-learning tool in the Science subject through satisfying the needs for competence, autonomy and relatedness. In this study, the context was e-learning in Science class for secondary school students in Hong Kong. The learning tasks were junior secondary school level Physics and Chemistry. Questionnaire was utilized for quantitative data collection and a subgroup of students were invited to have individual interviews for qualitative data collection. A modified model based on SDT was proposed in this applied field research to study the influence of the intervention of needs-satisfying approaches to the motivation of using science e-learning tool in Science subjects on Hong Kong secondary school students. All rights reserved.

Self-regulation behaviours are a significant predictor of students’ academic achievement. However, few students are proficient in regulating their learning. Feedback is a promising way to support students in becoming self-regulated learners, but the large class sizes and tight teaching schedules make this difficult to implement in Hong Kong schools.The flipped classroom approach and seven principles of high-quality feedback practices were adapted to formulate the current study’s theoretical framework—the self-regulated flipped classroom (SRFC) approach. The flipped classroom could free up classroom time by moving teacher-centred instruction out of the classroom using online learning resources. The primary goal was to provide more opportunities for active learning activities, teachers to provide quality feedback and students to respond to the feedback.To investigate whether the SRFC approach can enhance students’ self-regulated learning (SRL) skills, a pretest, posttest nonequivalent quasi-experiment study design using a mixed-method approach was conducted. The experiment collects evidence for investigating whether the approach can (1) enhance students’ SRL, (2) foster better feedback practice, (3) enhance students’ second language writing skills and (4) foster the use of SRL strategies. Quantitative measures included two self-report questionnaires MSLQ-RCV and AEQ, students’ ELS written test and SRLIS structured interview. ANCOVA was used to analyse the data. Students’ responses to the SRLIS also transcribed, categorised into 15 SRLIS strategies and analysed qualitatively.The results indicate that students’ self-efficacy, use of feedback and writing skills were significantly higher in the SRFC classroom experimental group than in the control group. Moreover, students’ test anxiety was statistically significantly lower in the experimental group. These findings suggest that the SRFC approach can enhance students’self-efficacy, reduce their test anxiety, foster better use

Differentiated instruction has been advocated for embracing learner diversity, but it has been found that differentiated instruction implementation is difficult and teachers often feel unprepared. This qualitative case study explored the professional development of two English language teachers in two participating schools of a school-university collaboration project on diversity management in Hong Kong. Based on the data collected from co-planning meetings, lesson observations, semi-structured interviews, focus groups and artefacts, the study showed that research-informed teaching and teaching-informed research were both indispensable to differentiated instruction infrastructure building; school cultures and teacher efficacies both affected teachers’ attitudes towards researcher-practitioner collaboration modes for professional development. Teachers whose efficacy and professional learning community remained at a developing stage tended to rely on an expert-guided collaboration mode. Yet, those whose efficacy and professional learning community had advanced would prefer a more self-redirected learning mode. These findings shed light on bridging the researcher-practitioner divide in teacher education. Copyright © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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.

This study investigates whether demographics, L2 enjoyment, L2 anxiety, psychological well-being, or informal digital learning of English (IDLE) affect willingness to communicate in L2 (L2 WTC) at trait or state levels. Across two weeks, 16 Hong Kong EFL students completed pre-and post-trait-level surveys and generated 1,120 state-level responses via the experience sampling method (ESM). The survey findings revealed that students who were older, had higher language proficiency, or had higher pre-WTC digitally reported higher L2 WTC in the classroom. Students who had studied English longer, had higher language proficiency, had higher pre-psychological well-being, had a higher standard deviation L2 WTC over 14 days, or had higher teacher appreciation showed higher L2 WTC outside of class. Students with higher language proficiency, higher pre-WTC digitally, or higher post-psychological well-being reported higher L2 WTC in digital settings. The ESM findings revealed that students with higher teacher appreciation, currently engaged in productive IDLE or both receptive and productive types of IDLE, currently experienced greater L2 enjoyment, or currently experienced greater well-being had higher L2 WTC now. Our findings are relevant to: (a) L2 WTC, informal language learning, and positive psychology theories, and (b) strategies that can be used to enhance students’ L2 WTC overall and at a particular moment. Copyright © 2024 The Author(s).

This study investigated the perceptions of second language (L2) English learners from Hong Kong on the speech produced by third language (L3) English learners from the Greater Bay Area (GBA) of China. Twenty L2 learners from a local university were asked to listen to speech recordings from two L3 learners, and then complete an online survey, which focused on comprehension of the speech and four dimensions of language attitudes, namely Appropriateness, Solidarity, Status, and Dynamism. Results showed correlations between the phonological performance of learners and the perception of listeners. Specifically, vowel replacement and addition, as well as consonant addition were found to have a negative correlation with the learners’ actual comprehensibility. Replacing /ə/ with Chinese ‘er’ /ɚ/ only affected their perceived comprehensibility. For perceived attitude, the presence of vowel replacement and addition had an adverse effect on the rating of Dynamism. These two features, along with consonant addition, also negatively affected the rating of Status. Moreover, consonant addition was the sole factor that negatively affected the rating of Solidarity. These findings provided pedagogical insights for learners to communicate in English as well as social implications for language paradigm, particularly in a multilingual and multicultural context such as the GBA. Copyright © 2024 Informa UK Limited, trading as Taylor & Francis Group.