Recent years have witnessed a growing application of generative artificial intelligence (GenAI) technology in writing instruction. Students should mobilise their metacognitive strategies during this endeavour to maximise the benefits of GenAI while avoiding the potential negative impacts. Within the context of tertiary education in Hong Kong, this qualitative research investigates 13 postgraduate students' metacognitive strategies when utilising ChatGPT for English academic writing. Using data collected from audio recordings, semi-structured interviews and human-GenAI chat logs, we explored students' metacognitive strategies within five dimensions, namely, planning, monitoring, evaluating, information management and debugging. The identified themes and subthemes within each dimension exhibited similarities to those observed in other educational settings. Meanwhile, certain metacognitive strategies (e.g., debugging) were found to be unique to the context of GenAI-supported academic writing. This study contributes to the literature in two ways. Firstly, it provides a detailed and thorough understanding of metacognitive strategies, complementing the extensive quantitative research in this area. Secondly, this research expands the framework of metacognitive strategies to the context of GenAI-supported academic writing learning. Copyright © 2025 Wiley-Blackwell Publishing Ltd.

Students’ development of multilingual competence has attracted increasing attention from language researchers and educators. However, research on students’ interaction strategy use in group discussions across different language settings remains scarce. In this study, therefore, we examined interaction strategy use in Cantonese as a first language (L1) and Putonghua as a second language (L2) during group discussion tasks among 42 primary school students in Hong Kong. We also investigated the effects of interaction strategy use on performance in respective tasks. We discovered that students employed significantly more interaction strategies in L1 than in L2, with a higher contribution to L1 task performance. Specifically, three of the five strategies identified—Strategy 2 (S2) asking for opinions, S3 expressing attitude, and S5 non-verbal language—were employed more frequently in L1 than in L2. Furthermore, we found that strategy use had various effects on oral performance between the two languages. In the L1 task, S1 expressing actively, S3 expressing attitude, and S4 giving clarification significantly predicted students’ group discussion performance, whereas this effect was only observed in S1 expressing actively in the L2 task. Pedagogical implications for primary students’ learning of interaction strategies for group discussions in both L1 and L2 are discussed. Copyright © 2024 John Wiley & Sons Ltd.