ScholarSpace

ScholarSpace is an open-access, digital institutional repository for the University of Hawaiʻi at Mānoa community. ScholarSpace stores the intellectual works and unique collections of the UH at Mānoa academic community and also provides a permanent web location for those accessing these resources.

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University of Hawaii Press 2026 Fall Catalog
(2026-06-05)
Generative AI and metaverse in developing pre-service teachers’ content knowledge
(University of Hawaii National Foreign Language Resource Center, 2026-06-08) Lee, Seongyong; Jeon, Jaeho
Although essential for teachers’ professional development, developing content knowledge (CK) remains a challenge in pre-service language teacher education, where applied linguistics concepts are often perceived as disconnected from practice. While research on technology integration emphasizes pedagogical or technological knowledge (TK), little is known about how emerging tools can mediate CK development. Thus, this study implemented a design-based learning project: 23 pre-service English teachers used generative AI (GenAI) and the metaverse to design their brands and 3D showrooms, using applied linguistics concepts. Reflective journals and semi-structured interviews were analyzed through thematic analysis to explore how CK developed through TK and learner agency. The findings show that their CK was enhanced when applied linguistics knowledge was used to craft brands and showrooms through iterative design cycles. Agency mediated this process, as they calibrated the outputs and collaborated through distributed agency, using GenAI and metaverse affordances. Finally, reflective inquiry enhanced critical AI literacy, which supported CK development by prompting participants to work on GenAI-mediated decisions (e.g., reliability, bias, authorship, and inclusion) while designing their artefacts. The study discusses theoretical implications for affordance–agency mechanisms in technology-mediated learning and pedagogical implications for integrating GenAI-metaverse design and critical AI literacy in teacher education.
RFL Special issue call for papers: Multimodality and L2 reading
(University of Hawaii National Foreign Language Resource Center, 2026-06-02) Jeon, Eun Lee; Yamashita, Junko
Annual Report for UHM CSEAS
(2024) CSEAS
Vocabulary grit, task emotions, and behavioral engagement during after-class app-assisted vocabulary learning among Chinese university EFL learners
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Li, Banban; Teimouri, Yasser; Mao, Shenglan; Wang, Na; Kruk, Mariusz; Pawlak, Mirosław
Drawing on the Control-Value Theory (CVT), this study investigates the impact of vocabulary grit on behavioral engagement in AVL, with task enjoyment and boredom serving as mediators. A mixed-methods approach was employed, combining survey data from 102 Chinese university EFL learners with follow-up interviews from 10 participants. In addition, a domain-specific L2 vocabulary grit scale was developed for use in the study. Structural equation modeling (SEM) results indicate that vocabulary perseverance of effort (PE) strongly predicts behavioral engagement both directly and indirectly via task enjoyment. Vocabulary consistency of interest (CI) influences behavioral engagement primarily through its effect on task enjoyment. While task boredom negatively correlates with behavioral engagement, it does not significantly mediate the vocabulary grit-behavioral engagement relationship, suggesting the presence of coping mechanisms or external motivators. Qualitative findings further illustrate that students’ behavioral engagement is driven by a combination of perseverance of effort, interest, positive emotional reinforcement, and external motivational factors such as exams. These findings highlight the complex interplay between L2 grit, task emotions, and behavioral engagement in AVL. The study offers theoretical and pedagogical insights into fostering sustained engagement in AVL by enhancing perseverance, cultivating interest, and promoting positive emotions.
Pride and shame in CALL: Links to appraisals, engagement, and performance
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Shao, Kaiqi; Amiri, Elmakki; Kutuk, Gulsah; Kruk, Mariusz; Pawlak, Mirosław
Guided by the control-value theory of achievement emotions, this study examines the relationships among two understudied foreign language emotions, namely pride and shame, control-value appraisals, engagement, and performance in a Computer-Assisted Language Learning (CALL) setting. A total of 652 Chinese university students from a massive open online course (MOOC) participated in the study. Structural equation modeling (SEM) results showed that control and value appraisals positively predicted pride but negatively predicted shame. Pride positively predicted each of the three dimensions of engagement (i.e., cognitive, emotional, and behavioral) while shame negatively predicted these dimensions, except for cognitive engagement. Emotional and behavioral engagement, but not cognitive engagement, positively predicted performance. Pride and shame mediated the relationship between control-value appraisals and emotional and behavioral engagement, which, in turn, mediated the relationship between pride or shame and performance. By contrast, pathways through cognitive engagement were not significantly linked to performance. Overall, pride and shame, along with emotional and behavioral engagement rather than cognitive engagement serially mediated the relationship between control-value appraisals and performance. We discuss the implications for language teachers and highlight the importance of addressing pride and shame, alongside their appraisal antecedents and learning outcomes in CALL.
The developmental trajectory of L2 students’ positive achievement emotions and flow experience within AI-enhanced classrooms: A latent growth curve modeling (LGCM)
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Qin, Lili; Derakhshan, Ali; Kruk, Mariusz; Pawlak, Mirosław
The integration of artificial intelligence (AI) in L2 classrooms has garnered remarkable attention due to its potential to enhance students’ language achievements. While existing research has highlighted the implications of incorporating AI into L2 classrooms, there remains a gap in understanding how this incorporation may affect students’ achievement emotions and flow experiences. To narrow this gap, this intervention study sought to assess the influence of AI-enhanced instruction on L2 students’ positive achievement emotions: pride, hope, enjoyment, and their flow experiences. Furthermore, with the aid of latent growth curve modeling (LGCM), the study tried to track the developmental trajectory of L2 students’ positive achievement emotions and flow experiences over the course of a semester. To these aims, a large sample of 217 L2 students was recruited and randomly divided into the control or experimental groups. To measure participants’ flow and positive achievement emotions, two questionnaires were administered to them at distinct intervals throughout the intervention. The results evinced a notable enhancement in both the flow experience and positive achievement emotions of participants who were exposed to AI-enhanced instruction. This research underscores the critical role of AI-enhanced instruction in fostering students’ positive achievement emotions and flow experiences within L2 classrooms.
Incorporating digital multimodal composing into game-enhanced language learning
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Li, Ke; Peterson, Mark; Fan, Qin; Kruk, Mariusz; Pawlak, Mirosław
As part of a research project on the use of digital games for language learning, this study explored the emotional trajectory and experiences of EFL learners during game-enhanced digital multimodal composing (DMC), with a focus on enjoyment and boredom. Informed by the control-value theory, this exploratory multiple case study centered on two groups of learners who volunteered to participate in this out-of-school project in which they played the digital game Genshin Impact and completed DMC over the course of six weeks. Both quantitative and qualitative data were collected and analyzed, including emotion questionnaires, participants’ gaming journals, DMC productions, semi-structured interviews, and critical incident forms. The results showed that despite fluctuations, the high achievers in DMC demonstrated high levels of enjoyment and moderate levels of boredom. Low achievers experienced relatively high levels of boredom and moderate levels of enjoyment during DMC tasks. Analysis further revealed the control and value ascribed to the tasks as potential causes for these differences and emotional fluctuations. The findings also highlight the role identity played in the control-value appraisal of the learning activity. The pedagogical implications of the study are discussed and suggestions for future research are provided.
Dynamicity of EFL learners’ emotions and WTC in Human-AI interactions
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Cheng, Qian; Chen, Xiuwen; Luo, Yiyang; Wang, Hao; Kruk, Mariusz; Pawlak, Mirosław
This study investigates dynamic fluctuations in willingness to communicate (WTC) and emotional states among six Chinese English as a Foreign Language (EFL) learners during interactions with Replika, an AI-powered chatbot. Using an idiodynamic method and stimulated recall interviews, the study provides a granular understanding of WTC and emotional dynamics. Participants exhibited a range of emotional states, including epistemic and retrospective emotions, which were intermittently elicited by moment-to-moment interactional events. Fluctuations were induced by various factors, including anthropomorphism, conversational responsiveness, perceived naturalness of interaction, and learners’ perceptions of Replika as either a conversational companion or a tool for language practice. Finally, this study proposes expectation appraisal as a key mediating mechanism between interactional factors, emotional states, and WTC. Learners’ expectations constituted a significant factor influencing emotional outcomes and ongoing WTC. These findings are discussed with reference to the L2 WTC pyramid model, emphasizing the interplay between emotions and communicative behaviors in AI-mediated language-learning environments.
Students’ emotions and cognitive loads in chatbot-versus peer-supported reading
(University of Hawaii National Foreign Language Resource Center, 2026-06-01) Guan, Xiaotian; Su, Yanfang; Jin, Tan; Lai, Chun; Li, Yuanke; Kruk, Mariusz; Pawlak, Mirosław
Using a within-subject design, this study engaged 60 Chinese EFL university students in reading English academic passages either with GenAI chatbot support or with peer support. Employing questionnaires, we compared the levels of positive and negative emotions and intrinsic and extraneous cognitive loads reported by students in these two reading conditions. Additionally, semi-structured interviews were conducted with 16 students to delve into the factors affecting their emotions and cognitive loads in the two interactive reading conditions. The results of questionnaires show that students experienced a significantly higher level of positive activating and deactivating emotions such as hope and relief and a lower level of negative activating emotion such as anxiety, as well as significantly lower levels of intrinsic and extraneous cognitive load in chatbot-supported reading. The interviews further reveal that students attributed the observed advantages of reading with chatbot to its immediate support, high efficiency, convenience of tracking the discussion record, and the low-stress learning environment. In the meantime, they reported disadvantages in emotional communication and social dynamics when communicating with AI chatbot. Overall, this study has elucidated the mechanisms underlying differential effects of reading with GenAI chatbot support versus peer support on students’ emotions and cognitive loads.