Volume 28 Number 1, 2024
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ItemThe effects of feedback type and explicit associative memory on the effectiveness of delayed corrective feedback in computer-mediated communication(University of Hawaii National Foreign Language Resource Center, 2024-07-29)The present study examines the impact of the explicitness of corrective feedback and explicit associative memory on the acquisition of -ing/-ed participial adjectives through delayed video-based corrective feedback. Fifty-two L1 Spanish learners were randomly assigned to one of three groups (implicit, explicit, or no-feedback) and performed an interactive task with an experimenter via a video-conferencing tool without receiving any feedback. At the end of the task, the feedback groups received a video replay with inserted oral corrections (either partial recasts or explicit corrections). The no-feedback group performed the interactive task without receiving corrective feedback. A paired-associates test with delayed recall was used to measure explicit associative memory. Pretest-posttest development was measured using oral production and grammaticality judgment tasks. Both corrective feedback groups outperformed the no-feedback group. While no statistical difference emerged between the two delayed corrective feedback groups, a small difference was detected for the explicit group when considering effect sizes. Moreover, a positive relationship was found between explicit associative memory and learning gains on the grammaticality judgment task.
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ItemAudiovisual input in language learning: Teachers’ perspectives(University of Hawaii National Foreign Language Resource Center, 2024-07-22)A substantial body of research shows that various types of audiovisual (AV) input such as videos and videos with second language (L2) subtitles can facilitate language learning. However, language teachers’ day-to-day practices with regard to multimodal input is less understood. To bridge the gap in language education, this study investigates teachers’ perceived use of four types of AV input (video only, video with subtitles, video with captions and video with enhanced captions) and factors influencing teachers’ perspectives on these types of input for in-class and out-of-class learning. Questionnaire data were collected from 193 L2 teachers across the globe about their perceived use of AV input. Teachers reported that they use video and captioned video most frequently in both classroom and out-of-class contexts. Logistic regression analyses revealed that teachers’ perceived importance and comfort using specific AV input types were the two most important factors explaining teachers’ reported use. Complementarily, open-ended responses were analyzed qualitatively to identify teachers’ additional reasons for (non)use of such input.
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ItemThe AI chatbot interaction for semantic learning: A collaborative note-taking approach with EFL students(University of Hawaii National Foreign Language Resource Center, 2024-07-15)This study explores the impact of an innovative approach that combines artificial intelligence (AI) chatbot support with collaborative note-taking (CNT) in the comprehension of semantic terms among English as a Foreign Language (EFL) learners. Given the significance of semantics in English language learning, traditional didactic methods often present challenges for EFL learners. The proposed AI chatbot-supported approach aims to foster learner interaction, while the CNT strategy focuses on enhancing knowledge retention and engagement with learning materials. Conducted as a quasi-experimental pre-test-post-test design, the study involved 60 English Language and Literature majors from a non-English-speaking area enrolled at a private university. Participants were divided into the AI chatbot-supported and CNT (AI-CNT) group and the conventional CNT (cCNT) group. Results indicated that the AI-CNT group outperformed the cCNT group across various dimensions of semantic learning outcomes, including performance, achievement, self-efficacy, metacognition, and anxiety reduction. This study highlights the potential of integrating AI chatbot support and the CNT strategy to significantly enhance the EFL semantic learning experience. The personalized and interaction-based linguistic practices, enriched with feedback and emotional support, offer a promising avenue for advancing language learning outcomes in the digital age.
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ItemEffects of machine translation on L2 writing proficiency: The complexity accuracy, lexical diversity, and fluency(University of Hawaii National Foreign Language Resource Center, 2024-07-08)With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students’ retention of learning or secondary school students’ use of MT in L2 writing has rarely been researched. The current study investigates the effectiveness of using machine translation on Korean middle school students’ L2 writing over an extended period of time. This study evaluated the complexity, accuracy, lexical diversity, and fluency of four versions of the students’ writing (pretest, MT-assisted version, posttest, and 2-week or 4-week retention tests) and measured errors in punctuation, spelling, vocabulary, and grammar in each version. The study employed a quantitative research method including descriptive statistics, repeated measures ANOVA, and paired t tests. The results showed that fluency, accuracy, and complexity significantly increased in the MT-assisted version in every aspect of writing, but decreased in the subsequent versions without MT (post- and retention tests). Decreases occurred more frequently with grammatical items than with lexical items. Despite the decreases, all of the items measured in the study scored higher in the retention tests than in the pretest, which indicates that the use of MT had a positive effect on L2 writing.
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ItemThe deliberate study of concrete nouns with tablet-based augmented reality(University of Hawaii National Foreign Language Resource Center, 2024-07-01)Three modes of deliberate vocabulary study were investigated to determine how well they assisted learners’ recall of the meaning of target concrete nouns. Two modes of tablet-based augmented reality, one context-independent (AR1) and one context-dependent (AR2), were compared with each other and with paper-based word cards (WC) in the deliberate study of three sets of nonwords representative of concrete nouns. An orthogonal Latin square design was used to counterbalance 39 participants. We hypothesized that both AR conditions would be more beneficial than word cards in terms of participants’ ability to retain the meaning of the target words as demonstrated by performance on Yes/No and meaning-recall test items, and that AR2 conditions would be more beneficial as compared with AR1 conditions. Generalized linear mixed models revealed that both AR study modes significantly outperformed word cards. The context-dependent and context-independent augmented reality study modes did not significantly differ indicating that a visuospatial bootstrapping effect (VSB) was likely at play regardless of how dependent on or independent of their respective scenes the items studied were. These findings offer pedagogical implications of mobile-based AR use in vocabulary study and language learning in general.
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ItemInvestigating the types and use of feedback in middle-school English language learners’ academic writing(University of Hawaii National Foreign Language Resource Center, 2024-06-24)With the increased rigor of academic standards, high expectations of academic writing skills have been imposed on students in U.S. K-12 schools. For English learner (EL) students who cope with the dual challenges of learning rigorous subject matters and developing their English language proficiency simultaneously, extra support and effective instructional strategies are crucial. Given the rapidly growing use of computerized testing and the prevalence of writing on computers in K-12 education, this study explored the use of an automated writing evaluation (AWE) tool in support of the needs of EL students and teachers. Specifically, this study examined the types of feedback that middle-school EL students received from the AWE tool as well as from teachers and how the students addressed the feedback. A total of 130 students participated in the study, including 106 EL students with different English proficiency levels and 24 non-EL students as a comparison group. The results suggest that the AWE tool provided considerably more feedback to EL students compared to non-EL students and that teachers’ feedback was mainly regarding language use rather than content development and organization. Drawing on the findings, implications for practice and research are discussed.
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ItemCorrective feedback accuracy and pronunciation improvement: Feedback that is ‘good enough’(University of Hawaii National Foreign Language Resource Center, 2024-06-17)It is unclear whether corrective feedback (CF) provided by L2 computer-assisted pronunciation training (CAPT) tools must be 100% accurate to promote an acceptable level of improvement in pronunciation. Using a web-based interface, 30 native speakers of Chinese completed a pretest, a computer-based training session to produce nine sound contrasts in English, and a posttest. The study manipulated feedback accuracy using a modified “Wizard of Oz” protocol in which a phonetically-trained human listener in a separate room provided CF on the trainees’ productions, but the trainees thought that the computer-based system provided the CF. The computer system presented a set of three sound contrasts with 100% accuracy, three with 66% accuracy (with one of three human responses changed randomly), and three with 33% accuracy (with two of three human feedback responses being changed). The trainees’ pre- and posttest productions were rated for accuracy by native speakers of English. For trained items, productions were not significantly different when the trainees received CF with 100% or 66% accuracy, but both resulted in greater improvement than feedback with 33% accuracy. An important implication for L2 pronunciation training software is that machine feedback can be beneficial even when it is ‘good enough’ (i.e., not 100% accurate).
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ItemMoving from off-the-shelf chatbots to a user-designed bespoke L2 chatbot(University of Hawaii National Foreign Language Resource Center, 2024-06-10)This study investigates the application of Large Language Model (LLM)-based chatbots for second language (L2) learning, focusing on the three chatbot-building platforms such as ChatGPT, Poe AI, and Pi. Engaging 96 pre-service teachers in South Korea, it examined their perceptions of chatbots built via these platforms concerning human-likeness, pedagogical usefulness, and specific strengths and weaknesses. Participants were asked to create task-oriented chatbots using these platforms and to converse with them. The findings reveal varied perceptions of human-likeness among the chatbots, with Pi rated the highest. Regarding usefulness for L2 learning, the chatbots built via all three platforms were deemed beneficial, especially for engaging in realistic scenarios and providing authentic, context-appropriate expressions. Each platform demonstrated unique strengths but also showed some limitations, based on which we provide the pedagogical implications. Overall, the present study contributes to the evolving field of chatbot-assisted language learning, demonstrating the utility of LLM-based platforms in creating customized L2 learning chatbots.
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ItemThe effectiveness of computerized listening dynamic assessment: Attribute-based mediation model(University of Hawaii National Foreign Language Resource Center, 2024-06-10)There is growing literature on computerized dynamic assessment (C-DA) wherein individual items are accompanied by mediating prompts, but its effectiveness at fine-grained levels across time has not been explored sufficiently. This study constructed a computerized listening dynamic assessment (CLDA) system, where mediation was informed by an attribute-based mediation model (AMM) that established the relationship between the listening items and their underlying cognitive attributes. One hundred and twelve low-level university learners participated in the study, with the experimental group using the AMM-informed CLDA system (hereafter the CLDA group) and the control group (CG) using a non-dynamic assessment. Results indicated that the CLDA group significantly outperformed the CG in the post- and transfer- tests at both the test and attribute levels, and mediation was more effective for items of low and medium difficulty levels than those of high difficulty levels. Questionnaire and interview data indicated that most students perceived the CLDA system positively. The study demonstrates the advantages of AMM-informed C-DA in fine-grained diagnosis and tailored mediation. At the same time, it helps advance the validation pursuit of future mediation development.
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ItemSelf-regulated and collaborative personalised vocabulary learning approach in MALL. Language Learning & Technology(University of Hawaii National Foreign Language Resource Center, 2024-06-03)Students often have difficulties in self-regulating their vocabulary learning in mobile-assisted language learning (MALL). Building on past studies of vocabulary learning, MALL, self-regulation, and personalised learning (PL), we propose a self-regulated, collaborative, personalised vocabulary (SCPV) learning approach in MALL. In this exploratory mixed-methods study, 35 university students learned second language (L2) vocabulary via the SCPV or a self-regulation-only (S) approach. Data were collected through pre- and post-surveys, personalised vocabulary tests, and interviews. The results indicated that the new approach may hold more potential to help learners achieve better productive vocabulary knowledge. Thematic analyses of interviews indicated that the SCPV students enhanced their vocabulary learning; specifically, these students demonstrated a systematic understanding of vocabulary learning processes. Furthermore, specific PL roles (e.g., community sharing of self-regulated vocabulary learning) showed how collaborative PL could aid participants' development of self-regulated learning. Implications include how to conduct self-regulated training in MALL and designing both individual and collaborative tasks that involve PL.