刊讯丨SSCI 期刊《语言学习与技术》2024年1-2期
Language Learning & Technology
Volume 28, Number 1-2 , 2024
Language Learning & Technology（SSCI一区，2022 IF：3.8，排名：14/194）2024年第1-2期共发文38篇，其中，2024年第1期共发文28篇，包括研究性论文20篇，专栏5篇，媒体评论3篇；2024年第2期共发文10篇，包括研究性论文8篇，专栏2篇。研究论文涉及多语研究、二语习得研究、二语教学研究等。欢迎转发扩散！
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目录
Number 1
ARTICLES
Corrective feedback accuracy and pronunciation improvement: Feedback that is ‘good enough’, by Alif Silpachai, Reza Neiriz, MacKenzie Novotny, Ricardo Gutierrez-Osuna, John M. Levis & Evgeny Chukharey, P1-16
The effectiveness of computerized listening dynamic assessment: Attribute-based mediation model, by Yaru Meng, Hua Fu & Chuang Wang，P1-28
Self-regulated and collaborative personalised vocabulary learning approach in MALL. Language Learning & Technology, by Qing Ma & Ming Ming Chiu
Lag effects for foreign language vocabulary learning through Quizlet,by Jonathon Serfaty & Raquel Serrano
English L2 vocabulary learning with clickers: Investigating pedagogical effectiveness, by Anne-Marie Sénécal & Walcir Cardoso
Computer-Assisted Pronunciation Training (CAPT): An empirical evaluation of EPSS Multimedia Lab, by María de los Ángeles Gómez González & Alfonso Lago Ferreiro
Multimodal interactive alignment: Language learners’ interaction in CMC tasks through Instagram, by Muntaha Muntaha, Julian Chen & Toni Dobinson
The impact of the pandemic on student Spanish language proficiency, by Jesse Gleason, Resha Cardone & Andrew Bartlett
An innovative pictographic glosses design for East Asian EFL vocabulary learners: Effects on retention performance and situational interest, by Liu-Cheng Pan & Jerry Chih-Yuan Sun
Visual reinforcement through digital zoom technology in FL pronunciation instruction, by Siqi Wang, Jian Li & Qian Liang
Speech-to-text applications’ accuracy in English language learners’ speech transcription, by Akiyo Hirai & Angelina Kovalyova
Digital game-based learning’s effectiveness on EFL learners’ receptive and productive vocabulary knowledge, by Wen Jia, Liping Zhang, Austin Pack, Yi Guan & Bin Zou
Effects of mobile-assisted language learning on foreign language learners’ speaking skill development, by Rui Li
Hey Siri: Should #language, 😕, and follow me be taught?: A historical review of evolving communication conventions across digital media environments and uncomfortable questions for language teachers, by Heather Lotherington & Noah Bradley
Pretask training for web-based second language collaborative writing,by Hsiu-Chen Hsu
Pragmatic feedback on refusals in a computer-simulated advising session, by Paul Richards
Second language processing of errors in Korean-to-English machine-translated output, by Eun Seon Chung
A reflective e-learning approach for reading, thinking, and behavioral engagement, by Mei-Rong Alice Chen & Yi-Hsuan Lin
How competitive, cooperative, and collaborative gamification impacts student learning and engagement, by Shen Qiao, Susanna Siu-sze Yeung, Xiaoai Shen, Jac Ka Lok Leung, Davy Tsz Kit Ng & Samual Kai Wah Chu
Online videos for self-directed second language learning, by Louisa Willoughby & Cathy Sell
Openings and closings in human-human versus human-spoken dialogue system conversations, by Judit Dombi, Tetyana Sydorenko & Veronika Timpe-Laughlin
Using chatbots to support EFL listening decoding skills in a fully online environment, by Weijiao Huang, Chengyuan Jia, Khe Foon Hew & Jia Guo
Teaching foreign language with conversational AI: Teacher-student-AI interaction, by Hyangeun Ji, Insook Han & Soyeon Park
Effects of learner uptake following automatic corrective recast from Artificial Intelligence chatbots on the learning of English caused-motion construction, by Rakhun Kim
The effects of AI-guided individualized language learning: A meta-analysis, by Hansol Lee & Jang Ho Lee
Teacher engagement with automated text simplification for differentiated instruction, by Fengkai Liu, Yishi Jiang, Chun Lai & Tan Jin
Exploring AI-Generated text in student writing: How does AI help? byDavid James Woo, Hengky Susanto, Chi Ho Yeung, Kai Guo & April Ka Yeng Fung
Automated versus peer assessment: Effects of learners' English public speaking, by Chunping Zheng, Xu Chen, Huayang Zhang & Ching Sing Chai
摘要
Corrective feedback accuracy and pronunciation improvement: Feedback that is ‘good enough’Alif Silpachai, Radboud UniversityReza Neiriz, Iowa State UniversityMacKenzie Novotny, Iowa State UniversityRicardo Gutierrez-Osuna, Texas A&M UniversityJohn M. Levis, Iowa State UniversityEvgeny Chukharev, Iowa State University
Abstract 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).
Key words Corrective Feedback, Second Language Pronunciation, English as a Second Language, CAPT
Abstract 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-based C-DA in fine-grained diagnosis and tailored mediation. At the same time, it helps advance the validation pursuit of future mediation development.
Key words Dynamic Assessment, Computerized Dynamic Assessment (C-DA), EFL listening, Attribute- based Mediation Model
Abstract 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.
Key words Second Language (L2) Vocabulary Learning, Self-regulation, Personalisation, Mobile-Assisted Language Learning (MALL)
Abstract Digital flashcard apps allow students to learn and practice foreign language vocabulary independently and efficiently, leaving more classroom time for communicative activities. However, words learned this way may be forgotten. Previous lab studies have shown that vocabulary retrieval practice can be optimized for long-term memory by employing longer intersession intervals, but this lag effect has not been shown in classroom conditions. The present study investigated the optimal gap between two Quizlet sessions for retaining new vocabulary. Secondary-school students (N = 96, mean age = 13.44) learned 16 novel words in an unknown language with either a 1-day or 1-week interval. Their productive and receptive knowledge was tested after seven or 28 days. Results showed that longer spacing was beneficial for vocabulary retention, contrary to previous findings reported with school-aged learners using other types of training. The effect was small, but significantly larger on receptive tests, suggesting that the lag effect depends upon the kind of knowledge being tested.
Key words Lag Effect, Vocabulary, Retrieval, Productive, Receptive Knowledge
Abstract A growing body of literature on the pedagogical effectiveness of clickers in a second language (L2) context has revealed that clickers can promote learning. However, the extent to which clickers play a role in L2 acquisition compared to other pedagogical approaches lacks consensus; in addition, most research has focused on adult learners and has taken place in large classrooms. To address these limitations, the current research investigated the effects of clickers on L2 vocabulary acquisition in a K-12 educational setting. Two intact groups of Grade 8 students learning L2 English were assigned to a treatment: while the Clicker Group (n = 31) received instruction via clickers, the Non-Clicker Group (n = 30) was treated via hand- raising without the target technology. The pedagogical effectiveness of clickers on participants’ acquisition of the target vocabulary was measured via pretests, posttests and delayed posttests. Overall, the results indicate that vocabulary acquisition was comparable in both groups. The discussion of the findings explores the role of individual differences among users (i.e., some participants improved significantly more than others) and highlights the implications of the study for L2 teaching/learning.
Key words Learner Response Systems, Clickers, L2 Pedagogy, Pedagogical Effectiveness
Abstract Previous research has established that phonetics has been marginalized within language teaching, proving to be particularly challenging for learners in EFL contexts. This paper presents EPSSML (https://www.usc.gal/multimlab/), an e-learning platform designed within Mayer’s (2008, 2009) Cognitive Theory of Multimedia Learning to instruct English phonetics and phonology in an EFL context. Inspired by prior work (e.g., Clark, 2009; Godwin-Jones, 2009; Hansen Edwards et al., 2021), we examined the efficiency of EPSSML as a Computer Assisted Pronunciation Training (CAPT) resource alongside the students’ perceptions of it including gender differences. The scores obtained by 504 Spanish EFL learners in an English phonetics undergraduate course were analyzed comparing performance before and after EPSSML-assisted instruction. The analysis of rated results shows that there is a significant difference between the means of scores of those learners that used and those that did not use the platform, as well as between male and female students. Additionally, 127 students that used EPSSML responded to an online questionnaire on the tool and course methodology. Responses reveal that 91.3% of the learners enjoyed and were very interested in EPSSML and web-mediated phonetic training. The findings demonstrate the importance of CAPT-based instruction and suggestions are also made for additional resources and approaches for its implementation, thereby contributing to the educational shift from traditional, teacher- centered learning methods to blended instructional methodologies in formal and informal settings.
Key words Computer Assisted Pronunciation Training, EFL Phonetics Web-Mediated Learning, Phonetic Skills, Contrastive Phonetics
Abstract Technological advancement has enabled language learners to employ verbal and nonverbal cues in computer-mediated communication (CMC). These cues can support language use for learners wishing to communicate more effectively in English. Interactive alignment is one phenomenon that shows how humans tend to collaborate in their language use by adapting, priming, and reusing verbal and nonverbal cues to achieve mutual understanding. Informed by a sociocognitive framework, this study explored and documented English language learners’ multimodal interactive alignment during their CMC task engagement through Instagram. We collected data from 30 first-year Indonesian business school learners who participated in seven online CMC tasks using Instagram chat features: text chat, voice chat, and video chat. To examine various interactive alignments (e.g., how interlocutors adapt, prime, and reuse verbal and nonverbal cues to achieve mutual understanding) that occurred during multimodal task communication, we employed multimodal (inter)action analysis. Findings revealed that learners adapted and reused various nonverbal features (e.g., emojis, GIFs, facial expressions, gestures) and verbal cues (e.g., expression, lexical) to convey and comprehend meaning during CMC task completion. Caveats about using various nonverbal alignment patterns for supporting better English online communication were also noted. The study highlights how language learners use the full repertoire of semiotic resources in CMC to maximize their online language learning.
Key words Interactive Alignment, Multimodal (Inter)action Analysis, Instagram, Computer-Mediated Communication (CMC)
Abstract In the aftermath of the COVID-19 pandemic, we continue to take stock of student learning. Although the “crisis-context” (Gacs et al., 2020) move to fully online instruction may be over, a complete understanding of how student outcomes have been impacted remains. The present study focuses on how students’ Spanish language proficiency, as measured by the STAMP test, was affected by moving all on-ground language courses online in March 2020 at a small public university in the northeastern US. Comparing overall student Spanish language proficiency as well as reading, writing, speaking, and listening skills across 30 sections of a third-semester Spanish course before and during the pandemic, we examined student learning outcomes based upon the modality of instruction. Results revealed a significant increase in students' overall Spanish language proficiency and significant increases in sub-level proficiencies in three out of the four skills in the online modality. Thus, in spite of the many changes that took place as a result of the COVID- 19 pandemic, students' Spanish language proficiencies were either positively impacted or unimpacted. We discuss the implications of these results and pose questions for on-ground and online language courses moving forward.
Key words Language Proficiency, Pandemic, Online Learning, On-ground Learning
Abstract Taking into account the challenges of EFL vocabulary learning for East Asian learners, this study developed a set of experimental English vocabulary material with pictographic glosses which may stimulate students’ situational interest (with dimensions of exploration intention, instant enjoyment, novelty, attention demand, challenge, and total interest) in learning vocabulary and facilitate their vocabulary retention. To examine the effectiveness of the learning material, this study utilized a within-subjects quasi-experimental design. The participants were 108 graduate and college students who used the learning materials presented in text-only, text-with-picture, and pictographic formats in an online learning system. Results revealed that students’ retention performance on the pictographic materials was significantly higher than on the text- only materials, while no significant differences were found between the pictographic and text-with-picture materials. The perceived situational interest in the pictographic material was significantly higher than in the other two formats. The results suggest that the pictographic vocabulary material could trigger EFL learners’ situational interest and help to promote their English vocabulary learning. It could therefore serve as a novel approach to designing EFL vocabulary materials for multimedia environments.
Key words Pictographic Glosses, EFL Vocabulary Learning, Retention Performance, Situational Interest
Abstract Drawing on skill acquisition theory (DeKeyser, 2017) and the Information Feedforward and Feedback Loop model (de Bot, 1980), this study aimed to explore the effects of digital zoom technology as a visual reinforcement tool (VRT) in foreign language (FL) pronunciation instruction on learners’ segmental production, and learners’ attitudes toward and experience with it. The study was conducted during a two- week introductory FL Spanish course with a cross-over design. In the experimental class, the teacher used a tablet to provide magnified visual feedforward for articulatory gestures during explicit instruction of target consonants that were new to Chinese learners, and the students used smartphone apps with digital zoom for augmented visual self-feedback during their practice. In the control class, the teacher adopted a traditional analytic-linguistic approach for explicit instruction and an audio-only intuitive- imitative approach for students’ practice. The results of the production test show that the experimental group performed significantly better in the production of the postvocalic /l/ and the dental fricatives /θ/ and /ð/, but not in the trill /r/. Interview data suggests that the VRT strategy was advantageous in directing the participants’ attention to articulatory gestures, and that most students showed positive attitudes toward this new method.
Key words Mobile-assisted Language Learning (MALL), Computer-assisted Pronunciation Training (CAPT), Pronunciation, Second Language Acquisition (SLA)
Abstract Speech-to-text applications have great potential for helping students with English language comprehension and pronunciation practice. This study explores the functionality of five speech-to-text (STT) applications (Google Docs voice typing tool, Apple Dictation, Windows 10 Dictation, Dictation.io [a website service], and “Transcribe” [an app on iOS]) to measure their speech transcription accuracy of American English. The experiment involved 30 nonnative speakers, who were asked to perform four speaking tasks and whose speeches were recorded and transcribed with these applications. The transcriptions produced by the applications were then compared with human-made transcriptions to evaluate the accuracy rate of each application’s speech transcription ability. The results revealed that the accuracy rate of speech transcriptions depends not only on the applications’ automatic speech recognition ability but also on the types of speech produced, as well as each speaker’s L1 influence on L2 (English). The study also offers examples of Japanese speakers’ pronunciation errors attained through STT transcription, demonstrating great pedagogical potential for pronunciation practice and assessment in English classrooms.
Key words Automatic Speech Recognition, Speech-to-text Applications, Pronunciation, Loanwords
Abstract Although digital game-based vocabulary learning (DGBVL) has received increasing attention in the past two decades, the impacts of DGBVL on the depth of word knowledge are still not well understood, especially in regard to productive vocabulary learning and DGBVL’s long-term efficacy. This study leverages a quasi- experimental research design to investigate DGBVL’s long-term effects on receptive vocabulary (RV) and productive vocabulary (PV). Forty-eight Chinese English-as-a-foreign-language (EFL) university students, assigned to the experimental and control groups, were instructed by a DGBVL approach and PowerPoint (PPT) lecturing, respectively, over the course of 18 weeks. Specifically, a mixed 2×2 repeated measures experimental design was conducted by adopting instruction type (DGBVL and PPT lecturing) and testing time (pretest and posttest) as the independent variables, with RV and PV proficiency as the respective dependent variables. The results suggest that instruction type and teaching time have significant effects on participants’ RV and PV learning achievements. However, teaching time’s effect size outweighs instruction type. The findings are highly encouraging for the use of DGBVL in the EFL classroom, as it may serve as an effective and long-lasting pedagogical tool within this context.
Key words Digital Game-Based Learning, Receptive Vocabulary, Productive Vocabulary, English as a Foreign Language
Effects of mobile-assisted language learning on foreign language learners’ speaking skill developmentRui Li, Hunan University
Abstract Despite the growing body of research regarding the effectiveness of MALL (mobile-assisted language learning) technologies on foreign language (FL) learners’ speaking skill development, a comprehensively quantitative meta-analysis regarding the effect sizes of these studies is still lacking. To solve the problem, this study reported results based on a meta-analysis of 20 effect sizes among 932 participants from 18 experimental and quasi-experimental studies. The results showed that the overall effect size was significantly large, suggesting the use of MALL for FL learners’ speaking skill development is more effective than traditional methods. Furthermore, learner-related, instruction-related and methodology- related moderator analysis results indicated that instructional approaches and intervention durations were significant moderators, while proficiency levels, educational levels, language types, intervention settings, software types, measured outcome types and duration intensity did not find a significant moderating effect. The results of the study provide some pedagogical implications into the use of MALL technologies for FL learners’ speaking skill development.
Key words Evidence-based Applied Linguistics (EBAL), Foreign Language (FL), Meta-analysis, Mobile- assisted Language Learning (MALL), Speaking Skill
Abstract This article presents a study on novel language forms and uses across evolving digital environments, and questions whether emerging digital communication conventions should have a place in language education. The study was motivated by the deepening gap between the content of and approaches to language instruction evident in popular mobile-(assisted) language learning (MALL) apps and the sophisticated evolutions in digital communication over the past 30 years. A team of researchers conducted an environmental scan to locate academic journals publishing on digitally-mediated language and language teaching/learning applications, and to determine topical themes and discussions. This scan was followed by a collaborative in-depth focused literature review to document technological advances and evolutionary changes in social communication across the lifespan of the WWW. The authors posit that language teaching theory and practice must attend to digital convergence and posthumanism, and pose uncomfortable questions for the language teaching profession, such as: What is the place of conversational digital agents in language teaching? Should new media grammar forms be specifically taught? Who is the arbiter of appropriate language use in digital communication?
Key words Multimodality, Mobile Learning, Apps, Posthuman LinguisticsMultimodality, Mobile Learning, Apps, Posthuman Linguistics
Abstract This study examined the effects of pretask training to promote peer collaboration, encourage learning opportunities, and foster individual L2 writing development in web-based L2 collaborative writing (CW) tasks. The participants were 48 students from two junior English composition classes at a Taiwanese university. One class (n = 24) was assigned to be a pretask training (PT) group and the other (n = 24) to a no pretask training (NPT) group. Both groups completed an individual pre- and post-test writing, and two L2 CW tasks via Google Docs. The PT group received pretask training before the CW tasks, whereas the NPT group did not. The interaction between the learners was analyzed for the number, outcome, and engagement level of content-, organization-, and language-related episodes (LREs) and for the learners’ interaction patterns. Pre- and post-test writing was analyzed in terms of content and organization and language complexity and accuracy. The PT group (a) produced more collaborative interaction during the CW processes than the NPT group, (b) produced more LREs and correctly resolved a greater proportion of LREs and content-related episodes, and (c) made greater improvement in content and language accuracy of individual L2 writing.
Key words Pretask Training, Peer Collaboration, Learning Opportunities, Web-Based Collaborative Writing
Abstract This study experimentally investigated the effectiveness of feedback on learner refusals in a computer- simulated academic advising session. Ninety participants were assigned to one of three conditions: implicit feedback, explicit feedback, and comparison group. Oral and written discourse completion tasks (DCTs) were administered in a pretest immediate posttest design. Pragmatic development was identified by examining uptake, which was operationalized as incorporation of pragmatic features from the simulation that were absent on the pretests. This analysis, therefore, focuses on the subset of learners who did not make use of the target pragmatic features from the simulation on either pretest (n = 59). Participants in the explicit feedback group showed a significantly greater degree of uptake on the posttest ODCT than the comparison group, while both feedback groups showed significantly greater uptake than the comparison group on the posttest WDCT. The study also used a written retrospective comparison task to examine how learners described changes in their language use following treatment. Responses on this task indicated a greater degree of attention to (im)politeness and evidence of learning among participants in the feedback groups, while participants in the comparison group primarily described their responses as the same as before treatment.
Key words L2 Pragmatics, Corrective Feedback, Computer Simulations, Refusals
Abstract While previous investigations on online machine translation (MT) in language learning have analyzed how second language (L2) learners use and post-edit MT output, no study as of yet has investigated how the learners process MT errors and what factors affect this process using response and reading times. The present study thus investigates L2 processing of MT errors that are caused by syntactic, morphological, and semantic differences between the source and target language and also examines how L2 proficiency and visual display affect this process. Forty-seven Korean learners of English participated in an acceptability judgment task in which they read a Korean sentence and then its translated counterpart in English and had to judge the accuracy of the translated sentence on a four-point scale. The response latencies for the accuracy judgment as well as the total reading times of source and target sentences were measured. The results revealed that (a) learners generally find it harder to reject mistranslations than to accept correct translations, (b) high and low proficiency learners focus on different aspects of language when processing translated output, and (c) constant visual access to the source text does not facilitate but rather interferes with processing MT errors.
Key words Machine Translation, Error Processing, L2 Proficiency, Visual Display
Abstract One of the main goals of the English as a Foreign Language (EFL) course is to facilitate the development of learners’ reading comprehension and reflective skills in English, which can be developed with appropriate instruction. However, in EFL courses, many students are inactive in reflecting on their reading and are disengaged from learning. To fill this gap, a reflective reading-based e-learning approach was proposed to explore the impact of the suggested approach on reading comprehension, reflective thinking, and behavioral engagement. The study aimed to improve the comprehension of the student’s reading using the proposed reflective e-learning approach. The study employed a quasi-experimental design in which the experimental group used reflective reading-based e-learning (n = 51) and the control group used conventional e-learning (n = 50) for a total of 13 weeks of participation. The experiment was designed to examine reading comprehension, reflective thinking, and behavioral engagement (e.g., reading time, Marker list, Quiz score, Memo list). The results revealed that the reflective reading-based e-learning approach could improve the comprehension and reflective thinking of the learners and promote behavioral engagement. These findings can be valuable for educators designing strategies to improve students’ reading comprehension skills and stimulate behavioral engagement in e-learning systems.
Key words Reflective E-learning Approach, Thinking, Behavioral Engagement, Reflective Thinking Skills
Abstract Gamification is an increasingly popular approach to engage learners in educational contexts. Although many studies have examined the effects of gamification in comparison to a non-gamification approach, less attention has been paid to the impact of different ways of implementing gamification on students’ learning and engagement. In this study, we performed a quasi-experiment on the competitive, cooperative, and collaborative types of gamification among secondary school students who learn English as a foreign language. The quantitative results indicate students in the competitive condition significantly outperformed their peers in the cooperative condition on a reading-related skill (morphological awareness), word reading, and reading comprehension. They also had higher gains in morphological awareness than students in the collaborative condition, although these two groups showed similar improvement in fartransfer measures (i.e., word reading and reading comprehension). Concerning engagement, qualitative data collected from interviews suggested gamification contributed to students’ behavioural, emotional, and cognitive engagement. The qualitative data also reflected the possible reasons for the quantitative results. We conclude that cooperative and collaborative gamification should be designed carefully and take various factors into account (e.g., establishing shared goals and rewards, emphasising individual and collective contributions, and collaboration training) to ensure that the gamification approach does not hinder student learning.
Key words Gamification, Competition, Cooperation, Collaboration
Abstract Recent years have seen an explosion in video content available online. Yet there is relatively scant research on if, how, and why second language (L2) learners engage with videos in their target language as part of their self-directed study—especially for languages with a smaller media footprint. This paper presents qualitative findings from a longitudinal study of the self-directed study behaviours, collected through learning diaries and stimulated recall interviews, of eight intermediate-advanced learners of Auslan (Australia Sign Language) enrolled at an Australian higher education provider. Findings show that our participants were sporadic video watchers, who largely relied on YouTube and social media for discovering Auslan content. The lack of an Auslan media industry means that online texts were often dry informational texts or user-generated content of varied quality and this negatively affected some participants motivation for watching. However, when they made time to engage with it, participants proved themselves to be highly strategic L2 viewers, who used a sophisticated range of approaches in comprehending linguistically demanding content.
Key words Sign Language, Videos, Extensive Viewing, Learning Beyond the Classroom (LBC)
Openings and closings in human-human versus human-spoken dialogue system conversations
Judit Dombi, University of Pécs, Hungary
Tetyana Sydorenko, Portland State University, Portland, OR
Veronika Timpe-Laughlin, Educational Testing Service, Princeton, NJ
Abstract Although conversation openings and closings are ritualized speech acts (House & Kádár, 2023), they do require interactional work (Schegloff, 1986). Thus, they are important elements of interactional competence (Roever, 2022) and have been studied extensively in L2 interactions, including various types of technology-mediated communication contexts (e.g., Abe & Roever, 2019; 2020). However, to our knowledge, no research on openings and closings has been conducted with newer technologies such as spoken dialogue systems (SDS). To address this gap, this study compares conversation openings and closings across two modalities: a role-play with a human interlocutor versus with a fully automated agent. We analyzed interactional data from 47 tertiary-level learners of English. A quantitative (e.g., number of turns) and a qualitative, discursive analysis rendered several key findings: 1) learners were more transactionally oriented in SDS modality, but tended to engage in relational discourse with a human interlocutor; 2) humans adapted to the emergent discourse in both modalities; 3) despite training, the human interlocutor was inconsistent in displaying transactional versus interactional patterns with different participants, while the SDS followed the same dialogue structure in each interaction. Findings will be discussed in terms of specific affordances of the two modalities for interactional competence.
Key words Openings, Closings, Interactional Competence, Artificial Intelligence, Spoken Dialogue Systems
Abstract Aural decoding skill is an important contributor to successful EFL listening comprehension. This paper first described a preliminary study involving a 12-week undergraduate flipped decoding course, based on the flipped SEF-ARCS decoding model. Although the decoding model (N = 44) was significantly more effective in supporting students’ decoding performance than a conventional decoding course (N = 36), two main challenges were reported: teacher’s excessive workload, and high requirement for the individual teacher’s decoding skills. To address these challenges, we developed a chatbot based on the self- determination theory and social presence theory to serve as a 24/7 conversational agent, and adapted the flipped decoding course to a fully online chatbot-supported learning course to reduce the dependence on the teacher. Although results revealed that the chatbot-supported fully online group (N = 46) and the flipped group (N = 43) performed equally well in decoding test, the chatbot-supported fully online approach was more effective in supporting students’ behavioral and emotional engagement than the flipped learning approach. Students’ perceptions of the chatbot-supported decoding activities were also explored. This study provides a useful pedagogical model involving the innovative use of chatbot to develop undergraduate EFL aural decoding skills in a fully online environment.
Key words Chatbot, EFL Listening, Fully Online Learning, Student Engagement
Abstract This study investigated the usage of conversational artificial intelligence (CAI) to support learners in foreign language classrooms. It employed Google Assistant and focused on the interactions between the teacher, learners, and CAI, as well as the teacher’s collaboration with CAI. Using social network and content analyses of two 50-minute language classes and group interviews, this study revealed that the teacher and CAI played a significant role during classroom interactions. The teacher employed various talk moves to facilitate interactions between the students and CAI. There were several instances of collaboration between the teacher and CAI during classroom facilitation. This study highlights the implications of the collaboration between human teachers and CAI in classrooms for teaching foreign languages and suggests avenues for future research.
Key words Conversational AI (CAI), Foreign Language Learning, Classroom Interaction, Teacher Facilitation
Abstract This study investigated the instructional effects of learner uptake following automatic corrective recast from artificial intelligence (AI) chatbots on the learning of the English caused-motion construction. 69 novice-level EFL learners in a Korean high school were recruited to investigate the instructional effects of corrective recast from AI chatbots on the learning of the English caused-motion construction. Results from the elicited writing tasks (EWT) revealed that statistically significant gains were observed in both immediate and delayed posttests for the production of the English caused-motion construction by experimental group participants. Also, the relationship between learner uptake from AI chatbots’ corrective recast and the learning of the English caused-motion construction were analyzed. The results demonstrated that learners’ successful repair from AI chatbots’ corrective recast was positively correlated with the learning gains in the two EWT posttests. The study concludes by highlighting the significance of noticeability in AI chatbots’ corrective feedback for foreign language learning.
Key words Artificial Intelligence Chatbot, Caused-motion Construction, Corrective Feedback, Crosslinguistic Interference
The effects of AI-guided individualized language learning: A meta-analysisHansol Lee, Korea Military Academy Jang Ho Lee, Chung-Ang University
Abstract Artificial intelligence (AI) has considerably advanced the methods for individualizing language learning opportunities, such as assessing learning progress and recommending effective individual instruction. In the present study, we conducted a meta-analysis to synthesize recent empirical findings pertaining to the utilization of AI-guided language learning and collected 61 samples (N = 8,282) from 17 research projects (e.g., Assessment to Instruction [A2i], Duolingo, and Project LISTEN). The results of our meta-analysis confirmed that AI-guided individualized language learning was effective for learners’ language development (d = 1.18, based on 26 within-group samples, N = 2,262) and had an overall positive treatment effect compared to business-as-usual conditions (d = 0.39, based on 35 between-group samples, N = 6,020). Moreover, the results of our moderator analyses for the treatment effect revealed that AI-guided language learning with machine learning and hybrid systems were more impactful than those with rule-based systems, which may be more helpful (compared to the former) in understanding how predictions are made from a pedagogical perspective. Evidence-based implications are provided based on the results of this meta-analysis.
Key words Artificial Intelligence (AI), Individualized Instruction, Language Learning, Meta-Analysis
Abstract Differentiated instruction is much demanded yet quite challenging in face of the growing student diversity in today’s K-12 classrooms. One major challenge is the provision of differentiated materials to students. Automated text simplification (ATS) tools fueled by natural language processing may serve as a useful assistant for teachers. However, little is known about teachers’ contextualized use of ATS over time. This case study traced two teachers’ use of ATS systems over a semester. Drawing upon three semi-structured interviews and teacher-generated materials with ATS, we identified an evolving pattern of teachers’ engagement with ATS systems, a progression from a blind reliance on the tool to a more critical and coordinated use of the tool over time. We further revealed that teachers’ evolving understanding of DI, positioning of the role of ATS systems and human instructors, and interpretation of DI need in specific teaching situations interplayed to shape their particular ways of engagement. Overall, this study contributes to the understanding of teachers’ contextualized use of ATS technology for DI. By revealing the influencing factors, the findings hold significant pedagogical implications to inform the design of ATS tools and the creation of favorable conditions to maximize the potential of ATS tools for DI and language teaching and learning in general.
Key words Automated Text Simplification (ATS), Differentiated Instruction (DI), Reading materials, Teacher contextualized engagement
Abstract English as a foreign language (EFL) students’ use of artificial intelligence (AI) tools that generate human-like text may enhance students’ written work. However, the extent to which students use AI- generated text to complete a written composition and how AI-generated text influences the overall writing quality remain uncertain. 23 Hong Kong secondary school students wrote stories with AI-writing tools, integrating their own words and AI-generated text into the stories. We analyzed the basic structure, organization, and syntactic complexity of each story and its AI-generated text. Experts scored the quality of each story’s content, language, and organization. By employing multiple linear regression and cluster analyses, we found that both the number of human words and the number of AI-generated words significantly contributed to writing scores. Furthermore, students could be classified into competent and less competent writers based on the variations of students’ usage of AI-generated text compared to their peers. Cluster analyses revealed some benefit of AI-generated text in improving the scores of both high- scoring students’ and low-scoring students’ writing. We suggest differentiated, pedagogical strategies for EFL students to effectively use AI-writing tools and AI-generated text to complete writing tasks.
Key words Artificial Intelligence, Natural Language Generation, Creative Writing, Short Stories
Abstract This quasi-experimental research investigates the employment of a formative assessment platform aided by artificial intelligence in an English public speaking course. The platform integrates deep learning, automatic speech recognition, and automatic writing evaluation. It provides automated assessment and immediate feedback on speakers’ public speaking anxiety and their speaking and writing competence. Fifty- two English public speaking learners were randomly assigned to two groups. The control group (G1) undertook self-, peer, and teacher assessment via the platform, while the experimental group (G2) experienced self-, automated, and teacher assessment. The ANCOVA results revealed that students in G1 perceived significantly higher social engagement than those in G2, which indicates that social interaction between learners during peer assessment cannot be substituted by automated assessment. The chi-square analysis showed students’ different concerns regarding online formative assessment. While students in G1 showed concerns for peers’ qualifications and willingness to provide feedback, students in G2 suggested generating more detailed automated feedback to improve self-learning. No significant differences were found in learners’ English public speaking self-efficacy, engagement, or competence. This indicates that automated assessment can serve as an effective strategy for formative assessment and that AI tools may supplement peers as reliable learning companions in the foreseeable future.
Key words Automated Assessment, Peer Assessment, English Public Speaking, Learner Engagement, Self- efficacy
期刊简介
Learning & Technology (LLT) is a free, fully-refereed, open journal which has been published exclusively online since July 1997. Originally published tri-annually, the journal is now published continously (read more about this model here) throughout the year by the National Foreign Language Resource Center at the University of Hawai‘i at Mānoa. The journal seeks to disseminate research to foreign and second language educators on issues related to technology and language education. The focus of LLT is not technology per se, but rather issues related to language learning and language teaching, and how they are affected or enhanced by the use of digital technologies. LLT has an editorial board of scholars in the fields of second language acquisition and computer-assisted language learning.
《语言学习与技术》(LLT)是一本免费的、完全审阅的、开放的期刊，自1997年7月以来一直在网上独家出版。该杂志最初每三年出版一次，现在由夏威夷大学国家外语资源中心全年连续出版。该杂志旨在向外语和第二语言教育者传播有关技术和语言教育问题的研究。LLT的重点不是技术本身，而是与语言学习和语言教学相关的问题，以及数字技术的使用如何影响或使之增强。LLT拥有一个由第二语言习得和计算机辅助语言学习领域的学者组成的编委会。
最新的2022年ISI期刊引文报告®排名显示，LLT的影响因子为3.80，在194种语言学期刊中排名第14位，在269种教育和教育研究期刊中排名第55位。
LLT 的最新 CiteScore 为 9.0，在语言和语言学的 1001 人中排名第 10 位（第 99 个百分位）。
官网地址：
https://www.lltjournal.org
本文来源：Language Learning & Technology 官网
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