PanSIG 2026 - Building Language Competencies through Community

Session

801

23 May 2026, 11:00

0号building/8-801 (Chukyo University)

247. SIG Forum: Computer Assisted Language Learning

Jeanette Dennisson (St. Marianna University School of Medicine), Michael Hofmeyr (Tokyo University of Science), Robert Dykes (Conference Chair (CALL 2024, PanSIG 2025, SUTLF 2026)), Geoffrey Carr (Asahikawa City University)

23/05/2026, 11:00

JALTCALL welcomes you to a two-part forum. Come, listen, inquire, participate.

1. Student and Instructor Dialogue: AI in Language Education: Are Instructors Providing What Students Need?
2. Open CALL: What is JALTCALL? What are we doing now? What role does CALL play in the Age of AI? How can you join...

15. Building Pragmatic Competence Through Human-AI Collaborative Learning

Oliver Cakebread-Andrews (Kwansei Gakuin University)

23/05/2026, 12:20

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This research demonstrates how collaborative human-AI analysis builds pragmatic competence in EFL learners. Comparing native speakers, non-native speakers, and AI models on sarcasm detection revealed shared challenges (60% accuracy for natives, 51% for non-natives). These insights informed a pedagogical intervention where students learned through computational pattern analysis and peer...

36. Integrating Personalized AI Agents into the Writing Curriculum

George MacLean (University of the Ryukyus), Norman Fewell (Meio University)

23/05/2026, 13:30

CALL: Computer Assisted Language Learning

B. Practice-oriented Presentation (25 minutes)

Personalizing language instruction is challenging. This session introduces a model for creating custom AI tutors that provide individualized support. Instructors modify NCSSFL-ACTFL Can-Do Statements to serve as writing prompts for activities. The AI provides instant feedback on grammar and syntax, eliminating student waiting periods. This allows educators to focus on high-level mentoring. You...

144. A Taxonomy of AI Prompt Types in First-Year ESL Writing in Japan

Omar Massoud (Meiji Gakuin University)

23/05/2026, 14:10

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This study examines how first-year Japanese ESL students use generative AI during academic writing by analyzing the types of prompts they produce and how these relate to writing development and ethical clarity. Using prompt logs and draft revisions collected over six weeks, the study identifies prompt types that support learning-oriented revision and those associated with surface-level...

175. The Impact of Generative AI vs. Peer Feedback on Student Engagement

Jerry Huang

23/05/2026, 14:50

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This year-long study compared GenAI-based feedback with peer feedback regarding affective, behavioral, and cognitive engagement among Japanese EFL students (n = 37). Results showed no significant differences between the two groups, suggesting GenAI provides an "equal ground" for sustaining student involvement. While students valued the social aspects of peer feedback, they appreciated GenAI’s...

225. Designing Affective AI Language Partners: Evidence for Community Integration

Jeanette Dennisson (St. Marianna University School of Medicine)

23/05/2026, 15:30

CALL: Computer Assisted Language Learning

B. Practice-oriented Presentation (25 minutes)

AI chatbots can demonstrate real character and become part of the learning community. For some role-play practices, overly supportive AI partners can reduce realism. We demonstrate how to design AI partners to become more like us with role-appropriate charateristics. These AI partners showed more effective as language partners by encouraging risk-taking and reducing anxiety compared to peer...

102. Iterative AI Feedback in PEEL Writing: EFL Learners’ Reflections

Mr Joselito Bisenio (Ritsumeikan Uji Junior and Senior High School)

24/05/2026, 09:30

CALL: Computer Assisted Language Learning

B. Practice-oriented Presentation (25 minutes)

Writing remains a challenge for EFL high school students, but generative AI helps improve drafting, revising, and feedback in PEEL paragraph writing tasks. First year students revised drafts after AI generated feedback and improvements in grammar, vocabulary, and structure were noted. Thematic analysis of the reflections shows AI’s value as a writing aid and stresses the importance of teacher...

8. The Feedback Loop: ESL Autonomy & Trust in GenAI

Shuyi Li (University of Tokyo)

24/05/2026, 10:10

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This study investigates how 87 university ESL learners experience Generative AI during vocabulary acquisition. We compared groups using English-only versus L1-supported feedback to understand impacts on motivation, confidence, and learner autonomy. Findings reveal that while ChatGPT-4o boosts engagement through contextualized explanations, technical inconsistencies can hinder trust. We provide...

89. Take Control of Your Listening Materials – With AI

Ryan Richardson (Konan University Hirao School of Management)

24/05/2026, 10:50

CALL: Computer Assisted Language Learning

B. Practice-oriented Presentation (25 minutes)

This talk will look at some ways to use various AI tools to create targeted and appropriate listening materials for classes.

168. Don’t just copy it! Teaching students to use AI for editing their writing

Nicole Moskowitz (University of Hyogo)

24/05/2026, 11:30

CALL: Computer Assisted Language Learning

B. Practice-oriented Presentation (25 minutes)

This presentation will detail a weekly writing activity which encouraged university students to use AI to edit their original work, and not simply blindly copy and paste answers. The steps to implement this activity in class will be explained. Also, the results of a survey on student perception of AI use, and AI feedback compared to teacher feedback will also be detailed.

35. Can teachers spot machine-generated English?: Designing a pilot study

John Bankier (Kanagawa University)

24/05/2026, 12:40

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This study compares the ability of language teachers, AI checker apps and large language models to distinguish human-written from machine-generated text produced by an LLM (ChatGPT) or translation software (DeepL). This presentation will discuss how texts were produced which were representative of student writing practices. In addition, the design of the study will be described, including use...

223. Strategic Communication in Online Tandem Learning

Jehan Cruz (Ritsumeikan University)

24/05/2026, 13:20

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

This presentation explores how English and Japanese learners sustain interaction in online tandem learning through the strategic use of multimodal resources. Drawing on video-recorded Zoom exchanges, it shows how learners combine linguistic, paralinguistic, digital, and interactional strategies to negotiate meaning, maintain engagement, and collaborate effectively. The findings highlight how...

109. Virtual Exchange: Developing Critical Language Competencies for Peace

Tim Cleminson (Okayama University), Susan Meiki (JALT Business Manager / Okayama University / Poster Chair)

24/05/2026, 14:00

CALL: Computer Assisted Language Learning

A. Research-oriented Oral Presentation (25 minutes)

Drawing on a Ukraine-Japan collaboration, this presentation explores Virtual Exchange as a peacebuilding community. We demonstrate how collaborative tasks and human encounters transform critical media literacy into tools for real-world mediation. We introduce a pedagogical framework showing how instrumental and ontological capacities must be nurtured to help students navigate the complexities...