36.3369, Confs: 2026 Taiwan Computer-Assisted Language Learning (TaiwanCALL) and Global Computer-Assisted Language Learning (GLoCALL) Joint Conference (Taiwan)

Tue Nov 4 13:05:02 UTC 2025

LINGUIST List: Vol-36-3369. Tue Nov 04 2025. ISSN: 1069 - 4875.

Subject: 36.3369, Confs: 2026 Taiwan Computer-Assisted Language Learning (TaiwanCALL) and Global Computer-Assisted Language Learning (GLoCALL) Joint Conference (Taiwan)

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Date: 04-Nov-2025
From: Min-Hsun Liao [minhsunl at thu.edu.tw]
Subject: 2026 Taiwan Computer-Assisted Language Learning (TaiwanCALL) and Global Computer-Assisted Language Learning (GLoCALL) Joint Conference

2026 Taiwan Computer-Assisted Language Learning (TaiwanCALL) and
Global Computer-Assisted Language Learning (GLoCALL) Joint Conference
Short Title: TaiwanCALL & GloCALL Joint Conference
Theme: CALL for All: Designing Inclusive, Adaptive, and Engaging
Language Learning

Date: 07-May-2026 - 09-May-2026
Location: Taichung, Taiwan
Meeting URL: https://conference.twcall.org/index.php

Linguistic Field(s): Applied Linguistics; Language Acquisition

Submission Deadline: 30-Nov-2025

The 2026 Taiwan Computer-Assisted Language Learning (TaiwanCALL) and
Global Computer-Assisted Language Learning (GLoCALL) Joint Conference
adopts the theme “CALL for All: Inclusive, Adaptive, and Engaging
Language Learning.” This conference aims to bring together
international scholars and practitioners in the field of
Computer-Assisted Language Learning (CALL) to examine current progress
and challenges in achieving educational equity through
technology-enhanced language learning. It seeks to explore how the
integration of technological innovation and pedagogical design can
ensure that all learners benefit from digital language learning
advancements, moving toward the vision of “CALL for All.”
Over the past fifty years, CALL has evolved from behaviorist
drill-and-practice programs to intelligent learning systems powered by
artificial intelligence. Technological progress has created
unprecedented opportunities for language education. However, as
Chapelle (2007) noted, while technology expands learning
possibilities, it does not automatically guarantee equitable access.
Recent research continues to highlight this gap: despite the rapid
growth of Mobile-Assisted Language Learning (MALL), many learners
remain excluded due to limited access to devices, networks, or digital
literacy.
The emergence of Artificial Intelligence in Language Learning (AIALL)
represents a pivotal turning point. Recent studies (e.g., Education
and Information Technologies, 2025) reveal that AI-integrated CALL
models hold great promise for personalized learning but may also
intensify resource disparities. Learners with high-speed internet and
advanced devices can fully leverage AI tutors, while those in
under-resourced contexts risk further marginalization. To address
these challenges, the 2026 TaiwanCALL & GLoCALL Joint Conference
invites participants to engage in critical dialogue across three main
dimensions of CALL development:
1. Inclusive Design
Inclusive CALL design goes beyond technical accessibility—it calls for
a fundamental rethinking of language learning theory and practice.
According to a recent study published in the Computer Assisted
Language Learning Electronic Journal (2025, Vol. 26[1]), true
inclusivity encompasses multiple dimensions: usability, pedagogical
relevance, and cultural responsiveness. The study proposes a
conceptual model emphasizing that accessibility must empower all
users—regardless of background—to engage meaningfully in digital
learning environments.
As highlighted in Computer-Assisted Language Learning in the Global
South (McCallum & Tafazoli, 2024, Routledge), infrastructure
limitations and policy misalignments continue to pose substantial
barriers in developing regions. Mainstream CALL design often assumes
an “ideal learner”—digitally literate, familiar with Western
pedagogical models, and with reliable internet access—thereby
excluding Indigenous learners, adult migrants, and learners with
special needs. The conference theme, “CALL for All: Inclusive,
Adaptive, and Engaging Language Learning,” directly responds to these
inequities by promoting diversity, accessibility, and cross-cultural
awareness in CALL research and practice.
2. Adaptive Learning
The development of adaptive CALL systems lies at the intersection of
second language acquisition (SLA) theories and learning technologies.
As Chapelle (2009) argued in The Relationship Between Second Language
Acquisition Theory and Computer-Assisted Language Learning, CALL
research must draw from diverse theoretical orientations—cognitive
linguistics, psycholinguistics, learning sciences, and sociocultural
theory.
Recent studies, such as Xiao (2024) in Humanities and Social Sciences
Communications, demonstrate how AI-enhanced reading platforms with
biometric feedback can improve comprehension and reduce learner
anxiety. Yet, many adaptive systems still focus narrowly on adjusting
task difficulty, overlooking deeper factors such as learning style,
cultural context, and motivation. The conference will therefore
encourage discussions on how to advance truly adaptive and
human-centered CALL designs.
3. Engaging Learning
The focus on learner engagement in CALL reflects a theoretical shift
from cognitive to socio-constructivist perspectives. Zhang and Hasim’s
(2023) systematic review in Frontiers in Psychology reveals the global
spread of gamification in EFL/ESL teaching, demonstrating its
potential to enhance language skills, motivation, and learner autonomy
through authentic, interactive contexts. However, Yin’s (2023) review
in Behavioral Sciences cautions that gamification outcomes are
mixed—positive in some cases, neutral or even negative in others.
Importantly, cognitive engagement remains an underexplored yet crucial
factor in determining the effectiveness of gamified learning.
By examining such findings, the conference aims to foster innovative,
evidence-based approaches to learner engagement in digital
environments.

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