Not the Artificial Intelligence, but the Sequence: Instructional Design and Oral Communication Strategy Development

This study examines how instructional design shapes the development of oral communication strategies in an 18-week English-as-a-foreign-language speaking course, at a time when generative artificial intelligence is often assumed to enhance speaking performance. All three classes worked with the same curriculum and speaking tasks. One class learned through a BOPPPS (Bridge-In, Objective, Pre-Assessment, Participatory Learning, Post-Assessment, and Summary) based sequence in which students prepared ideas, participated in guided speaking activities, and reviewed their performance, with each cycle including a stage where they generated their own content before using ChatGPT to refine it. A second class received regular teacher guidance and completed the same tasks, but their use of ChatGPT was self-directed and not part of a fixed sequence (the artificial intelligence-flex condition). A third class covered the same material through teacher-supported face-to-face interaction without artificial intelligence (the traditional condition). Learners completed the Oral Communication Strategy Inventory at the beginning and end of the semester and provided reflections on how their course format influenced their speaking. The findings show a clear hierarchy in strategic development. The BOPPPS based class demonstrated the strongest gains, especially in negotiation for meaning, fluency regulation, and accuracy monitoring. The traditional class showed moderate improvements, particularly in nonverbal and social-affective strategies. The artificial intelligence-flex class displayed the smallest increases, a pattern reflected in learners’ descriptions of artificial intelligence-driven exchanges involving fewer occasions to plan, clarify, or monitor meaning. Overall, the results indicate that strategic growth is driven primarily by instructional design, with artificial intelligence contributing meaningfully only when situated within a structured pedagogical frame.

Authors

Institutions

Publication Details

Journal
Language Teaching Research
Published
2026-07-17
DOI
https://doi.org/10.1177/13621688261463373
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Not the Artificial Intelligence, but the Sequence: Instructional Design and Oral Communication Strategy Development

Zola Chi-Chin Lai
Language Teaching Research
AI in Service Interactions
article

Not the Artificial Intelligence, but the Sequence: Instructional Design and Oral Communication Strategy Development

Zola Chi-Chin Lai
article en

Abstract

This study examines how instructional design shapes the development of oral communication strategies in an 18-week English-as-a-foreign-language speaking course, at a time when generative artificial intelligence is often assumed to enhance speaking performance. All three classes worked with the same curriculum and speaking tasks. One class learned through a BOPPPS (Bridge-In, Objective, Pre-Assessment, Participatory Learning, Post-Assessment, and Summary) based sequence in which students prepared ideas, participated in guided speaking activities, and reviewed their performance, with each cycle including a stage where they generated their own content before using ChatGPT to refine it. A second class received regular teacher guidance and completed the same tasks, but their use of ChatGPT was self-directed and not part of a fixed sequence (the artificial intelligence-flex condition). A third class covered the same material through teacher-supported face-to-face interaction without artificial intelligence (the traditional condition). Learners completed the Oral Communication Strategy Inventory at the beginning and end of the semester and provided reflections on how their course format influenced their speaking. The findings show a clear hierarchy in strategic development. The BOPPPS based class demonstrated the strongest gains, especially in negotiation for meaning, fluency regulation, and accuracy monitoring. The traditional class showed moderate improvements, particularly in nonverbal and social-affective strategies. The artificial intelligence-flex class displayed the smallest increases, a pattern reflected in learners’ descriptions of artificial intelligence-driven exchanges involving fewer occasions to plan, clarify, or monitor meaning. Overall, the results indicate that strategic growth is driven primarily by instructional design, with artificial intelligence contributing meaningfully only when situated within a structured pedagogical frame.

Language Teaching Research
Wenzao Ursuline University of Languages (TW)
Ministry of Education, India
Quality Education
Openalex Percentile: Top 6%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Not the Artificial Intelligence, but the Sequence: Instructional Design and Oral Communication Strategy Development — Zola Chi-Chin Lai · Language Teaching Research (2026) | TGRS Research Map | TGRS