Developing the Teaching Components of the ICC-Based Instructional Model to Enhance the Intercultural Competence of Thai EFL Tertiary Students: A Synthesis Study
Bibliographic record
Abstract
This synthesis study aims to develop an ICC-based instructional model for enhancing Thai EFL tertiary students’ intercultural competence. The purpose of this study is to synthesize which ICC teaching components can enhance the intercultural competence of Thai EFL undergraduates. The research methodology is a synthesis of pertinent literature and previous investigations on ICC models within a globalizing paradigm. Used a semi-systematic literature review to collect data. In accordance with the document-based and content-based analyses conducted at this stage, Quantitative Content Analysis and Qualitative Content Analysis are utilized to synthesize the ICC-based instructional model study by integrating the research frameworks of the ADDIE model and the SPIE model .The research findings indicate that the principles of four ICC models developed by four ICC scholars, 1. Bennett's (1993), 2. Deardorff's (2006), 3. Byram's (1997), and 4. Baker's, can be applied to develop an ICC-based instructional model for enhancing the intercultural competence of Thai EFL tertiary students. This study identifies seven ICC teaching components, including: 1. Intercultural-English-World Communication Knowledge; Incorporation; 3. Comprehension; 4. Practice; 5. Promotion; 6. Outcome; and 7. Enhancing Intercultural Competence. The principles of ICC teaching materials for EFL classrooms have to incorporate a variety of intercultural communication knowledge that can stimulate students' interests. The ICC teaching materials concepts comprise the following: 1. Authentic 2. acceptable 4. Activity-based and precise 5. Awareness and attitude.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".