How teachers talk about AI when they talk to each other
As AI tools spread into English language teaching (ELT) in 2023, teachers turned to online communities to share what worked. This thesis asked three questions: how teachers describe their experiences with AI tools in Facebook groups, what those discussions reveal about benefits, challenges, and effective practice, and how teachers collaborate in these virtual communities.
Two frameworks guided the analysis: Technological Pedagogical and Content Knowledge (TPACK), to assess how teachers integrate technology, pedagogy, and content, and Virtual Communities of Practice (VCoP), to examine group dynamics. The thesis record is held in the Universitas Negeri Malang repository.
The evidence base
Data came from six open Facebook groups, covering discussions up to May 19, 2023: 235 initial posts and 1,712 follow-up comments about AI tools in ELT.
The posts were extracted with the web-scraping tool Apify, and a panel of four experienced university educators checked the dataset for accuracy and relevance before analysis.
Where Evidano fit
The study used Taguette and Evidano as its analytical software, combined with thematic analysis and the TPACK and VCoP frameworks. Social-media text of this kind is high in volume and uneven in length, which makes software support for organizing and theming it especially useful.
What the study found
Teachers balanced technological proficiency with pedagogical intent, consistent with the TPACK framework, while ethical and psychological factors complicated adoption. Teachers appeared as proactive contributors who tailored technology to their educational goals.
Discussions highlighted AI’s potential for instant feedback and cross-cultural engagement, alongside persistent issues of technology access and uneven digital literacy among educators.
Within the VCoP framework, the groups moved from simple resource sharing toward deeper collaborative engagement, making them a meaningful site of ongoing teacher professional development.
The thesis recommends updating teacher education to cover theoretical and practical AI use, developing practitioner guidelines, and recognizing participation in virtual communities as part of professional development.
Why this case matters
This case extends Evidano to web and social-media data. Nearly two thousand posts and comments were organized into themes interpreted through two established frameworks.
For education researchers studying online communities, it shows a workflow that combines scraping, expert verification of the dataset, and software-supported thematic analysis.
Limits and responsible interpretation
The thesis notes that open Facebook groups may not represent all ELT teachers using AI, that data collection was time-bound, and that there was no direct observation of classroom practice.
This summary is based on the thesis abstract in the university repository. The abstract names Evidano and Taguette together and does not separate their roles.
How Evidano fit the workflow
- 1Choose the communities
Six open Facebook groups for English teachers were selected.
- 2Scrape the discussions
Apify extracted 235 posts and 1,712 comments up to May 19, 2023.
- 3Verify the dataset
Four experienced university educators checked accuracy and relevance.
- 4Analyze with software
Taguette and Evidano supported the thematic analysis.
- 5Interpret through frameworks
Themes were read through TPACK and Virtual Communities of Practice.
“The study utilized Taguette and Ailyze as analytical software tools”
Posts and comments were organized into themes at scale.
A panel of four educators checked the scraped dataset before analysis.
TPACK and VCoP structured the interpretation.
The thesis names Evidano among its analytical tools.