I Don’t Want Students to Hide Their AI Use.
I Want Them to Show Their Work
This fall 2026 semester (August 10, 2026 - November 27, 2026) I teach the following courses to English language teacher trainers: Academic Writing (7th semester), Discourse Analysis (5th semester), Writing I (propaedeutic), and Listening I (propaedeutic). The plan is to be more intentional with AI as the university is beginning to be more explicit in expectations in how learners are engaging with LLMs to achieve learning outcomes.
The bachelor’s degree in English language teaching program includes courses that fall into four separate strands: English skills development (i.e., reading, writing, listening, speaking, vocabulary, grammar, and pronunciation); teaching methodology (i.e., the theory of learning); applied linguistics (i.e., how languages are learned); and teaching practicum. Three out of the four courses I teach fall under the English skills development strand while the other - Discourse Analysis - under the applied linguistics strand.
Regarding updates to the syllabus, GenAI is explicitly stated in the content objectives for each unit and also throughout the methodology, teaching resources, assessment, and references sections. As an example, one unit objective for discourse analysis states,
Students will analyze how grammatical and lexical choices construct cohesion, coherence, stance, and interpersonal meaning within extended discourse and use GenAI as a critical friend to evaluate the clarity, register, and accuracy of their independently completed analyses through a documented revision trail.
In the same unit, contents mention the following as it relates to AI Practice:
AI Practice (level 3):
AI as Critical Friend: Students draft an initial analysis diagramming thematic progression in a text. They then feed their analysis into an AI to act as an editor or critical friend to check for academic clarity, hedging, and register.
Revision Trail: Assessment mandates an annotated revision trail. Students must submit their original draft alongside the AI-assisted version, featuring tracked changes and commentary explaining their pedagogical rationale for accepting or rejecting the AI’s suggestions.
The language used throughout the syllabus to make GenAI use more explicit (e.g., “level 3”, “critical friend”, etc.) comes from a GenAI Assessment Scale for BA in English language teaching (ELT) programs. Gemini Pro was used to generate this document and remains as is - no additional modifications were made. A deep research prompt was used to find more information about the AI Assessment Scale (AIAS) to get options for adapting the scale to the different types of courses offered in our BA program in ELT.
The Discourse Analysis course, falling under the applied linguistics strand of the BA, adheres more to the GenAI Assessment Scale for English for Academic Purposes (EAP) subjects. Level three of the five-point scale reads as follows:
Level 3: AI as editor + critical friend (clarity, cohesion, hedging, register). Require a revision train + academic integrity statement (no fabricated references; verify all claims).
When implementing this unit, criteria for completing learning outcomes will include students completing an AI Appendix to their work to make explicit how AI was used throughout their personal workflow. For coming up with an AI Appendix, I used Gemini Pro to generate the Student GenAI Collaboration Appendices document, which has not been modified. One of my last pending items is to divide up the document and modify it as necessary for each of my courses.
Currently, there is nothing in place at the university level when it comes to assessment scales and policies related to AI use, but it’s coming. Meanwhile, I plan to learn what I can this semester, share my thoughts and experiences, and learn from what others are doing in this space. My hunch though is that I will essentially be applying Kleon’s (2014), Show your Work! to my students, which takes the term, “process over product” to a new level.
Curious what others think…
What has worked for you when it comes to working with learners using AI in the class?
What terminology do you use for what goes into an AI appendix where students reveal their process and AI use: revision trail, declaration of use, GenAI use declaration, AI acknowledgement, etc.?
What has not worked? Why?
How much of what you do is rooted in institutional policy vs. personal choice?
How do professional learning communities where you work function? Are they helpful?
Are there best practices that you employ that help you anticipate where educational systems and the use of AI are going in the future?