Posted on by Adam Hawkins

AI & Language Teaching

Kate Cammack, CfT Co-Director

Language educators have been grappling with AI-related issues for far longer than educators in most other disciplines. Google Translate was launched nearly 20 years ago, in 2006; this is around the year that many of our current college students were born, so basic language-translation tools have been available to them for most (if not all) of their lives.

Recently, the CfT hosted facilitated small-group discussions between language faculty that focused primarily on pedagogical compatibility (e.g., alignment of GenAI with evidence-based language teaching practices) and preparation of students. The discussion focused on (a) how/when they were discussing language learning in the context of AI with their students, and (b) whether/how/when they were incorporating AI tools into students’ learning experiences. While I’ll do my best (as a non-language-faculty) to summarize some key points here, I encourage you to connect directly with our language colleagues for more (!)

Motivating students to put in time & effort

Challenge #1: Learning a language requires some rote memorization, which requires dedicated time to practice. As a basic example, students must be familiar with vocabulary in order to form sentences and express thoughts; in other words, some lower-level Bloom’s work (e.g., what is the word for “apple”) is required in order to do more high-level activities (e.g., ask a child if they would like an apple). Faculty reported that their general sense was that students perceived “language learning” to be important and valuable, but it was not always clear that students’ working definitions of “language learning” included this lower-level Bloom’s work. As it is very easy to have AI assist much of this lower-level Blooms work, it is additionally challenging to motivate students to invest in this type of work.

Ideas and/or “things they’ve tried”:

  • Dedicate a few minutes of class time to define and think critically about the components involved in “language learning.”
  • Remind students that “language learning” requires putting in the time to practice the basics, as you won’t be able to build fluency without them
  • Help students envision what their language learning goal is (e.g., having a basic conversation with a neighbor) and provide opportunities for them to revisit their “whys,” which may help sustain their interest and persistence

Perfectionism & concerns over embarrassment

A challenge: We all make many mistakes when we’re learning a language, and mistakes can make people feel embarrassed or self-conscious. Students might perceive that AI will help improve their writing so that it contains fewer mistakes; it may also allow them to practice a language in private, without fear of others’ reactions. Some faculty wondered how/whether AI tools might help students practice certain aspects of language, without inadvertently shortchanging or shortcutting their learning experience.

Ideas and/or “things they’ve tried”:

  • Explicitly reassure students that they can have meaningful interactions with incomplete sentences and without perfect grammar.
  • Underscore the unique value and importance of Authentic Interaction (a different AI!) and cross-cultural understanding as critical components of language learning & communication; these interpersonal skills and face-to-face interactions may in fact help ameliorate some of the losses that students feel in the face of AI
  • Be clear about what AI tools (from translators to chatbots to tutorbots) do well and don’t do well (yet), and provide examples specific to your course so that students know whether/when it’s OK to use those tools. Knowing when & why college students use AI can also be helpful in framing your conversations effectively.

To reduce overreliance on AI and/or empower students to begin work without AI assistance:

  • Short-write at the beginning of class, to ensure students’ own words/thinking
  • Start larger essays or projects together in class
    • Introduces the project as a collaborative learning activity
    • Reduces “blank document phobia” by allowing students to leave class with their project/paper already started
  • Break up medium-sized projects into smaller, more manageable chunks (as students often turn to AI in the face of deadline crunches and/or large/daunting assignments)
  • All Sewanee faculty have pro versions of Microsoft CoPilot, which is worth playing around with. If you’re interested in other platforms (e.g., ChatGPT), please contact Lauryl or Kate so that we can “check out” a paid platform/version to you.

Additional resources*:

 * identified by your soundly non-language CfT co-director (!) you likely have others, please add to this list!