This was a blog post assignment for an Issues in Education course in my EdD that attempts to capture a few big-picture ideas regarding the potential usefulness of Generative AI.

Boundaries are everywhere. They can be found in definitions, metaphors, national borders, bureaucracy, geographical features, the makeups of literary canons, the speed of light, colouring books, set theory, traditional grammar, club membership, merchandise return limits, binaries, social markers, ethnic and racial identities, the divisions between life and death, and so on.

Many of these boundaries have become more porous as a result of globalization, technology, and the increased mobility that comes with them, but in many places, boundaries remain. One such location where they remain is in schools, where traditional assessment methods, organizational necessities, and lack of differentiation between written and spoken forms of language, mean that obstacles to learning remain for all students.

Then along came ChatGPT and the transformative Generative AI revolution, which has already challenged the necessity of boundaries we once thought might have been fixed.

I am interested in the ways that Generative AI can cross or remove some of the barriers limiting opportunities for our students, especially students using English as a second language, but specifically these opportunities that relate to formative feedback, authentic assessment, and ultimately, linguistic preservation.

Formative feedback

Formative assessment for language teachers is laborious, especially when it is done effectively. Using Generative AI to deliver feedback is now relatively easy, and with only a little additional training in how to input high-quality prompts, teachers can use Generative AI to greatly improve the quality and target of this feedback.

In the language classroom, especially English language classrooms, there is considerable variety in the abilities of the students. In settings such as international schools in Hong Kong, these differences can be substantial and prove challenging to teachers as the nature of mistakes in first-language and second-language writers are often different (Hinkel 2003). The abundance of after-school language tuition and English media consumption means that students’ exposure to English and abilities using English can be quite different. The boundaries between English as a Foreign Language, Second Language, and Native Language while holding true for differentiating pedagogical approaches in the past, no longer hold as easily (Buschfeld and Kautzsch 2019). Generative AI can provide better-differentiated feedback.

Authentic Assessment

Ivan Ilych criticized formal education as artificially reinforcing the structures desired by society (2002). Research (Weigle 2002) and my experience working in Hong Kong would suggest that schooling is often focused on meeting the requirements of post-secondary education. Enormous financial and time resources are spent equipping students to gain admittance into universities. The values and purposes of schooling are often lost in the process (Anson 2008).

In his book Orality and Literacy (2013), Walter Ong describes the transformative effect that the technology of writing had on human culture. He describes writing as a secondary system, derived from sound, “the natural habitat of language” (8). My experience of teaching is that the distinctions between these systems – oral and written – are often confused in schools. Young learners are taught the names of letters as opposed to their sounds and often their phonetic awareness remains undeveloped. Older second language learners’ intelligence can be questioned simply because of these students’ lower proficiency in spoken English. Assessments are often not designed with these considerations in mind, so a student may be asked to write out their reasoning for a math or science problem when a spoken answer may yield better information about understanding.

Perhaps Generative AI can help students articulate their ideas. How many students would benefit from being assessed on knowledge and skills in formats apart from writing? I imagine a multi-modal classroom recording teacher and student interactions, student-teacher conversations, collecting work, and providing actionable formative feedback as outlined above. The boundaries between written and spoken forms of language can further be bridged.

First Language Preservation

English is the world’s lingua franca and is spoken by more people as a second language than as a first (“Ethnologue” 2024). In my career as an international school educator, I have seen again and again parents place their child in an English medium school only to discover after just a few years that their child will no longer communicate with them in their home language. International schools are paradoxically very good at wiping first languages.

The motivation of parents to enhance their children’s future prospects is understandable, but is it worth it at the expense of first language proficiency? Too often students make the switch before they have established first language literacy. This makes it harder for them to acquire literacy in a second language literacy (Cummins 1979). Children cannot just switch back and forth between different languages within schools and not expect an impact on literacy and writing ability even if the perception is that children naturally learn spoken language.

What if with the rise of Generative AI, parents can delay the transition to a second language, giving time for first language literacy to develop? What if Generative AI can mediate the complexities of formative feedback in the classroom and contribute to generating more forms of authentic assessment. If Generative AI becomes embedded in the workforce to assist with language communication, then perhaps people can retain their connections and fluency in first languages without the fear of being left behind.

Works Cited

Anson, Chris M. 2008. “Closed Systems and Standardized Writing Tests.” College Composition and Communication 60 (1): 113–28. https://www.jstor.org/stable/20457046.

Buschfeld, Sarah, and Alexander Kautzsch. 2019. “Theoretical Models of English as a World Language.” In The Cambridge Handbook of World Englishes, edited by Daniel Schreier, Marianne Hundt, and Edgar W. Schneider, 1st ed., 51–71. Cambridge University Press. https://doi.org/10.1017/9781108349406.003.

Cummins, James. 1979. “Linguistic Interdependence and the Educational Development of Bilingual Children.” Review of Educational Research 49 (2): 222–51.

“Ethnologue.” 2024. Ethnologue. https://www.ethnologue.com.

Hinkel, Eli. 2003. “Simplicity without Elegance: Features of Sentences in L1 and L2 Academic Texts.” TESOL Quarterly 37 (2): 275. https://doi.org/10.2307/3588505.

Illich, Ivan. 2002. Deschooling Society. Reissued. London: Marion Boyars.

Ong, Walter J. 2013. Orality and Literacy. 2nd ed. Hoboken: Taylor and Francis.

Weigle, Sara Cushing. 2002. Assessing Writing. Cambridge Language Assessment Series. Cambridge: Cambridge University Press.