Speaker
Abstract section 4: Outcomes/results
Preliminary results suggest substantial variation in how educators conceptualize AI within academic writing. While many respondents view AI primarily as a tool for editing or language support, opinions diverge when AI contributes to idea generation, drafting, or analysis. The findings reveal inconsistencies in how authorship and responsibility are assigned across different forms of technological assistance. The poster presents these results alongside a conceptual continuum illustrating how educators position AI in the writing process. The goal is to encourage discussion about transparency, authorship, disclosure, and responsibility as generative AI becomes increasingly embedded in academic research and writing practices.
Abstract section 2: Contribution/research questions
This poster investigates how educators conceptualize authorship when gen-AI tools are involved in academic writing. Using survey data from university educators in Japan, the study explores variation in beliefs regarding disclosure, responsibility, and acceptable AI assistance. The research asks: (1) How do educators conceptualize AI within the writing process (tool, mediator, collaborator)? (2) Which types of AI assistance are viewed as acceptable or problematic? (3) How do these perceptions influence expectations of authorship and responsibility?
Abstract section 1: Relevance
Generative AI has introduced new uncertainty about authorship, responsibility, and intellectual ownership in academic writing. While debates often focus on ethics and academic integrity, theoretical perspectives suggest that authorship has always been socially and technologically mediated. Foucault’s concept of the author-function highlights how authorship operates as a cultural mechanism for assigning meaning and responsibility (Foucault, 1998). Sociocultural theory similarly frames writing and learning as mediated activity shaped by tools and social interaction (Vygotsky, 1978; Lantolf, 2000). This poster situates generative AI within these traditions while examining how educators in Japan conceptualize AI-assisted authorship in contemporary academic practice.
Abstract section 5: References
Foucault, M. (1998). What is an author? In J. D. Faubion (Ed.), Aesthetics, method, and epistemology (R. Hurley et al., Trans., pp. 205–222). New Press. (Original work published 1969)
Lantolf, J. P. (2000). Sociocultural theory and second language learning. Oxford University Press.
Neff, J., & Arciaga, K. (in press). Discussing the vignette technique for assessing student perception of ethical AI use in the L2 learning environment. In R. Dykes, O. Edwards, D. Bollen, & T. Shu-wen Lin (Eds.), Artificial intelligence in Japan’s language learning classrooms. Candlin & Mynard.
Swain, M. (2000). The output hypothesis and beyond: Mediating acquisition through collaborative dialogue. In J. P. Lantolf (Ed.), Sociocultural theory and second language learning (pp. 97–114). Oxford University Press.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Abstract section 3: Content/method
Data are drawn from a large-scale survey of university educators in Japan examining attitudes toward AI-assisted academic writing. The instrument includes Likert-scale and matrix items assessing perceptions of authorship, responsibility, and disclosure expectations. Scenario-based vignettes, informed by Neff and Arciaga’s (in press) discussion of the vignette technique for examining perceptions of ethical AI use in L2 contexts, were used to explore how judgments shift across different forms of AI-assisted writing.
| Title | Who Wrote This? Rethinking Authorship, Ethics, and Ownership |
|---|---|
| Teaching Context | College and university education |