BACKGROUND
Strategic learning priorities
The project aligned with the UNESCO Recommendation on the Ethics of AI, specifically Policy Area 8, which aims to “ensure that AI technologies empower students and teachers” (p. 34), and StEAR Roadmap’s Objective 1.8 on “integration of EDI principles…” when procuring learning technology (Strategic Action C) to “enhance capacity to diversify curriculum and ways of learning” (Objective 2.2, p. 20).
In a recently concluded panel for BC’s Academic Integrity Network (October 2023), UBC students identified the importance of recognizing:
- how cultures shape and influence students’ attitudes and behaviors regarding academic integrity,
- how ethical values can be cultivated, and
- how students may be misinformed about biased technological systems (such as Chat GPT).
Creating equitable and inclusive learning systems that invite students’ views on academic integrity and generative artificial intelligence (AI) was an important takeaway from the panel. This relates with how students, especially HPSM learners, face “policies, practices, culture, behaviours, and beliefs… a systematic process that discriminates” and continues “recreating historical exclusions” (StEAR Roadmap, p. 8).
The purpose of this initiative was to partner with students and impact institutional conversation on academic integrity and use of generative AI for teaching and learning. The project used photovoice (Young, 2017), an action research method that promotes equity, to gather photographic/visual impressions and observations from UBC students to address systemic “bias/discrimination” (StEAR Framework, 2.1 B) in, for example, “academic misconduct hearings… [that] are inherently flawed and subject to professor discretion, which can be inherently subject to unconscious bias.” (Recommendation #39, ARIE-Students Committee Report, p. 37). Use of advanced technology has created opportunities and highlighted inequities of practice. This project took an asset-based approach to “foster discrimination-free… learning environments, particularly for racialized students” (StEAR Framework, 2.1 D).
With generative AI and the concern for plagiarism in the upswing, research recommends asking questions such as, “What are the ethical implications of advanced technology on education? How can artificial intelligence promote equity, diversity, inclusion, and accessibility?” (Eaton, 2023, p. 3) The project team envisioned that asking similar questions and using the photovoice method will generate visual narratives that benefit UBC’s:
- Student community by storying peer observations or recommendations to support clear guidelines/ strategies for integrous AI use for academic purposes.
- Instructional community to rethink curricular objectives that resonate with student expectations to shape a more responsive and informed culture on academic integrity.
- Administrators to review policies and respond to AI use by students.
The project team hopes that the student work included in this website will directly sustain policy making and knowledge dissemination efforts on equitable AI use for teaching and learning at UBC.
PHOTOVOICE METHOD
“Photovoice goes beyond the conventional role of needs assessment by inviting people to become advocates for their own and their community’s well-being.” (Wang and Burris, 1997, p. 373)
Photovoice has been described by researchers (for example, Sierra-Martínez et al., 2024 and Wass et al., 2020) as a creative and flexible way to approach conversations and engage a community not just through written and verbal means but also visual texts. The photographs act as visual starting points to develop a better understanding of how participants identify with a topic, find representative image, and engage other community members and stakeholders.
Photograph-taking involves an active approach and is inquiry focused. This is particularly relevant to the topic of the StEARing AI project which asks UBC students to share their understanding or use of generative AI tools for learning. The action-oriented aspect of the photovoice method involves all participants in decision-making on ways to utilize the potential of AI in learning, assignment and assessment design, learning strategies, and study habits.
Most importantly, the project team sought to promote equitable and diverse conversations on AI and academic integrity. Application of the photovoice technique to understand the implications of AI on academic integrity was, therefore, a novel way to:
- capture student feedback that can inform institutional policy-making;
- visualize using student lens how generative AI supports learning and its impact on academic integrity;
- encourage students to critically think about AI vis-à-vis their learning goals;
- understand complex and unique affordances of using or not using generative AI-based tools;
- incorporate multiple mediums of communication– visual (photographs), textual (short narrative included with images and survey data), and oral-aural (focus group interviews) to gather student feedback
A discussion on the project outcomes was presented at UBC’s Celebrate Learning Event in May 2024 titled, StEARing AI: A SaP Project on Generative AI and Academic Integrity. The event recording is available on this site.
References
Sierra-Martínez, S., Martínez-Figueira, M-E., Castro Pais, M. D. & Pessoa, T. (2024). ‘You work, I copy’. Images, narratives and metaphors around academic plagiarism through Fotovoz. British Educational Research Journal, 00, 1–19. https://doi.org/10.1002/berj.3977
Wang, C., & Burris, M. A. (1997). Photovoice: Concept, methodology, and use for participatory needs assessment. Health Education & Behavior, 24(3), 369-387. https://doi.org/10.1177/109019819702400309
Wass, R., Anderson, V., Rabello, R., Golding, C., Rangi, A., & Eteuati, E. (2020). Photovoice as a research method for higher education research. Higher Education Research and Development, 39(4), 834-850. https://doi.org/10.1080/07294360.2019.1692791