9 Can machines respond to students’ feedback needs?

Universities are greenhouses for and of experimentation, intellectual and human connection, and learning that push the boundaries of what is possible. Not everything will work; not everything will succeed. While we love learning to be fun and filled with happiness, it is also messy, confusing, disorientating, and discomforting. Hard. Lonely at times. Sometimes a struggle. As learning also means unlearning and re-learning. And learning from (our own) mistakes. Sometimes(?) we wish learning was easier, much easier, and the pain of learning would go away.

Learning relationships

What role do learning relationships play in celebrating the ups and helping students get through the downs? How can we learn from (own) mistakes? We often talk about creating safe spaces and that we need to be brave, but Ahenkorah (2020) warns us against such narratives. For her, accountable spaces are the way forward, where each one of us takes full responsibility for our actions.

How can we foster and nurture diverse learning relationships to create a respectful learning culture characterised by openness, humane and intellectual connection?

These learning relationships between educators and students are also experienced through feedback, which can create challenges, as research shows. Feedback is not always understood and can create anxiety (Fong et al., 2023), and other times students don’t know what to do with it, or how it is useful for them (Little et al., 2023). It seems to be the case that feedback satisfaction remains low in higher education (Ferrell & Knight, 2022). But is it about feedback satisfaction or recognising value in feedback for learning? For some years now, educators have been engaging with diversifying feedback approaches, often using the affordances of digital and networked technologies, including multimodal formats.

However, one element that seems to matter in how feedback is experienced is the strength and nature of the learning relationship. This is no surprise as we are social beings. Carless (2019), for example, speaks about the value of feedback partnerships, and Robson et al. (2023) recognise the importance of dialogic feedback. We recognise the value of multidirectional feedback and know that when the exclusive source of feedback is the tutor, it can create dependency (Dunbar-Morris et al., 2023). While we talk about the value of feedback partnerships and mean the involvement of others, Nicol and Kushwah (2023) bring our attention to the importance for students to engage first critically with their own work through what they call self-feedback before reaching out for feedback from peers or their tutor. Does this mean that a feedback partnership with themselves is equally important, perhaps?

Emerging feedback practices

New feedback practices are emerging, which I think links with the above and how we would like our students to have agency and deeply engage with their own work in critical ways. Yes, students are proactively seeking feedback on their work-in-progress from the machine, GenAI tools, to support their learning (Wiersma, 2024). There is an opportunity for human-to-machine feedback conversations, always, however, initiated by the human (at least for now) and switched on 24/7. Available on demand and command. Is this a good thing? Does it create new dependencies? And voice chatbots are here too, and some talk about synthetic relationships and the associated dangers. However, could we also see these conversations as a form of what Boud and Molley (2013) called Mark 2 feedback? Where the student takes responsibility for their learning and (pro-)actively seeks ways to critically and creatively engage with their own work in order to learn? Could this move reveal agency? An inventive and resourceful way to learn through questioning and from one’s own mistakes? To share work-in-progress, students are often reluctant to share in a less exposing way. Could it therefore make students feel less vulnerable perhaps? Even when students articulate the prompt or question (The Innovating Pedagogies 2024 report (Kukulska-Hulme et al., 2024), published by the Open University, talks about a resemblance to Socratic questioning and recognises the conversational nature of student and GenAI interactions for learning) with precision on which aspects of their work they wish the machine to provide feedback, there is detail and sharpness that students are perhaps less used to including in their message when they seek feedback from their peers, tutors, and others.

Are new feedback practices emerging that have the potential to transform how students engage in feedback to deepen their learning and get some of the support they feel they need? When they need it? Er et al. (2024) comparative study with 2nd year undergraduate students (n=54) on a Java programming course illuminated the potential and challenges regarding AI generated feedback and propose a hybrid system going forward to retain the benefits that human feedback brings such as depth in contextual knowledge and effective feedback personalisation strategies while using models that are trained on educational data to make AI generated feedback more useful and relevant.

How can we help students develop AI literacy to use it responsibly and be aware of the pitfalls? How can we nurture accountable spaces where we are all responsible and respectful towards each other and ourselves also? How will human-to-human and human-to-machine learning relationships evolve with GenAI as a new study buddy? Is this even possible?

Note: An earlier version of this article was published as

Nerantzi, C. 2024. Can machines respond to students’ feedback needs? Media and Learning Association, 2 August 2024. https://media-and-learning.eu/subject/artificial-intelligence/can-machines-respond-to-students-feedback-needs/

References

Ahenkorah, E. 2021. Safe and Brave Spaces Don’t Work (and What You Can Do Instead). 21 September 2021. https://medium.com/@elise.k.ahen/safe-and-brave-spaces-dont-work-and-what-you-can-do-instead-f265aa339aff

Boud, D. and Molloy, E. 2013. Rethinking models of feedback for learning: The challenge of Design Assessment and Evaluation in Higher Education. Assessment and Design in Higher Education. 38(6), 698-712.  https://doi.org/10.1080/02602938.2012.691462

Carless, D. 2019. Learners’ Feedback Literacy and the Longer Term: Developing Capacity for Impact. In: Henderson, M., Ajjawi, R., Boud, D., Molloy, E. (Eds.) The Impact of Feedback in Higher Education. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-25112-3_4

Dunbar-Morris, H., Nerantzi, C., Sharp, L. and Sidiropoulou, M. 2023. (In)dependent learning as explored in a cross-institutional collaborative project studying the perceptions of learning of ethnically diverse students. In: In: Fitzgerald, R., Huijser, H., Altena, S. and Armellini, A. (Eds.) Addressing the ‘challenging’ elements of learning at a distance. Distance Education. Special Edition. https://doi.org/10.1080/01587919.2023.2198492

Er,  E., Akçapınar,  G., Bayazıt,  A., Noroozi, O. and Banihashem, S. K. 2024. Assessing student perceptions and use of instructor versus AI-generated feedback. British Journal of Educational Technology. 1-18. https://doi.org/10.1111/bjet.13558

Ferrell, G. and Knight, S. 2022. Principles of good assessment and feedback. How good learning, teaching and assessment can be applied to improving assessment and feedback practice. Jisc. https://www.jisc.ac.uk/guides/principles-of-good-assessment-and-feedback

Fong, C. J., Schallert, D. L., Williamson, Z. H., Lin, S., Williams, K. M. and Kim, Y. W. 2023. Are self-compassionate writers more feedback literate? Exploring undergraduates’ perceptions of feedback constructiveness. Assessing Writing. 57. https://doi.org/10.1016/j.asw.2023.100761

Kukulska-Hulme, A., Wise, A.F., Coughlan, T., Biswas, G., Bossu, C., Burriss, S.K., Charitonos, K., Crossley, S.A., Enyedy, N., Ferguson, R., FitzGerald, E., Gaved, M., Herodotou, C., Hundley, M., McTamaney, C., Molvig, O., Pendergrass, E., Ramey, L., Sargent, J., Scanlon, E., Smith, B.E., & Whitelock, D. 2024. Innovating Pedagogy 2024: Open University Innovation Report 12. Milton Keynes: The Open University. https://iet.open.ac.uk/files/innovating-pedagogy-2024.pdf

Little, T., Dawson, P., Boud, D. and Tai, J. 2023. Can students’ feedback literacy be improved? A scoping review of interventions. Assessment & Evaluation in Higher Education. 49(1), 39–52. https://doi.org/10.1080/02602938.2023.2177613

Nicol, D. and Kushwah, L. 2023. Shifting feedback agency to students by having them write their own feedback comments. Assessment & Evaluation in Higher Education. 49(3), 419–439. https://doi.org/10.1080/02602938.2023.2265080

Robinson, H., Al-Freith, M., Kilgore, T. A. and Kilgore. W. 2023. Critical pedagogy and care ethics. Feedback as care. In: Suzan Köseoğlu, S., Veletsianos, G. and Rowell, C. (Eds.) Critical digital pedagogy in higher education. Athabasca University Press, https://doi.org/10.15215/aupress/9781778290015.01

Shea, P. 2024. The resistance to AI in Education isn’t really about learning. 19 July 2024. https://medium.com/the-quantastic-journal/the-resistance-to-ai-in-education-isnt-really-about-learning-41d2d9cf4476

Watkins, M. 2024. Synthetic relationships will alter real ones. 2 August 2024. https://marcwatkins.substack.com/p/synthetic-relationships-will-alter?r=1z9b3o&utm_campaign=post&utm_medium=web&triedRedirect=true