The readings presented a view into potential futures that I see as both inspiring and quasi-dystopian. Stories like Scenario 1 (Macgilchrist et al., 2020) present a future where educational data offers powerful methods for streamlining education. In Iona’s story (Maughan, 2014) we’re shown a small glimpse into how this data could reduce teacher tasks by linking virtual tutors to learning outcomes that tie into other course requirements. This leads me toward a future where data-centric education is used as a means of reducing inequalities in higher education (HE) (Macgilchrist, 2018); but if it only brings out inequalities defined by data, who will be left behind? As HE focuses on performance metrics for students, courses, and programs (Williamson, 2019), it can use this data to automate teacher tasks which could be as simple as assessing and addressing student engagement but also to create personalized student learning pathways, assessments, and feedback, making the need for data dashboards secondary due to the AI making those choices automatically. In theory, this could lead to HE institutions increasing enrolment and class sizes due to the reduction in the teacher’s workload, placing teachers literally in the role of the “guide on the side,” a human assistant for when the virtual assistant has failed. Teachers — or subject matter experts — will continue to shape the curriculum and pedagogy, but the day-to-day “teaching” will be highly personalized for each student by AI through the gathering, analysis, and application of data. These advancements will work to help close the achievement gap and build greater social equality (Macgilchrist, 2018), but what risks are run by automating equality?


Macgilchrist, F. (2018). Cruel optimism in edtech: When the digital data practices of educational technology providers inadvertently hinder educational equity. Learning, Media and Technology, 44(4), 1–10.

Macgilchrist, F., Allert, H., & Bruch, A. (2020). Students and society in the 2020s. Three future ‘histories’ of education and technology. Learning, Media and Technology, 45(1), 76–89.

Maughan, T. (2014, June 22). The future of ed tech is here, it’s just not evenly distributed. Futures Exchange.

Selwyn, N., Pangrazio, L., Nemorin, S., & Perrotta, C. (2020). What might the school of 2030 be like? An exercise in social science fiction. Learning, Media and Technology, 45(1), 90–106.

Williamson, B. (2019). Policy networks, performance metrics and platform markets: Charting the expanding data infrastructure of higher education. British Journal of Educational Technology, 50(6), 2794–2809.