Digital technologies are central to how public schooling is being reimagined. For example, in the US online charter schools are one of the fastest growing education sectors (Woodworth, et al., 2015). Many of these putatively ‘public’ schools utilise adaptive learning technologies that aim to motivate online learners through delivering personalised curriculum, learning tasks and assessment. The co-opting of engagement through technology as a means to disrupt traditional forms of public education is a recent phenomenon that paradoxically is rooted in a ‘morality of efficiency’ in regards to schools A potent tool in this disruption is a logistics of engagement where “educational resources and learning environments are continually modified with the goal that learners remain invested” through technology that is “continually updated and responsive to the profiles/patterns of the learner” (Thompson & Cook, 2016, p. 6). This paper investigates whether these tools represent a break with the values of public education, or whether they are particular inflexions of those values expressed in digital form. Combining Stiegler’s conceptual work regarding the industrialisation of technics (Stiegler, 1998) and Deleuze and Guattari’s concept of desiring-machines (Deleuze & Guattari, 1983), this paper explores the promise of learning personalisation. The key argument is that this desire for learning personalisation emerges as a new intonation of the moral character of efficiency. This paper uses a Deleuzian orientation to ‘genealogical’ or ‘critical’ philosophy (Deleuze, 2006). This will necessitate two important steps that constitute the ‘method’ of this paper. First, the paper will trace back the fascination with, or desire for, machines that promised to make teaching more efficient through the use of technical devices. Second, the paper will compare the ‘sense’ of these machines to contemporary AI interventions. Learning personalisation promises to have significant impact on the day-to-day operations of the classroom, and the subjectivities of teachers and learners. This paper examines these new digital AI tools and their effectiveness for teaching and learning as forms of moral reasoning that express values regarding efficiency and learning. Comparing the justifications expressed, and hopes for, teaching machines in the early parts of the twentieth century against the claims for effectiveness in the early parts of the 21st century sheds makes sense of how efficiency is being constructed and measured.

Benjamin, L. T. (1988). A history of teaching machines. American Psychologist, 43(9), 703. Deleuze, G. (2006). Nietzsche and philosophy. New York: Columbia University Press. Deleuze, G., & Guattari, F. (1983). Anti-Oedipus. Minneapolis: University of Minnesotta Press. Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: a meta-analytic review. Review of Educational Research, 86(1), 42-78. Stiegler, B. (1998). Technics and time: The fault of Epimetheus (Vol. 1). Stanford: Stanford University Press. Thompson, G., & Cook, I. (2016). The logic of data-sense: thinking through Learning Personalisation. Discourse: Studies in the Cultural Politics of Education, 1-15. doi:10.1080/01596306.2016.1148833 Woodworth, J. L., Raymond, M. E., Chirbas, K., Gonzalez, M., Negassi, Y., Snow, W., & Van Donge, C. (2015). Online charter school study 2015. Credo Center for Research on Education Outcomes.