Adaptive technologies seek to provide equal opportunities and fulfill student needs through hyperpersonalization (McRae, 2013). A complete mapping of student data creates complete transparency of the learner and her situation.Rasmus Leth jørnø, Bjarke Lindsø Andersen & Peter gundersen
● Semi-autonomous adaptive systems make lowlevel decisions that mimic (and relieve) the expert teacher. Intelligent tutoring systems engage students on recurring issues. Expert systems and early warning systems help assess skill levels and levels of engagement. Machine learning helps grade papers, check spelling, grammar and plagiarism. Recommendation systems help with didactic choices and order of subjects.
● Platform solutions bring efficiency and economies of scale. They relieve the teacher, whose hands now are free to focus on more pertinent matters.
● Finally, these systems solve the one hitherto unsolvable problem of fulfiling all students’ needs 1:1, i.e. the 2-Sigma problem or as it is known colloquially: lack of funding. These systems are privately funded such that the noble pursuits of education and profitability go hand in hand (Williamson, 2014).
Rasmus Leth Jørnø, Bjarke Lindsø Andersen & Peter Gundersen (2022) The
imaginary of personalization in relation to platforms and teacher agency in Denmark, Nordic Journal of Studies in Educational Policy, 8:1, 20-29, DOI: 10.1080/20020317.2021.2022073