ABSTRACT
At its essence, human learning is a complex neurological phenomenon that has traditionally been understood and measured through observable behaviour. More recently though, learning analytics (LA) has emerged to conceptualise and facilitate human learning by measuring learning correlates, including physiological metrics such as pupil dilation and perspiration rates. In this chapter, we show that these correlates of learning are distinct from actual learning (the map is not the territory), and warn of the risks and challenges of inferring truth from one discipline (LA) to another (education). We demonstrate the importance of valid and logical translation of LA evidence into education, and to this end we describe a conceptual framework and translation schema by which the benefits of LA can be validly translated, leading to the direct benefit of both educators and learners.
