Abstract

Assessment practices have come to dominate much of formalized education, especially within the United States. Currently, learning analytics (la) and educational data mining (edm) are purported by many educational companies and institutions to successfully improve learning through what are often considered as objective collection, classification, and analysis of educational data. Enthusiasm about big data in education has contributed to the naturalization of datafication within the field. Educational data is regarded as a natural resource that exists ‘out there’ to be mined by edm and refined by la. Once refined, it is thought to bear the truth of educational assessment that leads to successful learning outcomes.