Learning Analytics, Educational Data Mining, Adaptive Learning

Automated learning pathways are currently a hot topic in discussions on education because those pathways have the potential to personalize learning and provide timely intervention for students. With automated pathways, also known as adaptive learning, the instruction changes based on the students’ current levels of understanding. In some cases, adaptive learning is teacher-directed. In this case, teachers push new content to their students based on the learners’ previous performances. In other cases, the pathways are “system-generated” so the technology “automatically” adapts to meet the needs of individual students. The latter option is far more controversial because it elicits this question: Are algorithms replacing teachers? What if the system “misunderstands” and doesn’t provide students with the proper support and intervention?1