Dede, C., Richards, J., & Saxberg, B. (2019). Learning Engineering for online education: Theoretical contexts and design-based examples. New York, NY: Routledge. (Journal of Applied Learning and Teaching, 2019)
In 2016, Massive Open Online Courses (MOOCs) had 50 million students enrolled from around the world. At the same time, Google Analytics that was running free Analytics Academy courses with 5.9 million users, found that 90% of student traffic fell off after just two sessions due to the lack of interactivity and personalisation. Student participation in online education offerings is creating valuable data that can be used to help drive their motivations and learning outcomes. Against this backdrop, industry-leading academics and practitioners in the fields of learning engineering, AI, learning technologies and instructional design have written Learning engineering for online education: Theoretical contexts and design-based examples. This book posits that learning engineering, or “evidence-based approaches, measurable and measured outcomes, and iterative processes” (7), can utilise student data from online platforms to create better and more engaging learning experiences.