Three questions have stirred controversies, fueled perpetual debates, and polarized educators, parents and students for as long as educational institutions have existed: What constitutes good teaching? What are effective learning practices? And, perhaps most importantly, what does “student achievement” mean? Attempts to answer these questions have evolved from philosophical musings to data-based modern educational research. Today, Big Data research adds to our power as we unravel the secret of successful learning and teaching .  The MIDAS Learning Analytics Research Hub is a new addition to U-M’s nationally renowned research in learning analytics.  MIDAS funds two initial core research projects.  Through a variety of hub activities, MIDAS hopes to:

  • Disseminate tools and methods to empower campus-wide learning analytics research.
  • Build a collaborative network of Big Data learning analytics researchers, and help UM stay at the forefront of learning analytics research in the nation.
  • Form industry partnerships and transform research findings into the next generation of learning systems.

LEAP: analytics for LEarners As People

The goal of this project is to build a new generation of learning analytics tools which integrate our understanding of “student as a person” and “student as a learner”.  The research team will develop language, speech, and sensor-based machine learning tools that translate input data (academic performance, social media streams, WiFi access data and survey data from 1000 students) into attributes that will form a student profile.

Holistic Modeling of Education (HOME)

The research team aims to bring revolutionary changes in our understanding of education and learning through the holistic modeling of learners, impact the development and deployment of effective learning tools and methods, and greatly enhance U-M’s research capability in learning analytics.