This field of research employs the use of computational analysis and reporting of data on learners for the purposes of understanding learners, optimizing learning and the environment in which learning occurs. It involves the collection, measurement, and analysis of the data for visual reporting to gain more insights into in the behavior of learners and their environment. Leaning analytics compiles large amount of data about students from a complex network of information for better understanding of learner goals and supports in the improvement of learning contents for better pedagogy. This type of analytics assists in finding out what courses and materials engages and matters the most to learners, identify and fill the gaps in courses based on the needs of learners and determine how specific course objectives are being met by these learners as they study the course contents. Both faculty and learners benefit from the use of learning Analytics.
The Smart Lab research into Learning analytics will focus on:
- Suggesting better materials and identifying relevant and interesting topic areas to enhance learner engagement.
- Improving design and development of courses to help faculty fill in the gaps in their skill set and help learners grasp their study materials better.
- Interpreting wide range of educational data into useful actions to foster learning.
- Assisting schools act towards educational improvement to provide more personalized education for each student.
The learning analytics cluster is interdisciplinary and comprises researchers from Ohio University and other universities in the United States. A special emphasis is being laid on better understanding STEM education.