COIL is proud to have supported the Learning Analytics: Leveraging Big Data to Improve Learner Success project through our Research Initiation Grant Program.
During the past year our team of interdisciplinary researchers has explored the emerging field of learning analytics, with the goal of leveraging student data to develop systems that adapt to the specific needs of students (Long & Siemens, 2011; Siemens, 2010).
We will develop learning analytics competencies at Penn State in a three-phase process: 1) data acquisition, cleaning and storage; 2) data analysis and modeling; and 3) prototype development and data visualization. Our project focuses on the resident and online sections of Math 110. We chose this course due to the high opportunity for success: The course enrolls approximately 1,000 students each semester yet up to a third of enrolled students receive a “D” or below. We hope to identify the behaviors that lead to success, predict student outcomes, and help teaching assistants and instructors focus specific resources to address student knowledge gaps.
Our long-term goal is to broaden our scope, working with identified collaborators in other disciplines to apply similar tools to support student success. This also provides opportunities for future research, exploring how analytics systems might differ across disciplines and if predictors of student success uncovered through Math 110 data are the same predictors found in other disciplines.
Faculty Programs Coordinator, Teaching and Learning with Technology
Information Technology Services
202C Rider Building
University Park, PA 16802