Diving into the Deep End of Learning Analytics – Are You Ready?

Concurrent Session 1

Session Materials

Brief Abstract

Is your institution on the brink of using learning analytics to inform data-driven decisions?  Or are you on the fence about the potential of analytics?  Come hear the story of one institution’s journey through analytics implementation, which will include lessons learned and helpful tips.  Participants will leave with ideas they can incorporate in their own analytics projects

Presenters

Lead Presenter: Molly Mead, University of Missouri-Kansas City

Molly Mead, Ph.D., has been an Instructional Designer for UMKC since March 2011. Molly has Quality Matters and Online Learning Consortium certification in online teaching and learning. Prior to that, Molly worked for the UMKC School of Education and the Missouri Department of Elementary and Secondary Education for over 20 years in a variety of roles related to the educational use of technology. Molly has researched and provided instruction in the use of tools such as electronic whiteboards, student response systems, learning management systems and social media applications. Molly teaches several online graduate courses for the School of Education related to the selection, use and assessment of educational technology. Molly is also the co-founder and past President of the Kansas City Metropolitan Area Educational Technology Network, serving over 32 school districts, universities and other organizations.

Co-presenter: Lara Mabry, University of Missouri - Kansas City

Lara Mabry is an Instructional Designer at UMKC Online. Lara has a devoted interest in bringing education to an unlimited audience in accessible, innovative, and most importantly, meaningful ways. Prior to coming to UMKC, she taught face to face, online, and blended courses for five years in clinical laboratory sciences at Virginia Commonwealth University. She incorporated and assessed several eLearning tools including mobile devices, active learning platforms, and virtual collaboration techniques in the health sciences environment. Lara has disseminated her research in mobile learning at regional and national conferences and is currently pursuing a PhD in Health Related Sciences with a focus in education from Virginia Commonwealth University. Her dissertation research involves the development and assessment of a mobile app evaluating critical thinking skills in a health professional program. Lara holds a BS and MS in Clinical Laboratory Sciences from Virginia Commonwealth University in addition to certifications as a Medical Laboratory Scientist (MLS) and Specialist in Hematology (SH) from the American Society for Clinical Pathology (ASCP). She is also certified by Quality Matters in online teaching and learning.

Tags

Analytics Evaluation Learning analytics Models Online Planning. dashboards

Extended Abstract

With the intent to improve quality of online courses and inform instructional design decisions, the University of Missouri in Kansas City (UMKC) dove head-first into learning analytics with the purchase of Blackboard Analytics for Learn.  This analytics tool merges extensive data from the university's learning management system (LMS) with course attributes from the student information system (SIS) to offer self-service reporting options, dashboards, and trend analyses to gain insight into user activity, student performance, and course design.  UMKC initiated the implementation process for Blackboard Analytics in the summer of 2015, and for the past year, the university has navigated the waters of system integration, data validation, and fostering the idea of using learning analytics data to improve teaching and learning through workshops and training.

This presentation will reveal the trials and tribulations experienced during this software deployment with recommendations to consider when incorporating a learning analytics tool at your institution.  Tips include: 1) Record all training provided by the vendor, 2) Include all team members in all of the phases of implementation, 3) Allow enough time for data validation, 4) Create a ticketing system for the data validation process, and 5) Have a clear picture of what you want to do with the data before you begin data validation.  

After months of data validation and many lessons learned, UMKC is now ready to shift focus to how analytics will be used as a tool to improve instructional design of online courses.  While it has not been an easy process, the extensive evaluation of the data provides confidence in the power of the tool to promote positive change. 

At the end of this session, participants will be able to:

  • Identify important phases in the analytics implementation process
  • Integrate tips and recommendations into their own analytics projects
  • Better articulate their institution’s roadmap for learning analytics