Creating Digital Education Quality: Everyone Can Improve
Concurrent Session 2
Brief Abstract
The current environment within academic education and the rush during the pandemic to create remote learning has developed learner distrust of digital education. This presentation demonstrates a model of success in applying OLC standards within a quality framework at a course and curriculum level. Unique application of data collection with learners at mid- and end-of-term provide feedback for improvement is discussed. Speakers discuss the learning analytics in combination with data collected in areas of course design, faculty engagement, student engagement, and development of a community of learning. Data provides faculty and instructional designers with actionable information to modify learning activities. Consolidation of data provides program leaders with the ability to easily evaluate curriculum and apply effective quality improvement and change practices. This presentation provides an overview of a school-wide quality model adapted to assure the high quality of courses while allowing faculty in higher education the freedom to develop new and innovative learning strategies and activities.
Presenters
Extended Abstract
A model for data collection, analysis and data dashboard for course level to curriculum level will be presented.
Development of a school wide digital education quality and quality improvement focus will be outlined.
Learners will come away from this presentation with an actionable plan, adaptable to a variety of learning settings focused in quality improvement evidence-based practices.