We have had four talks accepted to OLC Innovate 2019 in Denver, Colorado. The talks are:
- “Comparing Online and In-Person: Guidelines for Creating Better Outcomes Online”, by myself and Melinda McDaniel.
- “Clustering Code Submissions for Scalable and Social Feedback”, by myself and Keren Shamir
- “MOOCs for Academic Credit”, by me
- “A 7-Principle Model for Designing and Developing Instructional Video”, by Chaohua Ou and myself
The abstracts for the talks are available after the jump.
Abstract (Comparing Online and In-Person): In Spring 2017, Georgia Tech launched an online for-credit version of its CS1 class. In Spring 2018, students in this online version achieved better learning outcomes than students in the traditional version. In this session, we present the experiment and the design of the course that led to these outcomes.
Abstract (Clustering Code Submissions): Large online classes often suffer from difficulty in getting students feedback on their work. For computer science classes, code submissions lend themselves to intelligent clustering. In this demonstration, we will show how such a tool can be used to author individual feedback, as well as give students social feedback.
Abstract (MOOCs for Academic Credit):After their early days focused largely on opening up access, MOOCs have increasingly shifted toward offering credit for open learning opportunities. In this session, we’ll explore the opportunities and challenges in offering academic credit for MOOC completion.
Abstract (A 7-Principle Model):This session will discuss a model of seven principles drawn from learning sciences and empirical evidence for designing and developing instructional videos. It will also present findings from surveys among students in an online graduate course for eight semesters on their perceptions of the effectiveness of the videos and the course.