Author(s):
Project-based learning (PBL) and data-informed teaching (DIT) are two effective methods to offer and support technology courses at scale. These methods are critical to meet industry’s growing demand for an effective and competitive workforce.Project-based learning (PBL) is effective when the following key elements are adopted: knowledge application to address authentic problems, integrating real-life experiences with course materials, independently learning new topics, communicating learning achievements, and multi-learner interactions. Best practices include incorporating authentic scenarios and utilizing near-instant, automated, contextualized, and actionable grader feedback to train a large number of learners with reduced instructor intervention. There are pronounced challenges to teaching online PBL courses. Encouraging students to relate grading feedback to learning; troubleshooting their solutions independently; training students to ask sophisticated questions containing sufficient context and trigger meaningful conversations; and applying traditional active and interactive learning activities (e.g. reflective discussion), are important instructor considerations when teaching PBL courses.It is critical for instructors to monitor engagement and progress in large courses, gain insight into student behavior, detect outliers, and trigger interventions. This requires instructors to apply data-informed teaching (DIT) by carefully assessing data visualizations about student learning activity and trigger action.In this workshop, we will present best practices to integrate PBL and DIT to teach online project-based courses at scale. We will discuss contextualized and actionable autograder feedback as well as best practices and challenges of using DIT.
Coauthors
Marshall An (haokanga@andrew.cmu.edu)
