WIP: Teaching a Knowledge Engineering Course Using Active Learning, Gamification, and Scaffolding
Several courses offered by the College of Engineering and Computer Science (CECS) rely heavily on lectures as the primary vehicle of instruction. This is even true of courses that emphasize student project work. Many engineering educators regard experiential or active learning as the best way to train the next generation of engineers. Soft skills are increasingly important to the engineering profession and course modifications are often needed to ensure students have opportunities to practice them prior to graduation. It is important to develop teaching methodologies that bring real-world issues into engineering classrooms.
The goal of the project described in this paper is to enhance and transform a lecture heavy class (CIS 479 Introduction to Artificial Intelligence) into a series of mini learning workshops by incorporating academic research on active learning and gamification with software industry best-practices to improve the experiential character of this key required course. In this project the investigators created activities designed to engage students studying artificial intelligence and help them to think like computer scientists or software engineers, not merely programmers. We created software tools as a means of providing scaffolding to support student activities designed to allow them to experience the experimental nature of AI work, without getting bogged down in the details of programming. The software and algorithm visualization tools created in this project allow students to focus on the knowledge engineering and heuristic programming techniques taught in this course.
The project team critically examined the existing software project course (artificial intelligence) offered at our university and created by one of the authors in 1988. The project team created new instructional materials for selected course topics, identified new topics to add to the course, and devised delivery strategies that incorporate academic research findings and software industry best practices, including gamification strategies. They followed a variation of the ADDIE (analyze, design, development, implementation, evaluation) process model to revise and create new course materials. The project team made use of a mixture of case-study review, role play, hands-on exercises involving work with software engineering artifacts, and created scaffolding tools to allow students to conduct experiments.
A gamification framework was created and used within the course to allow students to customize their course participation. The investigators have used gamification in other project-based courses to reward team members differentially for the self-selected tasks required to complete team-based software projects. This course contains a mixture of on campus and distance learning students. The investigators used gameful learning strategies to create multiple completion pathways within the course that do not depend on team-based project work. We used these strategies to encourage greater engagement on the part of distance learning students in this highbred class offering.
The project team created assessment instruments as the active learning materials were designed and deployed. Student learning assessments evaluated their use of higher-level cognitive skills (apply, analyze, evaluate, and create) from Bloom’s revised taxonomy. Student surveys were used to assess the usability of the student materials during their use in Summer 2018 and 2019.
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