The Impacts of Research-Based Computational Thinking (CT) Professional Learning on Teachers’ Practice Efficacy and Teaching

• In Event: Computer Science and Computational Thinking

Abstract

Computational thinking (CT) professional learning (PL) for in-service teachers is necessary as many teachers do not have the requisite CT knowledge and skills. However, there are few excellent PLs available. This study examined how a year-long PL program, grounded in best practices, affected teachers' CT practice efficacy, instruction, and which of the five PL components were effective. Data included close- and open-ended questions in surveys (pre-survey, 4 post-surveys, professional learning community (PLC) survey, and teacher leader survey), lesson observations, and focus group interview. The major findings include the increase in teachers’ CT practice efficacy and teaching efficacy, the effectiveness of the comprehensive package of interventions, and teachers’ indication of the need of PLs focusing on integrating CT into existing subjects.

Authors

• Jiangmei May Yuan, West Virginia University

• Carla Brigandi, West Virginia University

• Karen E. Rambo-Hernandez, Texas A&M University

• Catherine L. Manley, West Virginia University

• Sarah Elizabeth Spencer, Texas A&M University