Using Attribution Theory to Analyze STEM Teachers Experiences in Data Science and Cybersecurity Professional Development

Abstract

Attribution theory describes an individual’s interpretation of events and the influence the interpretation has on motivation for learning. Using the attribution achievement theory lens, we made meaning of teachers learning experiences during a six-week summer Research Experience for Teachers (RET) program. The study involved 11 STEM teachers—six men and three women during a data science and cybersecurity professional development. We used online observations, and teachers reflectional journals to record teachers’ learning behaviors. Evidence emerged that teachers attributed their learning achievement to task difficulty, personal effort, collaboration, and seeking help. Teachers exhibited causal factors as internal, stable, and controllable. Educators’ knowledge of how learning takes place can help in classroom management enabling learners to overcome self-blame and improve academic achievement.

Presenters

Joseph Wairungu
Graduate Research Assistant, Curriculum and Instruction, Texas Tech University, Texas, United States

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

Adult, Community, and Professional Learning

KEYWORDS

Professional Development, Attribution, Cybersecurity and Data Science, K-12 Education

Digital Media

This presenter hasn’t added media.
Request media and follow this presentation.