Date of Award
Action Research Project
Master of Arts in Education
This Action Research Project provides data from three different instructors teaching Computational Thinking (CT) to better understand the effects of CT instruction. The researchers focused on identifying problem-solving strategies used by students, what affect teaching CT has on student confidence and ability to problem solve, and what common challenges can be found at different age levels. The study used student pre and post-reflection to measure understanding and comfort with problem-solving. Researchers taught three common lessons of CT including the following concepts: algorithms, loops, conditional statements, and debugging. For data collection, each student was asked to work on a computer game called Human Resource Machine (HRM) while using video and audio to record themselves. Analysis showed a slight decrease in two categories related to working to find a solution to a difficult problem, and the ability to fix small problems that are part of a larger problem. There was a confidence increase in categories related to the ability to do math, the ability to give directions and the ability to someday build a computer. Two of the research sites were able to further break down the data to analyze the differences in the male vs. the female reflections. While CT is often seen as a separate subject, the analysis also showed that reading comprehension has a strong influence on students’ ability to solve CT problems and should be taught in conjunction with CT to ensure students receive the maximum benefit.
Belanger, Chris; Christenson, Hannah; and Lopac, Kathleen. (2018). Confidence and Common Challenges: The Effects of Teaching Computational Thinking to Students Ages 10-16. Retrieved from Sophia, the St. Catherine University repository website: http://sophia.stkate.edu/maed/267