Preservice Elementary Teachers' Perceptions of Challenges Pertaining to Integrating Computational Thinking in Science Teaching

• In Event: Preparing Computationally Literate Teacher Educators: A Professional Development Approach

Abstract

Objectives
This study aims to answer two research questions in the context of a science methods course: (1) What aspects of implementing CT do pre-service teachers (PSTs) find feasible and challenging? and (2) What CT concepts do they tend to integrate in their science plans?

Perspectives
Proper implementation of the science and engineering practice (SEP), “using mathematics and computational thinking” (NGSS Lead States, 2013) requires clarity of scope and deliberate effort in teacher education programs. This study uses Barr and Stephenson’s (2011) nine computational concepts: data collection, data analysis, data representation, problem decomposition, algorithms and procedures, parallelization, and simulation, as the basis for integrating CT in science teaching. Several of these CT concepts support other science and engineering practices such as: SEP#2: Developing and using models, SEP#3: Planning and carrying out investigations and SEP#4: Analyzing and interpreting data. Using CT in scientific problem-solving promotes deeper conceptual engagement.

Methods
This study was part of an intervention aimed at improving PST’s understanding of and ability to integrate CT in their science lessons. PSTs were assigned to read a practical article on CT in elementary science (Sneider et al., 2014), view and comment on a CT–related video and resources, and reflect on the provided examples and lesson plans. This report focuses on PST’s response to two prompts. The first elicits commentary on the feasibility of the science examples, challenges, and how they might manage them. The second prompt asks them to select three CT concepts to embed in their science lesson plans and to reflect on the challenges involved in implementing these elements.

Data Sources
This study analyzes the responses of 22 PSTs, enrolled in Spring 2021 in two sections of an elementary science methods course at a large mid-Atlantic university. Data from this assignment were compiled anonymously from the course’s learning management system and a conceptual content analysis was conducted to identify the range of ideas expressed in response to each prompt.

Results
The majority of participants noted that the CT examples provided in the instructional materials were feasible. Some, however, cited potential challenges related to equity and access to technology in and out of school, technical problems with websites, computers, or support in coding, making sure that the tasks are relevant to science learning. Few referred to concerns about managing group work.
Each of the nine CT concepts proposed by Barr & Stephenson was selected by at least one participant: simulation was selected by 72% of PSTs, followed by data collection and data analysis (45% each), followed by decomposition and abstraction (23% each). Least selected were the concepts of algorithm and automation (4.5% each).

Scholarly Significance
Identifying PST’s perceptions of challenges with CT integration in a science context enables course instructors and instructional coaches to provide the necessary support. In addition, the findings raise questions regarding the extent to which PST’s choice of CT concepts are motivated by their relevance to the lesson’s learning objectives, or PST’s own conceptual knowledge and confidence level.

Author

• Zoubeida R. Dagher, University of Delaware