How Do Educators Apply Computational Thinking to Instructional Planning?

Framework

Key to our process will be focused attention on Computational Thinking (CT). This important twenty-first-century skill is typically characterized by four distinct cognitive skills that have clear parallels to instructional planning tasks and skills:
Deconstruction (learning objectives.
Algorithmic thinking (task analysis).
Pattern recognition –(e.g., student misconceptions, assessing for blocks of enabling knowledge key points).
Abstraction – (e.g., modifying instruction in the moment using formative assessment).
These skills are aligned with the Universal Design for Learning (UDL) framework.
These four phrases of CT are associated with critical thinking necessary for problem-solving skills that are crucial for instructional planning.

Our exploratory study at the intersection of the learning sciences, teaching as a design science, and professional development will inform educator preparation for the design and planning of impactful learning experiences. This study examines how teachers’ mental models of learning and instructional design planning change through participation in instruction or professional development of Computational Thinking (CT), a key 21st-century skill. Participants will learn instructional design frameworks - UDL - LITE, and apply the four sub-skills (Decomposition, Algorithmic thinking, pattern recognition, and Abstraction) as a framework for thinking in the context of learning design for instructional planning and decision making. [3]
Using micro-lessons on CT, UDL, just-in-time learning, lesson study/ critique, and chunking the work of UDL leveraging cognitive load theory will support students’ understanding of the needed application of the intersecting skill sets.
Current research and evidence base related to the problem/idea
The relevant literature base for this project falls into several main areas:
1. Cognitive processes/ thinking of teachers for planning instruction
2. Computational thinking / UDL
3. Teacher beliefs about instructional planning
4. Common problems/ issues with lesson planning - focus on early childhood

Universal Design for Learning:
The concept of universal design for learning (UDL) pertains to “proactively addressing barriers to learning” (Israel, Wherfel, et al., 2015, p. 46). The goal of UDL is to develop methods that enable all students to be successful in learning. By making use of this method, students are given more flexibility when it comes to accessing, engaging with, and demonstrating their knowledge of the material they are studying. It is important to note that lesson plans created this way benefit all students, but they have been shown to be especially effective for students with learning and attention problems. It is the goal of UDL to eliminate any barriers to learning and provide all students with an equal opportunity to succeed when utilized in a variety of teaching methods. The point is to provide flexibility that can be adjusted according to the strengths and needs of each student. It is this flexibility that is intended to benefit all students.

Methods

Our mixed methods study explores the following questions:

Research Questions
Phase 1:

1. How do educators (including pre-service teachers) conceptualize the instructional planning process?
a) How does the use of computational thinking impact teacher perceptions of the instructional planning process?
2. How do educators apply computational thinking to instructional planning?
a) Are key challenges of lesson planning ameliorated through explicitly teaching computational thinking? design frameworks (e.g. LITE or UDL)?
3. How can teacher educators teach computational thinking effectively to teacher-learners?

Unit of Analysis/ Study
Our unit of analysis is be a cohort or class.

Participants
Participants in the study are pre-service or in-service teacher-learners in educator preparation contexts, primarily early childhood, secondary education or professional development courses.

Data sources / tools
Our sources of data are learning artifacts such as concept maps, task analysis documentation, lesson plans, analytic memos (researchers), a post-course survey and focus groups.

Data collection and analysis

•  pre and post-course learner artifacts to understand how educators initially conceptualize the lesson design and planning process. Each instructor will work individually to assess learners’ understanding by developing mental models – either visual representations or written descriptions of the instructional planning processes. We will analyze these data for patterns and trends.
• survey learners at the end of each course to collect perceptual data on the experience of using computational thinking, confidence, and self-efficacy in instructional planning.
•  a small number of focus groups to hear directly from the teacher-learners about their experiences, questions, concerns and understanding.
• research team own analytic memos about the process of teaching computational thinking, jointly analyzing and comparing ideas, questions and findings.

Results

Our preliminary findings suggest that educators have very different conceptualizations of the instructional planning process. We will continue to work with our students through the Fall term, which ends at the beginning of December. We expect that we will have an array of learning artifacts to from which we can discern patterns - particularly misconceptions or misunderstandings of learning experience design. We also expect that teachers' awareness of thinking skills that are core to the design process - eg task analysis, pattern recognition (eg. analyzing assessments), algorithmic thinking, and abstraction will improve. We may see a corresponding increase in self-efficacy for the design process. Using CT as a cognitive tool, we expect evidence of the educators' thinking about the design process to change. Our data collection from the courses will be complete at the end of the term, followed by focus groups. Data analysis will be complete by early Spring 2023.

Importance

Designing impactful learning experiences requires intentional planning of the learning outcomes, determining the rationale and sequence of activities as well as making decisions about formative and summative assessments. In addition to content knowledge, this kind of planning and organization requires a range of pedagogical skills and thinking, beginning with articulating the learning objectives. Teachers, particularly pre-service teachers, often struggle with developing the necessary skills. Our exploratory study tests the impact of direct instruction of computational thinking as a way to promote lesson design sub-skills by enhancing the quality and clarity of educators’ thinking and planning skills.
K-12 impact
If educators are better prepared to apply higher-order thinking skills when designing learning experiences and planning lessons, the clarity, and quality of instruction will be significantly improved. Our relatively simple but powerful strategies could potentially transform how educators in K-12 contexts think about their teaching – with a focus on student learning.

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