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CS4Impact: Measuring Computational Thinking Concepts Present in CS4HS Participant Lesson Plans. Heather Bort and Dennis Brylow SIGCSE 2013. Outline. Problem Solution Workshop Structure Rubric Results Future Work. The Problem.

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CS4Impact: Measuring Computational Thinking Concepts Present in CS4HS Participant Lesson Plans

Heather Bort and Dennis Brylow

SIGCSE 2013


Outline

Outline

  • Problem

  • Solution

  • Workshop Structure

  • Rubric

  • Results

  • Future Work


The problem

The Problem

  • Many current K-12 outreach efforts attempt to increase the number of students interested in majoring in computer science and related fields

  • Assessing these efforts has proven to be challenging

  • Most prior work on examining the impact of professional development interventions for K-12 CS teachers stops with indirect measures


Indirect vs direct

Indirect vs Direct

  • Measuring Knowledge

    • Before and After workshop attitudinal survey (indirect)

    • Concept Quiz (direct)

  • Measuring Concept Integration

    • Surveying attitudes about using the concepts in their classrooms (indirect)

    • Ability to integrate workshop material into lesson plans for the classroom (direct)


Measuring impact

Measuring Impact

  • Workshop structured around Computational Thinking (CT) lesson plan building and sharing

  • Designed a rubric to measure how CT concepts were used in the lesson plans

  • Applied the rubric during the sharing phase of the workshop



Data collection

Data Collection

  • Each participant presented their lesson plan to the group

  • Presentations were video taped for later analysis

  • 4 hours video data with full text of written plans coded with rubric


Rubric

Rubric

  • Computational Thinking Concepts

  • Level of Inquiry


Computational thinking

Computational Thinking

  • Jeannette Wing states that computational thinking “represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use”

  • a problem solving method that uses algorithmic processes and abstraction to arrive at a answer

  • showcase concepts over programming skill or computational tools in the classroom


Computational thinking concepts

Computational Thinking Concepts

  • Data Collection

  • Data Analysis

  • Data Representation

  • Problem Decomposition

  • Abstraction

  • Algorithms & Procedures

  • Automation

  • Simulation

  • Parallelization


Why inquiry based learning
Why Inquiry based learning?

  • We learn by inquiry from birth

  • Important skill set

  • Central to science learning

  • Right answer versus appropriate resolution


Traditional approach to learning
Traditional Approach to Learning

  • Focused on mastery of content

  • Teacher centered

  • Teacher dispenses “what is known”

  • Students are receivers of information

  • Assessment is focused on the importance of “one right answer”


Inquiry approach to learning
Inquiry Approach to Learning

  • Focused on using and learning content to develop information processing and problem solving skills.

  • More student centered

  • Teacher is the facilitator of learning

  • More emphasis on “how we come to know”

  • Students are involved in the construction of knowledge


Sage on the Stage

Versus

Guide on the Side




1 bloom s taxonomy
1. Bloom’s taxonomy

  • Inquiry based learning asks questions that come from the higher levels of Bloom’s Taxonomy


2 asks questions that motivate
2. Asks questions that motivate

  • Inquiry based learning involves questions that are interesting and motivating to students


Types of questions
Types of questions

  • Inference

  • Interpretation

  • Transfer

  • About hypotheses

  • Reflective


3 utilizes wide variety of resources
3. Utilizes wide variety of resources

  • Inquiry based learning utilizes a wide variety of resources so students can gather information and form opinions.


4 teacher as facilitator
4. Teacher as facilitator

  • Teachers play a new role as guide or facilitator


5 meaningful products come out of inquiry based learning
5. Meaningful products come out of inquiry based learning

  • Students must be meaningfully engaged in learning activities through interaction with others and worthwhile tasks.


Inquiry based learning in computer science
Inquiry based learning in Computer science

  • Cooperative Learning

  • Teamwork

  • Collaboration

  • Project-oriented learning

  • Authentic Focus





What we learned

What We Learned

  • Many of the participants did not effectively integrate the CT core concepts into their lessons

  • A large number of lesson plans scored 0 in some sections of the rubric


What we learned1

What We Learned

  • Among the experienced CS teachers, some are firmly entrenched in a pedagogical style that still emphasizes conveying facts and programming language syntax, not in focusing on skill building

  • Large number of participants were able to produce lesson plans with level 1 or level 2 components, sometimes in multiple core areas.


Follow up

Follow Up

  • One third of participants volunteered feedback for six month follow up survey.

  • All but one respondent has been incorporating concepts from the workshop in their classrooms


Moving forward

Moving Forward

  • Link CS4HS content to Common Core Standards

  • Better lesson plan development and assessment

  • Continued multi track structure


Our thanks to

Our Thanks To:

  • Google

  • Wisconsin Department of Public Instruction

  • The Leadership of the Wisconsin Dairyland CSTA

  • The many teachers that participated


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