1Marquette University

Heather Bort and Dennis Brylow

SIGCSE 2013

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

2Marquette University

Problem Solution Workshop Structure Rubric Results Future Work

Outline

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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

The Problem

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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)

Indirect vs Direct

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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

Measuring Impact

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A: basic • Exploring CS and

CT• Boolean Building

Blocks• HPC and

Sciences• CT and the

Sciences• Alice

Combined• Algorithms• Scratch• State and Curriculum

Issues• Problem/Project-Based

Learning and Computational Thinking

• Careers Panel• Google Keynote• TechSpots• Lesson Planning

B: advanced

• AP CS Principles• Creativity• Big Data• Scratch• Impact and the

Internet

Workshop Structure

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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

Data Collection

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Computational Thinking Concepts Level of Inquiry

Rubric

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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

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Data Collection Data Analysis Data Representation Problem Decomposition Abstraction Algorithms & Procedures Automation Simulation Parallelization

Computational Thinking Concepts

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Why Inquiry based learning?• We learn by inquiry from birth• Important skill set• Central to science learning• Right answer versus appropriate resolution

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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”

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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

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Sage on the Stage VersusGuide on the Side

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Levels of InquiryInquiry Level Question Procedure Solution1- Confirmation InquiryStudents confirm a principle through an activity when the results are known in advance.

X X X

2- Structured InquiryStudents investigate a teacher-presented question through a prescribed procedure.

X X

3- Guided InquiryStudents investigate a teacher-presented question using student designed/selected procedures.

X

4- Open InquiryStudents investigate questions that are student formulated through student designed/selected procedures.

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5 Characteristics Of Inquiry Based Learning

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

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Evaluation

Synthesis

Analysis

Application

Comprehension

Knowledge

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2. Asks questions that motivate

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

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Types of questions• Inference • Interpretation• Transfer• About hypotheses• Reflective

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3. Utilizes wide variety of resources

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

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4. Teacher as facilitator

• Teachers play a new role as guide or facilitator

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5. Meaningful products come out of inquiry based learning

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

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Inquiry based learning in Computer science• Cooperative Learning• Teamwork• Collaboration• Project-oriented learning• Authentic Focus

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Concept 0 1 2

Data Collection not incorporated provides the data the the student will use

students are required to collect

their own data

Data Analysis not incorporatedan interpretation of the

data is given to the student

students will analyze the data

Data Representation not incorporated the student is given a specific method to use

students are able to choose their own

method

Problem Decomposition not incorporated

an outline or similar structure is provided to

the student

students are required to break the

problem down on their own

Abstraction not incorporated provides an expected outcome

student arrives at an outcome

Rubric

26Marquette University

Concept 0 1 2

Algorithms and Procedures not incorporated

the basic steps for an algorithmic solution are

provided

students develop an algorithm or procedure

Automation not incorporatedstudents are provided

with a program or some other technology that

automates their process

students are able to automate their

process

Parallelization not incorporated students are instructed to work in parellel

students will decide how to distribute their

workload

Simulation not incorporated students are shown a simulation

students will produce their own simulation

Connecton to Other Fields not incorporated the connection is given

to the studentstudents are required to make a connection

to another field

Rubric

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Concept 0 1 2Data Collection 7 6 3Data Analysis 9 4 3

Data Representation 8 6 2

Problem Decomposition 5 10 1Abstraction 5 9 2

Algorithms and Procedures 4 9 3Automation 3 12 1

Parallelization 12 2 2

Simulation 0 13 3Connection to Other Fields 10 6 0

Results

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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 Learned

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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.

What We Learned

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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

Follow Up

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Link CS4HS content to Common Core Standards

Better lesson plan development and assessment

Continued multi track structure

Moving Forward

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Google Wisconsin Department of Public Instruction The Leadership of the Wisconsin Dairyland

CSTA The many teachers that participated

Our Thanks To: