
NSF Org: |
CNS Division Of Computer and Network Systems |
Recipient: |
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Initial Amendment Date: | August 19, 2014 |
Latest Amendment Date: | August 19, 2014 |
Award Number: | 1441045 |
Award Instrument: | Standard Grant |
Program Manager: |
Janice Cuny
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | January 1, 2015 |
End Date: | December 31, 2018 (Estimated) |
Total Intended Award Amount: | $663,051.00 |
Total Awarded Amount to Date: | $663,051.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
801 UNIVERSITY BLVD TUSCALOOSA AL US 35401 (205)348-5152 |
Sponsor Congressional District: |
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Primary Place of Performance: |
Box 870290 Tuscaloosa AL US 35487-0104 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Computing Ed for 21st Century |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
The University of Alabama Tuscaloosa, in collaboration with Duke University and Rutgers University, propose a project aimed at infusing Collaborative Learning (CL) into the new AP Computer Science Principles (CSP) courses. The curriculum framework for CSP was designed to be engaging to a broad and diverse group of students. However, curriculum alone is not enough to ensure student engagement: the most interesting and innovative curriculum can still be taught in a disengaged manner. The learning science literature on CL has shown that it increases class participation and student learning while also promoting diversity in a manner that supports the differentiated instruction needed to engage students who have mixed abilities. This project seeks to understand how the best practices of CL can be applied across the CSP curriculum framework and community.
This project will provide deep professional development opportunities for CSP teachers through face to face training and to create a publicly available collection of CL strategies applied to the CSP context. The project will connect the CL strategies within a series of 36 lesson plans, a teacher workbook, a YouTube video channel with examples on using CL strategies, while also providing direct professional development during an intensive week-long workshop. The project will directly reach 180 teachers but the developed materials will be disseminated through the CS Community.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Project resources are archived on the CSforAll Teachers site at the following link: https://csforallteachers.org/resource/cooperative-learning-structures-ap-csp
The Advanced Placement® Computer Science Principles (AP CSP) course was the culmination of an eight-year NSF/College Board pilot project that exceeded all expectations in terms of enrollment in its first two official years. Broadening the accessibility of computing to include a diverse population of students has been a fundamental design goal of the AP CSP curriculum framework (CF). This project is an NSF-sponsored multi-year effort to infuse cooperative learning (CL) structures into AP CSP classrooms to improve class participation and student learning. AP CSP was designed to engage all learners. CL structures have been demonstrated to engage diverse learners who are in the same classroom. The goal of CL is to offer an environment where every student is encouraged to participate equally toward their own academic achievement, while simultaneously working toward a positive common goal with teammates from different backgrounds and mixed abilities, thus promoting broadening participation in computer science (CS) classes.
The intellectual merit of this project is the design and assessment of the best practices of CL applied to the AP CSP CF. This project has potential broad impact by changing the way CS is viewed and taught. Through face-to-face (F2F) workshops spanning July 2015, 2016, and 2017, 143 AP CSP teachers were introduced to CL structures and guided in the integration of these structures with the AP CSP CF. The contribution of the project includes a workbook and accompanying videos of CL strategies that can be integrated in any CSP classroom, regardless of any specific CSP curriculum being used. The project's open resources will be made available on the CS10K Community of Practice for sustainability and scalability of the project to those who did not attend the workshops. Although this proposal focused on CL in the CSP classroom, the structured CL pedagogy can be used in any classroom with any discipline.
Our research efforts engaged in numerous and varied data collection activities with the participating teachers and their students. We sought to understand the effects of the professional development (PD) that focused on AP CSP pedagogical content knowledge using CL structures on teachers; specifically, how, and to what extent the teachers implemented CL in their AP CSP classrooms. We also sought to understand whether and to what extent the CL activities had an impact on student self-efficacy and AP Exam scores. We investigated the relationships between 1) PD that infuses CL structures within the AP CSP context, 2) classroom practices with CL structures, and 3) student outcomes. Specifically, we hypothesized that the Opportunity To Learn Collaboratively (OTLC) would positively impact students' learning (i.e., AP scores) and that students with high OTLC would outperform both a national sample and a carefully matched state composite sample, particularly for females and URM students. We also hypothesized that higher OTLC classes would positively predict students' self-efficacy in computer science.
The general findings of our project indicate that the F2F PD workshops led to gains in the understanding of and confidence in teaching with CL structures and the use of CL structures was a statistically significant and a positive predictor of student AP scores for participating classes. Student outcomes for the CL sample alone were analyzed in terms of the relationship between students' OTLC and students' self-efficacy in computer science (CSSE). OTLC scores did not significantly predict students' post-course CSSE levels. However, the use of Pair Programming alone predicted post-course CSSE.
Students' AP scores compared favorably to national sample of 2017 + 2018 AP CSP exam-takers. AP CSP scores of students in the CL sample were higher than would be expected based on this national data. CL sample passing rates were significantly higher than expected for:
- All students (76.8% vs. 72.3%)
- Male students (79.9% vs. 73.7%)
- Under-represented minority (URM) students (66.3% vs. 55.0%)
We also looked at a carefully matched state composite sample. Students in the CL sample outperformed a matched 2017+2018 state composite sample, constructed from state-level data (13 states). Passing rates were significantly higher than expected for:
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All students (76.7% vs. 70.4%,)
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Male students (79.9% vs. 72.3%)
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URM students (66.1% vs. 53.6%)
Passing rates for Female students (69.1% vs. 65.9%) and for Non-URM students (82.4% vs. 77.4%) were numerically higher but the difference was not statistically significant.
These powerful effects were realized from one week of summer F2F PD per teacher, and each teacher's daily choices of if, when, and how to incorporate CL structures into classroom activities. Teachers clearly communicated their need for additional support and resources (e.g., a learning community) throughout the academic year. The benefits of engaging in a persistent teacher learning community would have led to more effective use of CLs, prompting even stronger student outcomes.
Last Modified: 05/31/2019
Modified by: Jeffrey G Gray
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