| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 15, 2016 |
| Latest Amendment Date: | December 11, 2018 |
| Award Number: | 1640237 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Allyson Kennedy
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2016 |
| End Date: | September 30, 2019 (Estimated) |
| Total Intended Award Amount: | $1,000,000.00 |
| Total Awarded Amount to Date: | $1,000,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
333 RAVENSWOOD AVE MENLO PARK CA US 94025-3493 (609)734-2285 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
333 Ravenswood Avenue Menlo Park CA US 94025-3493 |
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Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | STEM + Computing (STEM+C) Part |
| 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
SRI Education, a division of SRI International, in partnership with the American Institutes for Research (AIR), their CS10K Community, and Exploring Computer Science (ECS) teachers, is investigating the design and delivery of high-quality assessment literacy materials and sustainable, ongoing training as part of the existing ECS teacher professional development model. As reforms under President Obama's Computer Science for All initiative start to scale across the country, stakeholders will be looking for evidence of student learning. It is critical to prepare CS teachers to competently use assessment evidence to make valid inferences about student learning and to use these inferences to guide instructional decisions. This need is arguably even more acute with ECS, which is viewed as an introductory course to CS and is intended to engage and open doors for students who are traditionally underrepresented in CS degrees and careers. SRI has been partnering with ECS to develop and validate end-of-unit assessments measuring computational thinking practices, and to use those assessments as outcome measures in an implementation study to determine factors with the most impact on student success. This investigation advances this work by engaging 75 ECS teachers and 2200 students in investigating the impacts of innovative PD materials and training in a blended learning environment on teachers' assessment attitudes and practices.
The project leverages existing partnerships and assessment materials, AIR's CS10K Community of Practice web site, and SRI's expertise creating and delivering high-quality professional development for STEM teachers. The results are the creation of innovative PD materials for supporting assessment literacy practices through adapting and applying an evidence-based methodology for modeling pedagogies of professional mathematics education practice. Learning and attitudinal measures are based on analysis of ECS teacher interview data and classroom assessment practices, while measures of implementation are adapted from studies in inquiry-oriented mathematics professional development and classrooms. Multiple methods to measure ECS teacher learning from professional development, implementation of assessment literacy practices in the classroom, and contextual and background variables are all utilized. From this data, the team conducts analyses to determine the impacts of the PD materials and activities on ECS teachers' attitudes and formative and summative assessment literacy practices. The project is guided by an advisory board with expertise in assessment, and CS education and professional development.
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.
The Teacher Assessment Literacy for Exploring Computer Science Teachers (TALECS) project was designed to address computer science teachers’ need for professional development around formative assessment. The project designed a set of three innovative online professional development (PD) courses that provided support for teacher in the development of three different topics: teacher journaling, portfolios and assessment development. Surveys and qualitative analysis of online discussion posts were used to determine if teachers found these materials supportive in their assessment literacy development.
The intellectual merit of the project is proof-of-concept findings that online PD can successfully support teachers in designing their own formative assessments—journals, portfolios, and performance assessment items. The project found that teachers generally felt favorably about the assessments they designed, and they planned to use them. Teachers expressed an increase in their knowledge about how to use these formative assessments through the PD. While different teachers found different topics to be more relevant (for example in year 2, some teachers didn’t see a need for designing their own assessments and so showed less interest in that topic) teachers still expressed that the PD was useful to them. These findings are part of an article submitted to a peer-reviewed journal on technology in teacher education.
The broader impacts of the project are manifested in the artifacts created for broader use by teachers and professional development providers. A set of blog posts delivers in compact form the content of our PD, so that teachers can read it, follow along, and design their own assessments for use in their computer science classes. Likewise, facilitator materials allow an experienced PD provider ready-to-use materials to follow our model, resulting in teachers designing formative assessments to richly capture student learning. These assessments promise to better collect evidence of learning from a broader range of learners, increasing the chances that these students will experience success in computer science and may continue studying and working in it.
Last Modified: 09/26/2019
Modified by: Jennifer Knudsen
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