Draft Executive Summary • November 27, 2013

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Washington STEM Framework for Action and Accountability Validation Project
Draft Executive Summary • November 27, 2013
The Washington STEM Framework for Action and Accountability
There is an urgent need to prepare and inspire Washington’s next generation in science, technology,
engineering, and math (STEM). STEM industries, such as aerospace, agriculture, clean energy, hightech, life sciences, and manufacturing, are active in every region of Washington state. Yet, according to a
2013 Boston Consulting Group report, local companies will experience 50,000 vacancies by 2017 due to
the state’s skills gap at a cost of $800M in lost tax revenue annually. STEM and health care jobs account
for 90% of the projected vacancies. Filling these jobs and increasing the state’s competiveness for new
jobs – from Boeing’s 777x to high-tech global leaders and small businesses alike – will require a worldclass STEM educated workforce statewide.
Washington STEM developed the Washington STEM Framework for Action and Accountability in
response to this need. Washington STEM is a nonprofit organization that advances excellence, equity,
and innovation in science, technology, engineering, and math (STEM) education. The Washington STEM
Framework for Action and Accountability (the Framework) is a comprehensive roadmap for action in
STEM education across Washington.
The Framework consists of:
•
•
•
•
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Vision: The future we are working to create.
Goal: A specific and measurable goal around which various parties can align.
Power Indicators: Research-based indicators alongside emergent ones that can be used to
measure collective impact.
High-Impact Strategies: Evidence-based and promising strategies identified to move the needle
on identified Power Indicators.
Policy Set: An enabling policy agenda to support strategies and indicators, ensuring efforts are
sustainable and implemented at scale from cradle to career.
The Framework provides an unprecedented tool to identify and focus resources on high-impact STEM
education innovations and solutions, align multiple actors around a unified goal, and measure collective
impact. Accordingly, the Framework is designed to accelerate impact across the state by:
•
•
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Strengthening the development and alignment of STEM resources, programs, and policy around
“what works”;
Creating a common research and development agenda to test, identify, and spread promising
practices; and
Creating unified messages and evaluation tools for researchers, policymakers, and practitioners.
Development and Validation Process
The Framework draws upon a review of state and national STEM education and workforce research
findings, data dashboards, programs, and policies. Washington STEM also leveraged stakeholder input
gathered from across the state during the organization’s 18-month incubation phase and nearly twoyears of work with funded partners, regional STEM networks, policymakers, and state and national
colleagues since its March 2011 founding. From there, Washington STEM developed a draft Framework
in January 2013. From January to June 2013, the organization solicited feedback from national and
state STEM education leaders, practitioners, and policymakers.
Draft Executive Summary
1
The overwhelming positive feedback regarding the value of such a Framework and Washington STEM’s
own commitment to acting upon evidence, accelerating equity and results, and spurring scalable
innovations led Washington STEM to seek a formal validation partner. The Washington State
Legislature’s June 2013 passage of E2SHB 1872, comprehensive STEM education legislation that
specifically calls for “a single, cohesive and comprehensive STEM Framework for Action and
Accountability,” added urgency and significantly increased the potential for statewide impact.
In July 2013, Washington STEM contracted WestEd, a nonprofit research and evaluation firm, to conduct
a formal analysis of the draft Framework and recommend improvements. WestEd’s analysis involved a
validation process that consisted of two types of work: 1) stakeholder engagement; and 2) research and
technical product development. These activities resulted in a research and stakeholder validated onepage Framework (see Appendix A), a literature review (see Appendix C), and recommendations for next
steps. Dr. Steven Schneider, the Senior Program Director of WestEd’s STEM education program, and
his team conducted the validation, and a charitable contribution from Battelle funded the validation
process.
Stakeholder engagement
WestEd engaged 36 external advisors drawing from partnering university, funder, business, policy, and
education leaders from Washington state and the nation (See list of advisors in Appendix B). These
stakeholders were grouped into two committees: a Technical Advisory Committee, consisting of
stakeholders who could provide access to data and information needed to directly inform the structure
and content of the Framework; and a Steering Advisory Committee that provided guidance and direction
to the project by giving feedback on how to shape and move forward with the Framework. The resulting
group of experts and partners provided a foundation for ensuring that the Framework validation work was
sufficiently comprehensive and that the criteria applied were rigorous and relevant to Washington
STEM’s vision for STEM education in the state.
Research and technical product development
As a unified product, the Framework communicates a logic model for improving STEM education and
workforce outcomes, with a particular focus on equity. In order to conduct a validation analysis of the
Framework, WestEd examined broad areas of the research base and findings from the field to identify
evidence in support of (or against) the inclusion of components in the Framework. This evidence, along
with input from advisors, represents research used to identify and cite empirical evidence in order to
validate the Framework. The validation analysis used current standards and best practices identified in
research to produce a literature review and full citations tagged to each Framework component.
Databases typically included in the literature search are ERIC, PsychINFO, Dissertation Abstracts,
Sociological Collection, Professional Development Collection, Wilson Educational Abstracts PlusText,
Academic Search Premier, WorldCat, and Google Scholar. Drafts of the analyses were sent to the
advisory groups via email for review and feedback, and all feedback received was considered for the
final recommendations and report.
As in similar review and validation analyses, the Framework validation process relied on industry
standard criteria to evaluate evidence from the research base. Generally, research studies should have
been published within the past 20 years. This time frame encompasses research that adequately
represents the current status of the field and of analytical methods and avoids inclusion of research
conducted with populations and in contexts that may be very different from those existing today.
Research studies identified in the literature search consisted of primary studies of specific interventions
and their impacts or effectiveness, along with studies of how well interventions have been implemented,
literature reviews, and meta-analyses. Primary studies typically used one of the following designs:
randomized controlled trial, quasi-experimental, regression discontinuity, and single subject.
Draft Executive Summary
2
Criteria for inclusion of specific components of the Framework included:
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•
•
Alignment - Is the indicator, strategy, or policy aligned with the goal statement? Is the indicator,
strategy, or policy appropriate for and targeted to the specified age or grade range?
Equity - Does the indicator, strategy, or policy address the needs of students traditionally
underserved in STEM education or underrepresented in STEM careers?
Predictive nature - Is the indicator a critical checkpoint or highly predictive of downstream
Framework outcomes?
Impact - Is there empirical evidence that a strategy or policy is related to an increase in the
aligned power indicator? Or great promise based on new research-based innovations?
Measurement
Success will be directly measured against the Framework’s goal statement:
All Washington high school graduates are STEM literate, prepared and inspired for postsecondary degrees and certificates, and able to contribute to the demands of a highly-skilled and
diverse STEM-driven workforce and society.
The validated power indicators directly align to the goal statement. For each power indicator, WestEd
identified specific measures and assessment tools. These measures were identified because of their
alignment with specific indicators and their demonstrated use in Washington to produce useful data or
their promise to be a useful instrument in generating actionable data if implemented in Washington.
A driving philosophy for the validation project was to consider the Framework as a blueprint for guiding
positive change in STEM education. It is important to remember that the best practices identified by the
research base as evidence in support of the Framework needed to be considered in the context they
were studied. In education research, there is often a desire to cut to the chase and look at absolutes. In
looking at any study for any particular intervention, or at a meta-analysis of multiple studies, there is,
however, no guarantee that what works in one context or environment will work in all others.
The implementation of the Framework will allow Washington STEM, regional STEM networks and other
partners to make informed decisions by applying what has been learned from research, but local
conditions will have a strong influence on how the Framework should be utilized and how successful any
implementation will ultimately be. In one sense, the Framework provides a hypothesis for what works and
implementation will be an opportunity to see what actually works and how STEM education in
Washington can be improved.
Potential Uses
Decision makers and program providers across the state are encouraged to use the Framework to:
•
Target future investments. In an environment of constrained resources, decision makers in the
state must make difficult choices about where to focus future spending. The Framework will help
decision makers identify strategies that: are aligned with best practices, have proven to be
effective in producing outcomes, or hold great promise. As a result, state and philanthropic
entities are expected to yield greater outcomes or a higher “return on investment.”
•
Guide research and development and drive measurement and evaluation. The Framework
represents just the first step in understanding how improvements in STEM education in
Washington can be made. Indicators can be evaluated and refined over time. Promising
strategies can be tested and, when evaluated as effective, developed into large-scale
interventions. As efforts to improve STEM education are undertaken, the Framework will be a
unifying tool for sharing knowledge and the transfer of effective strategies and policies, both
within Washington and among states.
Draft Executive Summary
3
•
Support policy development and advocacy campaigns. The Framework provides an
actionable roadmap for engaged policymakers involved in developing new policies to support
effective strategies, target specific indicators, and drive greater outcomes. As advocacy efforts
for STEM education continue within the state, the Framework can be used to support initiatives
that are aligned with identified best practices and evidence of effectiveness. The Framework also
provides a tool for unifying messages about the importance of STEM education and for
developing consensus regarding the most promising solutions across a variety of users and
audiences.
•
Spur knowledge transfer and impact across the state and country. The Framework provides
a research-based tool to define, lead, and coordinate state level work. At the state level, the
Framework will help to enhance and accelerate the impact of the growing statewide network of
regional STEM networks by increasing members’ ability to test, share, and spread promising
practices against a common Framework. Regional STEM networks will be able to track and
communicate impact using common measures and speak with a unified voice on cross-state
issues of practice and policy. At a national level, similar impacts can be expected across state
and national organizations that use the Framework to design, evaluate, and communicate their
work.
Implementation Strategies
WestEd sees three primary implementation vehicles for the Framework to inform the allocation of
statewide STEM resources, guide programmatic and policy efforts moving forward, and maximize
statewide impact.
•
Governor’s STEM Education Innovation Alliance. Established in June 2013 by E2SHB 1872,
the Education Innovation Alliance (the Alliance) will advise the governor and provide vision and
guidance in support of STEM education initiatives from early learning through postsecondary
education. An important initial task of the Alliance will be to adopt a STEM Framework for Action
and Accountability. Once adopted, the Alliance will develop a STEM Benchmark Report Card (the
Report Card) based on the Framework, with the first Report Card due on January 10, 2014. The
purpose of the Report Card is to monitor progress in aligning strategic plans and activities in
order to prepare students for STEM-related jobs and careers, with the longer-term goal of
improving educational, workforce, and economic outcomes. The governor and his forthcoming
Alliance are well-positioned to move quickly to action and impact by adopting this research- and
stakeholder-validated Framework.
WestEd encourages the following concrete action items:
o
o
o
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Washington STEM: Share the validated Framework and WestEd analysis with the
governor’s STEM Education Innovation Alliance upon the Alliance’s creation.
Governor’s STEM Education Innovation Alliance: Review and adopt the Washington
STEM Framework for Action and Accountability.
Washington STEM and governor’s STEM Education Innovation Alliance: Partner to
create actionable STEM Benchmark Report Cards and supportive implementation tools
and systems, such as state- and regional-level dashboards.
Washington STEM. Washington STEM will rely upon the validated Framework to prioritize its
future investments and efforts and will use its platform as the statewide STEM education
convener to introduce the Framework to a broad set of actors across the state. Washington
STEM will support its growing system of regional STEM networks to use the Framework as a
strategic planning and measurement tool. The regional STEM networks, which are tasked with
improving STEM education and equity in alignment with economic development priorities, should
use the validated Framework to guide their collective impact efforts at the regional level and
facilitate data collection, knowledge sharing, and the transfer of best practices across the state.
Draft Executive Summary
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Washington STEM will also welcome partners around the state to use the Framework in order to
maximize knowledge sharing, the spread and scale of best practices, and statewide impact.
WestEd encourages the following concrete action items:
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Washington STEM: Incorporate the Framework into operating agreements with the
regional STEM networks. Hold a workshop or training session for the regional STEM
networks. Develop supportive implementation tools, such as tools to develop regional
asset maps and gap analyses, identify model programs, and track evaluation data over
time. Post the validated Framework and validation analysis online.
Washington STEM: Consider developing a commitment model through which various
Washington state STEM education partners could make specific, time-bound, and
measureable goals against the Framework and share learnings. The opportunity in
developing such a model is to create an action-oriented and purposeful STEM learning
community in the state.
Regional STEM networks and Washington state STEM education actors: Learn more
about the Framework’s research base, help develop implementation tools, identify model
programs and practices, and collectively spur new and more coordinated research and
development efforts.
State and national STEM organizations. In addition to the uses for the Framework within
Washington state, the Framework will also be provided to other states as a potential model to
organize their work within and across states. Members of the STEMx multi-state network and
other state- and national-level STEM organizations can customize and utilize the Framework to
guide STEM education efforts within their respective states and use the Framework as a multistate tool to promote data collection, knowledge sharing, and the transfer of best practices
around the country.
WestEd encourages the following concrete action items:
•
•
Washington STEM and STEMx: Partner to create an interactive, web-based version of
the Framework that can be shared and utilized by STEMx member states. Collaborate to
create implementation, knowledge sharing, and evaluation tools.
National STEM education community: Learn more about the Framework’s research
base, help develop implementation tools, identify model programs and practices, and
collectively spur new and more coordinated research and development efforts.
Conclusion
The Washington STEM Framework for Action and Accountability is an unprecedented tool for focusing
state-level STEM education investments and efforts on proven practices and the most promising
innovations. The Framework is designed to accelerate equity and results at scale, and at the same time,
will enable the creation of a results-oriented and purposeful STEM education learning community across
Washington state. The state’s economic and civic imperative to act is clear, and with bold leadership and
decisive commitment against the Framework now, Washington state has great potential to serve as a
model for the nation. WestEd welcomes the opportunity to learn with and from your efforts.
A final report and executive summary will be available in early 2014.
Draft Executive Summary
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Appendix A
WASHINGTON STEM FRAMEWORK FOR ACTION + ACCOUNTABILITY
What is the Washington STEM Framework for Action and Accountability?
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•
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Comprehensive roadmap for action in STEM education across Washington
There is no intention that Washington STEM would be active in every space. Rather, the Framework provides a tool to identify and focus
resources on high-impact innovations and solutions, drive alignment of multiple parties, and measure our collective impact.
Created by Washington STEM; validated by the non-profit research and evaluation firm WestEd
It includes:
•
•
•
•
•
Vision: The future we are working to create
Goal: Specific and measurable goal around which various parties can align
Power Indicators: Research-based indicators alongside emergent ones against which we can measure our collective impact
High-Impact Strategies: Evidence-based strategies identified to move the needle on identified power indicators
Policy Set: An enabling policy agenda to support strategies and indicators, ensuring efforts are sustainable and implemented at scale
from cradle to career
Benefits:
•
•
•
Guide and focus Washington STEM’s work on “what works”
o Provides strategic planning and measurement tool for regional STEM Networks
o Informs future investments, research & development, and knowledge generation efforts
o Provides checklist of enabling policies to direct advocacy work
o Supports data measurement and evaluation in order to identify and spread promising innovations
Provide actionable roadmap for engaged policymakers
Rally and align other STEM efforts as a community of practice united by a common goal
Implementation strategies:
•
•
•
Governor’s STEM Education Innovation Alliance leverages the Framework to support the implementation of comprehensive state STEM
legislation, E2SHB1872 (2013)
Washington STEM activates Framework through regional STEM networks and a commitment model with other partners
State and national STEM organizations leverage Framework to support knowledge sharing and accelerate the identification and
transfer of best practices across the country
VISION Washingtonians are prepared and inspired with the science, technology, engineering and math (STEM) skills
necessary to live a life of opportunity and success in the state’s thriving innovation economy and democratic society.
GOAL All Washington high school graduates are STEM literate, prepared and inspired for post-secondary degrees and
certificates, and able to contribute to the demands of a highly-skilled and diverse STEM-driven workforce and society.
BAND
Power
Indicators
HighImpact
Strategies
EARLY LEARNING
Kindergarten readiness
ELEMENTARY
Proficient on college and
career ready standards
MIDDLE
Proficient on college and
career ready standards
Evidence-based
professional learning for
teachers and leaders
Positive attitudes
toward STEM courses
and experiences
Evidence-based
professional learning for
teachers and leaders
Positive attitudes
toward STEM courses
and experiences
Evidence-based
professional learning for
teachers and leaders
Quality in- and out-of
school STEM curricula
Quality in- and out-of
school STEM curricula
Quality in- and out-of
school STEM curricula
Quality in- and out-of
school STEM curricula
High-quality preschool
Student and family
STEM awareness
campaign
Student and family
STEM awareness
campaign
Student and family
STEM awareness
campaign
Student and family
STEM awareness
campaign
Full-day Kindergarten
HIGH
Graduate proficient on
college and career ready
standards
Interest in STEM majors
and careers
Evidence-based
professional learning for
teachers and leaders
STEM industry
internships
Dual credit pathways
Policy Set
Recruit, prepare, and
retain effective STEM
teachers
Include STEM in WA Kids
assessment and
program quality
indicators
Support high-quality
preschool, starting with
low-income students
Adopt rigorous
standards and
assessments (CTE and
core)
Adopt rigorous
standards and
assessments (CTE and
core)
Recruit, prepare, and
retain effective STEM
teachers
Recruit, prepare, and
retain effective STEM
teachers
Incent informal learning
Incent informal learning
Support full day
kindergarten, starting
with low-income
students
Adopt rigorous
standards, assessments,
and graduation
requirements (CTE and
core)
Recruit, prepare, and
retain effective STEM
teachers
Promote dual credit
pathways and
competency-based
credits
STEM POSTSECONDARY
Meet demand for STEM jobs
Earn certificates and degrees
aligned to high-demand STEM
jobs
Credentialing and job skills
training programs
Support services that fit the
needs of diverse populations
Increase capacity and
throughput at colleges and
universities in Washington
Rapid remediation
Regional businesspostsecondary partnerships
Retention and transition support
Accept Smarter Balanced cut
score as ready to take credit
bearing course
Establish production goals to
meet STEM job needs & align
funding
Ease of credit transfer
Appendix B
Washington STEM Framework for Action and Accountability Validation Project
Advisory Committees
Technical Committee
• Alan Burke – OSPI
• Jeff Charbonneau – Zillah School District; 2013
National Teacher of the Year
• Mary Kay Dugan – Battelle
• Stacia Edwards – Battelle
• Sheila Edwards Lange – University of
Washington
• Deepa Gupta – The Boeing Company
• Kevin Haggerty – UW School of Social Work
• Dierdre Holmberg – Pasco School District; TriCities STEM Network
• Michael Lach – University of Chicago, UEL
• Bill Moore – State Board of Community and
Technical Colleges
• Isabel Munoz Colon – City of Seattle Office of
Neighborhoods, Family & Education Levy
• Juan Sanchez – Bill & Melinda Gates
Foundation
• Jim Schmidt – State of Washington Office of
Financial Management, Education Research and
Data Collection
Steering Committee
• Margaret Ashida - STEMx™
• Anne Marie Axworthy – Greater Spokane Inc.
and Spokane STEM Network
• Kareen Borders – Peninsula School District
• Jane Broom – Microsoft
• Dee Chambliss – Educate Texas
• James Dorsey – MESA
• Susan Enfield – Highline Public Schools
• Jeff Estes – Pacific NW National Lab
• Trevor Greene – Association of Washington
School Principals; 2013 National Principal of the
Year
• Mack Hogans – M.L. Hogans, LLC Consulting
Services
• Ed Lazowska – University of Washington
• Kristin Lesseig – Washington State University
• Jim Meadows – Washington Education
Association
• Steve Mullin – Washington Roundtable
• Sharrone Navas – Education and Equity
Coalition
• Mari Offenbecher – Schools Out Washington
• Phil Ohl – Vista Engineering Technologies; TriCities STEM Network
• Eleni Papadakis – WA Workforce Training &
Education Coordinating Board
• Karen Peterson – EdLab Group/National Girls
Collaborative
• Chris Roe – CA STEM Learning Network
• Gene Sharratt – Washington Student
Achievement Council
• Sally Shuler – Washington Informal Science
Education Consortium
• Claus von Zastrow – Change the Equation
Appendix C
Washington STEM Framework for Action and Accountability Validation Project
Draft Literature Review and Citation List
Power Indicator: Early Learning: Kindergarten Readiness
1.
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11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
Barett, W. S., Hustedt, J. T., Robin, K. B., & Schulman, K. L. (2004). The state of preschool: 2004 state
preschool yearbook. New Brunswick, NJ: NIEER
Bodrova, E., & Leong, D. (1996). The Vygotskian approach to early childhood. Columbus, OH: Merrill an
Imprint of Prentice Hall.
Bredekamp, S. (1987). Developmentally appropriate practice in early childhood programs serving children
from birth through age 8. Washington, DC: National Association for the Education of Young Children.
Kleeck, A., & Schuele, C. M. (2010). Historical perspectives on literacy in early childhood. American
Journal of Speech-Language Pathology, 19, 341-355.
Nance, R. (2009). The importance of early childhood education. Quest Paper, 2-19.
Nicolopoulou, A. (2010). The alarming disappearance of play from early childhood education. Human
Development, 53, 1-4.
Stone, S. J. (1995). Wanted: Advocates for play in the primary grades. Young Children, 50 (6), 45-54.
Duhley, E. (2011). Who Benefits from Kindergarten? Evidence from the introduction of state subsidization.
Educational Evaluation and Policy Analysis, 33(1), 3-22.
Gormley, W. T., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of the universal pre-k on
cognitive development. Developmental Psychology, 41(6), 872.
NICHD ECCRN. (2002). Child care structure >process> outcome: Direct and indirect effects of child-care
quality on young children’s development. Psychological Science, 13, 199–206.
Phillips, D., Mekos, D., Scarr, S., McCartney, K., & Abott-Shim, M. (2001). Within and beyond the
classroom door: Assessing quality in child care centers. Early Childhood Research Quarterly, 15, 475–
496.
Ripple, C. H., Gilliam, W. S., Chanana, N., & Zigler, E. (1999). Will fifty cooks spoil the broth? American
Psychologist, 54, 327–343.
Smith, T., Kleiner, A., Parsad, B., Farris, E., & Green, B. (2003). Prekindergarten in US Public Schools.
Washington, DC: US Department of Education, National Center for Education Statistics.
Barnett, W. S., Hustedt, J. T., Robin, K. B., & Schulman, K. L. (2004). The state of preschool: 2004 state
preschool yearbook. New Brunswick, NJ: NIEER.
Schulman, K., Blank, H., & Ewen, D. (1999). Seeds of Success: State Prekindergarten Initiatives 1998–
1999. Washington, DC: Children’s Defense Fund.
Magnuson, K. A., Meyers, M., Ruhm, C., & Waldfogel, J. (2004). Inequality in preschool education and
school readiness. American Educational Research Journal, 41, 115–157.
Magnuson, K. A., Ruhm, C., & Waldfogel, J. (2007). Does prekindergarten improve school preparation
and performance? Economics of Education Review, 26(1), 33-51.
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., Pagani, L. S., &
Feinstein, L. (2007). Meta-analysis of research on school readiness and later achievement.Developmental
Psychology, 43(6), 1428-1446. doi: 10.1037/0012-1649.43.6.1428
Darling-Hammond, L., Chung Wei, R., Andree, A., & Richardson, N. (2009). Professional learning in the
learning profession: A status report on teacher development in the United States and abroad. Oxford, OH:
National Staff Development Council.
Corcoran, T., McVay, S., & Riordan, K. (2003). Getting it right: The MISE approach to professional
development. Philadelphia, PA: Consortium for Policy Research in Education.
French, V. W. (1997). Teachers must be learners, too: Professional development and national teaching
standards. NASSP bulletin, 81(585), 38-44.
Truesdale, W. T. (2003). The implementation of peer coaching on the transferability of staff development
to classroom practice in two selected Chicago public elementary schools. Dissertation Abstracts
International, 64 (11), 3923.
Knight, J. & Cornett, J. (2009). Studying the impact of instructional coaching. Lawrence, KS: Kansas
Coaching Project for the Center on Research on Learning.
van Zee, E. H., Hammer, D., Bell, M., Roy, P., & Peter, J. (2005). Learning and teaching science as
inquiry: A case study of elementary school teachers' investigations of light. Science Education, 89(6),
1007-1042.
1
25. Richardson, V. (1998). How teachers change. Focus on Basics, 2(C), 1-10.
26. Goldberg, J. S., & Cole, B. R. (2002). Quality management in education: building excellence and equity in
student performance. Quality Management Journal, 9(4), 8-22.
27. Bagley, W., Rice, M. L., & Wilson, E. K. (2001). Transforming learning with technology: Lessons from the
field. Journal of Technology and Teacher Education, 9(2), 211-230.
28. Black, S. (2001). A Lifeboat for New Teachers. American School Board Journal, 188(9), 46-48.
29. Licklider, B.L. (1997). Breaking ranks: Changing the in-service institution. NASSP Bulletin, 81(Jan.), 9-22.
30. Snow-Renner, R., & Lauer, P. A. (2005). Professional development analysis. Retrieved from Mid-continent
Research for Education and Learning website: http://www. mcrel.
org/PDF/ProfessionalDevelopment/5051IR_Prof_dvlpmt_analy sis. pdf# search%= 22Professional%
20development% 20analysis, 22.
31. Carpenter, T. P., Fennema, E., Peterson, P. L., Chiang, C. P., & Loef, M. (1989). Using knowledge of
children’s mathematics thinking in classroom teaching: An experimental study. American Educational
Research Journal,26(4), 499-531.
32. Cohen, D. K., & Hill, H. C. (2001). Learning policy: When state education reform works. Yale University
Press.
33. Garet, M. S., Porter, A. C., Desimone, L., Birman, B. F., & Yoon, K. S. (2001). What makes professional
development effective? Results from a national sample of teachers. American educational research
journal, 38(4), 915-945.
34. Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional
development on teachers’ instruction: Results from a three-year longitudinal study. Educational evaluation
and policy analysis, 24(2), 81-112.
35. Penuel, W. R., Fishman, B. J., Yamaguchi, R., & Gallagher, L. P. (2007). What makes professional
development effective? Strategies that foster curriculum implementation. American Educational Research
Journal, 44(4), 921-958.
36. Saxe, G., Gearhart, M., & Nasir, N. i. 2001'Enhancing Students' Understanding of Mathematics: A Study
of Three Contrasting Approaches to Professional Support'. Journal of Mathematics Teacher
Education, 4(1), 55-79.
37. Supovitz, J. A., Mayer, D. P., & Kahle, J. B. (2000). Promoting inquiry-based instructional practice: The
longitudinal impact of professional development in the context of systemic reform. Educational
Policy, 14(3), 331-356.
38. Blank, R. K., de las Alas, N., & Smith, C. (2007). Analysis of the quality of professional development
programs for mathematics and science teachers: Findings from a crossstate study. Washington, DC:
Council of Chief State School Officers. Retrieved February, 29, 2008
39. Lieberman, A., & Wood, D. (2001). When teachers write: Of networks and learning. Teachers caught in
the action: Professional development that matters, 174-187.
40. Marek, E. A., & Methven, S. B. (1991). Effects of the learning cycle upon student and classroom teacher
performance. Journal of Research in Science Teaching, 28(1), 41-53.
41. Wenglinsky, H. (2002). The Link between Teacher Classroom Practices and Student Academic
Performance. Education policy analysis archives, 10(12), n12.
42. McGill-Franzen, A., Allington, R. L., Yokoi, L., & Brooks, G. (1999). Putting books in the classroom seems
necessary but not sufficient. The Journal of Educational research, 93(2), 67-74.
Power Indicator: Elementary School: Proficiency on College and Career Ready Standards
1.
2.
3.
4.
5.
6.
7.
National Research Council. Successful K-12 STEM Education: Identifying Effective Approaches in
Science, Technology, Engineering, and Mathematics. Washington, DC: The National Academies Press,
2011.
National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National
Mathematics Advisory Panel. Washington, DC: U.S. Department of Education. Available at:
http://www2.ed.gov/about/bdscomm/list/mathpanel/report/finalreport.pdf.
National Research Council. (1999). How people learn: Brain, mind, experience, and school. Committee on
Developments in the Science of Learning. J.D. Bransford, A.L. Brown, and R.R. Cocking (Eds.).
Washington, DC:
National Academy Press.National Research Council. (2001). Adding it up: Helping children learn
mathematics. Washington, DC: National Academy Press.
National Research Council. (2005). How students learn: Mathematics in the classroom. Washington, DC:
The
National Academies Press.
National Research Council. (2007). Taking science to school: Learning and teaching science in grades K2
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
8. Washington, DC: The National Academies Press.
National Research Council. (2009a). Engineering in K-12 education: Understanding the status and
improving the prospects. Washington, DC: The National Academies Press.
National Research Council. (2009b). Learning science in informal environments: People, places, and
pursuits.
Washington, DC: The National Academies Press.
National Research Council. A Framework for K-12 Science Education: Practices, Crosscutting Concepts,
and Core Ideas. Washington, DC: The National Academies Press, 2012.
National Research Council. Next Generation Science Standards: For States, By States. Washington, DC:
The National Academies Press, 2013.
Common Core State Standards Initiative. (2010). Common core state standards for mathematics.
Available
at: http://www.corestandards.org/assets/CCSSIMath%20Standards.pdf
International Society for Technology in Education (ISTE). (2008). National education technology
standards for teachers, 2nd Ed. Available from http://www.iste.org/standards/nets-for-teachers/nets-forteachers-2008.aspx.
International Technology Education Association (ITEA). (2007). Standards for technological literacy:
Content for the study of technology (3rd Ed.). Reston, VA: ITEA.
International Technology Education Association (ITEA). (2003). Advancing excellence in technological
literacy: Student assessment, professional development, and program standards. Reston, VA: ITEA.
National Assessment Governing Board. (2008). Mathematics framework for the 2009 National
Assessment of Educational Progress. Washington, DC: Author.
National Assessment Governing Board. (2008). Science framework for the 2009 National Assessment of
Educational Progress. Washington, DC: Author.
National Council of Teachers of Mathematics (NCTM). (2000). Principles & standards for school
mathematics. Reston, VA: NCTM.
National Governors Association Center for Best Practices (NGA Center) & Council of Chief State School
Officers (CCSSO). (2010). Common core states standards. Washington, DC: Author
National Research Council (NRC). (1996). The national science education standards. Washington, DC:
National Academy Press
American Association for the Advancement of Science (AAAS). (1998). Blueprints for Reform: Science,
Mathematics, and Technology Education. New York: Oxford University Press.
College Board. (2009). Science: College Boards standards for college success. Available from
http://professionals.collegeboard.com/profdownload/cbscs-science-standards-2009.pdf.
National Academy of Engineering & National Research Council. (2006). Tech tally: Approaches to
assessing technological literacy. Washington, D.C.: National Academies Press.
National Academy of Engineering & National Research Council. (2002). Technically speaking: Why all
Americans need to know more about technology. Washington, D.C.: National Academy Press.
National Assessment Governing Board. (Pre-Publication). Technology and Engineering Literacy
Framework for the 2014 National Assessment of Educational Progress. Washington, DC: Author.
Partnership for 21st Century Skills. (2009). Framework for 21st century learning. Washington, DC:
Author.
American Association for the Advancement of Science (AAAS). (1993). Project 2061: Benchmarks for
science literacy. New York: Oxford University Press.
National Research Council. A Framework for K-12 Science Education: Practices, Crosscutting Concepts,
and Core Ideas. Washington, DC: The National Academies Press, 2012.
U.S. Department of Education. (2010). A blueprint for reform: The reauthorization of the elementary and
secondary education act. Available from: www2.ed.gov/policy/elsec/leg/blueprint.
Tweed, A. (2009) Designing effective science instruction: What works in science classrooms. NSTA
Press.
Rose, S., Schimke, K., & Education Commission of the, S. (2012). Third Grade Literacy Policies:
Identification, Intervention, Retention. Education Commission Of The States.
Hernandez, D. Double Jeopardy: How Third-Grade Reading Skills and Poverty Influence High School
Graduation (Baltimore: The Annie E. Casey Foundation, 2011).
Leila Feister, EARLY WARNING!: Why Reading by the End of Third Grade Matters. 2010. Annie E. Casey
Foundation: 7.
Barth, J. (2012). READING TO LEARN. http://www.aradvocates.org/assets/PDFs/K-12Education/Reading-to-Learn.pdf
Lesnick, J. (2006). A mixed-method multi-level randomized evaluation of the implementation and impact of
an audio-assisted reading program for struggling readers. (Unpublished doctoral dissertation).
Philadelphia: University of Pennsylvania.
3
38. Blank, R. K., de las Alas, N., & Smith, C. (2007). Analysis of the quality of professional development
programs for mathematics and science teachers: Findings from a crossstate study. Washington, DC:
Council of Chief State School Officers. Retrieved February, 29, 2008
39. Darling-Hammond, L., Chung Wei, R., Andree, A., & Richardson, N. (2009). Professional learning in the
learning profession: A status report on teacher development in the United States and abroad. Oxford, OH:
National Staff Development Council.
40. Corcoran, T., McVay, S., & Riordan, K. (2003). Getting it right: The MISE approach to professional
development. Philadelphia, PA: Consortium for Policy Research in Education.
41. French, V. W. (1997). Teachers must be learners, too: Professional development and national teaching
standards. NASSP bulletin, 81(585), 38-44.
42. Truesdale, W. T. (2003). The implementation of peer coaching on the transferability of staff development
to classroom practice in two selected Chicago public elementary schools. Dissertation Abstracts
International, 64 (11), 3923.
43. Knight, J. & Cornett, J. (2009). Studying the impact of instructional coaching. Lawrence, KS: Kansas
Coaching Project for the Center on Research on Learning.
44. van Zee, E. H., Hammer, D., Bell, M., Roy, P., & Peter, J. (2005). Learning and teaching science as
inquiry: A case study of elementary school teachers' investigations of light. Science Education, 89(6),
1007-1042.
45. Richardson, V. (1998). How teachers change. Focus on Basics, 2(C), 1-10.
46. Goldberg, J. S., & Cole, B. R. (2002). Quality management in education: building excellence and equity in
student performance. Quality Management Journal, 9(4), 8-22.
47. Bagley, W., Rice, M. L., & Wilson, E. K. (2001). Transforming learning with technology: Lessons from the
field. Journal of Technology and Teacher Education, 9(2), 211-230.
48. Black, S. (2001). A Lifeboat for New Teachers. American School Board Journal, 188(9), 46-48.
49. Licklider, B.L. (1997). Breaking ranks: Changing the in-service institution. NASSP Bulletin, 81(Jan.), 9-22.
50. Snow-Renner, R., & Lauer, P. A. (2005). Professional development analysis. Retrieved from Mid-continent
Research for Education and Learning website: http://www. mcrel.
org/PDF/ProfessionalDevelopment/5051IR_Prof_dvlpmt_analy sis. pdf# search%= 22Professional%
20development% 20analysis, 22.
51. Carpenter, T. P., Fennema, E., Peterson, P. L., Chiang, C. P., & Loef, M. (1989). Using knowledge of
children’s mathematics thinking in classroom teaching: An experimental study. American Educational
Research Journal,26(4), 499-531.
52. Cohen, D. K., & Hill, H. C. (2001). Learning policy: When state education reform works. Yale University
Press.
53. Garet, M. S., Porter, A. C., Desimone, L., Birman, B. F., & Yoon, K. S. (2001). What makes professional
development effective? Results from a national sample of teachers. American educational research
journal, 38(4), 915-945.
54. Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional
development on teachers’ instruction: Results from a three-year longitudinal study. Educational evaluation
and policy analysis, 24(2), 81-112.
55. Penuel, W. R., Fishman, B. J., Yamaguchi, R., & Gallagher, L. P. (2007). What makes professional
development effective? Strategies that foster curriculum implementation. American Educational Research
Journal, 44(4), 921-958.
56. Saxe, G., Gearhart, M., & Nasir, N. i. 2001'Enhancing Students' Understanding of Mathematics: A Study
of Three Contrasting Approaches to Professional Support'. Journal of Mathematics Teacher
Education, 4(1), 55-79.
57. Supovitz, J. A., Mayer, D. P., & Kahle, J. B. (2000). Promoting inquiry-based instructional practice: The
longitudinal impact of professional development in the context of systemic reform. Educational
Policy, 14(3), 331-356.
58. Lieberman, A., & Wood, D. (2001). When teachers write: Of networks and learning. Teachers caught in
the action: Professional development that matters, 174-187.
59. Marek, E. A., & Methven, S. B. (1991). Effects of the learning cycle upon student and classroom teacher
performance. Journal of Research in Science Teaching, 28(1), 41-53.
60. Wenglinsky, H. (2002). The Link between Teacher Classroom Practices and Student Academic
Performance. Education policy analysis archives, 10(12), n12.
61. McGill-Franzen, A., Allington, R. L., Yokoi, L., & Brooks, G. (1999). Putting books in the classroom seems
necessary but not sufficient. The Journal of Educational research, 93(2), 67-74.
62. Boaler, J., Wiliam, D., & Brown, M. (2000). Students' experiences of ability grouping-disaffection,
polarization and the construction of failure. British Educational Research Journal, 26(5), 631-648.
63. Boaler, J. (2002). Learning from teaching: Exploring the relationship between reform curriculum and
equity. Journal for Research in Mathematics Education, 239-258.
4
64. Hill, H. C., & Ball, D. L. (2004). Learning mathematics for teaching: Results from California's mathematics
professional development institutes. Journal for research in mathematics education, 330-351.
65. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on
student achievement. American educational research journal, 42(2), 371-406.
66. Rose, S., & Education Commission of the, S. (2012). Third Grade Reading Policies. Education
Commission Of The States.
Power Indicator: Elementary School: Positive Attitudes Toward STEM Courses and Experiences
1.
Tyler-Wood, Tandra, Gerald Knezek, and Rhonda Christensen. (2010). "Instruments for assessing interest
in STEM content and careers." Journal of Technology and Teacher Education 18.2: 345-368.
2. Beggs, J. M., Bantham, J. H., & Taylor, S. (2008). Distinguishing the factors influencing college students’
choice of a major. College Student Journal, 42, 381-394.
3. DeMarie, D., & Aloise-Young, P. A. (2003). College students’ interest in their major. College Student
Journal, 37, 462-469.
4. Hall, C., Dickerson, J., Batts, D., Kauffmann, P., & Bosse, M. (2011). “Are we missing opportunities to
encourage interest in STEM fields?” Journal of Technology Education 25.1.
5. House, J. D. (2000). Academic background and self-beliefs as predictors of student grade performance in
science, engineering, and mathematics. International Journal of Industrial Media, 27, 207-220.
6. Kuechler, W. L., McLeod, A., & Simkin, M. G. (2009). Why don’t more students major in IS? Decision
Sciences Journal of Innovative Education, 7, 463-488.
7. Malgwi, C. A., Howe, M. A., & Burnaby, P. A. (2005). Influences on students' choice of college
major. Journal of Education for Business, 275-282.
8. My College Options and STEMconnector. (2012). Where are the STEM Students? What are their Career
Interests? Where are the STEM Jobs?
9. Schwartz, B. (2004). The tyranny of choice. Chronicle of Higher Education, 50, B6-B8.
10. Tan, L. M., & Laswad, F. (2009). Understanding students’ choice of academic majors: A longitudinal
analysis. Accounting Education, 18, 233-253.
11. National Research Council. Learning Science in Informal Environments: People, Places, and Pursuits.
Washington, DC: The National Academies Press, 2009.
Power Indicator: Middle School: Proficiency on College and Career Ready Standards
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
International Society for Technology in Education (ISTE). (2008). National education technology
standards for teachers, 2nd Ed. Available from http://www.iste.org/standards/nets-for-teachers/nets-forteachers-2008.aspx.
International Technology Education Association (ITEA). (2007). Standards for technological literacy:
Content for the study of technology (3rd Ed.). Reston, VA: ITEA.
International Technology Education Association (ITEA). (2003). Advancing excellence in technological
literacy: Student assessment, professional development, and program standards. Reston, VA: ITEA.
National Assessment Governing Board. (2008). Mathematics framework for the 2009 National
Assessment of Educational Progress. Washington, DC: Author.
National Assessment Governing Board. (2008). Science framework for the 2009 National Assessment of
Educational Progress. Washington, DC: Author.
National Council of Teachers of Mathematics (NCTM). (2000). Principles & standards for school
mathematics. Reston, VA: NCTM.
National Governors Association Center for Best Practices (NGA Center) & Council of Chief State School
Officers (CCSSO). (2010). Common core states standards. Washington, DC: Author
National Research Council (NRC). (1996). The national science education standards. Washington, DC:
National Academy Press
American Association for the Advancement of Science (AAAS). (1998). Blueprints for Reform: Science,
Mathematics, and Technology Education. New York: Oxford University Press.
College Board. (2009). Science: College Boards standards for college success. Available from
http://professionals.collegeboard.com/profdownload/cbscs-science-standards-2009.pdf.
National Academy of Engineering & National Research Council. (2006). Tech tally: Approaches to
assessing technological literacy. Washington, D.C.: National Academies Press.
National Academy of Engineering & National Research Council. (2002). Technically speaking: Why all
Americans need to know more about technology. Washington, D.C.: National Academy Press.
National Assessment Governing Board. (Pre-Publication). Technology and Engineering Literacy
Framework for the 2014 National Assessment of Educational Progress. Washington, DC: Author.
5
14. Partnership for 21st Century Skills. (2009). Framework for 21st century learning. Washington, DC:
Author.
15. American Association for the Advancement of Science (AAAS). (1993). Project 2061: Benchmarks for
science literacy. New York: Oxford University Press.
16. National Research Council. A Framework for K-12 Science Education: Practices, Crosscutting Concepts,
and Core Ideas. Washington, DC: The National Academies Press, 2012.
17. U.S. Department of Education. (2010). A blueprint for reform: The reauthorization of the elementary and
secondary education act. Available from: www2.ed.gov/policy/elsec/leg/blueprint.
18. Tweed, A. (2009) Designing effective science instruction: What works in science classrooms. NSTA
Press.
19. ACT. (2008). The Forgotten Middle: Ensuring that All Students Are on Target for College and Career
Readiness before High School. ACT.
20. National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National
Mathematics Advisory Panel. US Department of Education.
21. Davis, Denise (2010). College Success for all Students: An Investigation of Early Warning Indicators of
College Readiness. Denton, Texas. UNT Digital Library.
http://digital.library.unt.edu/ark:/67531/metadc33141/.
22. Hoffman, N., Vargas, J., Venezia, A. & Miller, M. (2007). Minding the gap: Why integrating high school
with college makes sense and how to do it. Massachusetts: Harvard Education Press.
23. Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college.
Washington, DC: U.S. Department of Education.
24. Spielhagen, F. R. (2006). Closing the achievement gap in math: The long-term effects of eighth-grade
algebra. Journal of Advanced Academics, 18, 34–9.
25. Schmidt, W. (2003) Too little, too late: American high schools in an international context. In D. Ravitch
(Ed.), Brookings papers on edu- cation policy (pp. 253–278). Baltimore: Brookings Institute Press.
26. Greene, B. D., Herman, M., Haury, D. L., & ERIC Clearinghouse for Science, M. H. (2000). TIMSS: What
Have We Learned about Math and Science Teaching? ERIC Digest.
27. McCoy, L. P. (2005). Effect of demographic and personal variables on achievement in eighth-grade
algebra. The Journal of Educational Research, 98(3), 131-135.
28. Oakes, J., & Lipton, M. (1999). Teaching to change the world. Boston: McGraw-Hill College.
29. Moses, R. P., & Cobb Jr, C. (2001). Organizing Algebra: The Need To Voice a Demand. Social Policy, 4,
12.
30. Singh, K., & Granville, M. (1999). Factors that Affect Enrollment in Eighth Grade Algebra for AfricanAmerican Students. Research in middle level education quarterly, 22(2), 57-73.
31. Blank, R. K., de las Alas, N., & Smith, C. (2007). Analysis of the quality of professional development
programs for mathematics and science teachers: Findings from a crossstate study. Washington, DC:
Council of Chief State School Officers. Retrieved February, 29, 2008
32. Darling-Hammond, L., Chung Wei, R., Andree, A., & Richardson, N. (2009). Professional learning in the
learning profession: A status report on teacher development in the United States and abroad. Oxford, OH:
National Staff Development Council.
33. Corcoran, T., McVay, S., & Riordan, K. (2003). Getting it right: The MISE approach to professional
development. Philadelphia, PA: Consortium for Policy Research in Education.
34. French, V. W. (1997). Teachers must be learners, too: Professional development and national teaching
standards. NASSP bulletin, 81(585), 38-44.
35. Truesdale, W. T. (2003). The implementation of peer coaching on the transferability of staff development
to classroom practice in two selected Chicago public elementary schools. Dissertation Abstracts
International, 64 (11), 3923.
36. Knight, J. & Cornett, J. (2009). Studying the impact of instructional coaching. Lawrence, KS: Kansas
Coaching Project for the Center on Research on Learning.
37. van Zee, E. H., Hammer, D., Bell, M., Roy, P., & Peter, J. (2005). Learning and teaching science as
inquiry: A case study of elementary school teachers' investigations of light. Science Education, 89(6),
1007-1042.
38. Richardson, V. (1998). How teachers change. Focus on Basics, 2(C), 1-10.
39. Goldberg, J. S., & Cole, B. R. (2002). Quality management in education: building excellence and equity in
student performance. Quality Management Journal, 9(4), 8-22.
40. Bagley, W., Rice, M. L., & Wilson, E. K. (2001). Transforming learning with technology: Lessons from the
field. Journal of Technology and Teacher Education, 9(2), 211-230.
41. Black, S. (2001). A Lifeboat for New Teachers. American School Board Journal, 188(9), 46-48.
42. Licklider, B.L. (1997). Breaking ranks: Changing the in-service institution. NASSP Bulletin, 81(Jan.), 9-22.
6
43. Snow-Renner, R., & Lauer, P. A. (2005). Professional development analysis. Retrieved from Mid-continent
Research for Education and Learning website: http://www. mcrel.
org/PDF/ProfessionalDevelopment/5051IR_Prof_dvlpmt_analy sis. pdf# search%= 22Professional%
20development% 20analysis, 22.
44. Carpenter, T. P., Fennema, E., Peterson, P. L., Chiang, C. P., & Loef, M. (1989). Using knowledge of
children’s mathematics thinking in classroom teaching: An experimental study. American Educational
Research Journal,26(4), 499-531.
45. Cohen, D. K., & Hill, H. C. (2001). Learning policy: When state education reform works. Yale University
Press.
46. Garet, M. S., Porter, A. C., Desimone, L., Birman, B. F., & Yoon, K. S. (2001). What makes professional
development effective? Results from a national sample of teachers. American educational research
journal, 38(4), 915-945.
47. Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional
development on teachers’ instruction: Results from a three-year longitudinal study. Educational evaluation
and policy analysis, 24(2), 81-112.
48. Penuel, W. R., Fishman, B. J., Yamaguchi, R., & Gallagher, L. P. (2007). What makes professional
development effective? Strategies that foster curriculum implementation. American Educational Research
Journal, 44(4), 921-958.
49. Saxe, G., Gearhart, M., & Nasir, N. i. 2001'Enhancing Students' Understanding of Mathematics: A Study
of Three Contrasting Approaches to Professional Support'. Journal of Mathematics Teacher
Education, 4(1), 55-79.
50. Supovitz, J. A., Mayer, D. P., & Kahle, J. B. (2000). Promoting inquiry-based instructional practice: The
longitudinal impact of professional development in the context of systemic reform. Educational
Policy, 14(3), 331-356.
51. Lieberman, A., & Wood, D. (2001). When teachers write: Of networks and learning. Teachers caught in
the action: Professional development that matters, 174-187.
52. Marek, E. A., & Methven, S. B. (1991). Effects of the learning cycle upon student and classroom teacher
performance. Journal of Research in Science Teaching, 28(1), 41-53.
53. Wenglinsky, H. (2002). The Link between Teacher Classroom Practices and Student Academic
Performance. Education policy analysis archives, 10(12), n12.
54. McGill-Franzen, A., Allington, R. L., Yokoi, L., & Brooks, G. (1999). Putting books in the classroom seems
necessary but not sufficient. The Journal of Educational research, 93(2), 67-74.
55. Boaler, J., Wiliam, D., & Brown, M. (2000). Students' experiences of ability grouping-disaffection,
polarization and the construction of failure. British Educational Research Journal, 26(5), 631-648.
56. Boaler, J. (2002). Learning from teaching: Exploring the relationship between reform curriculum and
equity. Journal for Research in Mathematics Education, 239-258.
57. Hill, H. C., & Ball, D. L. (2004). Learning mathematics for teaching: Results from California's mathematics
professional development institutes. Journal for research in mathematics education, 330-351.
58. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on
student achievement. American educational research journal, 42(2), 371-406.
59. Edmonds, J. (2010). Study of the efficacy of North Carolina’s early college high school model. Paper
presented at the meeting of Jobs for the Future, Atlanta, GA.
60. National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics.
Reston, VA: Author.
61. Atweh, B., Bleicher, R., & Cooper, T. (1998). The construction of the social context of mathematics classrooms: A sociolinguistic analysis. Journal for Research in Mathematics Education, 29, 63-82.
62. Lubienski, S. (2002). A closer look at Black-White mathematics gaps: Intersections of race and SES in
NAEP achievement and instructional practices data. Journal of Negro Education, 71 (4), 269-87.
63. Schiller, K. S., & Muller, C. (2003). Raising the bar and equity? Effects of state high school graduation
requirements and accountability policies on students' mathematics course taking. Educational Evaluation
and Policy Analysis, 25(3), 299-318.
Power Indicator: Middle School: Positive Attitudes Toward STEM Courses and Experiences
1.
2.
3.
Tyler-Wood, Tandra, Gerald Knezek, and Rhonda Christensen. (2010). "Instruments for assessing interest
in STEM content and careers." Journal of Technology and Teacher Education 18.2: 345-368.
Beggs, J. M., Bantham, J. H., & Taylor, S. (2008). Distinguishing the factors influencing college students’
choice of a major. College Student Journal, 42, 381-394.
DeMarie, D., & Aloise-Young, P. A. (2003). College students’ interest in their major. College Student
Journal, 37, 462-469.
7
4.
Hall, C., Dickerson, J., Batts, D., Kauffmann, P., & Bosse, M. (2011). “Are we missing opportunities to
encourage interest in STEM fields?” Journal of Technology Education 25.1.
5. House, J. D. (2000). Academic background and self-beliefs as predictors of student grade performance in
science, engineering, and mathematics. International Journal of Industrial Media, 27, 207-220.
6. Kuechler, W. L., McLeod, A., & Simkin, M. G. (2009). Why don’t more students major in IS? Decision
Sciences Journal of Innovative Education, 7, 463-488.
7. Malgwi, C. A., Howe, M. A., & Burnaby, P. A. (2005). Influences on students' choice of college
major. Journal of Education for Business, 275-282.
8. My College Options and STEMconnector. (2012). Where are the STEM Students? What are their Career
Interests? Where are the STEM Jobs?
9. Schwartz, B. (2004). The tyranny of choice. Chronicle of Higher Education, 50, B6-B8.
10. Tan, L. M., & Laswad, F. (2009). Understanding students’ choice of academic majors: A longitudinal
analysis. Accounting Education, 18, 233-253.
11. National Research Council. Learning Science in Informal Environments: People, Places, and Pursuits.
Washington, DC: The National Academies Press, 2009.
Power Indicator: High School: Proficiency on College and Career Ready Standards
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
International Society for Technology in Education (ISTE). (2008). National education technology
standards for teachers, 2nd Ed. Available from http://www.iste.org/standards/nets-for-teachers/nets-forteachers-2008.aspx.
International Technology Education Association (ITEA). (2007). Standards for technological literacy:
Content for the study of technology (3rd Ed.). Reston, VA: ITEA.
International Technology Education Association (ITEA). (2003). Advancing excellence in technological
literacy: Student assessment, professional development, and program standards. Reston, VA: ITEA.
National Assessment Governing Board. (2008). Mathematics framework for the 2009 National
Assessment of Educational Progress. Washington, DC: Author.
National Assessment Governing Board. (2008). Science framework for the 2009 National Assessment of
Educational Progress. Washington, DC: Author.
National Council of Teachers of Mathematics (NCTM). (2000). Principles & standards for school
mathematics. Reston, VA: NCTM.
National Governors Association Center for Best Practices (NGA Center) & Council of Chief State School
Officers (CCSSO). (2010). Common core states standards. Washington, DC: Author
National Research Council (NRC). (1996). The national science education standards. Washington, DC:
National Academy Press
American Association for the Advancement of Science (AAAS). (1998). Blueprints for Reform: Science,
Mathematics, and Technology Education. New York: Oxford University Press.
College Board. (2009). Science: College Boards standards for college success. Available from
http://professionals.collegeboard.com/profdownload/cbscs-science-standards-2009.pdf.
National Academy of Engineering & National Research Council. (2006). Tech tally: Approaches to
assessing technological literacy. Washington, D.C.: National Academies Press.
National Academy of Engineering & National Research Council. (2002). Technically speaking: Why all
Americans need to know more about technology. Washington, D.C.: National Academy Press.
National Assessment Governing Board. (Pre-Publication). Technology and Engineering Literacy
Framework for the 2014 National Assessment of Educational Progress. Washington, DC: Author.
Partnership for 21st Century Skills. (2009). Framework for 21st century learning. Washington, DC:
Author.
American Association for the Advancement of Science (AAAS). (1993). Project 2061: Benchmarks for
science literacy. New York: Oxford University Press.
National Research Council. A Framework for K-12 Science Education: Practices, Crosscutting Concepts,
and Core Ideas. Washington, DC: The National Academies Press, 2012.
U.S. Department of Education. (2010). A blueprint for reform: The reauthorization of the elementary and
secondary education act. Available from: www2.ed.gov/policy/elsec/leg/blueprint.
Tweed, A. (2009) Designing effective science instruction: What works in science classrooms. NSTA
Press.
ACT. (2008). The Forgotten Middle: Ensuring that All Students Are on Target for College and Career
Readiness before High School. ACT.
National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National
Mathematics Advisory Panel. US Department of Education.
8
21. Davis, Denise (2010). College Success for all Students: An Investigation of Early Warning Indicators of
College Readiness. Denton, Texas. UNT Digital Library.
http://digital.library.unt.edu/ark:/67531/metadc33141/.
22. Hoffman, N., Vargas, J., Venezia, A. & Miller, M. (2007). Minding the gap: Why integrating high school
with college makes sense and how to do it. Massachusetts: Harvard Education Press.
23. Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college.
Washington, DC: U.S. Department of Education.
24. Spielhagen, F. R. (2006). Closing the achievement gap in math: The long-term effects of eighth-grade
algebra. Journal of Advanced Academics, 18, 34–9.
25. Schmidt, W. (2003) Too little, too late: American high schools in an international context. In D. Ravitch
(Ed.), Brookings papers on edu- cation policy (pp. 253–278). Baltimore: Brookings Institute Press.
26. Greene, B. D., Herman, M., Haury, D. L., & ERIC Clearinghouse for Science, M. H. (2000). TIMSS: What
Have We Learned about Math and Science Teaching? ERIC Digest.
27. McCoy, L. P. (2005). Effect of demographic and personal variables on achievement in eighth-grade
algebra. The Journal of Educational Research, 98(3), 131-135.
28. Oakes, J., & Lipton, M. (1999). Teaching to change the world. Boston: McGraw-Hill College.
29. Moses, R. P., & Cobb Jr, C. (2001). Organizing Algebra: The Need To Voice a Demand. Social Policy, 4,
12.
30. Singh, K., & Granville, M. (1999). Factors that Affect Enrollment in Eighth Grade Algebra for AfricanAmerican Students. Research in middle level education quarterly, 22(2), 57-73.
31. Blank, R. K., de las Alas, N., & Smith, C. (2007). Analysis of the quality of professional development
programs for mathematics and science teachers: Findings from a crossstate study. Washington, DC:
Council of Chief State School Officers. Retrieved February, 29, 2008
32. Darling-Hammond, L., Chung Wei, R., Andree, A., & Richardson, N. (2009). Professional learning in the
learning profession: A status report on teacher development in the United States and abroad. Oxford, OH:
National Staff Development Council.
33. Corcoran, T., McVay, S., & Riordan, K. (2003). Getting it right: The MISE approach to professional
development. Philadelphia, PA: Consortium for Policy Research in Education.
34. French, V. W. (1997). Teachers must be learners, too: Professional development and national teaching
standards. NASSP bulletin, 81(585), 38-44.
35. Truesdale, W. T. (2003). The implementation of peer coaching on the transferability of staff development
to classroom practice in two selected Chicago public elementary schools. Dissertation Abstracts
International, 64 (11), 3923.
36. Knight, J. & Cornett, J. (2009). Studying the impact of instructional coaching. Lawrence, KS: Kansas
Coaching Project for the Center on Research on Learning.
37. van Zee, E. H., Hammer, D., Bell, M., Roy, P., & Peter, J. (2005). Learning and teaching science as
inquiry: A case study of elementary school teachers' investigations of light. Science Education, 89(6),
1007-1042.
38. Richardson, V. (1998). How teachers change. Focus on Basics, 2(C), 1-10.
39. Goldberg, J. S., & Cole, B. R. (2002). Quality management in education: building excellence and equity in
student performance. Quality Management Journal, 9(4), 8-22.
40. Bagley, W., Rice, M. L., & Wilson, E. K. (2001). Transforming learning with technology: Lessons from the
field. Journal of Technology and Teacher Education, 9(2), 211-230.
41. Black, S. (2001). A Lifeboat for New Teachers. American School Board Journal, 188(9), 46-48.
42. Licklider, B.L. (1997). Breaking ranks: Changing the in-service institution. NASSP Bulletin, 81(Jan.), 9-22.
43. Snow-Renner, R., & Lauer, P. A. (2005). Professional development analysis. Retrieved from Mid-continent
Research for Education and Learning website: http://www. mcrel.
org/PDF/ProfessionalDevelopment/5051IR_Prof_dvlpmt_analy sis. pdf# search%= 22Professional%
20development% 20analysis, 22.
44. Carpenter, T. P., Fennema, E., Peterson, P. L., Chiang, C. P., & Loef, M. (1989). Using knowledge of
children’s mathematics thinking in classroom teaching: An experimental study. American Educational
Research Journal,26(4), 499-531.
45. Cohen, D. K., & Hill, H. C. (2001). Learning policy: When state education reform works. Yale University
Press.
46. Garet, M. S., Porter, A. C., Desimone, L., Birman, B. F., & Yoon, K. S. (2001). What makes professional
development effective? Results from a national sample of teachers. American educational research
journal, 38(4), 915-945.
47. Desimone, L. M., Porter, A. C., Garet, M. S., Yoon, K. S., & Birman, B. F. (2002). Effects of professional
development on teachers’ instruction: Results from a three-year longitudinal study. Educational evaluation
and policy analysis, 24(2), 81-112.
9
48. Penuel, W. R., Fishman, B. J., Yamaguchi, R., & Gallagher, L. P. (2007). What makes professional
development effective? Strategies that foster curriculum implementation. American Educational Research
Journal, 44(4), 921-958.
49. Saxe, G., Gearhart, M., & Nasir, N. i. 2001'Enhancing Students' Understanding of Mathematics: A Study
of Three Contrasting Approaches to Professional Support'. Journal of Mathematics Teacher
Education, 4(1), 55-79.
50. Supovitz, J. A., Mayer, D. P., & Kahle, J. B. (2000). Promoting inquiry-based instructional practice: The
longitudinal impact of professional development in the context of systemic reform. Educational
Policy, 14(3), 331-356.
51. Lieberman, A., & Wood, D. (2001). When teachers write: Of networks and learning. Teachers caught in
the action: Professional development that matters, 174-187.
52. Marek, E. A., & Methven, S. B. (1991). Effects of the learning cycle upon student and classroom teacher
performance. Journal of Research in Science Teaching, 28(1), 41-53.
53. Wenglinsky, H. (2002). The Link between Teacher Classroom Practices and Student Academic
Performance. Education policy analysis archives, 10(12), n12.
54. McGill-Franzen, A., Allington, R. L., Yokoi, L., & Brooks, G. (1999). Putting books in the classroom seems
necessary but not sufficient. The Journal of Educational research, 93(2), 67-74.
55. Boaler, J., Wiliam, D., & Brown, M. (2000). Students' experiences of ability grouping-disaffection,
polarization and the construction of failure. British Educational Research Journal, 26(5), 631-648.
56. Boaler, J. (2002). Learning from teaching: Exploring the relationship between reform curriculum and
equity. Journal for Research in Mathematics Education, 239-258.
57. Hill, H. C., & Ball, D. L. (2004). Learning mathematics for teaching: Results from California's mathematics
professional development institutes. Journal for research in mathematics education, 330-351.
58. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on
student achievement. American educational research journal, 42(2), 371-406.
59. Edmonds, J. (2010). Study of the efficacy of North Carolina’s early college high school model. Paper
presented at the meeting of Jobs for the Future, Atlanta, GA.
60. National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics.
Reston, VA: Author.
61. Atweh, B., Bleicher, R., & Cooper, T. (1998). The construction of the social context of mathematics classrooms: A sociolinguistic analysis. Journal for Research in Mathematics Education, 29, 63-82.
62. Lubienski, S. (2002). A closer look at Black-White mathematics gaps: Intersections of race and SES in
NAEP achievement and instructional practices data. Journal of Negro Education, 71 (4), 269-87.
63. Schiller, K. S., & Muller, C. (2003). Raising the bar and equity? Effects of state high school graduation
requirements and accountability policies on students' mathematics course taking. Educational Evaluation
and Policy Analysis, 25(3), 299-318.
Power Indicator: High School: Interest in STEM Majors and Careers
1.
Tyler-Wood, Tandra, Gerald Knezek, and Rhonda Christensen. (2010). "Instruments for assessing interest
in STEM content and careers." Journal of Technology and Teacher Education 18.2: 345-368.
2. Beggs, J. M., Bantham, J. H., & Taylor, S. (2008). Distinguishing the factors influencing college students’
choice of a major. College Student Journal, 42, 381-394.
3. DeMarie, D., & Aloise-Young, P. A. (2003). College students’ interest in their major. College Student
Journal, 37, 462-469.
4. Hall, C., Dickerson, J., Batts, D., Kauffmann, P., & Bosse, M. (2011). “Are we missing opportunities to
encourage interest in STEM fields?” Journal of Technology Education 25.1.
5. House, J. D. (2000). Academic background and self-beliefs as predictors of student grade performance in
science, engineering, and mathematics. International Journal of Industrial Media, 27, 207-220.
6. Kuechler, W. L., McLeod, A., & Simkin, M. G. (2009). Why don’t more students major in IS? Decision
Sciences Journal of Innovative Education, 7, 463-488.
7. Malgwi, C. A., Howe, M. A., & Burnaby, P. A. (2005). Influences on students' choice of college
major. Journal of Education for Business, 275-282.
8. My College Options and STEMconnector. (2012). Where are the STEM Students? What are their Career
Interests? Where are the STEM Jobs?
9. Schwartz, B. (2004). The tyranny of choice. Chronicle of Higher Education, 50, B6-B8.
10. Tan, L. M., & Laswad, F. (2009). Understanding students’ choice of academic majors: A longitudinal
analysis. Accounting Education, 18, 233-253.
11. National Research Council. Learning Science in Informal Environments: People, Places, and Pursuits.
Washington, DC: The National Academies Press, 2009.
10
12. K. Haghighi (2005). Quiet No Longer: Birth of a New Discipline, Journal of Engineering Education 94, pp.
351-353.
13. J.J. Duderstadt, Engineering for a Changing World: A Roadmap to the Future of Engineering Practice,
Research, and Education, The Millennium Project, The University of Michigan, 2008.`
14. National Science Board, Moving Forward to Improve Engineering Education, NSB 07-122, Arlington, VA.
15. Fifolt, M., & Abbott, G., (2008). Differential experiences of women and minority engineering students in a
cooperative education program. Journal of Women and Minorities and Science and Engineering, 14 (3),
253-267.
16. Frehill, L. M., Ketcham, L. N., & Jeser-Cannavale, C. (2004). Women in engineering: A review of the 2004
literature. SWE Magazine, 51 (3), 22-46.
17. Gibson, L. K., & Angel, D. L. (1995). Mentoring: A successful tool for developing co-op students. Journal
of Cooperative Education, 30 (3), 48-55.
18. LaBonty, D., & Stull, W. A. (1993). Mentoring: A useful concept for cooperative education programs.
Journal of Cooperative Education, 28 (3), 12-20.
19. Linn, P. L., Ferguson, J., & Egart, K. 2004. Career exploration via cooperative education and lifespan
occupational choice. Journal of Vocational Behavior, 64, 430-447.
20. Maletta, M. J., Anderson, B. H., & Angelini, J. P. 1999. Experience, instruction and knowledge acquisition:
a study in taxation. Journal of Accounting Education, 17, 351-366.
21. Pelton, J. N., Johnson, R., & Flournoy, D. 2004. Needs in space education for the 21st century. Space
Policy, 20, 197-205.
22. Westerberg, C., & Wickersham, C. 2011. Internships have value, whether or not students are paid. The
Chronicle of Higher Education (April 24, 2011). http://chronicle.com/article/Internships-Have-Value/127231
23. Scholz, R. W., Steiner, R., & Hansmann, R. 2004. Internships in higher education in environmental
sciences. Journal of Research in Science Teaching, 41, 24-46.
24. Vargas, J., and Hoffman, N. Dual Enrollment in Rhode Island: Opportunities for State Policy. Boston: Jobs
for the Future, 2006.
25. Fletcher, J. “Dual Enrollment.” Presentation to the Florida House of Representatives, Jan. 11, 2006.
Florida Legislature Office of Program Policy Analysis and Government Accountability, 2006.
26. Adelman, C. Answers in the Tool Box: Academic Intensity, Attendance Patterns, and Bachelor’s Degree
Attainment. Washington, D.C.: U.S. Department of Education, 1999.
27. Adelman, C. The Toolbox Revisited: Paths to Degree Completion from High School Through College.
Washington, D.C.: U.S. Department of Education, 2006.
28. Kleiner, B., and Lewis, L. Dual Enrollment of High School Students at Postsecondary Institutions: 2002–
03. Washington, D.C: U.S. Department of Education, National Center for Education Statistics, 2005.
Power Indicator: STEM Postsecondary: Earning Certificates and Degrees Aligned to HighDemand STEM Jobs
1.
2.
3.
4.
5.
6.
7.
8.
Attewell, P., Lavin, D., Domina, T., & Levey, T. (2006). New evidence on college remediation. Journal of
Higher Education, 77, 886–924.
Bahr, P. R. (2008). Does mathematics remediation work?: A comparative analysis of academic attainment
among community college students. Research in Higher Education, 49, 420–450. B
ahr, P. R. (2010a). Preparing the underprepared: An analysis of racial disparities in postsecondary
mathematics remediation. The Journal of Higher Education, 81(2), 209-237.
Bahr, P. R. (2010b). Revisiting the efficacy of postsecondary remediation: The moderating effects of
depth/breadth of deficiency. The Review of Higher Education, 33(2), 177-205.
Bettinger, E., & Long, B. T. (2004). Shape up or ship out: The effects of remediation on students at fouryear colleges. National Bureau of Economic Research, Working Paper No. W10369. Cambridge,
Massachusetts.
Bettinger, E. P, & Long, B. T. (2008). Addressing the needs of underprepared students in higher
education: Does college remediation work?
Howell, J. S., Kurlaender, M., & Grodsky, E. (2010). Postsecondary preparation and remediation:
Examining the effect of the Early Assessment Program at California State University. Journal of Policy
Analysis and Management, 29(4), 726-748.
Parsad, B., Lewis, L., & Greene, B. (2003). Remedial education at degree-granting postsecondary
institutions in fall 2000. (NCES 2004–010). Washington, DC: National Center for Education Statistics.
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