Subcommittee on STEM Learning
and STEM Learning Environments
The Subcommittee on STEM Learning and STEM
Learning Environments offers three overarching
recommendations to guide NSF-EHR investments
over the next several years:
 Capitalize on promising trends in STEM learning
 Create coordinated programs of research
 Develop a knowledge base of NSF funded research
on STEM learning and learning environments
Subcommittee on STEM Learning
and STEM Learning Environments
1. Capitalize on promising trends in STEM learning
Context: a confluence of major forces
 Recognition of the role of postsecondary education and STEM skills
 New education standards, including CCSS and NGSS
 New information, communication, and collaborative technologies
 The rise of improvement science and its application to data collection,
analyses, and pedagogical practice
 Understanding that learning occurs across environments and the
lifespan
These trends in the wider field of education open significant new
opportunities to improve STEM learning for all American students.
Subcommittee on STEM Learning
and STEM Learning Environments
1. Capitalize on promising trends in STEM learning
Opportunities
 Encourage researchers and practitioners to improve the field’s
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understanding of core questions
Exploit the potential of cyberlearning to accelerate and personalize
STEM learning
Study shifts in educators’ roles in the STEM disciplines
Employ multi-modal learning analytics and data-intensive methods to
address educational questions (e.g., STEM performance assessments)
Take leadership to engage emerging concerns for human subjects’
protections in STEM learning environments
Subcommittee on STEM Learning
and STEM Learning Environments
2. Create coordinated programs of research
Context: common problems of practice
 Growing capacity in the field to identify common problems of practice,
including “stumbling blocks” to student learning
 Potential to raise levels of STEM learning for girls and young women
and students from underrepresented racial and ethnic groups
 Technology infrastructure and improvement science open new ways to
expand field participation in designing and testing solutions
NSF investment should be designed to spark broad interest,
understanding, and dialogue about how problems can be solved and
solutions applied.
Subcommittee on STEM Learning
and STEM Learning Environments
2. Create coordinated programs of research
Opportunities
 Build knowledge about how to recognize and overcome common
“stumbling blocks” that hamper student learning. Examples include:
 Understanding rational numbers, ratios and proportional reasoning
 Applying core concepts and problem-solving strategies for
computational thinking
 Other potential high-leverage topics include:
 Mastering interdisciplinary
 Overcoming barriers that limit the success of underrepresented
students in postsecondary STEM learning
Subcommittee on STEM Learning
and STEM Learning Environments
3. Develop a knowledge base of NSF-funded research
Context: coordination and transparency
 New NSF/IES guidelines provide a basis for coordinated, transparent
programs of knowledge generation
 Programs should encompass projects across research “types,” including
foundational, design and development, impact, scaling, and evaluation
 Balanced portfolios could help fill gaps and drive evidence and theory
toward development, design, and implementation.
Greater transparency about NSF priorities and how NSF-funded
research efforts fit together could help educators, researchers, and others
in the field to recognize potential connections with their work.
Subcommittee on STEM Learning
and STEM Learning Environments
3. Develop a knowledge base of NSF-funded research
Opportunities
 Develop a logic model and associated schematics that articulate the
Directorate’s vision
 Strengthen relationships with educators and others to identify highleverage topics
 Broaden participation by practitioners and researchers, especially those
from underserved populations
 Establish and/or charge translational research centers with developing
common standards for collecting and tagging data