Science Instruction and Identity

Science learning under NGSS depends on what teachers do in classrooms and how students engage in scientific practices, not just what content is covered. This collection of instruments covers four main aspects of the science learning ecosystem: (1) student outcomes related to science aspirations, interest, and identity; (2) teacher knowledge; (3) classroom instructional practice; and (4) socio-scientific issues instruction. It is worth noting the overlapping but distinct reasons to collect data in each of these areas.

1. Students' science aspirations, interest, and identities are early indicators of whether they see science as for them. This in turn shapes course-taking, persistence, and participation—especially for students historically excluded from science pathways. In addition, tracking interest and identity helps schools diagnose whether instruction is engaging, culturally responsive, and motivating, not just whether students can recall content. They support improvement efforts aimed at expanding STEM pipelines, diversifying advanced science enrollment, and strengthening long-term student engagement.
2. Teacher knowledge, of both content and pedagogy, directly shapes instructional quality and student access to rigorous learning opportunities. Measuring teacher knowledge also helps districts target professional learning, coaching, and curriculum support more strategically.
3. Focusing on classroom instructional practice is the most direct way schools can improve science learning. Studying practice allows leaders to assess alignment with standards, identify strengths and gaps, and guide coaching and observation systems. It helps schools move beyond compliance to focus on the quality of sense-making, discourse, and student engagement in science.

Socio-scientific issues (SSI) instruction helps students connect science learning to real-world problems, civic decision-making, and their own communities, increasing relevance and engagement. It supports district goals related to scientific literacy, critical thinking, and preparing students to navigate complex societal challenges like climate change and public health. Studying SSI implementation helps schools ensure that these approaches are rigorous, inclusive, and instructionally coherent, not add-ons.

History: For much of the late twentieth century, data collection in science education focused primarily on student test scores and discrete content knowledge. In the 1990s and early 2000s, measurement efforts expanded to examine inquiry-based teaching, reflecting a growing interest in how students learn science through investigation rather than memorization alone.

In the early 2000s, research in the psychology of learning gave rise to what has been called the “practice turn.”4,5,6,7 Drawing on developments in learning theory, this shift argued that classroom instruction should incorporate disciplinary practices as central to learning, not as add-ons to content. Rather than treating science as a set of disembodied laboratory procedures delivered through teacher-centered instruction, this approach encourages teachers and students to actively do science together in the classroom. Students engage in the creative and social sides of science by representing phenomena, building and testing models, developing explanations, debating ideas, and making sense of evidence. In the practice turn, “content” is inseparable from practice. Learning science now means not just knowing facts, but participating meaningfully in the practices of the discipline.

This theoretical reconceptualization was later codified in the Framework for K–12 Science Education and the Next Generation Science Standards (NGSS), which emphasize three-dimensional learning that integrates disciplinary core ideas, crosscutting concepts, and science and engineering practices. However, many existing instruments were designed before this shift and do not adequately capture this integrated vision.

Today, as 49 states have adopted standards based on the Framework, there is growing recognition that measurement must extend beyond instructional moves to encompass students’ interest, identity, and STEM aspirations; their engagement with socio-scientific issues; and teachers’ knowledge for supporting practice-rich instruction. State and district leaders, school networks, and improvement teams increasingly need practical instruments to monitor implementation, evaluate professional learning, and ensure equitable access to meaningful science learning across classrooms.

Respondent types: When deciding how to gather data on science instruction, teacher knowledge, and student experiences, it's important to consider what you're trying to measure and who can best provide that information. Student surveys are ideal for capturing students' own perspectives on their interest, identity, aspirations, and classroom experiences—things only they can report on directly. Teacher surveys and assessments are better suited for measuring teachers' content knowledge, pedagogical knowledge, and their own perceptions of instructional practices. Classroom observations provide an external perspective on what's actually happening during instruction, which can complement both student and teacher self-reports.

The most comprehensive picture often comes from using multiple data sources. For example, you might pair a student survey like the Next Generation Science Classroom (NGSC) Questionnaire, which captures students' perceptions of three-dimensional learning opportunities, with an observation protocol like the Instructional Quality Assessment, which provides trained observers' ratings of the same instructional practices. This combination allows you to see both how students experience instruction and what an objective observer notices about teaching quality, helping you understand whether implementation gaps exist and where professional learning or curriculum support might be needed. When making your decision, consider your resources (observations require training and time), your goals (monitoring implementation vs. understanding student outcomes), and whether you need triangulation across multiple perspectives to build a convincing case for improvement efforts.

Populations of validation: When selecting instruments, it's critical to consider whether they've been tested and validated with populations similar to yours, though the stakes vary by instrument type.

For student surveys measuring interest, identity, and aspirations, population alignment is especially important because students' cultural backgrounds, language proficiency, age, and prior experiences with science significantly shape how they interpret questions and express their attitudes. An instrument validated only with suburban high schoolers may not work well with elementary students, English learners, or students from underrepresented groups in STEM.

Teacher knowledge assessments also require careful attention to population fit—a content knowledge test designed for secondary biology teachers won't be appropriate for elementary generalists, and pedagogical content knowledge instruments are often grade-band and subject specific.

Observation protocols tend to be somewhat more transferable across contexts since they focus on observable instructional features, but even these may need adaptation if validated only in particular settings (e.g., high school vs. elementary, traditional classrooms vs. lab-based learning).

If you can't find an instrument validated with your specific population, consider piloting it on a small scale first, conducting cognitive interviews with a few students or teachers to ensure questions are interpreted as intended, and being cautious about making high-stakes decisions based on results. Some instruments include guidance for adaptation or provide multiple versions for different contexts, which can be a good starting point for tailoring tools to your specific population's needs.

Timing and frequency: For teacher knowledge measures, it is best to administer before and after professional learning activities designed specifically to assess changes that were directly supported by those activities. For instructional practice measures, consider administering at the same time each year, over 2-3 years, as teacher learning is a gradual process, and measurement can be impacted by the season/time of year. 

This collection includes instruments with validity and reliability information in four main areas: (1) student outcomes related to science aspirations, interest, and identity; (2) teacher knowledge; (3) classroom instructional practice; and (4) socio-scientific issues instruction. We chose to include outcomes related to student aspirations, interest, and identity, because these are increasingly recognized as important for learning⁸.

This collection excludes measures of student learning for two reasons. First, few three-dimensional assessments* have been published with validity information. Second, those that have been published focus only on one area of science. Those who are interested in three-dimensional assessments are invited to read first this article from Science³, and to visit two web sites with tools for educators to use to develop assessments: https://www.5dassessment.org/⁹ and https://contextus.science/¹⁰

*Three-dimensional learning, as defined in A Framework for K-12 Science Education¹, integrates three distinct dimensions: scientific and engineering practices (such as asking questions, developing models, and constructing explanations), crosscutting concepts that apply across all science disciplines (such as patterns, cause and effect, and systems), and disciplinary core ideas in physical sciences, life sciences, earth and space sciences, and engineering. Rather than teaching these dimensions in isolation, the Framework emphasizes that students should engage with all three simultaneously, using practices and crosscutting concepts to make sense of core ideas and build coherent understanding over time. This approach represents a significant shift from traditional science education, which often focused primarily on memorizing facts and vocabulary within individual disciplines.

While this collection highlights a growing body of instruments aligned with contemporary science education reforms, reviewing the landscape also reveals important gaps. These gaps are especially relevant for researchers developing new measures and for practitioners seeking tools to support implementation and improvement efforts.

Few tools assess three-dimensional learning outcomes directly. Three-dimensional learning standards are broad, even though the intent was to have fewer, deeper ideas to focus on in science. There are still many gaps in what standards have been assessed.

Limited measures exist for elementary-aged students' science identity and interest. The tools that are available for student interest and identity are for adolescents, primarily. Observation schemes and survey tools exist for measuring instructional practices at all levels.

Family perspectives are largely absent from current science measurement tools. Family members are not well represented in measures in the domain of science. There are strong practices for inclusion of families,¹¹ however, that have been advanced in the field.

Culturally and linguistically inclusive assessment remains underdeveloped in practice. There exist useful frameworks¹² for developing assessments that are expansive with respect to how they support emergent multilingual learners in expressing what they know and can do.

Identity measures often lack longitudinal or multidimensional depth. Many of the tools for measuring identity lack depth and are not well aligned with how scholars think about identity—as developing over many years, and across different constructs. Identity is also difficult to measure at all using quantitative methods, or when relying on measures given at only two or even three points in time.

¹ National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: The National Academies Press. https://doi.org/10.17226/13165

² National Science Teaching Association & Next Generation Science Standards. Retrieved February 20, 2026, from https://www.nextgenscience.org/

³ Pellegrino, James W. (2013). Proficiency in Science: Assessment Challenges and Opportunities. Science, 340(6130), 320-323. DOI:10.1126/science.1232065

⁴ Bell, P., Lewenstein, B., Shouse, A. W., & Feder, M. A. (2009). Learning science in informal environments: People, places, and pursuits. National Academies Press.

⁵ Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge University Press.

⁶ Lehrer, R., & Schauble, L. (2006). Scientific thinking and science literacy: Supporting development in learning in contexts. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 153–176). Cambridge University Press.

⁷ Osborne, J. (2010). Arguing to learn in science: The role of collaborative, critical discourse. Science, 328(5977), 463–466. https://doi.org/10.1126/science.1183944

⁸ National Academies of Sciences Engineering and Medicine. (2018). How people learn II: Learners, cultures, and contexts. National Academies Press. https://doi.org/10.17226/24783

⁹ 5D Assessment Project. Retrieved February 20, 2026, from https://www.5dassessment.org/

¹⁰ Contextus: Science Assessment in Context. Retrieved February 20, 2026, from https://contextus.science/

¹¹ UW Institute for Science + Math Education. (n.d.). Practice Brief 77: Building Family-Centered Models for Science Education through Learning in Places. In STEM Teaching Tools. Retrieved February 20, 2026, from https://stemteachingtools.org/brief/77

¹² Fine, C. G. M., & Furtak, E. M. (2020). The SAEBL Checklist. The Science Teacher, 87(9), 38-48.