Science

Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.

Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.

Big ideas in science education are meant to be interpretive frameworks that empower student learning. Unfortunately, outside of the broad conception of scientific evaluation, there are few theoretical explanations of how this might happen. Therefore, we contribute one such explanation, an instructional concept called integrative analysis wherein students use a big idea to interconnect isolated scenarios and enrich their meanings. We illustrate the characteristics and value of integrative analysis within an empirical study of student learning in 9th-grade biology.

This study explores how the interplay between data and model design shifts 6th graders’ students' ideas about diffusion as they build a range of models (“paper and pencil” and computational models). We present a new web-based environment and approach that integrates model-based and data-based features in the same display which facilitates the comparison of models and real-world data. Further, we illustrate how this environment and approach lead students to converge on one canonical scientific model.

Coordinating modeling and real-world data is central to building scientific theories. This paper examines how a complementary focus on modeling and data contributed to 8th grade students’ learning of mechanisms underlying wildfire smoke spread in MoDa, a web-based environment that integrates computational modeling side-by-side with real-world data for comparison and validation. Epistemic network analysis of student responses in pre-post tests revealed a shift from primarily macro-level explanations to explanations that integrated macro and micro-level explanations of the phenomenon.

This study explored the use of a three-part suite of practice-based activities -- one- and two-player online simulations, an avatar-based simulation, and a virtual teaching simulator—for supporting preservice teachers in learning how to facilitate argumentation-focused discussions in elementary mathematics and science. We share findings from analysis of survey data examining four elementary teacher educators’ perceptions about using these activities within their respective elementary methods courses.

Eliciting and interpreting students’ ideas are essential skills in teaching, yet pre-service teachers (PSTs) rarely have adequate opportunities to develop these skills. In this study, we examine PSTs’ patterns of discourse and perceived learning through engaging in an interactive digital simulation called Eliciting Learner Knowledge (ELK). ELK is a seven-minute, chat-based virtual role play between a PST playing a “teacher” and a PST playing a “student” where the goal is for the teacher to find out what the student knows about a topic.

Facilitating discussions is a key approach that science teachers use to engage students in scientific argumentation. However, learning how to facilitate argumentation-focused discussions is an ambitious teaching practice that can be difficult to learn how to do well, especially for preservice teachers (PSTs) who typically have limited opportunities to tryout and refine this teaching practice.

Despite the importance of developing elementary science teachers' content knowledge for teaching (CKT), there are limited assessments that have been designed to measure the full breadth of their CKT at scale. Our overall research project addressed this gap by developing an online assessment to measure elementary preservice teachers' CKT about matter and its interactions. This study, which was part of our larger project, reports on findings from one component of the item development process examining the construct validity of 118 different CKT about matter assessment items.

American schools are becoming more linguistically diverse as immigrants and resettled refugees who speak various languages and dialects arrive at the United States from around the world. This demographic change shifts US classrooms toward super-diversity as the new norm or mainstream in all grade levels (Enright 2011; Park, Zong and Batalova 2018; Vertovec 2007). In super-diverse classroom contexts, students come from varied migration channels, immigration statuses, languages, countries of origin, and religions, which contribute to new and complex social configurations of the classroom.