In this article, we turn our attention to context-based approaches to science instruction. We studied the effects of changes to a set of secondary science teacher education programs, all of which were redesigned with attention to the Secondary Science Teaching with English Language and Literacy Acquisition (SSTELLA) instructional framework, a framework for responsive and contextualized instruction in multilingual science classrooms. Contextualizing science activity is one of the key dimensions of the SSTELLA instructional framework.
In this paper, I theorize reciprocal noticing as a relational practice through which teachers and students exchange roles as knowers by reciprocating each other’s noticing as they study mathematics concepts. Findings from a unit on measuring time implemented in two classrooms with non-dominant students illustrate how teachers and students—through their reciprocal noticing—mobilize concepts back to previous understandings and forward to possible new meanings.
This study is focused on engineering for sustainable communities (EfSC) in three middle school classrooms. Three in‐depth case studies are presented that explore how two related EfSC epistemic toolsets—(a) community engineering and ethnography tools for defining problems, and (b) integrating perspectives in design specification and optimization through iterative design sketch‐up and prototyping—work to support the following: (a) Students' recruitment of multiple epistemologies; (b) Navigation of multiple epistemologies; and (c) students' onto‐epistemological developments in engineering.
This study uses a mixed-method sequential exploratory design to examine influences on urban adolescents’ engagement and disengagement in school. First, we interviewed 22 middle and high school students who varied in their level of engagement and disengagement. Support from adults and peers, opportunities to make choices, and external incentives aligned with greater engagement. In contrast, a strict disciplinary structure, an irrelevant and boring curriculum, disengaged peers, and lack of respect by adults coincided with greater disengagement.
Emotions are central to how students experience mathematics, yet we know little about how specific instructional practices relate to students’ emotions in mathematics learning. We examined how dialogic instruction, a socially dynamic form of instruction, was associated with four learning emotions in mathematics: enjoyment, pride, anger, and boredom. We also examined whether these associations differed by student gender and prior mathematics achievement.
Student-centered instruction is featured in reforms that aim to improve excellence and equity in mathematics education. Although research on stereotype threat suggests that student-centered instruction may have differential effects on racial minority students, the relationship between student-centered mathematics instruction and student engagement remains understudied.
School engagement researchers have historically focused on academic engagement or academic-related activities. Although academic engagement is vital to adolescents’ educational success, school is a complex developmental context in which adolescents also engage in social interactions while exploring their interests and developing competencies. In this article, school engagement is re-conceptualized as a multi-contextual construct that includes both academic and social contexts of school.
As part of the STEP UP 4 Women project, a national initiative to empower high school teachers to recruit women to pursue physics degrees in college, we developed two lessons for high school physics classes that are intended to facilitate the physics identity development of female students. One discusses physics careers and links to students' own values and goals; the other focuses on a discussion of underrepresentation of women in physics with the intention of having students elicit and examine stereotypes in physics.
Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.