This study investigated the effectiveness of Solve It! instruction on students’ knowledge of math problem-solving strategies. Solve It! is a cognitive strategy intervention designed to improve the math problem solving of middle school students with learning disabilities (LD). Participants included seventh- and eighth-grade students with LD (n = 77) and average-achieving students (n = 77). We examined treatment effects of the intervention, as well as differential effects of treatment across ability levels, on students’ knowledge of problem-solving strategies using the Math Problem-Solving Assessment. Results showed that students across ability levels who received Solve It! instruction reported using significantly more strategies than students in the comparison group. Implications for instruction are discussed as well as directions for future research.
The concept of active learning as a superior mode of instruction has recently received great attention in the education research literature. It holds promise of steering students away from rote memorization towards higher order thinking. However, few studies focus on student perceptions of higher order thinking activities and diverse student voices are all but absent in this regard. This study applies a combined approach of exploratory qualitative and supplementary quantitative analysis to address this gap. We examined perceptions of underrepresented and non-underrepresented students regarding their engagement in active learning to foster higher order thinking. The study was set within a large enrollment (198 students), undergraduate course in the area of science, technology, engineering and mathematics (STEM). The study sample comprised of 33 purposefully selected, ethnically and racially diverse students. Data sources included class attendance/participation, graded activity assignments, and a perception survey. Class attendance and graded assignments were used to triangulate responses on the perception surveys. The Generic Inductive Approach supported our qualitative analysis. Quantitative data were analyzed via two-way ANOVA, non-parametric Mann-Whitney Test (when assumptions did not hold) and simple linear regression. Findings include three themes that cut across groups; participants perceived their higher order thinking skills improved, that there were benefits and challenges to active learning and a fear of failing the course. Quantitative data from the active learning activities and attendance supported similar engagement and achievement in higher order thinking activities across race/ethnicity groups as differences failed to reach the a priori established significance threshold. This study extends the knowledge on active learning and demonstrates that it was possible to engage underrepresented and non-underrepresented students equally and effectively in higher order thinking actives in large enrollment courses and that students perceived this as beneficial.
Engaging in culturally responsive practices is considered best practice in classroom instruction, particularly within diverse schools, however, when making data-based decisions, there is little guidance for culturally responsive practitioners on how to engage in this work. This article introduces a model of culturally responsive data-based decision making (CR-DBDM) by outlining culturally responsive practices and combining them with Deno’s IDEAL (Identify, Define, Explore, Apply, and Look) problem solving model. The article provides members of high school-based problem-solving teams (PSTs), working within a response to intervention (RTI) framework, suggestions for decision making in ways that do not contribute to the disproportionate representation of culturally and linguistically diverse students in special education and empowers students and families by valuing their voices throughout the RTI process.
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