Chemistry topics posing incommensurate difficulty to students with low math aptitude scores

Abstract

The identification of students at risk for academic failure in undergraduate chemistry courses has been heavily addressed in the literature. Arguably one of the strongest and most well-supported predictors of undergraduate success in chemistry is the mathematics portion of the SAT (SAT-M), a college-entrance, standardized test administered by the College Board. While students scoring in the bottom quartile of the SAT-M (herein referred to as at-risk) perform significantly worse on first-semester chemistry assessments, little is known of the topics on which these students differentially struggle. The purpose of this study is to provide insight as to which first-semester chemistry topics present an incommensurate challenge to at-risk students. Students were identified as either at-risk or not at-riskviaSAT-M scores. Students’ assessment responses were collected across four semesters of first-semester chemistry courses at a large, public university (N= 5636). At-risk students struggled consistently across all topics but disproportionately with mole concept and stoichiometry. Analyzing the trend in topics suggests that the struggles of at-risk students are not entirely attributable to topics that rely heavily on algorithms or algebraic math. Moreso, at-risk students found to have performed well on mole concept and stoichiometry went on to perform similarly as their not at-risk peers. The results support an instructional emphasis on these topics with reviewed literature offering promising, practical options to better serve at-risk students and broaden representation in the sciences.

Using Students’ Concept-building Tendencies to Better Characterize Average-Performing Student Learning and Problem-Solving Approaches in General Chemistry

“…Structure and bonding, as well as spatial and symbolic representations, are important in both biology and chemistry, and thus may allow us to generalize our findings to courses in biology and organic chemistry (e.g., Graulich, 2015;Hoskinson et al, 2013). In addition, focusing on Lewis structure problems allowed us to eliminate the possible contribution of math skills in solving a problem, a factor that could occur in many general chemistry problems (e.g., Frey et al, 2017;Ralph and Lewis, 2018).…”

“…In addition, focusing on Lewis structure problems allowed us to eliminate the possible contribution of math skills in solving a problem, a factor that could occur in many general chemistry problems (e.g., Frey et al. , 2017 ; Ralph and Lewis, 2018 ).…”

Development of the Sci-math Sensemaking Framework: categorizing sensemaking of mathematical equations in science

“…Students' difficulties with quantitative problem-solving have been attributed to difficulties with making sense of the conceptual knowledge embedded in the mathematical equations (Bing & Redish, 2007Schuchardt & Schunn, 2016;Tuminaro & Redish, 2007). In physics, chemistry, and biology, students struggle to apply mathematical equations they have learned in class to novel or more complex scenarios (Becker & Towns, 2012;Nakhleh, 1993;Ralph & Lewis, 2018;Schuchardt & Schunn, 2016;Stamovlasis et al, 2005). This difficulty has been attributed to students' tendency to apply memorized algorithmic procedures instead of making sense of connections between the mathematical equations and the modeled scientific phenomenon (Bing & Redish, 2009;Stewart, 1983;Taasoobshirazi & Glynn, 2009;Tuminaro & Redish, 2007).…”

“…However, studies on students solving quantitative problems show that they often solve problems by relying on algorithmic procedures without making connections between the mathematical equation and the scientific phenomenon (Bing & Redish, 2009;Stewart, 1983;Taasoobshirazi & Glynn, 2009;Tuminaro & Redish, 2007). This tendency to solve problems algorithmically has been associated with a failure to transfer problem-solving techniques to novel contexts or more complex problems (Becker & Towns, 2012;Nakhleh, 1993;Ralph & Lewis, 2018;Schuchardt & Schunn, 2016;Stamovlasis, Tsaparlis, Kamilatos, Papaoikonomou, & Zarotiadou, 2005). The reliance on algorithmic problem-solving strategies has been attributed to the different opportunities provided for sensemaking of mathematical equations in science during instruction (Bing & Redish, 2008;Lythcott, 1990;Schuchardt & Schunn, 2016).…”

Enhanced 7E Instructional Model towards Enriching Science Inquiry Skills

“…In reality, learners are no longer fond of developing their vocabulary in the second language, and more so, in Science-related subjects. Likewise, Ralph and Lewis (2018) stated that poor mathematical skills increase the difficulty of Chemistry Incidentally, the researchers had observed that some learners tend to use their mobile phones during classroom discussion. It prompted him to develop a supplementary material that can assist the learners to easily access information at their own disposal.…”