Examining Some of Students’ Challenges and Use of Algorithmic ProblemSolving Approaches in Electrochemical Titrations

Abstract

Redox titration problems are considered difficult for students to learn due to their abstract nature, the myriad amount of representations, and the mathematical competency required to learn and solve. The goal of this research project is to examine challenges students face in learning about redox titration-related problems, approaches they use in learning about electrochemical titration problems, and reliance on algorithmic problem-solving instead of conceptual understanding in solving these problems. The research project took place at the City College of New York, which is an urban, minority serving, and public institution. The research instrument used in this research investigation is a survey comprised of Likert-type and open-ended questions. The number of research participants is n = 184. The data was collected and analyzed and histograms and figures were made based on the data analysis. A single factor ANOVA method was performed on the Likert-type questions which showed evidence against the null hypothesis and that shows a strong relationship between variables. The data indicate that the principal barrier to learning about redox titration related problems is that students’ reliance on algorithmic problems solving, rote learning, and mathematical approaches. Students’ dependence on rote learning and memorization in problem solving could be attributed to the lack of well-developed understanding of the concepts. The investigation shows that students focus on surface features in learning and this translates to hindrance of knowledge transfer.