Toward Designing and Developing Likert Items to Assess Mathematical Problem Solving
Access to science, technology, engineering, and mathematics (STEM) careers relies heavily on student success in their foundational university mathematics courses. For future STEM majors, there is little debate over the procedural skills that are needed in algebra to continue in STEM, but what are the mathematical problem solving (MPS) skills needed to persist in calculus and beyond? There are currently few efficient tools that can be used to explore research questions such as this one. In response, our project goal is to develop Likert MPS items that can be machine scored and used as an efficient tool in exploring students’ MPS practices. The items link a student’s MPS to five key domains of MPS derived from the research literature; items are designed for entry-level university students and do not require content knowledge beyond secondary school algebra. In this chapter, we report on the Likert item development, including the revision and validation processes. As part of the development, we explored the following research questions: (a) How are student scores on MPS items linked to their MPS practices during interviews, and (b) How are student scores on MPS items linked to their course performance? Participants were over 1500 students enrolled in College Algebra or Calculus at a large, urban university in the United States. Results illustrated trends in student practices within each MPS domain; these trends are informative for future item development and research. Results also suggest that students may not be developing many MPS skills in their foundational university mathematics courses.
KeywordsMathematical problem solving Mathematics assessment College algebra Calculus placement
Partial support for this work was provided by the National Science Foundation (NSF) Improving Undergraduate STEM Education (IUSE) program under Award No. 1544545. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. We also thank Dr. Lauren Coursey and Andrew Kercher for research assistance and reviewers for their feedback.
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