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The purpose of this investigation was to identify and describe the differences in the methods used by faculty teaching introductory chemistry and students enrolled in an introductory chemistry course at the university level to solve paired algorithmic and conceptual problems. Of the 180 students involved, the problem-solving schemas of 20 selected students and 2 professors were evaluated using a graphical method to dissect their think-aloud interviews into episodes indicative of solutions to paired problems on density, stoichiometry, bonding, and gas laws. The interviewed students were classified into four different problem-solving categories (i.e., high algorithmic/high conceptual, high algorithmic/low conceptual, low algorithmic/high conceptual, and low algorithmic/low conceptual), and composite graphs of their problem-solving schemas were compared to those representative of members of the faculty experts' category. Results of these comparisons indicated that as the students' ability to solve both algorithmic and conceptual problems improved, less time and fewer transitions between episodes of the problemsolving schemas were required to complete the problems. Regardless of the students' problem-solving ability, algorithmic-mode problems always required more time and a greater number of transitions for completion than did the paired conceptual-mode problems. However, regardless of topic, all students more frequently correctly solved the algorithmic-mode problems than the corresponding paired conceptual-mode problems. © 1997 John Wiley & Sons, Inc. J Res Sci Teach 34: 905-923, 1997. Many difficulties for beginning chemistry students involve problem solving. In most introductory courses, a large amount of information has to be processed and understood by a student to succeed academically. This information can be presented to students in two distinct modes: algorithmic and conceptual. Fundamental to students' success in introductory chemistry is a comprehensive understanding of content reflective of both types of instruction. The question addressed in this study is whether problem-solving schemas used by students differ as their ability JOURNAL

First-semester general chemistry is a known “gatekeeper” course due to its high failure rate. These higher education courses are taken by students who for the most part are regularly admitted freshmen, yet many struggle to succeed. In this investigation researchers from six higher-education institutions of varied sizes with student bodies of different ethnic composition teamed up to investigate the Math-Up Skills Test (MUST) as a potential tool to identify at-risk students in first-semester general chemistry (Chem I). A large population (N = 1073) was given the MUST at the beginning of the semester. The MUST had good internal consistency with the sample (Cronbach's alpha = 0.856). The MUST offers a quick 15 minute assessment of basic mathematics ability without a calculator. Instructors may find it easier than other documented predictors, which may take more time or involve obtaining student records (e.g., Math SAT). Results from the MUST support prior findings that mathematics skills correlate with course grades in chemistry. Poor arithmetic automaticity may be an underlying factor in lower performance by many students. With statistical modeling, the MUST, along with other demographic variables, was able to identify students who would go on to make a 69.5% or better in Chem I with a high percent of accuracy. The MUST, in tandem with other demographic variables, should be considered a potential tool for early identification of students at-risk for failing the class.

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