In this article a cognitive model of learning chemistry is reported first, followed by a discussion of students' chemical misconceptions, and finally the implications of these findings on instruction.

Bright students who perceive the world somewhat differently from the traditional math-oriented science/engineering students sit in every large general chemistry lecture. These students desire to explore the why of chemistry more than the how of chemistry. That is, they are more interested in the concepts than in algorithmic problem solving. Second-Tier Students in General ChemistryTobias (f) has studied these students and their reactions to general chemistry courses. She calls these students "second-tier students" and urges that some effort be made to recruit them into the study of chemistry. I became interested in the problem of identifying these students who have the ability to study chemistiy yet are not attracted to the discipline. This student population could be viewed as a potentially rich source of recruits into the scientific disciplines, which have experienced steady declines in majors for several years (2).Testing for Conceptual Thinking and Problem-Solving Skills However, no way has been devised of identifying, and thus recruiting, these students in the typically large lec-ture sections of general chemistry courses. This study created a short, simple test that might help identity these students in general chemistry by investigating differential

Chemical educators have often assumed that success in solving mathematical problems should indicate mastery of a chemical concept. To this end, we have developed algorithms. However, Nurrenbern and Piekering ( 1 ) and Pickering (2) found little connection between solving an algorithmically-based problem and understanding the chemical concept behind that problem. Sawrey (3) further supported Nurrenbern and Pickering's findings.These studies quantitatively evaluated success in solving a conceptual problem versus a similar algorithmic problem. These studies found that many students could not use chemical concepts to solve conceptual problems.These findings were further supported by Nakhleh (4).Nakhleh found that across all levels of first-year chemistry students (from remedial to honors) conceptual problem-solving ability lagged far behind algorithmic problemsolving ability. She determined through the use of paired exam questions, that a sizable percentage (31% in that sample) of our firsbyear students are low conceptualhigh algorithmic students; students adept a t solving problems with algebraic equations, hut having only limited understanding of the chemistry behind their algorithmic manipulations.In the present study our objective was to ascertain what students do think about when they solve conceptual and algorithmic problems and to determine further if there are differences andlor preferences in their approach to each.We. therefore. used aired exam auestions on rras laws to select studentsfor interviews. In tke interviewwe probed their conce~tual understandinrr and their ~roblem solvine in detail. w e tried to determhe how the' students weni about solving a conceptual problem versus an algorithmic problem. We also endeavored to probe their preferences for solving either type of problem. MethodOur sample consisted of 60 freshmen chemistry students who were all enrolled in the same introductory course for declared chemistry majors. No other majors were represented in this sample. The professor for the course used a traditional problem-oriented lecture approach.This study was completed in two parts. The first part of the study used the paired questions technique to identify students as being either conceptual or algorithmic problem solvers. Two problems--one conceptual gas law problem and one algorithmic gas law problem-were placed on the third exam in the course where gas laws were being examined. Success or failure on these were recorded and students were grouped in one of four categories: High AleorithmiJHirrh Conce~tual (answerine both ~m b l e m s coFrectly,; ~i~t ~l~o r i t h m i r /~o w ~once&al (&swering the conceptual prohlem incorrectly J; Low AlgorithmiJHigh Conceptual (answering the algorithmic problem incorrwtlv); Low AleorithmidLow Conce~tual (answering neiProblem I.The following diagram represents a cross-sectional area of a rigid sealed steel tank filled with hydrogen gas at 20 ' C and 3 atm pressure. The dots represent the distribution of all the hydrogen molecules in the tank.Whlch of the follow...

We investigated how different levels of information presented by various technologies affected secondary students' understanding of acid, base, and pH concepts. Secondary students who were selected for the study had just completed their study of acid–base chemistry. No attempt was made to provide further instruction. We analyzed changes in the understanding of individual students by constructing concept maps from the propositions that the students used in interviews conducted before and after a series of acid–base titrations. After the initial interview, students were divided into three groups. Within each group, students individually performed the same set of titrations using different technologies: chemical indicators, pH meters, and microcomputer‐based laboratories (MBL). After the titrations were completed, all students were interviewed again. We found that students using MBL exhibited a larger positive shift in their concept map scores, which indicates a greater differentiation and integration of their knowledge of acids and bases. The chemical indicator students exhibited a more moderate positive shift in their concept map scores, and the pH meter students exhibited a smaller positive shift. We also found that the MBL students constructed more inappropriate links in their concept maps than the chemical indicator or pH meter students. However, we speculate that this increased number of inappropriate links indicates a high level of involvement with the technology. We therefore argue that the level of information offered by the technology affected students' understanding of the chemical concepts.

The performance of freshman science, engineering, and in-service teacher students in three Israeli and American universities on algorithmic, lower-order cognitive skills (LOCS), and conceptual chemistry exam questions was investigated. The driving force for the study was an interest in moving chemistry instruction from an algorithm-oriented factual recall approach dominated by LOCS to a decision-making, problem-solving, and critical thinking approach dominated by higher-order cognitive skills (HOCS). Students' responses to the specially designed algorithmic, LOCS, and conceptual exam questions were scored and analyzed for correlations and for differences between the means within and across universities by the question's category. The main findings were: (1) students in all three universities performed consistently on each of the three categories in the order of algorithmic > LOCS > conceptual questions, (2) success on algorithmic does not imply success on conceptual, or even on LOCS questions, and (3) students taught in small classes outperformed by far those in large lecture sessions in all three categories. The implied paradigm shift from an algorithmic/LOCS to a conceptual/HOCS orientation should be moved from a research-based theoretical domain to actual implementation in order for a meaningful improvement of chemistry teaching to occur.