• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.1-8
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• 2006

This study investigated the causal relationships between high school student multiple-choice algorithmic chemistry problem solving and 1) the motivational variables of achievement goal (task goal/performance goal/performance-avoidance) and perceived ability, and 2) the cognitive variables of learning strategy (deep learning/surface learning) and self-regulation. Path analysis supported a causal model in which perceived ability and task goal were found to positively influence algorithmic chemistry problem-solving ability via self-regulation. In particular it was found that perceived ability directly influenced algorithmic chemistry problem-solving ability. Moreover, deep learning was found to have been influenced by perceived ability and task goal, while surface learning was influenced by performance-avoidance goal. Lastly, there did not appear to be any causal relationship between learning strategy and algorithmic chemistry problem-solving ability.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.79-87
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• 2005

We compared algorithmic problem solving and conceptual understanding of chemistry with three types (algorithmic, pictorial- and wordy-formatted conceptual) of problems. The familiarity, confidence, and preference to the three type of problems were also examined. The chemistry problem solving ability test was administered to 228 students from two top high schools in the province of Gyeonggi who were preparing the chemistry examination among the four optional subjects (biology, chemistry, earth science, physics) for enter university. After administrating the chemistry problem solving ability test, the degree of familiarity to some problems and the degree of confidence of their answers in a Likert scale were asked to the students. Besides, the students were asked to place preference to the type of problems in order. The students scored better on the algorithmic problems than on the conceptual problems (pictorial and wordy problems), and were also most familiar with the algorithmic problems. The students were more confident of their answers on both of types pictorial and algorithmic problems, and preferred pictorial problems rather than both of types algorithmic and wordy problems.

• Journal of the Korean Chemical Society
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• v.44 no.1
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• pp.68-73
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• 2000

In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.

• Journal of The Korean Association For Science Education
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• v.20 no.2
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• pp.214-220
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• 2000

The difference (bias) between self-efficacy and chemistry problem-solving ability was investigated for 96 (male: 48, female: 48) high school students. A self-efficacy instrument was administered, which asked the confidence in solving algorithmic and conceptual problems successfully. Their chemistry problem-solving ability was then assessed with 10 algorithmic and 10 conceptual problems as same in the self-efficacy instrument. Although students had higher scores in the algorithmic problems, no significant difference was found in the self-efficacy to solve the two different forms of problems. Therefore, the bias scores in the conceptual problems were higher than those in the algorithmic problems. Two-way ANOVA results for the bias in the algorithmic problems revealed a significant interaction between gender and the previous achievement level. Analysis of simple effects indicated that the bias scores of high-achieving boys were significantly higher than those of high-achieving girls. While most high-achieving boys were in the overconfident category, high-achieving girls were more likely to be in the underconfident category.

• Journal of the Korean Chemical Society
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• v.55 no.6
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• pp.1042-1055
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• 2011

The purpose of this study was to compare the conceptual and algorithmic problem solving ability on Boyle's law and Charles's law according to cognitive levels and characteristics of students in middle school 1st grade students. For this study, questionnaire items of conceptual and algorithmic problem solving ability were developed. and the problem solving ability according to cognitive levels and characteristics of students was compared. The long-term memory effect in conceptual and algorithmic problem solving ability according to cognitive levels was investigated, and problem solving process were analyzed by questionnaire items. In the results of this study, conceptual problem solving ability was higher than algorithmic problem solving ability in all cognitive levels. There was statistically significant difference in concrete operational period and transitional period students. In comparison of the long-term memory effect in conceptual and algorithmic problem solving ability, formal operational period students had the long-term memory effect. There was no statistically significant difference in the conceptual and algorithmic problem solving ability according to private education among the characteristics of students. But there was statistically significant difference in the problem solving ability according to experiences of the scientific activities and hopes to related scientific careers. From results of analysis of problem solving process, it is known that the students had a tendency to just remember macroscopic phenomena and to solve the problems without understanding the concepts. Therefore, teaching and learning strategy is necessary to replace unscientific concepts by the scientific concepts through identifying students's unscientific concepts in advance.

• Journal of The Korean Association For Science Education
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• v.21 no.2
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• pp.289-298
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• 2001

The effect of the instructional approach that asked students to check their problem-solving processes through a paired think-aloud problem solving after presenting molecular-level pictures and a four stage-problem solving strategy was investigated. Four high school classes (N = 191) were randomly assigned to St group (using Strategy individually), SL group (Solver Listener), St-SL group (using Strategy-Solver Listener), and control group. Although the test scores of the St-SL group on strategy performing ability were significantly higher than those of the control group, there was not significant difference for the scores in the multiple-choice algorithmic problems. Regarding the subcategories of strategy performing ability test, students' ability of understanding given of problems and deriving the proper physical quantity was improved, but their ability of setting up subgoals and reviewing their solving process was very low. The preference to the strategy of the St-SL group was more positive than that of the St group.

• Journal of The Korean Association For Science Education
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• v.18 no.3
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• pp.337-345
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• 1998

This study examined the influences of computer-assisted instruction(CAl) upon high school students' conceptual understanding, algorithmic problem solving ability, learning motivation, and attitudes toward chemistry instruction. CAl programs were designed to supply animated molecular motions for emphasizing the particulate dynamic nature of matter and immediate feedbacks according to students' response types at each stage of four stage problem-solving strategy(understanding, planning, solving, and reviewing). The CAl and control groups (2 classes) were selected from a girls high school in Seoul, and taught about gas law for four class hours. Data analysis indicated that the students at the CAl group scored significantly higher than those at the control group in the tests on conceptual understanding and algorithmic problem solving ability. In addition, the students at the CAl group performed significantly better in the tests on the learning motivation and attitudes toward chemistry instruction.

• Journal of The Korean Association For Science Education
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• v.16 no.3
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• pp.278-285
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• 1996

High school students' achievements in algorithmic problems, and figure-formatted and textual-formatted conceptual problems concerning stoichiometry, gaseous state, and solution, were measured by the Chemistry Problem Solving Ability Test. The relationships among the achievement scores in the three types of problems and cognitive variables such as logical thinking ability, mental capacity, and field dependence/field independence were examined. The portion of variance of explanation for each achievement score was also studied by a multiple regression analysis. The results showed that logical thinking ability was significantly correlated with the achievement score in the algorithmic problems, and accounted for the significant portion of the variance of the score. Mental capacity accounted for the significant portion of the variance of the score in the figure-formatted conceptual problems. Although field dependence/field independence was significantly correlated with all the achievement scores, it did not significantly account for any scores in multiple regression analyses. However, the magnitudes of correlation coefficients among the achievement scores were higher than those between the achievement scores and cognitive variables. The best predictor for each score was also found to be one of the other achievement scores. Educational implications are discussed.