Literaturnachweis - Detailanzeige
| Autor/inn/en | Willis, William K.; Williamson, Vickie M.; Chuu, Eric; Dabney, Alan R. |
|---|---|
| Titel | The Relationship between a Student's Success in First-Semester General Chemistry and Their Mathematics Fluency, Profile, and Performance on Common Questions |
| Quelle | In: Journal of Science Education and Technology, 31 (2022) 1, S.1-15 (15 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Zusatzinformation | ORCID (Williamson, Vickie M.) |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1059-0145 |
| DOI | 10.1007/s10956-021-09927-y |
| Schlagwörter | Chemistry; Mathematics Skills; Student Characteristics; Predictor Variables; Grades (Scholastic); Scores; Science Instruction; Correlation; At Risk Students; Validity; Reliability; Databases; Undergraduate Students; Scientific Concepts |
| Abstract | In an effort to investigate the factors that lead to success in general chemistry, the Math-Up Skills Test (MUST) and common questions were used along with a student characteristic questionnaire. The MUST is a 20-item instrument to measure mathematics fluency, which is done without a calculator with a 15-min time limit. It has been shown as a valid predictor of successful grades in general chemistry I and II (grades of A, B, or C). A large amount of data was collected from 1020 general chemistry students from six southwestern universities, including MUST score, demographic questions, common examination questions, and course performance as measured by final exams and course grades. The common questions were drawn from databases that had established statistics, reliability, and validity. Six topics were chosen for the first-semester common questions: the combined gas laws, frequency and wavelength of light, unit conversions, stoichiometry, enthalpy, and limiting reagents. Two questions were selected for each topic, one algorithmic (mathematical) and one conceptual. Relationships among the variables were investigated by statistical analysis to generate linear and logistic regression models to predict student success. An interesting finding was the strong relationship between the average course grade and number of common questions answered correctly. The predictability of identifying at-risk students was analyzed for the MUST and the common questions. Respective correlations with the course grade were established. The study concluded that the common questions were the better predictor of success but that the MUST can more effectively be used to predict class performance because it can be given as a single-use test early in the semester. (As Provided). |
| Anmerkungen | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
Literaturbeschaffung und Bestandsnachweise in Bibliotheken prüfen
Permalink als QR-Code
Inhalt auf sozialen Plattformen teilen (nur vorhanden, wenn Javascript eingeschaltet ist)
Teile diese Seite:
