Using concept maps to measure statistical understanding
| Autor: | Lyn Roberts |
|---|---|
| Rok vydání: | 1999 |
| Předmět: |
Scheme (programming language)
Measure (data warehouse) Higher education business.industry Concept map Applied Mathematics computer.software_genre Science education Education Mathematics (miscellaneous) Meaningful learning Evaluation methods ComputingMilieux_COMPUTERSANDEDUCATION Mathematics education Statistical inference Artificial intelligence business computer Natural language processing Mathematics computer.programming_language |
| Zdroj: | International Journal of Mathematical Education in Science and Technology. 30:707-717 |
| ISSN: | 1464-5211 0020-739X |
| DOI: | 10.1080/002073999287707 |
| Popis: | Concept maps have been used extensively in science education both to promote and to measure meaningful learning. This study examines the use of concept maps to measure tertiary science students' understanding of fundamental concepts in statistical inference. Different methods of scoring maps are examined, and a revised scheme developed. Student scores on concept maps of two aspects of statistics, namely problem definition and statistical inference, are compared before and after a practical statistical investigation conducted by the students. The concept map scores are also compared with marks awarded for the practical assignment. While there was no significant improvement in concept map scores over time, some significant correlations were found between aspects of the concept map scores and scores on the practical assignment. Valuable qualitative information can be gained from an investigation of student concept maps, which enables clarification of student misconceptions, and which cannot be obtained from ... |
| Databáze: | OpenAIRE |
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