首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Characteristics and Levels of Sophistication: An Analysis of Chemistry Students’ Ability to Think with Mental Models
Authors:Chia-Yu Wang and Lloyd H Barrow
Institution:(1) Institute of Education, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 30010, Taiwan;(2) Science Education Center, University of Missouri, Columbia, MO, USA
Abstract:This study employed a case-study approach to reveal how an ability to think with mental models contributes to differences in students’ understanding of molecular geometry and polarity. We were interested in characterizing features and levels of sophistication regarding first-year university chemistry learners’ mental modeling behaviors while the learners were solving problems associated with spatial information. To serve this purpose, we conducted case studies on nine students who were sampled from high-scoring, moderate-scoring, and low-scoring students. Our findings point to five characteristics of mental modeling ability that distinguish students in the high-, moderate-, and low-ability groups from one another. Although the levels of mental modeling abilities have been described in categories (high, moderate, and low), they can be thought of as a continuum with the low-ability group reflecting students who have very limited ability to generate and use mental models whereas students in the high-ability group not only construct and use mental models as a thinking tool, but also analyze the problems to be solved, evaluate their mental models, and oversee entire mental modeling processes. Cross-case comparisons for students with different levels of mental modeling ability indicate that experiences of generating and manipulating a mental model based on imposed propositions are crucial for a learner’s efforts to incorporate content knowledge with visual-spatial thinking skills. This paper summarizes potential factors that undermine learners’ comprehension of molecular geometry and polarity and that influence mastery of this mental modeling ability.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号