作者: Marcia C. Linn , Eliane S. Wiese
DOI: 10.1145/3415582
关键词: Term (time) 、 Operationalization 、 Computational thinking 、 Meaning (linguistics) 、 Mathematics education 、 Psychology 、 Scientific modelling 、 Phenomenon 、 Science class 、 Sample (statistics)
摘要: When middle school students encounter computer models of science phenomenon in class, how do they think those work? Computer operationalize real-world behaviors selected variables, and can simulate interactions between the modeled elements through programmed instructions. This study explores about high-level semantic meaning instructions, which we term rules. To investigate this aspect students’ computational thinking, developed Computational Modeling Inventory administered it to 253 7th grade students. The included three that interacted with during assessment. In our sample, 99% identified at least one key rule underlying a model, but only 14% all rules; 65% believed model rules contradict; 98% could not distinguish emergent patterns directly resulted from Despite these misconceptions, compared “typical” questions content alone, elicited deeper 2--10 times more responses including reasoning scientific mechanisms. These results suggest incorporating thinking instruction into courses might yield learning precise assessments around models.