Effect of Predicting Motion on Student Understanding of Kinematic Graphs
Different interactive engagements strategies have given students more hands-on involvement in the classroom and helped increase conceptual learning in physics. The purpose of this study was to test the effect of predicting motion graphs by utilizing motion analysis software. Two groups of high scho...
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| Format: | Others |
| Language: | en |
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LSU
2014
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| Online Access: | http://etd.lsu.edu/docs/available/etd-07112014-144145/ |
| Summary: | Different interactive engagements strategies have given students more hands-on involvement in the classroom and helped increase conceptual learning in physics. The purpose of this study was to test the effect of predicting motion graphs by utilizing motion analysis software. Two groups of high school students followed a modified version of Sokoloff and Thorntons seven step ILD process. One group was taught by making predictions. A second group was taught by watching demonstrations. To test for differences in the two groups understanding of kinematic graphs, pre and posttest where taken using the FMCE and Tug-K. The results of both the FMCE and Tug-K showed little to no gains from either the control group or treatment group. Modifying the ILD process and not allowing students the time to discuss their reasoning with other students seemed to be a major factor in the low scores. Although the results of my study are inconclusive compared to other research, there are many immeasurable findings that can help in developing future classroom activities. |
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