Characteristics of experiment focusing on data analysis.
| Category | Characteristics of Data Analysis Experiment |
|---|---|
| Advantage | - Time for data collection is not required and it prevents errors which can be generated in data collection. |
| - Students can develop specific inquiry skills related to data analysis. | |
| - Students can recognize the nature of science related to data analysis. | |
| - It gives opportunity to analyze data that cannot be collected by individuals or schools, such as big data. | |
| Disadvantage | - Students may not be able to relate data to real phenomena. |
| - Students cannot learn how to use and install experimental equipment to measure data. | |
| - In the case of big data, the data should be reconstructed to suit the student level. | |
| Conditions for effective use | - The data should be linked to what the actual phenomenon is about. |
| - Students should be able to recognize the situation/conditions when data is collected, and to interpret/predict changes in data according to their changes. | |
| - It is necessary to provide separate guidance on data analysis skills (e.g., how to use Excel, control variables, draw and interpret graphs, etc.). | |
| Others | - There are not many cases of inquiry activities using big data. |
| - Big data analysis experiments are expected to expand in the future science education. |