Students' understanding of measurement and uncertainty in the physics laboratory: Social construction, underlying concepts, and quantitative analysis

In the physical sciences and other fields, conclusions are made from experimental data. To succeed in such fields, people must know how to gather, analyze, and draw conclusions from data: not just following steps, but understanding the concepts of measurement and uncertainty. We design the Scientific Community Laboratory (SCL) to teach students to utilize their everyday skills of argument and decision-making for data gathering and analysis. We then develop research tools for studying students' understanding of measurement and uncertainty and use these tools to investigate students in the traditional laboratory and in the SCL.; For students to apply their everyday skills of argument and decision-making, they must be in a state of mind (a frame) where they consider these skills productive. The laboratory design should create an environment which encourages such a frame. We determine student's frames through information reported by students in interviews and surveys and through analyzing students' behavior. We find that the time students spend sense-making in the SCL is five times more than in traditional labs. Students in both labs frequently evaluate their level of understanding but only in the SCL does that evaluation cause a change to more productive behavior.; We analyze lab videotapes to determine underlying concepts commonly used by students when gathering and analyzing data. Our final goal is for students to use these concepts to analyze data in an appropriate manner. We develop a multiple-choice survey which asks students to analyze data from a hypothetical lab context. With this survey we find more students using range to compare data sets after the SCL (from 12% before to 43% after).; For students to understand measurement and uncertainty, we argue that the laboratory must be designed to encourage students to be in a frame where they view resources used to argue and evaluate as appropriate, engage in productive behavior and monitor their behavior, use productive resources to build an understanding of the underlying concepts, and use those concepts to analyze data. We make use of interviews, surveys, and video data to study each of these requirements and to evaluate the SCL curriculum.