We are exploring how to help middle and high school teachers and students to make sense from data they collect themselves (first hand data) and get from the internet or other sources (second hand data). Our conceptual framework recognizes two “directions” of data exploration (inquiry and critique) and the distinct but interacting facets of the process (collecting and dealing with raw data, data transformations, analyses and representations, filtering evidence, making claims based on data). This framework helps teachers and their students see the context of their explorations when dealing with first versus second hand data. We have formed a professional learning community (PCL) of seasoned biology and environmental science teachers to help us investigate different sequences and types of supports for student data exploration. To date, we have piloted several instructional modules, and continue to revise and refine our instructional materials, professional development plans, and assessment tools. Our research questions included: 1) What do students understand about data exploration? and 2) How does data exploration relate to environmental citizenship? This paper will present results from 2011-2012 and 2012-2013 student pre-tests given at the beginning of the school year.
Results/Conclusions
Students know what variability is (60%, N=282) and how to identify it (80%, N = 683), but this understanding is limited. Most students are not yet able to explain why variability is important for answering a scientific question, making a claim, or formulating a prediction. Interestingly, 10% of students think about variability as a way of understanding ecological processes or natural cycles. 22% of students think of sources of variability and the importance of evaluating the quality of data. Only 17% of students reported understanding how variability influences their interpretation of data and their ability to answer a question, make a claim, or formulate a prediction.
51% of students are more aware of real error (N=252) compared to induced error (21%, N=252). Interestingly, 7% of students reported anthropogenic activities (e.g., pollution or human activity near sample site) as sources of variability.
Students are able to use graphs as evidence to critique claims related to environmental issues. In addition, we also found evidence that students’ decisions to agree/disagree with claims related to environmental issues are occasionally influenced by their personal opinions and values.