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Promoting the Multidimensional Character of Scientific Reasoning.

ABSTRACT: This study reports part of a long-term program to help students improve scientific reasoning using higher-order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently-each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a "data analysis skills inventory," along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction.

SUBMITTER: Bradshaw WS

PROVIDER: S-EPMC5410765 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Promoting the Multidimensional Character of Scientific Reasoning.

Bradshaw William S WS Nelson Jennifer J Adams Byron J BJ Bell John D JD

Journal of microbiology & biology education 20170421 1

This study reports part of a long-term program to help students improve scientific reasoning using higher-order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank stu ...[more]

PMID: 28512524

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Project description:BackgroundWe address the goal of curating observations from published experiments in a generalizable form; reasoning over these observations to generate interpretations and then querying this interpreted knowledge to supply the supporting evidence. We present web-application software as part of the 'BioScholar' project (R01-GM083871) that fully instantiates this process for a well-defined domain: using tract-tracing experiments to study the neural connectivity of the rat brain.ResultsThe main contribution of this work is to provide the first instantiation of a knowledge representation for experimental observations called 'Knowledge Engineering from Experimental Design' (KEfED) based on experimental variables and their interdependencies. The software has three parts: (a) the KEfED model editor - a design editor for creating KEfED models by drawing a flow diagram of an experimental protocol; (b) the KEfED data interface - a spreadsheet-like tool that permits users to enter experimental data pertaining to a specific model; (c) a 'neural connection matrix' interface that presents neural connectivity as a table of ordinal connection strengths representing the interpretations of tract-tracing data. This tool also allows the user to view experimental evidence pertaining to a specific connection. BioScholar is built in Flex 3.5. It uses Persevere (a noSQL database) as a flexible data store and PowerLoom® (a mature First Order Logic reasoning system) to execute queries using spatial reasoning over the BAMS neuroanatomical ontology.ConclusionsWe first introduce the KEfED approach as a general approach and describe its possible role as a way of introducing structured reasoning into models of argumentation within new models of scientific publication. We then describe the design and implementation of our example application: the BioScholar software. This is presented as a possible biocuration interface and supplementary reasoning toolkit for a larger, more specialized bioinformatics system: the Brain Architecture Management System (BAMS).

Project description:Scientific reasoning involves a person's ability to think and act in ways that help advance their understanding of the natural world. Young children are naturally inclined to engage in scientific reasoning and display an emerging competence in the component skills of, for example, hypothesizing, experimenting and evaluating evidence. Developmental psychology research has shown that same-age children often differ considerably in their proficiency to perform these skills. Part of this variation comes from individual differences in cognition; another part is due to the fact that the component skills of scientific reasoning emerge at a different age and mature at a different pace. Significantly less attention has been paid to children's capacity to improve in scientific reasoning through instruction and deliberate practice. Although elementary science lessons are generally effective to raise the skill level of a group of learners, not all children benefit equally from the instructional treatment they receive. Knowing what causes this differential effectiveness is important as it can inform the design of adaptive instruction and support. The present study therefore aimed to identify and explain how fifth-graders (N = 138) improve their scientific reasoning skills over the course of a 5-week inquiry-based physics unit. In line with our expectations, significant progress was observed in children's achievements on a written scientific reasoning test, which was administered prior to and after the lessons, as well as in their responses to the questions and assignments that appeared on the worksheets they filled out during each lesson. Children's reading comprehension and mathematical skillfulness explained a portion of the variance in children's pretest-posttest gain. As these overall results did not apply equally to all component skills of scientific reasoning, we recommend science teachers to adapt their lessons based on children's past performance in reading and math and their actual performance of each scientific reasoning skill. The orchestration and relative effectiveness of both adaptive science teaching approaches is an interesting topic for future research.

Dataset Information

Promoting the Multidimensional Character of Scientific Reasoning.

Publications

Promoting the Multidimensional Character of Scientific Reasoning.

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