Teaching for higher levels of thinking: developing quantitative and analytical skills in environmental science courses. Issue 4 (25th April 2016)

• Record Type: Journal Article
• Authors: Bravo, Adriana; Porzecanski, Ana; Sterling, Eleanor; Bynum, Nora; Cawthorn, Michelle; Fernandez, Denny S.; Freeman, Laurie; Ketcham, Stuart; Leslie, Timothy; Mull, John; Vogler, Donna
• Editors: D'Avanzo, C.
• Is Part Of: Ecosphere. Volume 7:Issue 4(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-04-25
• Subjects: data analysis -- ecology -- process skills -- science courses -- undergraduate students; Ecology -- Periodicals; Ecology; Periodicals; 577.05
• DOI: 10.1002/ecs2.1290
• Languages: English
• ISSNs: 2150-8925

Abstract

Abstract: Professionals with strong quantitative and analytical skills are essential to understanding and responding to current environmental challenges. The goal of this study was to promote and evaluate the development of data analysis (DA) skills in undergraduate students through targeted interventions in environmental science courses. We developed materials to promote practice, instruction, and assessment of four core DA dimensions: the ability to make appropriate calculations, convert data to graphical representations, interpret graphical or mathematical information, and draw conclusions based on the analysis of data. We integrated two conservation exercises as pre/post assessment tools, flanking differentiated teaching interventions, into selected science courses and used a standardized rubric to measure students' performance level. We found that students improved their DA skills in a single semester, but the level of improvement varied across skill dimensions. Students struggled with dimensions that require higher levels of thinking such as data interpretation and drawing conclusions. The use of additional exercises targeting these dimensions and alternative practices might enhance gains. Importantly, students also gained content knowledge in ecological principles while developing skills, and demonstrated an increase in self‐confidence with their DA skills. Our approach and open‐access materials can be integrated into existing courses to develop and assess data skills in undergraduate learners.