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Autor/inResendes, Karen
TitelA Model for a Data Analysis - and Literature-Intensive Undergraduate Course
QuelleIn: Journal of College Science Teaching, 51 (2022) 5, S.42-54 (13 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0047-231X
SchlagwörterData Analysis; Science Instruction; College Science; Undergraduate Students; STEM Education; Journal Articles; Clubs; Critical Thinking; Instructional Effectiveness
AbstractThis article describes the use of literature to broaden students' skills in content comprehension, data analysis, modeling, and productive scientific discussion. The design builds on existing models to maximize student gains in ability, confidence, and postgraduate preparation. Course units are divided into 1-week modules consisting of three 1-hour sessions: (i) a secondary article-based lecture, introducing a theme; (ii) "Work it out Wednesday," when student teams answer questions, analyze data, and interpret results to develop a biological model linking back to lecture; and (iii) a student-led journal club to discuss an article related to the theme. Student gains in ability and confidence with critical-thinking skills were assessed and compared to the prerequisite course and alumni results. Greater gains across several metrics occurred, with students closing the precourse gap between ability and confidence. Alumni retained gains and reported advantages over peers in postgraduate programs. Comparison to other methods demonstrates multiple benefits and advantages over journal club alone. This structure is applicable to content across STEM disciplines, and adaptations for scaling are discussed. (As Provided).
AnmerkungenNational Science Teaching Association. 1840 Wilson Boulevard, Arlington, VA 22201-3000. Tel: 800-722-6782; Fax: 703-243-3924; e-mail: membership@nsta.org; Web site: https://www.nsta.org/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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