This work in progress is motivated by a self-study conducted at Texas State University. The study revealed that the average second year science, technology, engineering and math (STEM) student retention rate is 56% vs. 67% for all majors, and that 16% of STEM majors are female while 57% of all undergraduate students are female. Using these statistics, the authors identified the need to offer motivating experiences to freshman in STEM while creating a sense of community among other STEM students. This paper reports on the impact of two interventions designed by the authors and aligned with this need. The interventions are: (1) a one-day multi- disciplinary summer orientation (summer15) to give participants the opportunity to undertake projects that demonstrate the relevance of spatial and computational thinking skills and (2) a subsequent six-week spatial visualization skills training (fall 2015) for students in need to refine these skills. The interventions have spatial skills as a common topic and introduce participants to career applications through laboratory tours and talks. Swail et al.1 mentions that the three elements to address in order to best support students’ persistence and achievement are cognitive, social, and institutional factors. The interventions address all elements to some extent andmore »
Integrating Computer Science in Science Classrooms: Learning Computational Thinking and Expanding Perceptions of Computer Science
We will present emerging findings from an ongoing study of instruction at the intersection of science and computer science for middle school science classrooms. This paper focuses on student knowledge and dispositional outcomes in relation to a 2 week/10-lesson learning sequence. Instruction aims to broaden participation in STEM pathways through a virtual simulated internship in which students inhabit the role of interns working to develop a restoration plan to improve the health of coral reef populations. Through this collaborative work, students construct understanding of biotic and abiotic interactions within the reef and develop a computational model of the ecosystem. Analysis of pre/post surveys for n=381 students revealed that students who participated in the 2 week/10 lesson integrated computational thinking in science learning sequence demonstrated significant learning gains on an external measure of CT (0.522***; effect size=0.32). Drawing on scales from the Activation Lab suite of measures, pre/post surveys revealed increased competency beliefs about computer programming (mean difference =1.13***; effect size=1.01), and increased value assigned to STEM (0.78***; effect size=0.945). We also discuss the design of the instructional sequence and the theoretical framework for its development.
- Award ID(s):
- 1657002
- Publication Date:
- NSF-PAR ID:
- 10215760
- Journal Name:
- NARST 2021 ANNUAL INTERNATIONAL CONFERENCE
- Sponsoring Org:
- National Science Foundation
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This work in progress is motivated by a self-study conducted at Texas State University. The study revealed that the average second year science, technology, engineering and math (STEM) student retention rate is 56% vs. 67% for all majors, and that 16% of STEM majors are female while 57% of all undergraduate students are female. Using these statistics, the authors identified the need to offer motivating experiences to freshman in STEM while creating a sense of community among other STEM students. This paper reports on the impact of two interventions designed by the authors and aligned with this need. The interventions are: (1) a one-day multi- disciplinary summer orientation (summer15) to give participants the opportunity to undertake projects that demonstrate the relevance of spatial and computational thinking skills and (2) a subsequent six-week spatial visualization skills training (fall 2015) for students in need to refine these skills. The interventions have spatial skills as a common topic and introduce participants to career applications through laboratory tours and talks. Swail et al.[1] mentions that the three elements to address in order to best support students’ persistence and achievement are cognitive, social, and institutional factors. The interventions address all elements to some extent andmore »
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Computational tools, and the computational thinking (CT) involved in their use, are pervasive in science, supporting and often transforming scientific understanding. Yet, longstanding disparities in access to learning opportunities means that CT’s growing role risks deepening persistent inequities in STEM [2]. To address this problem, our team developed and studied two 10-lesson instructional units for middle school science classrooms, each designed to challenge persistent barriers to equitable participation in STEM. The units aim to position coding as a tool for doing science, and ultimately, encourage a broader range of students, and females in particular, to identify as programmers. Students who participated (n=391) in a recent study of the units demonstrated statistically significant learning gains, as measured on an external assessment of CT. Learning gains were particularly pronounced for female students. Findings suggest that students can develop CT through instruction that foregrounds science, and in ways that lead to more equitable outcomes.
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