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1. Integrating Computer Science in Science Classrooms: Learning Computational Thinking and Expanding Perceptions of Computer Science

   Greenwald, Eric; Krakowski, Ari (April 2021, NARST 2021 ANNUAL INTERNATIONAL CONFERENCE)

   null (Ed.)

   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. 

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2. Coherence across conceptual and computational representations of students’ scientific models.

   Hutchins, N.M.; Basu, S.; McElhaney, K.; Chiu, J.; Fick, S.; Zhang, N.; Biswas, G. (June 2021, Computersupported collaborative learning)

   de Vries, E. (Ed.)

   We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

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3. Coherence across conceptual and computational representations of students’ scientific models

   Hutchins, N.M.; Basu, S.; McElhaney, K.; Chiu, J.; Fick, S.; Zhang, N.; Biswas, G. (June 2021, Computersupported collaborative learning)

   de Vries, E. (Ed.)

   We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

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4. Coherence across conceptual and computational representations of students’ scientific models

   Hutchins, N.M.; Basu, S.; McElhaney, K.; Chiu, J.; Fick, S.; Zhang, N.; Biswas, G. (January 2021, 15th International Conference of the Learning Sciences)

   null (Ed.)

   We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

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5. Utilization of Remote Access Electron Microscopes to Enhance Technology Education and Foster STEM Interest in Preteen Students

   https://doi.org/10.1007/s11165-020-09964-4  

   Wolf, Vanessa; Hsiao, Valerie; Rodriguez, Brandon; Min, Ashley; Mayorga, Jill; Ashcroft, Jared (November 2020, Research in Science Education)

   null (Ed.)

   Remote access technology in STEM education fills dual roles as an educational tool to deliver science education (Educational Technology) and as a means to teach about technology itself (Technology Education). A five-lesson sequence was introduced to 11 and 12-year-old students at an urban school. The lesson sequences were inquiry-based, hands-on, and utilized active learning pedagogies, which have been implemented in STEM classrooms worldwide. Each lesson employed a scanning electron microscope (SEM) and energy dispersive spectroscopy (EDS) accessed remotely. Students were assessed using multiple-choice questions to ascertain (1) technology education learning gains: did students gain an understanding of how electron microscopes work? and (2) educational technology learning gains: did students gain a better understanding of lesson content through use of the electron microscope? Likert-item surveys were developed, distributed, and analyzed to established how remote access technology affected student attitudes toward science, college, and technology. Participating students had a positive increase in attitudes toward scientific technology by engaging in the lesson sequences, reported positive attitudes toward remote access experiences, and exhibited learning gains in the science behind the SEM technology they accessed remotely. These findings suggest that remote experiences are a strong form of technology education, but also that future research could explore ways to strengthen remote access as an educational technology (a tool to deliver lesson content), such as one-on-one engagement. This study promotes future research into inquiry-based, hands-on, integrated lessons approach that utilize educational technology learning through remote instruments as a pedagogy to increase students’ engagement with and learning of the T in STEM. 

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