- Barth-Cohen, L. & Jiang, S., Shen, J., *Chen, G., & Eltoukhy, M. (2018). Interpreting and Navigating Multiple Representations as Central to Computational Thinking in a Robotics Programming Environment. Journal of STEM Education Research. Vol. 1, 119-147. Published, 10/2018.
- Barth-Cohen, L. A., Greenberg, K. I., & Moretz, E. (September 2018). A Model for Earth’s Energy Budget: Unpackingthe relationship between energy and temperature to understand climate change. The Science Teacher, 86(2), 20-27. Published, 09/04/2018.
- Barth-Cohen, L. & Braden, S. (2018). A continuum of knowledge structures in an observation-based field geology setting. (pp. 1599-1600). Vol. 3. Rethinking Learning in the Digital Age: Making the Learning Sciences Count, 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 3. London, UK: International Society of the Learning Sciences. Published, 06/2018.
- Atkins Elliot, L. & Barth-Cohen, L. (2018). Constructing Entities in Scientific Models. (pp. 1679-1680). Vol. 3. Rethinking Learning in the Digital Age: Making the Learning Sciences Count, 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 3. London, UK: International Society of the Learning Sciences. Published, 06/2018.
- Barth-Cohen, L. (2018). Threads of Local Continuity Between Centralized and Decentralized Causality: The Emergence of an Emergent Explanation. Instructional Science.
- Barth-Cohen, L. A. & Little, A., & Abrahamson, D. (2018). Building Reflective Practices in a Pre- Service Science Teacher Education Course that Focuses on Qualitative Video Analysis. Journal of Science Teacher Education. Vol. 29, 83-101.
- Barth-Cohen, L., & Medina, E. (2017). USING MODELS TO UNDERSTAND SEA LEVEL RISE. The Science Teacher, 84(7), 33.
- Shen, J., Chen, G. Barth-Cohen, L., Jiang, S., Huang, X, and Eltoukhy, M. (2017). Assessing Elementary Students’ Computational Thinking. Computers & Education.
- Barth-Cohen, L. A, & Wittmann, M. C. (2017). Aligning Coordination Class Theory with a New Context: Applying a Theory of Individual Learning to Group Learning. Science Education.
- Barth-Cohen, L., & Wittmann, M. C. (2016, June). Expanding Coordination Class Theory to Capture Conceptual Learning in a Classroom Environment. In Looi, C. K., Polman, J. L., Cress, U., and Reimann, P. (Eds.). (2016). Transforming Learning, Empowering Learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 1. Singapore: International Society of the Learning Sciences. pp. 386-393. Published, 06/2016.
- Shen, J. Chen, G. Barth-Cohen, L. & Eltoukhy, M. (2016, June). Developing a Language-neutral Instrument to Assess Fifth Graders’ Computational Thinking. In Looi, C. K., Polman, J. L., Cress, U., and Reimann, P. (Eds.). (2016). Transforming Learning, Empowering Learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 1. Singapore: International Society of the Learning Sciences. pp.1179-1180. Published, 06/2016.
- Barth-Cohen, L. A., Smith, M. K., Capps, D. K., Lewin, J. D., Shemwell, J. T., & Stetzer, M. R. (2016). What are middle school students talking about during clicker questions? Characterizing small-group conversations mediated by classroom response systems. Journal of Science Education and Technology, 25(1), 50-61. Published, 02/2016.
Dr. Barth-Cohen’s research focuses on student learning in science and she works to translate that research in ways that can be useful to K-12 teachers. She studies student learning of the often-difficult concepts in science that are foundational to the scientific enterprise and central to science education. In her research, she designs and implements learning environments aiming to scaffold such conceptual learning. She video tapes the instruction and then conducts qualitative video analysis on changes to learners conceptual understanding over time. Her approach to learning focuses on characterizing learners’ knowledge system over time, and she concentrate on contexts where they are engaged in a variety of knowledge building practices that are similar to the practices of professional science and central to reform based science education efforts (e.g. developing and using scientific modeling, analyzing and interpreting data, and engaging in argument from evidence). A recently project has focused on student learning about the physics of climate change in a conceptual modeling unit. Another project examines how learners come to generate scientific observations that can function as evidence in a field geology setting. An additional line of research focuses on elementary school students’ learning of computational thinking skills in a humanoid robotics setting. A recent National Science Foundation funded grant (DUE-IUSE, #1712493) is aiming to build coherence in STEM learning opportunities (math and science content and methods classes at the University of Utah) to advance our understanding of how undergrad pre-service elementary teachers learn STEM content, instructional practices for teaching STEM, and principles and dispositions around equity and social justice.
- climate change education
- Teacher Education
- Science Education
- STEM Education
- Preservice Teachers
- Precollegiate Education - Science or Mathematics
- Mathematics Education
- Barth-Cohen, L.A., Jiang, S., Shen, J., Chen, G., Eltoukhy, M. (2017) Elementary School Students’ Computational Thinking Practices in a Robotics-Programming Environment. Paper presented at the 2017 American Education Research Association (AERA) Conference Annual Meeting, San Antonio, TX. Conference Paper, Refereed, Accepted, 11/2016.