We published nine articles in researcher and teacher practitioner journals and one book chapter in 2021 that showcase innovations in STEM teaching and learning through technology.
Learn how to design curricular materials that leverage digital tools for system modeling (#2), how to ensure powerful data learning experiences for all learners (#6), how to operationalize and assess computational thinking in STEM contexts (#1), and how biology teachers use an immersive digital genetics game in their science classes (#7). Plus read about a curriculum unit for high school biology that links evolution with ecology, cellular biology, and molecular biology (#4), a middle school unit that focuses on the computational thinking skills necessary for weather prediction (#5), and much more!
Read all Concord Consortium articles and papers.
1. Integrating computational thinking in stem education: A literature review
We conducted a semi-systematic literature review on 55 empirical studies of research focusing on the integration of computational thinking (CT) into science, technology, engineering, and mathematics (STEM) education. Based on our findings, suggestions for future research and practice are discussed in terms of operationalizing and assessing CT in STEM contexts, instructional strategies for integrating CT in STEM, and research for broadening participation in integrated CT and STEM education.
Wang, C., Shen, J., & Chao, J. (2021). Integrating computational thinking in STEM education: A literature review. International Journal of Science and Mathematics Education.
2. Supporting student system modelling practice through curriculum and technology design
We provide an in-depth examination and detailed evidence of 10th grade students engaging in four aspects of system modelling. We look at the choices students made when constructing models, whether they described evidence and reasoning for those choices, and whether they described the behavior of their models in connection with model usefulness in explaining and making predictions about the phenomena of interest. We conclude with a set of recommendations for designing curricular materials that leverage digital tools to facilitate the iterative constructing, using, evaluating, and revising of models.
Bielik, T., Stephens, L., McIntyre, C., Damelin, D., & Krajcik, J. S. (2021). Supporting student system modelling practice through curriculum and technology design. Journal of Science Education and Technology.
3. Model my watershed: An investigation into the role of big data, technology, and models in promoting student interest in watershed action
Teaching Environmental Sustainability—Model My Watershed is a data-rich middle school curriculum that promotes student analysis of local watersheds through meaningful watershed educational experiences. We report on a large-scale study conducted in 8 states across the U.S. from 2016 to 2018, with data from 38 teachers and 1,263 students ages 11–18. The data shows a positive impact on students’ environmental literacy in watershed content and action.
Marcum-Dietrich, N., Kerlin, S., Hendrix, A., Sorhagen, N., Staudt, C., & Krauss, Z. (2021). Model my watershed: An investigation into the role of big data, technology, and models in promoting student interest in watershed action. The Journal of Environmental Education.
4. ConnectedBio: An integrative & technology-enhanced approach to evolution education for high school
We describe our free online activities centered on a single evolutionary phenomenon—why deer mice have different fur colors in different subpopulations—to help high school students better understand how these different biological processes, operating at different scales, influence a single organismal trait. Through scaffolded investigations, model building, and more, students learn how ecology, cellular biology, molecular biology, genetic inheritance, and population genetics all work together to influence a shift in fur color over time. Using an innovative multilevel simulation, students manipulate and examine these different processes from the population level down to the DNA level.
Ellis, R., Reichsman, F., Mead, L. S., Smith, J. J., McElroy-Brown, K., & White, P. J. T. (2021). ConnectedBio: An integrative & technology-enhanced approach to evolution education for high school (pdf). The American Biology Teacher, 83(6), 362–371.
5. Weathering the virtual storm: Using computational thinking to make a forecast
Weather and weather prediction offer an ideal medium for students to engage in computational thinking (CT) as they break down a complex problem (forecasting the weather) into manageable steps and develop possible solutions. We describe a novel curriculum in the 5E format for middle school students with an “embedded phenomena” framework in which scientific phenomena are scaled to classroom size and become shared objects of collaborative inquiry. Through seven lessons, students act as meteorologists, applying CT skills including data aggregation, data abstraction, interpolation, and extrapolation to make a weather forecast.
Massicotte, J., Staudt, C., & McIntyre, C. (2021). Weathering the virtual storm: Using computational thinking to make a forecast (pdf). Science Scope, 44(5), 18–27.
6. Teaching in a world of messy data
Learners of all ages must be able to understand and work with data effectively, and opportunities must be provided equitably to all, especially to underrepresented learners. Preparing learners for a world drenched in data means changing how we teach and learn with data overall. While data education is still an emerging field, this commentary provides four guideposts that can help us think about how to ensure powerful data learning experiences.
Dorsey, C. (2021). Teaching in a world of messy data (pdf). The Science Teacher, 88(5), 8.
7. Co‑teaching with an immersive digital game: Supporting teacher‑game instructional partnerships
This study investigated the implementation approaches of nine biology teachers using an immersive digital genetics game in their science classes, focusing on factors that contributed to their ability to instruct with the game, and how their enactment of the game influenced the class experience. Analysis of teacher data identified a range of individual instructional decisions as well as similarities and differences across the cohort. A pattern of instructional orchestration emerged, resembling co-teaching—a reciprocal and supportive “relationship” between the teacher and the game.
Mutch‑Jones, K., Boulden, D. C., Gasca, S., Lord, T., Wiebe, E., & Reichsman, F. (2021). Co‑teaching with an immersive digital game: Supporting teacher‑game instructional partnerships. Educational Technology Research and Development, 69, 1453–1475.
8. Probeware for the modern era: IoT Dataflow System design for secondary classrooms
Sensor systems have the potential to make abstract science phenomena concrete for K-12 students. Internet of Things (IoT) sensor systems provide a variety of benefits for modern classrooms, creating the opportunity for global data production, orienting learners to the opportunities and drawbacks of distributed sensor and control systems, and reducing classroom hardware burden by allowing many students to “listen” to the same data stream. We present an architecture and sensor kit system that addresses issues of sensor ubiquity, acquisition clarity, data transparency, reliability, and security.
Bondaryk, L., Hsi, S., & Doren, S. V. (2021). Probeware for the modern era: IoT Dataflow System design for secondary classrooms. IEEE Transactions on Learning Technologies, 14(2), 226–237.
9. Machine learning-enabled automated feedback: Supporting students’ revision of scientific arguments based on data drawn from simulation
A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students’ revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks that were part of an online science curriculum module addressing groundwater systems for secondary school students. ML was used to develop automated scoring models for students’ argumentation texts and to explore emerging patterns between students’ simulation interactions and argumentation scores.
Lee, H.-S., Gweon, G.-H., Lord, T., Paessel, N., Pallant, A., & Pryputniewicz, S. (2021). Machine learning-enabled automated feedback: Supporting students’ revision of scientific arguments based on data drawn from simulation. Journal of Science Education and Technology, 30, 168–192.
10. Aligning teacher facilitation tools with pedagogies in a real-time environment for mathematics team learning
Digitally facilitated team-based classrooms require a rich set of tools to support teacher noticing and classroom orchestration. Our digital environment allows middle school mathematics teachers to effectively teach team-organized classes in an in-person, hybrid, or online environment. We describe two key features—a dashboard allowing teachers to monitor and inspect all student artifacts in real time and a workspace allowing teachers to generate and publish their own content—and the particular ways they facilitate effective classroom orchestration and noticing.
Bondaryk, L., & Dorsey, C. (2021). Aligning teacher facilitation tools with pedagogies in a real-time environment for mathematics team learning. In L. O. Campbell, R. Hartshorne, & R. F. DeMara (Eds.), Perspectives on digitally-mediated team learning. Springer.