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There is a critical need for research-based active learning instructional materials for the teaching and learning of STEM in online courses. Every year, hundreds of thousands of undergraduate non-science majors enroll in general education astronomy courses to fulfill their institution’s liberal arts requirements. When designing instructional materials for this population of learners, a central focus must be to help learners become more scientifically and data literate. As such, we developed a new, three-part, curricular model that was used to inform the creation of active-learning instructional materials designed for use in online courses. The instructional materials were designed to help introductory astronomy students engage meaningfully with science while simultaneously improving their data literacy self-efficacy (especially as it pertained to making evidence-based conclusions when presented with a variety of data representations). We conducted a pilot study of these instructional materials at nine different colleges and universities to better understand whether students’ engagement with these materials lead to improved beliefs and self-efficacy. The results of our student survey analysis showed statistically significant changes on survey items that assessed students’ beliefs about science engagement, citizen science, and their data literacy skills. Additionally, we assessed whether faculty who implemented these materials were able to easily incorporate them into existing online astronomy courses. The instructor feedback emphasized that our curriculum development model did successfully inform the creation of easy-to-implement instructional materials, generating the potential for widespread dissemination and use at the undergraduate level. 

In most middle schools, learning is segregated by discipline. Yet interdisciplinary approaches have been shown to cultivate creative thinking, support problem solving, and develop interest while supporting knowledge gains (NAE & NRC in STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. National Academies Press, Washington, 2014). The Designing Biomimetic Robots project emphasizes problem-based learning to integrate engineering, science, and computational thinking (CT). During a 3 to 4-week unit, students study the natural world to learn how animals accomplish different tasks, then design a robot inspired by what they learned. The project engages students in science, engineering, and CT practices. Over the course of a 3-year project, we used a design-based research approach to: (1) identify and describe strategies and challenges that emerge from integrated curriculum design, (2) explicate how a balance of integrated disciplines can provide opportunities for student participation in science, engineering, and CT practices, and (3) explore how a technology design task can support students’ participation in integrated learning. Data from three focal groups (one from each year of the project) suggest that a focused design task, supported by explicit and targeted supports for science, CT, and engineering practices, led to a student technology design process that was driven by disciplinary understanding. This work highlights the importance of drawing out and prioritizing alignments between disciplines (Barber in Educ Des, 2(8), 2015), to enable integrated learning. Additionally, this work demonstrates how a technology design task can support student learning across disciplines, and how engaging in CT practices can further help students draw these connections.

 

Optimal cordon-metering rates are obtained using Macroscopic Fundamental Diagrams in combination with flow conservation laws. A model-predictive control algorithm is also used so that time-varying metering rates are generated based on their forecasted impacts. Our scalable algorithm can do this for an arbitrary number of cordoned neighborhoods within a city. Unlike its predecessors, the proposed model accounts for the time-varying constraining effects that cordon queues impose on a neighborhood’s circulating traffic, as those queues expand and recede over time. The model does so at every time step by approximating a neighborhood’s street space occupied by cordon queues, and re-scaling the MFD to describe the state of circulating traffic that results. The model also differentiates between saturated and under-saturated cordon-metering operations. Computer simulations of an idealized network show that these enhancements can substantially improve the predictions of both, the trip completion rates in a neighborhood and the rates that vehicles cross metered cordons. Optimal metering policies generated as a result are similarly shown to do a better job in reducing the Vehicle Hours Traveled on the network. The VHT reductions stemming from the proposed model and from its predecessors differed by as much as 14%.