Undergraduate field experiences (UFEs), where students learn and sometimes live together in nature, are critical for the field-based science disciplines. The Undergraduate Field Experiences Research Network (UFERN) brings together UFE educators and researchers to improve and broaden participation in field education. Integrating research on UFEs and general STEM education and the expertise of the UFERN community, we present a model and evidence that describes the impact of intended student outcomes, student context factors, and program design factors on UFE student outcomes. The UFERN model is relevant for a diversity of UFE formats and the diverse students potentially engaged in them, and it supports the field science community to consider a range of ways students can engage with the field. The UFERN model can be applied to guide the design, implementation, and evaluation of student-centered UFEs and to guide research on the mechanisms underlying outcomes across UFE formats and disciplines.
HITS: Harnessing a Collaborative Training Network to Create Case Studies that Integrate High-Throughput, Complex Datasets into Curricula
As educators and researchers, we often enjoy enlivening classroom discussions by including examples of cutting-edge high-throughput (HT) technologies that propelled scientific discovery and created repositories of new information. We also call for the use of evidence-based teaching practices to engage students in ways that promote equity and learning. The complex datasets produced by HT approaches can open the doors to discovery of novel genes, drugs, and regulatory networks, so students need experience with the effective design, implementation, and analysis of HT research. Nevertheless, we miss opportunities to contextualize, define, and explain the potential and limitations of HT methods. One evidence-based approach is to engage students in realistic HT case studies. HT cases immerse students with messy data, asking them to critically consider data analysis, experimental design, ethical implications, and HT technologies.The NSF HITS (High-throughput Discovery Science and Inquiry-based Case Studies for Today’s Students) Research Coordination Network in Undergraduate Biology Education seeks to improve student quantitative skills and participation in HT discovery. Researchers and instructors in the network learn about case pedagogy, HT technologies, publicly available datasets, and computational tools. Leveraging this training and interdisciplinary teamwork, HITS participants then create and implement HT cases. Our initial case collection has been used in >15 different courses at a variety of institutions engaging >600 students in HT discovery. We share here our rationale for engaging students in HT science, our HT cases, and network model to encourage other life science educators to join us and further develop and integrate HT complex datasets into curricula.
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- Award ID(s):
- 1730317
- PAR ID:
- 10339414
- Date Published:
- Journal Name:
- Frontiers in Education
- Volume:
- 6
- ISSN:
- 2504-284X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The rapid development and application of machine learning (ML) techniques in materials science have led to new tools for machine-enabled and autonomous/high-throughput materials design and discovery. Alongside, efforts to extract data from traditional experiments in the published literature with natural language processing (NLP) algorithms provide opportunities to develop tremendous data troves for these in silico design and discovery endeavors. While NLP is used in all aspects of society, its application in materials science is still in the very early stages. This perspective provides a case study on the application of NLP to extract information related to the preparation of organic materials. We present the case study at a basic level with the aim to discuss these technologies and processes with researchers from diverse scientific backgrounds. We also discuss the challenges faced in the case study and provide an assessment to improve the accuracy of NLP techniques for materials science with the aid of community contributions.more » « less
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ABSTRACT During the COVID-19 pandemic, biology educators were forced to think of ways to communicate with their students, engaging them in science and with the scientific community. For educators using course-based undergraduate research experiences (CUREs), the challenge to have students perform real science, analyze their work, and present their results to a larger scientific audience was difficult as the world moved online. Many instructors were able to adapt CUREs utilizing online data analysis and virtual meeting software for class discussions and synchronous learning. However, interaction with the larger scientific community, an integral component of making science relevant for students and allowing them to network with other young scientists and experts in their fields, was still missing. Even before COVID-19, a subset of students would travel to regional or national meetings to present their work, but most did not have these opportunities. With over 300 million active users, Twitter provided a unique platform for students to present their work to a large and varied audience. The Cell Biology Education Consortium hosted an innovative scientific poster session entirely on Twitter to engage undergraduate researchers with one another and with the much broader community. The format for posting on this popular social media platform challenged students to simplify their science and make their points using only a few words and slides. Nineteen institutions and over one hundred students participated in this event. Even though these practices emerged as a necessity during the COVID-19 pandemic, the Twitter presentation strategy shared in this paper can be used widely.more » « less
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Ecosystem response to hurricane disturbance is complex and multi-faceted. The likelihood of increased frequency of severe hurricanes creates a need for the general public to understand how ecosystems respond to hurricanes. Yet, opportunities to study disturbances to complex systems are rare in U.S. K–12 schools. Educators and researchers in the Luquillo Long-Term Ecological Research program used the results of research on ecosystem response to hurricane disturbance in the Luquillo Experimental Forest as a foundation for the development of Journey to El Yunque, a web-based, middle-school curriculum unit. The program engages students in using models as evidence to develop explanations for how particular species respond to hurricane disturbance. Prior research in education has shown that engaging students in a particular role, like that of a scientist, could have detrimental effects on students’ abilities to transfer what is learned from one context to another. In this research, we sought to understand whether having students engage in authentic scientific practices could support transfer of knowledge to the abstract context of a standards-based assessment. Students were randomly assigned to engage in the program in the role of a scientist or in the role of a student learning about an ecosystem. The dependent variables included students’ comprehension of the background readings, their predictions of population changes, and their overall learning of ecology. The results indicate that taking on a scientist role during the learning activities had an indirect effect on general ecology knowledge by increasing the quality of students’ notetaking during background reading. The results also indicate that students struggled to use their knowledge to develop a robust explanation for how species respond to hurricane disturbance. Journey to El Yunque provides a framework for engaging students in authentic investigations of hurricane disturbance. Future research will examine how to improve the quality of students’ final explanations.more » « less
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Recent years have seen a growing recognition of the importance of enabling K-12 students to engage in computational thinking, particularly in elementary grades where students' dispositions toward STEM are developing. Block-based programming has emerged as an effective tool for engaging these novice learners in computational thinking. At the same time, digital storytelling has emerged as a promising avenue for creating motivating problem-solving scenarios that engage students in science investigations. Although block-based programming and digital storytelling are in many ways synergistic, there is a lingering question of how to design block-based languages at an age-appropriate level to enable effective and engaging storytelling. In this work, we review design principles from prior block-based and digital storytelling systems as well as propose the design of block-based programming language features to enable the creation of rich, interactive science narratives by upper elementary students.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/feduc.2021.711512
