A 2019 report from the National Academies on Minority Serving Institutions (MSIs) concluded that MSIs need to change their culture to successfully serve students with marginalized racial and/or ethnic identities. The report recommends institutional responsiveness to meet students “where they are,” metaphorically, creating supportive campus environments and providing tailored academic and social support structures. In recent years, the faculty, staff, and administrators at California State University, Los Angeles have made significant efforts to enhance student success through multiple initiatives including a summer bridge program, first-year in engineering program, etc. However, it has become clear that more profound changes are needed to create a culture that meets students “where they are.”
In 2020, we were awarded NSF support for Eco-STEM, an initiative designed to change a system that demands "college-ready" students into one that is "student-ready." Aimed at shifting the deficit mindset prevailing in engineering education, the Eco-STEM project embraces an asset-based ecosystem model that thinks of education as cultivation, and ideas as seeds we are planting, rather than a system of standards and quality checks. This significant paradigm and culture transformation is accomplished through:
1) The Eco-STEM Faculty Fellows’ Community of Practice (CoP), which employs critically reflective dialogue[ ][ ] to enhance the learning environment using asset-based learner-centered instructional approaches;
2) A Leadership CoP with department chairs and program directors that guides cultural change at the department/program level;
3) A Facilitators’ CoP that prepares facilitators to lead, sustain, update, and expand the Faculty and Leadership CoPs;
4) Reform of the teaching evaluation system to sustain the cultural changes.
This paper presents the progress and preliminary findings of the Eco-STEM project. During the first project year, the project team formulated the curriculum for the Faculty CoP with a focus on inclusive pedagogy, community cultural wealth, and community building, developed a classroom peer observation tool to provide formative data for teaching reflection, and designed research inquiry tools. The latter investigates the following research questions:
1) To what extent do the Eco-STEM CoPs effectively shift the mental models of participants from a factory-like model to an ecosystem model of education?
2) To what extent does this shift support an emphasis on the assets of our students, faculty, and staff members and, in turn, allow for enhanced motivation, excellence and success?
3) To what extent do new faculty assessment tools designed to provide feedback that reflects ecosystem-centric principles and values allow for individuals within the system to thrive?
In Fall 2021, the first cohort of Eco-STEM Faculty Fellows were recruited, and rich conversations and in-depth reflections in our CoP meetings indicated Fellows’ positive responses to both the CoP curriculum and facilitation practices. This paper offers a work-in-progress introduction to the
Eco-STEM project, including the Faculty CoP, the classroom peer observation tool, and the proposed research instruments. We hope this work will cultivate broader conversations within the engineering education research community about cultural change in engineering education and methods towards its implementation.
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Understanding landowner decisions regarding access to private land for conservation research
This manuscript explores the reasons why landowners allow or decline to allow research on their properties based on a combination of surveys and interviews. Based on our findings, we make recommendations for how researchers hoping to conduct research on private land can successfully gain access and encourage a good experience for all involved.
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- Award ID(s):
- 1755055
- NSF-PAR ID:
- 10462064
- Date Published:
- Journal Name:
- Conservation Science and Practice
- Volume:
- 3
- Issue:
- 11
- ISSN:
- 2578-4854
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract In the modern industrial setting, there is an increasing demand for all types of sensors. The demand for both the quantity and quality of sensors is increasing annually. Our research focuses on thin-film nitrate sensors in particular, and it seeks to provide a robust method to monitor the quality of the sensors while reducing the cost of production.
We are researching an image-based machine learning method to allow for real-time quality assessment of every sensor in the manufacturing pipeline. It opens up the possibility of real-time production parameter adjustments to enhance sensor performance. This technology has the potential to significantly reduce the cost of quality control and improve sensor quality at the same time. Previous research has proven that the texture of the topical layer (ion-selective membrane (ISM) layer) of the sensor directly correlates with the performance of the sensor. Our method seeks to use the correlation so established to train a learning-based system to predict the performance of any given sensor from a still photo of the sensor active region, i.e. the ISM. This will allow for the real-time assessment of every sensor instead of sample testing. Random sample testing is both costly in time and labor, and therefore, it does not account for all of the individual sensors.
Sensor measurement is a crucial portion of the data collection process. To measure the performance of the sensors, the sensors are taken to a specialized lab to be measured for performance. During the measurement process, noise and error are unavoidable; therefore, we generated credibility data based on the performance data to show the reliability of each sensor performance signal at each sample time.
In this paper, we propose a machine learning based method to predict sensor performance using image features extracted from the non-contact sensor images guided by the credibility data. This will eliminate the need to test every sensor as it is manufactured, which is not practical in a high-speed roll-to-roll setting, thus truely enabling a certify as built framework.
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1. Description of the objectives and motivation for the contribution to ECE education The demand for wireless data transmission capacity is increasing rapidly and this growth is expected to continue due to ongoing prevalence of cellular phones and new and emerging bandwidth-intensive applications that encompass high-definition video, unmanned aerial systems (UAS), intelligent transportation systems (ITS) including autonomous vehicles, and others. Meanwhile, vital military and public safety applications also depend on access to the radio frequency spectrum. To meet these demands, the US federal government is beginning to move from the proven but inefficient model of exclusive frequency assignments to a more-efficient, shared-spectrum approach in some bands of the radio frequency spectrum. A STEM workforce that understands the radio frequency spectrum and applications that use the spectrum is needed to further increase spectrum efficiency and cost-effectiveness of wireless systems over the next several decades to meet anticipated and unanticipated increases in wireless data capacity. 2. Relevant background including literature search examples if appropriate CISCO Systems’ annual survey indicates continued strong growth in demand for wireless data capacity. Meanwhile, undergraduate electrical and computer engineering courses in communication systems, electromagnetics, and networks tend to emphasize mathematical and theoretical fundamentals and higher-layer protocols, with less focus on fundamental concepts that are more specific to radio frequency wireless systems, including the physical and media access control layers of wireless communication systems and networks. An efficient way is needed to introduce basic RF system and spectrum concepts to undergraduate engineering students in courses such as those mentioned above who are unable to, or had not planned to take a full course in radio frequency / microwave engineering or wireless systems and networks. We have developed a series of interactive online modules that introduce concepts fundamental to wireless communications, the radio frequency spectrum, and spectrum sharing, and seek to present these concepts in context. The modules include interactive, JavaScript-based simulation exercises intended to reinforce the concepts that are presented in the modules through narrated slide presentations, text, and external links. Additional modules in development will introduce advanced undergraduate and graduate students and STEM professionals to configuration and programming of adaptive frequency-agile radios and spectrum management systems that can operate efficiently in congested radio frequency environments. Simulation exercises developed for the advanced modules allow both manual and automatic control of simulated radio links in timed, game-like simulations, and some exercises will enable students to select from among multiple pre-coded controller strategies and optionally edit the code before running the timed simulation. Additionally, we have developed infrastructure for running remote laboratory experiments that can also be embedded within the online modules, including a web-based user interface, an experiment management framework, and software defined radio (SDR) application software that runs in a wireless testbed initially developed for research. Although these experiments rely on limited hardware resources and introduce additional logistical considerations, they provide additional realism that may further challenge and motivate students. 3. Description of any assessment methods used to evaluate the effectiveness of the contribution, Each set of modules is preceded and followed by a survey. Each individual module is preceded by a quiz and followed by another quiz, with pre- and post-quiz questions drawn from the same pool. The pre-surveys allow students to opt in or out of having their survey and quiz results used anonymously in research. 4. Statement of results. The initial modules have been and are being used by three groups of students: (1) students in an undergraduate Introduction to Communication Systems course; (2) an interdisciplinary group of engineering students, including computer science students, who are participating in related undergraduate research project; and (3) students in a graduate-level communications course that includes both electrical and computer engineers. Analysis of results from the first group of students showed statistically significant increases from pre-quiz to post-quiz for each of four modules on fundamental wireless communication concepts. Results for the other students have not yet been analyzed, but also appear to show substantial pre-quiz to post-quiz increases in mean scores.more » « less
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null (Ed.)The Tweet Collection Management (TWT) Team aims to ingest 5 billion tweets, clean this data, analyze the metadata present, extract key information, classify tweets into categories, and finally, index these tweets into Elasticsearch to browse and query. The main deliverable of this project is a running software application for searching tweets and for viewing Twitter collections from Digital Library Research Laboratory (DLRL) event archive projects. As a starting point, we focused on two development goals: (1) hashtag-based and (2) username-based search for tweets. For IR1, we completed extraction of two fields within our sample collection: hashtags and username. Sample code for TwiRole, a user-classification program, was investigated for use in our project. We were able to sample from multiple collections of tweets, spanning topics like COVID-19 and hurricanes. Initial work encompassed using a sample collection, provided via Google Drive. An NFS-based persistent storage was later involved to allow access to larger collections. In total, we have developed 9 services to extract key information like username, hashtags, geo-location, and keywords from tweets. We have also developed services to allow for parsing and cleaning of raw API data, and backup of data in an Apache Parquet filestore. All services are Dockerized and added to the GitLab Container Registry. The services are deployed in the CS cloud cluster to integrate services into the full search engine workflow. A service is created to convert WARC files to JSON for reading archive files into the application. Unit testing of services is complete and end-to-end tests have been conducted to improve system robustness and avoid failure during deployment. The TWT team has indexed 3,200 tweets into the Elasticsearch index. Future work could involve parallelization of the extraction of metadata, an alternative feature-flag approach, advanced geo-location inference, and adoption of the DMI-TCAT format. Key deliverables include a data body that allows for search, sort, filter, and visualization of raw tweet collections and metadata analysis; a running software application for searching tweets and for viewing Twitter collections from Digital Library Research Laboratory (DLRL) event archive projects; and a user guide to assist those using the system.more » « less
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Optical techniques for recording and manipulating cellular electrophysiology have advanced rapidly in just a few decades. These developments allow for the analysis of cardiac cellular dynamics at multiple scales while largely overcoming the drawbacks associated with the use of electrodes. The recent advent of optogenetics opens up new possibilities for regional and tissue-level electrophysiological control and hold promise for future novel clinical applications. This article, which emerged from the international NOTICE workshop in 2018 1 , reviews the state-of-the-art optical techniques used for cardiac electrophysiological research and the underlying biophysics. The design and performance of optical reporters and optogenetic actuators are reviewed along with limitations of current probes. The physics of light interaction with cardiac tissue is detailed and associated challenges with the use of optical sensors and actuators are presented. Case studies include the use of fluorescence recovery after photobleaching and super-resolution microscopy to explore the micro-structure of cardiac cells and a review of two photon and light sheet technologies applied to cardiac tissue. The emergence of cardiac optogenetics is reviewed and the current work exploring the potential clinical use of optogenetics is also described. Approaches which combine optogenetic manipulation and optical voltage measurement are discussed, in terms of platforms that allow real-time manipulation of whole heart electrophysiology in open and closed-loop systems to study optimal ways to terminate spiral arrhythmias. The design and operation of optics-based approaches that allow high-throughput cardiac electrophysiological assays is presented. Finally, emerging techniques of photo-acoustic imaging and stress sensors are described along with strategies for future development and establishment of these techniques in mainstream electrophysiological research.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/csp2.522
