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Engineering Technology (ET) programs at community colleges and colleges/universities play a vital role in meeting the growing national demand for STEM graduates. Many accredited ET programs feature design projects that allow students to apply content knowledge and gain valuable workplace skills. Undergraduate research, especially inquiry-based projects, helps students take ownership of their own learning and see the real-world relevance of research as they learn problem-solving skills. EvaluateUR-CURE, an evidence-based method developed at SUNY Buffalo, measures a broad range of desirable outcomes that include both content knowledge and outcomes that are critically important in the workplace, such as communication skills, creativity, autonomy, an ability to overcome obstacles, critical thinking, and problem-solving skills. EvaluateUR-CURE also provides students opportunities to develop metacognitive skills as a way to identify how much academic progress they have made or still need to make. This paper addresses the process of development of performance indicators and presents the results of assessment and evaluation of ETAC ABET student outcomes and outcome categories of EvaluateUR-CURE.
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When Workers Want to Say No: A View into Critical Consciousness and Workplace Democracy in Data Work
In this paper, we describe and reflect upon the development of critical consciousness and workplace democracy within an experimental workplace called DataWorks. Through DataWorks, we hire adults from communities historically minoritized in computing education and data careers, and train them in entry-level data skills developed through work on client projects. In this process, workers gain a range of skills. Some of these skills are technical, such as programming for data analysis; some are managerial, such as scoping and bidding projects; others are social, perhaps even political, such as the ability to say No to projects. In what follows, we describe a workshop series developed to build the workers' critical literacy and consciousness about their data work, specifically regarding the use of data in machine learning systems. After that, we describe a data project the workers questioned and resisted because they determined the work to be harmful. In that process, they demonstrated and enacted a critical consciousness towards data and machine learning. Reflecting on this enactment of data-focused critical consciousness, we identify themes that characterize a democratic workplace, describe the work of designing for organizational action and institutional relations, and discuss how worker and researcher positionality affects this work. In doing so, we argue for enabling workers to resist and refuse harmful data work and challenge the standard power structures of academic research and data work.
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- Award ID(s):
- 1951818
- PAR ID:
- 10548248
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 8
- Issue:
- CSCW1
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 24
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3637433
