Computational thinking is identified as one of the “essential skills for 21st-Century students.” [1] Studies of CT in school programs are being funded by many organizations, including the United States National Science Foundation. In this paper, we describe “lessons learned” over the first two years of a research program (PREDICTS: Principles and Resources for Educators to Infuse Computational Thinking in the Sciences) with the goal of developing knowledge of how to integrate CT into introductory high school biology and chemistry classes for all students. Using curricular modules developed by program staff, two in biology and two in chemistry, teachers piloting the program engaged students in CT with computational evidence from authentic tools in order to develop understanding of science concepts. Each module, representing about a week of instruction, addresses science ideas in the prescribed course of study for high school programs. Project researchers have collected survey data on teachers’: (1) beliefs about effective science teaching; (2) beliefs about their effectiveness as a science teacher and their students’ ability to learn science, and; (3) content preparedness. In addition, we observed module implementation, collected and analyzed student artifacts, and interviewed teachers at the conclusion of module implementation. Preliminary results indicated some challenges (access to technology, varying levels of experience among students) and cause for optimism (student and teacher engagement in CT and the computational tools used in the modules). Continuing research efforts are described in this paper, along with descriptions of the curricular modules and the use of observations and “CT check-ins” to assess student engagement in, application of, and learning of CT.
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Building Air Quality Sensors & Inspiring Citizen Scientists
Using low-cost electronic components and building blocks, we have developed an effective teaching module where students design and test light-scattering, air-quality sensors to introduce them to chemical and environmental engineering research. This module has been successful in engaging the public, developing citizen scientists, and bridging gaps in understanding. To date, we have visited over 30 middle school and high school classrooms and over 1,000 students.
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- Award ID(s):
- 1642513
- NSF-PAR ID:
- 10067791
- Date Published:
- Journal Name:
- Chemical engineering education
- Volume:
- 52
- Issue:
- 3
- ISSN:
- 0009-2479
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Using low-cost electronic components and building blocks, we have developed an effective teaching module where students design and test light-scattering, air-quality sensors to introduce them to chemical and environmental engineering research. This module has been successful in engaging the public, developing citizen scientists, and bridging gaps in understanding. To date, we have visited over 30 middle school and high school classrooms and over 1,000 students.more » « less
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Abstract The resources for carrying out and analyzing microbial evolution experiments have become more accessible, making it possible to expand these studies beyond the research laboratory and into the classroom. We developed five connected, standards‐aligned yeast evolution laboratory modules, called “yEvo,” for high school students. The modules enable students to take agency in answering open‐ended research questions. In Module 1, students evolve baker's yeast to tolerate an antifungal drug, and in subsequent modules, investigate how evolved yeasts adapted to this stressful condition at both the phenotype and genotype levels. We used pre‐ and post‐surveys from 72 students at two different schools and post‐interviews with students and teachers to assess our program goals and guide module improvement over 3 years. We measured changes in student conceptions, confidence in scientific practices, and interest in STEM careers. Students who participated in yEvo showed improvements in understanding of activity‐specific concepts and reported increased confidence in designing a valid biology experiment. Student experimental data replicated literature findings and has led to new insights into antifungal resistance. The modules and provided materials, alongside “proof of concept” evaluation metrics, will serve as a model for other university researchers and K − 16 classrooms interested in engaging in open‐ended research questions using yeast as a model system.
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Healthcare applications on Voice Personal Assistant System (e.g., Amazon Alexa), have shown a great promise to deliver personalized health services via a conversational interface. However, concerns are also raised about privacy, safety, and service quality. In this paper, we propose VerHealth, to systematically assess health-related applications on Alexa for how well they comply with existing privacy and safety policies. VerHealth contains a static module and a dynamic module based on machine learning that can trigger and detect violation behaviors hidden deep in the interaction threads. We use VerHealth to analyze 813 health-related applications on Alexa by sending over 855,000 probing questions and analyzing 863,000 responses. We also consult with three medical school students (domain experts) to confirm and assess the potential violations. We show that violations are quite common, e.g., 86.36% of them miss disclaimers when providing medical information; 30.23% of them store user physical or mental health data without approval. Domain experts believe that the applications' medical suggestions are often factually-correct but are of poor relevance, and applications should have asked more questions before providing suggestions for over half of the cases. Finally, we use our results to discuss possible directions for improvements.more » « less
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Abstract Many STEM disciplines are underrepresented to High School students. This is problematic as many students' decisions for college are shaped by their experiences and achievements in high school. Short content‐oriented modules have been shown to encourage science identity and otherwise benefit the students' learning. Following the ASBMB's outreach protocol, we developed a short content‐oriented module aimed at a high school biology classroom. Students interacted with 3D models of DNA and transcription factors while exploring structure–function relationships and introductory biochemistry topics. The high school teacher was impressed with the students' response to the module, specifically the ease with which students learned, their enthusiasm, and their recall of the experience. We provide all materials necessary to use this module, including student worksheet and printable model coordinates. We encourage both high school instructors and professional biochemists to consider similar module using physical models.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
