An interview with metallurgical engineer Wendi Cooksey

An interview with Kate Harding

Within this Idea Bank, we offer practical strategies to integrate ChatGPT across three science and engineering practices (i.e., asking questions and defining problems, planning and carrying out investigations, and analyzing and interpreting data) during engineering design challenges. ChatGPT offers newfound student choice, interest, and motivation, and we share relevant and useful prompts to guide student application in the aforementioned SEP outcomes. To meet the “asking questions and defining problems” outcome, students can use closed- and open-ended questions in ChatGPT throughout the engineering design challenge to engage in inquiry. This practice can help students better conceptualize the initial challenge by introducing and unpacking relevant factors, variables, constraints, criteria, theories, and characteristics. To improve access in understanding the challenge, ChatGPT presents an on-demand option that elaborates unfamiliar terms, translates terminology or text to another language, and introduces text-based scaffolding. To address the “planning and carrying out investigations” and “analyzing and interpreting data” outcomes, ChatGPT supports extended opportunities to brainstorm possible investigations and solutions, conduct theoretical experiments with conceptual and hypothetical results, analyze data both qualitatively and quantitatively, and suggest follow-up options from data analysis. Thus, ChatGPT enhances opportunities for SEP outcomes within engineering design challenges.

What other profession gives summers off, with the bonus of teaching in different locations? In this article I’ll tell how taking leaves of absence to teach at other locations was one of the opportunities that I enjoyed, which hopefully is available to other teachers as well.

This paper describes the design and implementation of a week-long engineering summer camp that engages pre-college learners in human-centered design principles. Students worked in teams of 3-5 to create and present a viable prototype for a specified user group. The one-week camp engaged students in understanding, ideating, and low-fidelity prototyping. Takeaways from the camp design and implementation are described and possible adaptations to high school science classroom contexts are discussed.

The Next Generation Science Standards (NGSS) define science literacy as having the knowledge and understanding of scientific concepts and processes and the ability to question natural world phenomena (National Research Council, 2012). When students work with texts that deal with real world issues, they can look for claims supported by evidence (Berland, et al., 2017; Levin et al., 2021) and work with reasoning of other students through interactive conversations about the data and sharing of ideas (Michales & O’Connor, 2017). Therefore, integrating scientific arguments into the classroom is an important step in developing scientific literacy (Cavagnetto, 2010) as it helps students engage in authentic learning through a variety of practices and methods to construct and evaluate claims (Ford, 2012). In our teaching and professional learning programs, we address the question of how to meaningfully assess students' science literacy and ability to engage in science argumentation through a CER framework that incorporates the Next Generation Science Standards (NGSS, 2013). The answer to our inquiry was the development of Scenario-based Assessments (SBA). This article explains the elements of an SBA and presents the findings of using SBAs in middle and high school STEM classrooms.

Students are provided with plenty of opportunities to acquire new knowledge based on the various scientific disciplines they explore in their schooling. However, it can sometimes be difficult to integrate activities that build scientific literacy amidst all of the other assignments. This idea bank shares an assignment that encourages students to read scientific articles of their choosing and write abstracts based on what they read. Students are introduced to popular science magazines such as National Geographic and Popular Science and given time to explore the various topics that those magazines write about. After that, they are introduced to the "Science, science, read all about it!" assignment and informed that they will be writing abstracts based on their readings. Students are then provided background on the purpose of an abstract, as well as an example. This recurring assignment is due on a bi-weekly basis throughout the school year and allows students to continually engage with literature, build scientific literacy, and improve their skills in writing and abstract which may also benefit them in the future. Overall, it is important for students to build scientific literacy as they embark on their journey through life.

Plausible scientific arguments abound. Those who wish to deceive often weave a tangled web of plausible scientific arguments to support their case. What can the science teacher do to prevent their students being duped? Given that many of the claims are scientific – which says something about the importance of scientific authority in our culture – science education must surely stand at the forefront of building students’ capacity to detect the true from the flawed – but seemingly plausible argument. Fact or faux? Equipping students to navigate the maze of misinformation, though, needs clarity about the challenge and clarity about the methods.

Over the past few years, computer science education has expanded globally, including aspects of artificial intelligence (AI), especially in graduate and undergraduate education settings. However, less has been accomplished regarding how to introduce AI to K-12 students. While many K-12 students regularly interact with AI in the form of predictive text, facial recognition, cellphone voice assistants, etc., there has been little effort made by educational researchers regarding how best to introduce K-12 students to AI and help them understand how it works. However, the AI for K-12 Working Group is developing national guidelines for K-12 AI education (Touretzky et al., 2019). AI has become ubiquitous, revolutionizing many of the fields it touches, from medicine to education to the business world, and its capabilities are rapidly expanding along with its role across the globe. AI is applicable across multiple contexts, including K-12 education, and students need to be learning what it is and how it works from a young age so they will be better prepared for a future where AI plays a prominent role. In this article, the author shares three lessons that serve to introduce high school students to artificial intelligence/machine learning.