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.

How do we as teachers balance the need of students to practice class content with their intense schedules, extracurriculars, and need for a healthy and balanced life? An alternative to traditional, mandatory homework is offered herein, in the form of a Suggested Practice document and classroom routine for incorporating self-selected practice into your classroom structure. These documents break each unit down by topic, offer practice opportunities, provide resource links, and include reminders of labs, assessments, or extension opportunities that accompany the unit. By building a clear classroom routine around this optional practice, students are encouraged to take ownership over their own learning in a way that allows them to create balance in their own lives and prepare for college, while also providing immediate feedback and differentiation on practice materials. The author shares the impact such a routine had on her own classroom environment and engagement, and recommendations for building successful Suggested Practice documents of your own.

As applications of AI have proliferated, the call has grown for educating students about what AI is, how it works, and how it can affect us. In response, [an American University], in collaboration with an external implementation partner, developed 12 modular, short-format curricula for educators of students aged 5-18 years to use for developing AI literacy among students. The curricula incorporate the National Research Council’s core ideas of engineering design. This article describes the curricula, how they were implemented in 2022-23, and findings from an external evaluation on the impact of this AI literacy initiative. In survey responses and interviews, teachers reported that both they and their students gained knowledge about how AI works, key AI concepts, current uses of AI, and potential benefits and harms to society. In addition, learning more about AI increased their levels of optimism about the potential benefits of AI to society and about their own abilities to contribute to shaping the future of AI. The reported impact is impressive given how little time students engage in the curriculum content relative to other topics and subjects they study.

Artificial Intelligence (AI) has taken the world by storm, consequently bringing a hurricane to the seas of education. The purpose of this article is to encapsulate commonly used classroom strategies into practices that can effectively build content acquisition yet preserve academic integrity. Implementing these best practices is as simple as knowing the ABCs of Teaching with AI: Apply, Build, and Collaborate. Encouraging students to be responsible users of content gathered from AI while primarily focusing instruction on the Science and Engineering Practices (SEPs) will support authentic learning in an age of AI. AI is here to stay; educators must adjust their methodology to allow students to grow and learn alongside its capabilities. By embracing the knowledge available through AI and adjusting instructional practices, educators can support using AI as a tool for growth and not a crutch hindering stride.

It is critical to understand past science education reform to know what could be explored in the future (Cheng et al., 2010). The purpose of this position paper is to describe a historical timeline of science education. Using historical documents and current science education research, the authors create an evolutionary description of science education changes over time and how these shifts could influence how Artificial Intelligence is used in science education. Teachers should meaningfully implement the use of AI in ways that focuses on student-centered learning and restore the progress made by the K-12 Framework and NGSS, including generating ideas about problems that students can solve in an interest area, analyzing large sets of real-world data, generating grade appropriate science readings to develop background knowledge, and using AI to grade unique student work to replace multiple-choice response exams. AI and science education may best be described by a Chat GPT response… “It's important to note that while AI can enhance science education, it should not replace human teachers. Instead, it should be used as a tool to augment and support their expertise, fostering a blended learning environment that combines the benefits of technology with human guidance and mentorship”.

An interview with metallurgical engineer Wendi Cooksey