Computer Science As a Test Case (Research to Practice)AbstractIntroduction: Because developing integrated computer science (CS) curriculum is aresource-intensive process, there is interest in leveraging the capabilities of AI tools, includinglarge language models (LLMs), to streamline this task. However, given the novelty of LLMs,little is known about their ability to generate appropriate curriculum content.Research Question: How do current LLMs perform on the task of creating appropriate learningactivities for integrated computer science education?Methods: We tested two LLMs (Claude 3.5 Sonnet and ChatGPT 4-o) by providing them with asubset of K-12 national learning standards for both CS and language arts and
STEM majors to reconnect with and definehuman talents and abilities to solve human problems and develop technological solutions.IntroductionGenerative Artificial Intelligence (GenAI) offers tools to transform K-12 science, engineering,technology, and mathematics (STEM) education. Teachers can use GenAI technology such asChatGPT to supplement their teaching methods or create content such as course outlines andquizzes; students can use it to help with homework and to receive formative feedback on theirwork [1, 2]. ChatGPT is a large-lanuage model (LLM) chatbot; it generates human-like textresponses based on training from a large amount of data [3]. A March 2023 survey of 1,002 K-12teachers found that over half of respondents (51%) reported using
, 2022, and 2023. A total of 78 students and 3 teachers participated in the program during thistime period.Each team of students submits a project report at the end of the spring semester as part of the programrequirements.3.3 Data Collection Instrument(s)For this study, a total of 10 reports were randomly selected from the participants' submissions. Thesereports were analyzed using Open ChatGPT to explore the students' experiences in the Dual-CreditEngineering program.Open ChatGPT was utilized to conduct a thematic analysis of the reports. Each report was inputted intoOpen ChatGPT, which generated codes based on its content. These codes were then combined to formoverall themes across all 10 reports.The procedure for thematic analysis with Open
Research and Practice in Technology Enhanced Learning. He is also the upcoming Program Chair-Elect of the PCEE Division at ASEE. His current research interests include STEM+C education, specifically artificial intelligence literacy, computational thinking, and engineering. ©American Society for Engineering Education, 2024 K-12 STEM Pre-Service Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress)AbstractRecent technological advancements have led to the emergence of generative artificialintelligence (GenAI) applications like Gemini and ChatGPT. Consequently, these applications ofAI and others have proliferated aspects of daily life. Notably, there is a growing
developing systemscapable of performing tasks that usually require human intelligence, including learning,reasoning, and decision-making [21]. Generative AI (Gen-AI) is a subset of AI thatspecializes in creating human-like content, including text, images, and audio [22]. With AI'srecent innovations, many have explored its educational applications. Many educatorscurrently utilize AI tools to increase efficiency within the classroom [1]. Two examples ofGen AI tools include 1) ChatGPT, a generative AI chatbot, and 2) Grammarly, an AI-powered writing assistant. Both tools have proven valuable educational assistants [2, 3].GenAI can help educators with tasks like creating assessments and streamliningadministrative tasks and lessons [23, 24]. In the field
for educators and policymakers to enhance AI literacy among kindergarten teachers.IntroductionEducation, one of the industries most significantly impacted by rapid advancements in artificialintelligence (AI), is on the brink of a revolution. Since the introduction of generative AItechnologies in 2022, as demonstrated by ChatGPT and other platforms, the potential of thesetools to revolutionize a range of educational processes has come to light more and more [1]. AIenables a revolutionary change in education by utilizing its powers in data analysis, patternrecognition, and personalized feedback. In addition to improving teaching strategies, thistechnology is changing how students learn, encouraging participation and comprehension [2, 3
describe – all of whichare at the lowest two Bloom’s levels. Thus, it seems to be the case that the different standardsemphasize lower-order thinking skills.It is perhaps surprising given the recent expansion of AI technologies that the least paralleledCSTA standard concerns the implementation of AI algorithms. However, that expansion is sorecent – largely stemming from the November 2022 introduction of ChatGPT – that it has not yethad an impact on learning standards at scale. We anticipate that future iterations of state andCSTA standards will probably focus more on AI. Many states adopted their standards between2016 and 2022 – a narrow window in itself, with significant policy implications.Third, the most frequent difference between the state
Research Traineeship(TRANSCEND) under Grant No. 2152202 at the time this research was conducted. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation.During the preparation of this paper, the authors used OpenAI’s ChatGPT models as a writingassistant to check grammar and to enhance the clarity of the written text. These models wereused with extreme oversight and care. The authors have reviewed and edited the output and takefull responsibility for the content of this publication.Ethics StatementThe study regarding human subjects was reviewed and approved by the University ofConnecticut’s Storrs-campus Institutional
. Students generated a wall ofideas, with over three hundred ideas written on brightly colored sticky notes. For the initialideation round, students were asked to think of societal problems without the assistance of theirphones or computers. After they seemed exhausted thinking on their own, with 5-10 ideas each,they were next directed to use available resources to gather ideas. Facilitators suggested thatstudents review UN Sustainable Development Goals and explore global grand challenge lists.In the third ideation phase, students were guided to use generative AI applications and to recordand share their iteration process in prompting. The decision to support the exploration of productideas with ChatGPT was not made lightly. Aligned with