Since the release of ChatGPT in November 2022, national interest in artificial intelligence (AI) tools and applications has skyrocketed. Five days after the release, it reached a million users; and by March 2023 the website reached the billion visits. Questions sparked on how to incorporate the use of AI in schools, if at all.
While AI was already quotidian before November 2022, the acceleration of advancements in machine learning, generative AI, and large language models have made it imperative for AI users to understand how the AI tools are developed, which data is used to train them, their limitations, and what implications do these tools have for our lives and communities. Furthermore, as careers become intertwined with AI, it is crucial for students to develop an interest for using and developing AI solutions.
The NSF ITEST program has invested in AI education research since 2016. Below we've assembled a list of resources from the ITEST community on AI, beginning with the 2022 Artificial Intelligence and Learning: NSF ITEST Projects At-A-Glance.
Just this week, NSF released a Rapid Response Research (RAPID) proposal opportunity for 12-month research grants for research on the use of AI, and the teaching of AI in K-12 classroom and informal settings.
Building the Foundational Skills Needed for Success in Work at the Human-Technology Frontier
Our recently-released paper explores the future of work, expanding the conversation to include the importance of work for social stability, the challenges associated with broadening participation at the Human-Technology Frontier, the psycho-social factors affecting career development at the Human-Technology Frontier and illustrate how the NSF ITEST program is uniquely positioned to add value as an early intervention model for building a robust future ready STEM workforce.
Exploring Artificial Intelligence in English Language Arts with StoryQ
Narrative Modeling with StoryQ
Artificial intelligence (AI) is reshaping society, and AI will almost certainly be among the most dominant factors in the coming decades. While not every student needs to become an AI scientist or engineer, almost everyone will enter a workforce powered and transformed by AI technologies. Preparing youth to enter and engage with an AI-filled future is one of our most critical challenges.
STELAR Webinar: Future Work at the Human-Technology Frontier
On Thursday, January 25, the STELAR authors of Building the Foundational Skills Needed for Success in Work at the Human-Technology Frontier presented in the first of four webinars in our series exploring the educational and social implications of living, learning and working in a future driven by technology.
DAILy AI Concept Inventory - questions related to artificial intelligence
In this survey you will be asked to answer a series of questions related to artificial intelligence (AI). The purpose of these questions is to capture your pre-existing ideas about AI and AI concept knowledge before you start the Everyday AI program. So it’s totally OK if you are unsure of a lot of your answers - Just make your best guesses! We will not grade your answers. This survey data will be used to help us figure out what you have learned through this program (between the start and end of the program) so that we can make the program better!
Towards an Understanding of Affect and Knowledge from Student Interaction with an Intelligent Tutoring System
Csikszentmihalyi’s Flow theory states that a balance between challenge and skill leads to high engagement, overwhelming challenge leads to anxiety or frustration, and insufficient challenge leads to boredom. In this paper, we test this theory within the context of student interaction with an intelligent tutoring system. Automated detectors of student affect and knowledge were developed, validated, and applied to a large data set.
Artificial Intelligence and Learning: NSF ITEST Projects At-A-Glance
Artificial intelligence (AI) is permeating the world around us, changing the ways we live, work, and learn. The National Science Foundation (NSF) lists AI as one of its organization-wide priorities, and is encouraging programs like ITEST to pursue what it means to prepare youth for careers in AI. In response to this, the STELAR convened an AI working group comprised of more than 20 projects funded through a variety of NSF programs.