International Technology and Engineering Educators Association 2024 ITEEA Conference; Memphis, TN
To learn more, visit https://web.cvent.com/event/1f813b5b-d665-4a47-bff0-0d84449da2e8/summary.
To learn more, visit https://web.cvent.com/event/1f813b5b-d665-4a47-bff0-0d84449da2e8/summary.
To learn more, visit https://2024.isls.org/.
To learn more, visit https://conference.iste.org/2024/.
To learn more, visit https://www.cosn.org/cosn2024/.
To learn more, visit https://csedu.scitevents.org/Home.aspx.
To learn more, visit https://cue.org/page/conferences.
This report takes stock of what we currently know as well as what we need to know to make classroom assessment maximally beneficial for the teaching and learning of STEM subject matter in K–12 classrooms.
Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies.
Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies.
This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.
Zhai, X. (2023). ChatGPT for Next Generation Science Learning | XRDS: Crossroads, 29(3), 42-46. https://doi.org/10.1145/3589649
This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.
The need for mathematical modeling is vital in answering critical questions like disease spread and climate change, but beginners lack the necessary skills to plan, organize, and execute such tasks. Also, current tools are insufficient for optimal learning. To address these issues, we're developing a web-based technology (M2Studio) and a 10.5-hour curriculum to introduce students to mathematical modeling using dynamically linked representations. This three-year project aims to enhance students' modeling skills and understanding.