As computing skills become necessary for 21st-century students, infused computational thinking (CT) lessons must be created for core courses to truly provide computing education for all. This will bring challenges as students will have widely varying experience and programming ability. Additionally, STEM teachers might have little experience teaching CT and instructing using unfamiliar technology might create discomfort. We present a design pattern for infused CT assignments that scaffold students and teachers into block-based programming environments. Beginning with existing code, students and teachers work together 'Using' and comprehending code before 'Modifying' it together to fix their programs. The activity ends with students 'Choosing' their own extensions from a pre-set list. We present a comparison of two implementations of a simulation activity, one ending with student choosing how to extend their models and one having all students create the same option. Through triangulating data from classroom observations, student feedback, teacher interviews, and programming interaction logs, we present support for student and teacher preference of the 'Student-Choice' model. We end with recommended strategies for developing curricula that follow our design model. 
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                    This content will become publicly available on January 22, 2026
                            
                            Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools
                        
                    
    
            Generative AI (GenAI) is advancing rapidly, and the literature in computing education is expanding almost as quickly. Initial responses to GenAI tools were mixed between panic and utopian optimism. Many were fast to point out the opportunities and challenges of GenAI. Researchers reported that these new tools are capable of solving most introductory programming tasks and are causing disruptions throughout the curriculum. These tools can write and explain code, enhance error messages, create resources for instructors, and even provide feedback and help for students like a traditional teaching assistant. In 2024, new research started to emerge on the effects of GenAI usage in the computing classroom. These new data involve the use of GenAI to support classroom instruction at scale and to teach students how to code with GenAI. In support of the former, a new class of tools is emerging that can provide personalized feedback to students on their programming assignments or teach both programming and prompting skills at the same time. With the literature expanding so rapidly, this report aims to summarize and explain what is happening on the ground in computing classrooms. We provide a systematic literature review; a survey of educators and industry professionals; and interviews with educators using GenAI in their courses, educators studying GenAI, and researchers who create GenAI tools to support computing education. The triangulation of these methods and data sources expands the understanding of GenAI usage and perceptions at this critical moment for our community. 
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                            - Award ID(s):
- 2417374
- PAR ID:
- 10635629
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400712081
- Page Range / eLocation ID:
- 300 to 338
- Subject(s) / Keyword(s):
- generative AI GenAI large language models artificial intelligence pedagogical practices teaching computing computing education
- Format(s):
- Medium: X
- Location:
- Milan Italy
- Sponsoring Org:
- National Science Foundation
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