User:Grave Isotope/Computing education
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Generative AI and Computing Education
[edit]Generative Artificial Intelligence (GAI) is becoming more popular and widespread in the public sector.[1] Both teachers and students have reported to believing that it is a useful educational tool, while expressing concerns about over-reliance during learning.[2] GAI has been known to hallucinate information, causing concerns for the trustworthiness of the information it provides. More work on how to use these tools needs to occur for effective teaching.[3]
Teaching Methods - Algorithm Visualization
[edit]
It can be difficult to effectively teach the interactive components of computing or the way an algorithm works with static text and images that are popular in textbooks and lectures. Instructors often utilize document cameras or classroom boards to draw out the processes and supplement the verbal explanation.[4] The drawings are subject to frequent changes throughout the walkthrough of the process, causing challenges for students to grasp the concepts. To combat this problem, an interest in Algorithm Visualization has developed to demonstrate dynamic systems.
Algorithm Visualization dates back to the early 1980’s with Baecker's Sorting Out Sorting.[5] If used effectively, it can graphically demonstrate different states of algorithms in engaging ways. This helps students focus on the conceptual aspects of a process without worrying about the implementation such as memory addresses and specific function calls.[4] Increased use of algorithm visualization engagement by students typically results in better learning for the students.[6]
Algorithm Visualization can be used for a myriad of different topics. Data structures, graph algorithms, and sorting algorithms are all examples of computation based concepts where students can benefit from learning about with the aid of an algorithm visualization.
Accessibility
[edit]Both government and private industry are showing increasing interest in developing software that is accessible to everyone, including people with disabilities.[7] Although there is a strong demand, only 2% of industry leaders indicate that finding candidates with the required accessibility skills is easy or very easy.[8] As a result, teaching accessibility in computer science classrooms is becoming more important, which involves the communication of metainformation surrounding information and accessibility. Current approaches include course integration and teaching accessibility knowledge.[9]
Course integration takes multiple disciplines and combines them into one class or program. There are three main types of integration: special topics courses, thematic courses, and module integration. Special topic courses is when a given discipline is the entire topic of a course[10], i.e. a course on accessibility within an Information school. Thematic courses are when a class is not about a given topic directly, but rather use a topic as a focus or lens to teach the primary topic[11], for example teaching User experience design through the perception of disabled users. Module Integration teaches a given topic in an isolated unit, like a web design class having a unit on optimizing a website for screen-readers.
Teaching accessibility knowledge directly teaches accessibility throughout an entire program by teaching how a subfield can encourage accessible practices.[12] This includes, but is not limited to, screen readers, adaptive keyboards, and screen magnifiers, captioning and subtitle services, and diction software. These can be applicable in several computational subfields such has web development, human computer interaction, and software engineering.
There exists a gap in the support that instructors have while teaching accessibility that is rooted in a lack of knowledge on the different approaches to teaching accessibility.[9] University of Washington, Gallaudet University, Tufts University, and University of California Irvine have collaborated with AccessComputing, a program designed to help instructors and students increase disability representation in careers in computing.[13]
References
[edit]- ^ Bright, Jonathan; Enock, Florence E.; Esnaashari, Saba; Francis, John; Hashem, Youmna; Morgan, Deborah (2024-01-02), Generative AI is already widespread in the public sector, arXiv, doi:10.48550/arXiv.2401.01291, arXiv:2401.01291, retrieved 2025-04-24
- ^ Zastudil, Cynthia; Rogalska, Magdalena; Kapp, Christine; Vaughn, Jennifer; MacNeil, Stephen (October 2023). "Generative AI in Computing Education: Perspectives of Students and Instructors". 2023 IEEE Frontiers in Education Conference (FIE): 1–9. doi:10.1109/FIE58773.2023.10343467.
- ^ Prather, James; Denny, Paul; Leinonen, Juho; Becker, Brett A.; Albluwi, Ibrahim; Craig, Michelle; Keuning, Hieke; Kiesler, Natalie; Kohn, Tobias; Luxton-Reilly, Andrew; MacNeil, Stephen; Petersen, Andrew; Pettit, Raymond; Reeves, Brent N.; Savelka, Jaromir (2023-12-28). "The Robots Are Here: Navigating the Generative AI Revolution in Computing Education". Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education. ITiCSE-WGR '23. New York, NY, USA: Association for Computing Machinery: 108–159. doi:10.1145/3623762.3633499. ISBN 979-8-4007-0405-5.
- ^ a b Fouh, Eric; Akbar, Monika; Shaffer, Clifford A. (2012-01-01). "The Role of Visualization in Computer Science Education". Computers in the Schools. 29 (1–2): 95–117. doi:10.1080/07380569.2012.651422. ISSN 0738-0569.
- ^ Baecker, Ronald (1998). "Sorting Out Sorting A Case Study of Software Visualization for Teaching Computer Science" (PDF). Software Visualization: Programming as a Multimedia Experience. MIT Press: 369–381.
- ^ Grissom, Scott; McNally, Myles F.; Naps, Tom (2003-06-11). "Algorithm visualization in CS education: comparing levels of student engagement". Proceedings of the 2003 ACM symposium on Software visualization. SoftVis '03. New York, NY, USA: Association for Computing Machinery: 87–94. doi:10.1145/774833.774846. ISBN 978-1-58113-642-5.
- ^ "Teaching Digital Accessibility in Computing Education: Views of Educators in India". arxiv.org. Retrieved 2025-02-26.
- ^ "Accessible Technology Skills Gap – Teach Access". Retrieved 2025-02-26.
- ^ a b Baker, Catherine M.; El-Glaly, Yasmine N.; Shinohara, Kristen (2020-02-26). "A Systematic Analysis of Accessibility in Computing Education Research". Proceedings of the 51st ACM Technical Symposium on Computer Science Education. SIGCSE '20. New York, NY, USA: Association for Computing Machinery: 107–113. doi:10.1145/3328778.3366843. ISBN 978-1-4503-6793-6.
- ^ Ryker, Randy; Fanguy, Ronnie; Legendre, Amy (2008-12-01). "Undergraduate Special Topics Courses: What's on the Menu?". Journal of Computer Information Systems. 49 (2): 81–85. doi:10.1080/08874417.2009.11646051. ISSN 0887-4417.
- ^ Dreher, Heinz, Nick Scerbakov, and Denis Helic. "Thematic driven learning." E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. Association for the Advancement of Computing in Education (AACE), 2004.
- ^ Ladner, Richard R.; Ludi, Stephanie; Domanski, Robert J. "Teaching about Accessibility in Computer Science Education" (PDF). Association for Computing Machinery – via CS2023.
- ^ "AccessComputing". CSforALL. Retrieved 2025-02-26.