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The primary goal of the authentic learning approach is to engage and motivate students in learning real world problem solving. We report our experience in developing k-nearest neighbor (KNN) classification for anomaly user behavior detection, one of the authentic machine learning for cybersecurity (ML4Cybr) learning modules based on 10 cybersecurity (CybrS) cases with machine learning (ML) solutions. All portable labs are made available on Google CoLab. So students can access and practice these hands-on labs anywhere and anytime without software installation and configuration which will engage students in learning concepts immediately and getting more experience for hands-on problem solving skills.
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Designing Professional Learning Workshop for Shaping Teachers' Learning Pedagogical Content Knowledge in Computational Thinking
The study focuses on understanding the discourse, interaction, and problem-solving relating to pedagogical content knowledge (PCK) demonstrated by teachers in one professional training workshop on Computational Thinking (CT) and its implementations in classrooms.
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- Award ID(s):
- 2331742
- PAR ID:
- 10475890
- Editor(s):
- Blikstein, P.; Van Aalst, J.; Kizito, R.; & Brennan K.
- Publisher / Repository:
- International Society of the Learning Sciences
- Date Published:
- Journal Name:
- Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023
- ISSN:
- 1573-4552
- ISBN:
- 978-1-7373306-7-7
- Page Range / eLocation ID:
- 2071-2072
- Format(s):
- Medium: X
- Location:
- Montreal, Canada
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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