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Integrating AI and Machine Learning Techniques for Teachers of STEM Classes Students

عنوان مقاله: Integrating AI and Machine Learning Techniques for Teachers of STEM Classes Students
شناسه ملی مقاله: SECONGRESS02_029
منتشر شده در دومین کنگره بین المللی علوم، مهندسی و فن آوری های نو در سال 1403
مشخصات نویسندگان مقاله:

Sima Poudineh Jahan Tighi - Department of Management, Islamic Azad University Chabahar Branch, Chabahar, Iran
Navid Ehsanifar Radmanesh - Department of Biomedical Engineering, Islamic Azad University Tehran Branch, Tehran, Iran
Sohila Alizadeh - Department of Information Technology, Sadjad University, Mashhad, Iran

خلاصه مقاله:
This is the retraining plan, comprised of a PD course filled with AI course content and ethics concerns towards the AI bias, directed for teachers so that they acquire knowledge on AI topics and the understanding of ethics involved in AI and become able to integrate AI techniques in their existing STEM subjects. The classroom curriculum is divided into five-day cycles over the topics: Data Analytics, Decision Trees, Machine Learning, RNN Artificial Networks, and Transfer Learning. These modules are constructed through a gradual learning pathway and come with many engaging features such as simulated activities, online tool interactions, and the availability of actual AI model code placed in Google Colab notebooks to construct, train, and evaluate AI models. Educators from spanning biology, chemistry, physics, engineering, and mathematics were a part of the Teacher Professional Development program. This research paper covers the observations from the professional development workshops for instructors, suggesting modifications to the workshops. Finally, we conclude with the benefits and domestic hurdles in getting professors equipped for the use of AI instruction in their disciplinary classrooms.

کلمات کلیدی:
Artificial Intelligence, Machine Learning, STEM, ANN, AI Models

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/2049513/