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Teaching Special Seminar: Mai Dahshan, "Pedagogical Practices in Teaching Computer Programming Classes"

Event Type
Seminar/Symposium
Sponsor
Illinois Computer Science
Virtual
wifi event
Date
Feb 1, 2024   9:00 am  
Views
57
Originating Calendar
Computer Science Special Seminar Series

Zoom: https://illinois.zoom.us/j/84208571563?pwd=QmZtR2tOLzlDTUJVZ0REQ1ZZNU1Tdz09

Abstract: 
Teaching computer programming has become more challenging with the ever-evolving landscape of technology. These challenges are further heightened when students come from diverse backgrounds and cultures. Teaching is a lifelong learning process, with no universal approach or pedagogy that fits every scenario. This talk will provide an overview of key pedagogical practices for instructing programming concepts. It will explore various strategies, including active learning, flipped classroom models, and peer programming, with an emphasis on active learning. This involves methodologies such as interactive lectures that connect theoretical knowledge to the latest industry trends and practices, encouraging students to engage actively with programming concepts and develop their problem-solving skills. The talk will also dive into the exploration of diverse assessment methods, offering constructive feedback to guide students in enhancing their coding and critical thinking abilities. In addition, inclusive teaching practices will be highlighted to foster a supportive learning environment that recognizes diverse learning styles and backgrounds. In conclusion, the talk will discuss future plans for approaches to cultivate a dynamic and enriching environment for teaching computer programming.

Bio:
Mai Dahshan is an assistant professor in the School of Computing at the University of North Florida. Mai's research interests span Computer Education, Human-Computer Interaction, Scientific Visualization, and Machine Learning. Her current research focuses on preparing STEM K–12 educators to integrate computational thinking across subject areas. She also designs, develops, and evaluates visual analytics tools aimed at supporting scientists in the geoscience and medical domains to explore, understand, and make sense of their data. She earned a Ph.D. in Computer Science from Virginia Tech in 2021. She also worked as a research intern at Los Alamos National Lab in the summer of 2019 and as a graduate research assistant at the Virginia Tech Advanced Research Computing (ARC) Center from 2016 to 2021.

Faculty Host: Brad Solomon

Meeting ID: 842 0857 1563 ; Password: csillinois

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