Current Affiliation: University of Washington Information School
Monday, January 14, 2019 @ 11:00am-12:30pm
Room 1242, CSE Building
Talk Title: Support Students by Teaching How to Think Like a Computer Scientist
(CSE Colloquium Lecture Series)
I believe all students who want to learn computer science can. However, many students, particularly those from underrepresented populations, lack valuable experiences that contributes to adopting a computer science mindset. Supporting these students by explicitly teaching how to think like a computer scientist can lead to more confident, independent, and self-confident students. If we can retain these students, especially those from underrepresented groups, it would help meet the growing demand for computer scientists while also increasing diversity.
In this talk I will outline my efforts and future goals to increase diversity in computer science through my teaching. I will describe my background and perspective on how we can increase diversity in computer science. I will describe my research on understanding how programmers solve programming problems and how we might develop teaching methodologies to teach programming in a way that supports students from a variety of backgrounds and cognitive styles. I will then demonstrate some teaching techniques to get students to think critically about their own thinking and draw upon past experience to solve problems and relate to programming concepts. I’ll close with a projection of my future trajectory in both teaching and research collaborations.
Dastyni Loksa is a Ph.D. candidate from the University of Washington Information school. He has worked for several technology companies including VeriSign, Bandai Namco, and Signio and brings a perspective of computer science primarily as an opportunity for innovation and beneficial cultural impact. He believes computer science is an inherently creative discipline and that the field would benefit greatly by facilitating the inclusion of creative thinkers who might otherwise pursue fields like art or design. To this end, his research is focused on understanding how programmers think while solving programming problems and how we might explicitly teach problem solving for programming. He has investigated how programmers’ metacognition (thinking about their own problem solving process) develops and how it impacts their programming success. He has also found that teaching a problem solving framework for how to think about programming problems and scaffolding practice using it creates more productive, independent, and confident students. He has published research at the International Computing Education Research (ICER), Computer Science Education (SIGCSE), and Conference on Human Factors in Computing (CHI) conferences.
Faculty Host: Leo Porter