1 research outputs found
Subgoals, Problem Solving Phases, and Sources of Knowledge: A Complex Mangle
Educational researchers have increasingly drawn attention to how students
develop computational thinking (CT) skills, including in science, math, and
literacy contexts. A key component of CT is the process of abstraction, a
particularly challenging concept for novice programmers, but one vital to
problem solving. We propose a framework based on situated cognition that can be
used to document how instructors and students communicate about abstractions
during the problem solving process. We develop this framework in a multimodal
interaction analysis of a 32-minute long excerpt of a middle school student
working in the PixelBots JavaScript programming environment at a two-week
summer programming workshop taught by undergraduate CS majors. Through a
microgenetic analysis of the process of teaching and learning about abstraction
in this excerpt, we document the extemporaneous prioritization of subgoals and
the back-and-forth coordination of problem solving phases. In our case study,
we identify that (a) problem solving phases are nested with several instances
of context-switching within a single phase; (b) the introduction of new ideas
and information create bridges or opportunities to move between different
problem solving phases; (c) planning to solve a problem is a non-linear
process; and (d) pedagogical moves such as modeling and prompting highlight
situated resources and advance problem solving. Future research should address
how to help students structure subgoals and reflect on connections between
problem solving phases, and how to help instructors reflect on their routes to
supporting students in the problem solving process.Comment: ACM Student Research Competition (SRC) submission in Proceedings of
the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19);
3 pages; Poster:
https://docs.google.com/drawings/d/1OrfWGp7-o8sI7KJyx4-leY-A8TioXP1IQFKNBDceht4/edit?usp=sharin