Choosing Their Own Way: Guided Self-Placement for Students in an Introductory Programming Sequence
This program is tentative and subject to change.
As part of redesigning our introductory programming sequence, Anonymous University removed formal prerequisites from each course, allowing students to self-select into whichever course they believe best fits their experience level. To help facilitate these choices, we developed a guided self-placement tool that offers course recommendations based on students’ previous experience and confidence with course topics. In this report, we describe the design and implementation of the self-placement tool and reflect on its first years of use. The tool has been effective, with most students reporting that they used the tool, followed its recommendation, and are confident in their enrollment decision. The rates of students switching or dropping courses within the introductory sequence have been low. In addition, results from a preliminary interview study show that all students who followed the tool’s recommen- dation believed the suggested course was the right choice. Most students who opted for a different course were influenced by exter- nal factors, largely related to their confidence in the course content and perception of course difficulty levels. We conclude by reflecting on what we have learned so far and laying out next steps.
This program is tentative and subject to change.
Thu 19 FebDisplayed time zone: Central Time (US & Canada) change
15:40 - 17:00 | |||
15:40 20mTalk | Analogical Reasoning in Undergraduate Algorithms Papers Jonathan Liu University of Chicago, Erica Goodwin University of Chicago, Diana Franklin University of Chicago | ||
16:00 20mTalk | Choosing Their Own Way: Guided Self-Placement for Students in an Introductory Programming Sequence Papers Brett Wortzman pc, Melissa Chen Northwestern University, Miya Natsuhara pc, Eleanor O'Rourke Northwestern University | ||
16:20 20mTalk | Investigating Answer Choice Bias within a College-Level Introductory Computing Assessment Papers Miranda Parker University of North Carolina Charlotte, Sin Yu Ciou University of Washington, Yale Quan University of Washington, He Ren University of Washington, Chun Wang University of Washington, Min Li University of Washington | ||
16:40 20mTalk | Performance and Start-Time Trends in Asynchronous Computer-Based AssessmentsGlobal Papers Iris Xu University of British Columbia, Romina Mahinpei Princeton University, Steve Wolfman University of British Columbia, Firas Moosvi University of British Columbia Okanagan | ||