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Student Perceptions of Their Abilities and Learning Environment in Large Introductory Computer Programming Courses

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

Action on Diversity - Supporting Students at Multiple Levels

Tagged Topics

Diversity and ASEE Diversity Committee

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Paper Authors


Laura K Alford University of Michigan

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Laura K. Alford is a Lecturer and Research Investigator at the University of Michigan.

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Mary Lou Dorf University of Michigan

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Mary Lou Dorf received a B.S. from Alma College (1967). She received a M.S. in mathematics (1969) and the Ph.D. (1990) in systems engineering both from the University of Toledo. In Jan 2002, she joined the Electrical Engineering and Computer Science Department at the University of Michigan as a Lecturer. She has received multiple awards for her innovations in teaching and excellence in service. Her research interests include women in computer science and engineering education. Her current efforts are on increasing the number of women who declare computer science as a major

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Valeria Bertacco University of Michigan

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Over the past 30 years, women completing Computer Science and Computer Engineering undergraduate degrees have been a minority compared to their male counterparts [1]. Perhaps relatedly, studies often find that women have lower self-efficacy in STEM fields [e.g., 2]. As part of the continual improvement process for creating an inclusive learning environment in introduction to computer courses, we wished to gather current information on students’ perceptions of their own abilities and the overall learning environment in introductory programming courses. This information will then be used to guide future course development and possible interventions.

Entry and exit surveys were administered to students in two different large-enrollment (~700 students/semester) intro to computer programming courses at a large, midwestern research university. Course 1A is for first-year engineering students only; Course 1B is open to all students in the university. The Entry Survey gives insight to the students' perceptions at the beginning of the semester. The Exit Survey gives insight as to whether certain interventions (including having students take an implicit association test, reflect on the test, and attend a lecture on implicit bias) were effective.

The surveys were also administered to students in the follow-up computer programming course (designated here as Course 2 and consisting of mostly first- and second-year engineering students) to see if there were any changes in student perceptions after taking two programming courses.

Student survey responses from 1,208 students (432 women, 776 men, self-reported gender) are reported in this project.

The surveys asked about grades: What grade do you hope to get in this course? How confident are you that you can achieve this grade? (Entry Survey) What grade do you expect to get in this course? What grade do you think you deserve to get in this course? (Exit Survey)

Students were also asked on both surveys to provide their level of agreement to the following questions/statements: Do you think you will be/were successful in this course? I find computer programming intimidating. I believe that other students in computer programming courses will be welcoming of me. How interested are you in majoring or minoring in Computer Science or Computer Engineering?

These questions can be considered to be indicators of students’ confidence in their ability to succeed in a computer programming course (self-efficacy).

In this paper, we will present the full set of responses from students. As might be expected, women are still more intimidated by computer programming in the beginning, despite continued efforts to close the gap. Generally, the intimidation for both men and women decreases by the end of the class, but there is still a difference between men and women. Instructors for these types of large-enrollment courses need to be aware of these student perceptions so as to create opportunities for all students to succeed.


[1] National Center for Education Statistics (NCES), "Degrees in computer and information sciences conferred by level of degree and sex of student (Table 325.35)," in Digest of Education Statistics - 2013 edition, [2] A. Rittmayer and M. Beier, "Overview: Self-Efficacy in STEM," in SWE-AWE CASEE Overviews, 2008.

Alford, L. K., & Dorf, M. L., & Bertacco, V. (2017, June), Student Perceptions of Their Abilities and Learning Environment in Large Introductory Computer Programming Courses Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28867

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