Perceptions of Good Teaching
Teaching in Collegiate Computer Science
J McGrath Cohoon*, Dawn E Reed
University of Virginia
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Perceptions of Good Teaching
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Abstract
Surveys of faculty in 209 of the largest and/or most prestigious undergraduate computing
programs, and interviews with faculty and students in 18 of these programs provide quantitative
and qualitative data about common styles of pedagogy and student perceptions of teaching
quality. Survey results show that the learning facilitation style of pedagogy dominates in this
discipline. Based on comments about quality of teaching and other factors, students frequently
consider faculty to be the most discouraging factor or the most important coping factor in their
experience as computer science majors. Student gender differences were apparent in their ratings
of faculty characteristics and behaviors.
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Teaching in Collegiate Computer Science
Poor teaching has been implicated as one reason undergraduates migrate out of the
computer science major. Concern over the effect this migration has on the already low numbers
of women in the discipline prompted investigations into effective pedagogical practices. The
study reported here describes common pedagogical styles as reported by faculty, and it describes
students’ experience of computer science faculty in the classroom.
Background
“Gender Differences in Learning Styles” Severiens and T.D.
“Gender inequality in educational choices and careers appears to be partially due to the
way students learn”
“Kolb found that women tended to prefer concrete learning styles, whereas men were
more likely to opt for abstract conceptualization modes of learning.” 490
“A Survey of Gender and Learning Styles” (Philbin, Meir et. al.)
“Based on the results of this study, if females are watching and feeling or doing and
thinking, they learn best. If males are thinking and watching, they learn best.”
“A study of Gender Differences in Cognitive style and cognitive volition” Robert Fritz



Males are more field independent (analytical)
Females have higher mean scores for theoretical symbols
Females had conative preferences that suggest a social orientation and sensitivity
to the learning environment.
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
Females, more than males, rely on enculturated values to interpret situations,
desire peer input to organize experience and shape decisions, and want a variety
of instructional modalities to derive meaning from experience.
Field-independence: An analytical style that relates to internal frames of reference.
Active, discovery approach to learning, individual orientation, analytical interests, task
emphasis
Field-dependence: A social style that correlates to external frames of reference. chainlink reasoning process, with-people orientation, social interests, social emphasis, “takes it
as it is” passive in the learning context
-males more Field independent than females
Methods
The data for this paper were collected as part of a three-year study that examined computer
science programs and their undergraduate retention by gender. Two hundred ten study
departments in the contiguous United States were selected based on their rank among the most
prestigious computer science programs and/or their high number of recent computer science
baccalaureates awarded. As a group, the study departments produced approximately 60% of all
Bachelor-level computer science graduates in 1996 **.
Quantitative data were collected from faculty via web, mail, and telephone surveys in the
Spring of 2002. A stratified random sample of up to 25 faculty was selected for each study
department with women over-sampled. Sixty-eight percent of the faculty in 209 study
departments responded to the survey.
Qualitative data were gathered through face-to-face semi-structured interviews and focus
groups at 18 study departments in the Spring of 2001. Interview site selection criteria sought
variety in geographic location, type of institution, and gender composition of the program. Study
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departments were located in four urban locations and three non-urban locations. The urban sites
offered several study institutions in each locale - New York City, Chicago, San Diego/Los
Angeles, and Atlanta. The non-urban sites were all located in the state of Virginia. Eighteen of
the 22 departments (82%) initially selected agreed to be visited.
Coding of qualitative data. For purposes of coding faculty descriptions of their teaching into the
categories of facilitative or transmittive styles of pedagogy, we used the following definitions.
The learning facilitation teaching style included practices that were student-centered, focused on
helping students to learn, sought conceptual change, or involved active learning. Examples of
these practices included discussing open-ended questions and collaborating in groups (Von
Secker & Lissitz), making time for student interaction and conversation with instructor during
lectures (Trigwell, Prosser, & Waterhouse), and engaging students in problem-solving (**Atara
Sivan). The knowledge transmission teaching style included practices that were teacher-centered
and focused on communicating knowledge or content. Examples included lecture and
demonstration (Von Secker & Lissitz), and using media to impart information (Gow & Kember).
Coders used an extended list of definitions and examples to categorize and rate
statements about pedagogical methods in the interview transcripts. For the most part, these
statements came from faculty responses to the question, “How do you usually present the
material [in the required computer science classes you teach]? Responses describing practices
that were clear examples of knowledge transmission were coded as -2; mostly knowledge
transmission were coded as -1. For example, ***. Responses describing practices that were
equally knowledge transmission and learning facilitation were coded as 0. For example, ***
Responses that described mostly learning facilitation were coded as 1; clear examples of learning
facilitation were coded as 2. For example, ***.
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Coders also categorized and rated student comments about pedagogy. These comments
from undergraduate computer science majors usually came in response to the interview
questions, “What experiences have you had that encouraged you to continue or that increased
your initial enthusiasm for computer science here at [institution]?” “List any experiences you
have had that could have discouraged you or reduced your initial enthusiasm for computer
science here at [institution].” “Please take a minute now to write down what encouraged you to
continue or helped you overcome each type of discouraging experience on your list.” Responses
to these questions were discussed in the student focus groups, as were responses to more specific
probes about faculty and classes that encouraged or discouraged students. Strong positive
responses that were shared by several group members were rated as 1. For example, ***. Strong
negative responses …***.
Participating Institutions. The departments responding to the survey all offered 4-year
undergraduate programs, 37 percent offered graduate programs, 75 percent were at public
institutions, and 41% were selective in their undergraduate admissions (38% most selective). Of
those departments responding to the survey, 58 percent offered more than one undergraduate
computing program, and the median program size was 400 undergraduates. On average, the
gender composition of study institutions’ CS programs was 27% female in the mid-1990s.
The 18 departments that hosted interviews represented a broad range of institutional types
and characteristics. Seventy-one percent offered graduate programs, 65 percent were at public
institutions, and 41% were selective in their undergraduate admissions (53% most selective),
with the average incoming freshman scoring 1191 on the SAT. (Four institutions did not report
SAT scores.) On average, the gender composition of the CS programs that participated in this
study’s interviews was 26% female in the mid-1990s.
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Faculty Participants. Of the 1716 faculty who participated in the survey, 33% were Full
Professors, 29% were Associate Professors, 26% were Assistant Professors, and 10% were
Instructors/Lecturers in continuing positions. Sixty-one percent of the faculty respondents were
tenured, 82% were male, 95% were white, and 83% were United States citizens. Their average
age was 48.
The 120 faculty who participated in our interviews were most often white (87%) and
male (74%), although this race and sex did not dominate to the extent it did in the survey. Most
interviewees appeared to be middle aged (48%) or older (31%).
Student Focus Group Participants. The undergraduates who participated in our focus
groups were all current computer science majors. 79 women participated in 16 groups, and 103
men in 16 groups for a total of 182 undergraduates in 31 groups. (One focus group had both male
and female participants.) The participants were generally older than traditional undergraduates,
academically successful, and familiar with the realities of working as computing professionals.
Their average age was 23; more than three quarters of them were upper-level students. Their
mean computer science grade point average was 3.48. Fifty-three percent of them were White.
The second largest racial group was Asian (22%), followed by Hispanic (9%) and Black (8%),
with 9% not responding to this question. Sixty-four percent were employed, 73% of whom used
their computing skills on the job.
Results
[Insert body text here]
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CS departments generally used both types of pedagogical methods, but learning facilitation
dominated.
In all but two interview departments, the pedagogical practices reported most often by
faculty were facilitative as shown in the “mode” column of Table 1. Averaging the ratings of
reported behavior showed that every department but one described learning facilitation pedagogy
as the dominant method. This observation reflects the fact that mastery of computer science
involves the acquisition of skills in addition to information. For example, students must learn
how to program, so actually practicing programming is usually accepted as good procedure.
However there is also much information that students must acquire, so transmission of
knowledge is not uncommon.
These interview results reflect the situation in the computer science discipline as a whole,
as documented by the survey findings about the balance of facilitative and transmittive
pedagogies in undergraduate computer science programs. Eighty-two percent of the faculty in
the average computer science department use facilitative teaching methods. These faculty agreed
that when teaching an undergraduate class, they “provided many opportunities for hands-on
learning.” Another indicator of facilitative pedagogy, holding students “responsible for
independent learning of material not covered in class” was reported by 60% of faculty in the
average department. In contrast, indicators of transmittive pedagogy were less common in the
average CS department. Fifty-five percent of faculty believed that “lecture was the most
important element of instruction,” and 32% of faculty in the average department believed that
“presenting information to the students satisfied [their] responsibility as instructor.”
The survey results also confirm that it was uncommon for a department to utilize only
one type of pedagogy. According to the survey results, only one to nine percent of CS
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departments completely agreed that their faculty taught undergraduate classes in a transmittive
manner. Learning facilitation pedagogy was unanimously employed in a larger percentage of
departments, but it was still only seven to 32 percent of CS departments.
The survey results about the dominant pedagogical methods varied only slightly when a
program’s emphasis on teaching versus research was taken into account. Departments where the
faculty consensus was that teaching was emphasized were a little more likely than departments
that valued external funding to indicate that learning facilitation methods of instruction were
widely used.
Despite this slight variation, the overall picture remained the same. Regardless whether a
department was teaching oriented or research oriented, substantial proportions of the faculty in
undergraduate CS departments employed each type of pedagogical method, but facilitative
methods dominated. Examples of descriptions from the most transmittive and the most
facilitative interview departments illustrate that in the majority of CS departments, faculty
employed both types of pedagogical methods.
When Transmittive Pedagogy dominates. In the department where transmittive pedagogy
dominates, most faculty reported using the following teaching methods: employing an overhead
projector or PowerPoint, taking questions at the beginning and end of class, conducting in-class
exercises, and offering computer lab sessions to provide hands-on experience. The traditional
lecture format they used for introductory classes was described similarly by several professors.
In the words of one,
Broadly speaking my lecturing style is - it's more on the talking-head side, a traditional,
not as interactive as I'd like it to be, but - but that's the fact of the matter. … I teach in a
room that is equipped with a projection system and a computer and so on, and we use
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pretty much this canned pre-arranged stuff. But then I also still have an overhead
projector that I [use for] examples [etc.]. But the lecturing style tends to be more talkinghead than interactive.
This “talking-head” style of an instructor communicating material to passive students was more
common in this department than in any other.
However, the above list of teaching methods clearly contains practices that are not
transmittive. The faculty in this department reported reserving class time for answering student
questions, attempting to ask each student questions that encourage active class participation,
occasionally engaging in some in-class exercises, and providing a computer lab staffed with
graduate teaching assistants to help students through assigned tutorials. Even in this
“transmittive” department, one faculty member described himself as the students’ “tour guide”
rather than their teacher. He began his course by explaining, “I’m going to lead you down the
main roads, but I’m going to point out to you some alleyways on the side or some interesting
things you should go and visit. And you are responsible for that.” Thus, the difference between
transmittive and facilitative departments in this study is only a matter of degree; both types of
department use both types of pedagogy to some extent.
When Facilitative Pedagogy dominates. In the department where facilitative pedagogy is most
dominant, faculty who spoke with us all expressed sentiments succinctly stated by one when he
said, “I don't teach any classes where [students] just sit there and listen and never do anything,
because that's not computer science.” These instructors reported using collaborative learning, inclass group completion of sample programs, and email lists and interactive web pages for
constant communication among the students and between the students and instructor. The faculty
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in this department also employed traditional lecture with overhead slides, but to a much lesser
extent than reported in the transmittive department.
One faculty member described his instructional approach in the following way.
Let's say I have a three-hour class. I'll start off with a bit of a lecture and then I'll go to
some demonstration. Then I'll have some immediate hands-on application, and then I'll
probably break up into some groups for some group discussion.
Other instructors also spoke of how little they lectured, one describing a case-based
course where students develop applications to meet the needs of fictional clients, and another
describing how students learn in his compiler course.
Students work in teams. … There's very little theory presented although some of the
theory is alluded to and pointed to in other courses . . . Overviews of some of the main
theorems are given. But it's really a course in how do you take a relatively simple
language and build a compiler for a relatively simple assembly machine for it.
He described the experience in this hands-on course as “extremely intense,” both for himself and
the students.
Faculty played a central role in students’ experience as CS majors.
When asked about their positive/encouraging experiences and negative/discouraging
experiences as computer science majors, students frequently focused on faculty and pedagogy.
They often considered faculty to be either the most discouraging or the most helpful aspect of
their experience in the major. Overall, students expressed significantly more negative than
positive opinions about the faculty-related and pedagogical aspects of their experience as
computer science majors. This pattern was true for both male and female students, although
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women were more intensely negative than were men. The style of teaching that faculty reported
using was not related to these student opinions for either men or women undergraduates.
Students focused on teaching quality, faculty behavior, and faculty expertise.
Student comments about faculty and pedagogy fell into to three categories of issues:
teaching quality, the personal and interpersonal behaviors of faculty, and faculty expertise.
Teaching Quality. Comments about teaching quality related to students’ general assessment of
instructional quality, including whether students thought their instructors were organized and
prepared, whether faculty communicated effectively and taught at an appropriate level for the
class, and whether faculty properly constrained academic dishonesty. Students expressed
opinions about teaching quality in every focus group. Men and women were about equally
concerned with issues surrounding teaching, and both sexes made more negative than positive
comments. For example, ***
Faculty Behavior. Comments about faculty behavior related to whether faculty were
interested in students, encouraging, supportive, accessible, approachable, helpful, and flexible.
Students raised issues of faculty behavior in every focus group but one, and the discussions were
often lengthy with numerous examples recounted, particularly in the women’s focus groups. The
women made more comments than the men on matters of faculty behavior (98 comments, versus
68 for the men.) Most often, comments were positive; but the men were much more likely to be
positive than were the women. For example,***.
Expertise. Comments about expertise referred to whether faculty were knowledgeable
about their subject matter and whether they could offer more than information from the textbook.
Students raised the issue of faculty expertise in 12 focus groups. Most often, it was the male
students who mentioned faculty expertise; they made 10 comments, versus 7 made by women.
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When the males commented on faculty expertise, it was equally likely that the comment was a
compliment or a complaint. However, when women raised the issue of faculty expertise, it was
almost always to note an inadequacy. For example, ***.
Relationship between Teaching and Retention
In the departments for which retention data were available, ***.
Overall retention. When you reach the APA level 4 in your paper's organization, place
the heading at the beginning of the paragraph as a lead-in sentence and italicize it as shown in the
previous sentence.
Gendered retention. When you reach the APA level 4 in your paper's organization, place
the heading at the beginning of the paragraph as a lead-in sentence and italicize it as shown in the
previous sentence.
Discussion
In a discipline where one sex radically differs from the other in terms of social support
for selecting and persisting in the major, pedagogical practices that fail to satisfy student
expectations of good teaching could contribute to unequal experiences and outcomes. Our
research suggests that such a situation may exist in collegiate computing programs.
[Insert level 3 heading here]
[Insert body text here]
Example of a level 4 heading. When you reach the APA level 4 in your paper's
organization, place the heading at the beginning of the paragraph as a lead-in sentence and
italicize it as shown in the previous sentence. The APA Publication Manual uses a very complex
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system of headings. This template follows APA naming conventions for heading styles and is
preset for a paper using four levels of organization. If you require a different number of levels of
organization, you will need to select styles based on the number of levels you are using. Please
see Section 3.32 of the APA Publication Manual for details on APA heading conventions.
Further Research:
1. Institutional Support: Several faculty members stated that their teaching styles were
dictated by size constraints- (i.e. large class size limited interactive, hands on learning
and encouraged lecture format) What classes are typically large? (Several professors
mentioned intro classes as being large) Which classes are small? (Many of the
interviewees spoke of elective courses, or “special” interest courses as being small) How
does this vary from department to department? How does this affect attrition?
2. Students ideas about teaching with specific reference to gender. Do women succeed
under a specific teaching style? Do attrition rates reflect the overall pedagogy leaning of
the department?
3. How does what these Professors say about their teaching styles measure up to what
students say about them? Analyze data from student interviews to see what students have
to say about the teaching in their department.
Perceptions of Good Teaching
References
Gow, L., & Kember, D. Conceptions of teaching and their relationship to student learning.
Trigwell, K., Prosser, M. T., & Waterhouse, F. Relations between teachers' approaches to
teaching and students' approaches to learning.
Von Secker, C. E., & Lissitz, R. W. Estimating the impact of instructional practices on student
achievement in science.
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Perceptions of Good Teaching
Appendices
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Author Note
[Insert Author Note here]
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Perceptions of Good Teaching
Table 1
Pedagogical Practices That Transmit or Facilitate
Department
# of Chair and
Rating Mean
Rating Mode
-0.29
0.08
0.12
0.30
0.33
0.33
0.35
0.39
0.45
0.46
0.51
0.63
0.66
0.67
0.78
0.82
0.89
1.19
-1
1
-1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Faculty Interviews
220
72
168
64
30
75
20
71
224 B
65
224
73
19
221
167
61
166
170
9
6
8
12
12
5
7
15
10
5
9
9
4
5
9
8
3
6
Practices were rated on a scale from -2 to 2, where transmit only was rated -2,
and facilitate only was rated 2.
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Perceptions of Good Teaching
Table 2
Pedagogical Practices
Learning Facilitation
% of faculty in
average CS
department
% of faculty in
average
department
emphasizing
external
funding
% of faculty in
average
department
emphasizing
teaching
Knowledge Transmission
presenting
lecture most
information
important
suffices
hands-on
learning
independent
learning
82%
60%
55%
32%
81%
57%
54%
33%
83%
62%
55%
32%
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Perceptions of Good Teaching
Figure Captions
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Perceptions of Good Teaching
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