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Defensive Climate in the Computer Science Classroom
Lecia Jane Barker, Kathy Garvin-Doxas, and Michele Jackson
University of Colorado
Boulder, CO 80309
{Lecia.Barker, Michele.Jackson, Ronda.Garvin-Doxas}@Colorado.edu
Paper submitted to the 33rd ACM Technical Symposium on Computer Science Education (SIGCSE 2002)
This material is based upon work supported by the National
Science Foundation under Grant No. 0090026.
Abstract
As part of an NSF-funded IT Workforce grant, the authors
conducted ethnographic research to provide deep
understanding of the learning environment of computer
science classrooms. Categories emerging from data
analysis included impersonal environment and guarded
behavior, and the creation and maintenance of informal
hierarchy resulting in competitive behaviors. These
communication patterns lead to a defensive climate,
characterized by competitiveness rather cooperation,
judgments about others, superiority, and neutrality rather
than empathy. The authors identify particular and
recognizable types of discourse, which, when prevalent in a
classroom, can preclude the development of a collaborative
and supportive learning environment.
1 Introduction
The NSF Information Technology (IT) Workforce program
funds research to discover ways to attract and retain under-
represented professionals in IT fields. In line with these
goals, we studied two programs, one which actually
appeals to women in contrast with one which traditionally
graduates much fewer: computer science. This paper
focuses on the learning environment of the computer
science major at one university. The findings, while
relevant to retention of women, are also relevant to men.
That is, after a year of immersion in computer science
courses, we have identified communication patterns which
can be characterized as engendering a defensive climate, or
one in which people “perceive or anticipate threat” and in
which communicative interaction is more likely to be
focused on self-defense than on understanding [5]. Below
we discuss learning environment and social climate,
present the research methods and results of data collection
and analysis, then discuss the implications of the
communication patterns we observed in computer science
classrooms.
2 Learning Environment
Learning environment comprises “all of the physical
surroundings, psychosocial or emotional conditions, and
social or cultural influences” present in a learning situation
[7]. Both the physical and the social aspects of a learning
environment influence student participation and satisfaction
[4]. Learning environments are generally discussed and
studied as affecting the learning of people who function
within them and the effects can be positive or negative [9].
In fact, learning environments have effects beyond learning
to include socialization, particularly when certain patterns
of interaction occur across many courses in a curriculum,
such as a major.
The social aspect of the learning environment, often
called social climate, is influenced by traditional and
emergent beliefs about appropriate class activities,
relationships and roles, authority, trust, the personalities
and behaviors of individuals, and typical patterns of
communication. Communication patterns are extremely
important, since it is by creating shared understanding that
teaching and learning occur. Yet the communication
process is more than the transmission of information;
indeed, it is the means by which social order, culture, and
meaning are created and maintained. Communication
patterns that become typical provide not just information,
but represent order, implying and prescribing the way
things are done, and who can do them, “around here.”
In sorting through our data, we began to notice
patterns of communication that seemed to fit with what
Gibb termed defensive communication [5]. Six
overlapping categories of speech are characterized as
creating defensiveness in people. First, speech that is
interpreted as evaluative or judgmental (especially when
negative) often creates defensive reactions; it implies that
the person being evaluated is not up to par. Second, speech
seen as intending to control can lead to resistance; the
implication is that the speaker privately believes the
listener makes inadequate judgments. Third, people resist
and become defensive when they perceive that others are
using strategies on them rather than acting openly. Fourth,
individuals can become defensive when they perceive a
lack of concern or empathy; it may be seen as a rejection of
the self as a valuable person. Fifth, when people
communicate either implicitly or explicitly a perception of
themselves as superior, feelings of inadequacy are aroused.
Finally, when people communicate certainty in a dogmatic
fashion, they also tend to communication a low tolerance
for disagreement. When speech is characterized in any of
these ways, people may become defensive which can
discourage understanding of each other, lead to distrust of
others, and result in competition rather than cooperation.
While our research is part of an NSF-funded project
examining what attracts and repels women in IT programs
of study, the scope of this presentation is the computer
science classroom. Our research questions are:
RQ1: What are the characteristics of student-student and
student-teacher interactions within the learning
environments in the CS program?
RQ2: What, if any, patterns are evident across courses in
the program?
3 Method
The best way to understand student experience of the social
environment in IT classes is to immerse oneself in that
culture by observing from within. This data collection
method is primarily associated with ethnographic inquiry,
the goal of which is to capture the details and meanings of
interaction from the perspective of members of a group.
Through this approach, social scientists work to articulate
the shared, yet often unspoken, rules, beliefs, and values
which are produced communicatively and which surround
and influence the everyday practices of members of a social
setting.
Over the course of the 2000-2001 academic year, we
observed courses in two different types of IT programs: a
traditional Computer Science (CS) major and the
Technology, Arts, and Media (TAM) certificate program,
in which students acquire in-depth skill with high-end
multimedia software packages (e.g., Director, Flash) as
well as some html programming. Over the 2000-2001
academic year, we observed 10 courses for a total of 254
hours, as shown in Table 1 below. The extensive fieldnotes
recorded: number of students attending, sex, and
appearance; physical layout of classrooms and seating
arrangements; and descriptions of interaction (student-
student and student-instructor interaction) and interactants
male/ female; major). Fieldnotes were typed and the
resulting 648 pages of text bound into “books,” by course.
The analytical method employed best fits into content
analysis, in which researchers read through the data several
times, labeling them and establishing a classification
scheme. Patterns, themes, and categories of analysis
emerged through the systematic examination of the data
both during semesters and after; we then analyzed the
degree to which our categories overlapped. In an iterative
process, relevant data were coded according to category.
These categories are discussed in the results section, below.
Table 1: Observation Details
Program Level Lectures Recitations/
Labs/Other Hours
CS
Lower
16
7
29
CS
Lower
11
4
20.75
CS
Lower
14
3
20.5
CS
Lower
9
-
9
CS
Upper
12
9
24
CS/TAM
Mixed
28
2
47
CS/TAM
Upper
20
-
25
TAM
Upper
-
15
37.5
TA
M
Upper
-
9
22.5
TAM
Upper
15
-
18.75
Total
125
49
254
4 Categories of Interaction
The results included here are limited to Computer
Science courses, though understanding of the social
environment of TAM courses was useful for comparison.
Two categories which emerged from the data are presented
below. Although these categories are analytically
separable, they are part of a system (i.e., the social
environment of the computer science classroom) and are
mutually influential. While the actions of all members of
the system contribute to the particular “flavor” of the CS
major and the classrooms we observed, it is most heavily
shaped by the discourse and actions of those in authority:
the instructors and teaching assistants.
4.1 Impersonal Environment and Guarded Behavior
The social environment of most of the computer
science courses we observed can be characterized as
impersonal, an environment in which it is easy to remain
relatively anonymous and socially distant. Interpersonal
relationships usually begin with learning a person’s name,
then learning more about a person’s interests through
intentional self-disclosure and inferences drawn from
others’ speech and actions. In observations, it was rare to
hear the name of a student in class or any personal
information beyond that learned or guessed by appearance
and other obvious facts (e.g., only computer science majors
are allowed in this class, so a student would know that all
students in the room are computer science majors).
In only two courses were students required to
introduce themselves to the class; in only one of these did
student names continue to be used by the instructor. In
fact, instructors rarely used students’ names, even at the
end of the semester. Instructors sometimes called on
students according to their clothing, such as “the woman in
the red shirt.” When names were used, it seemed
surprising, leading the researchers to wonder if the student
and professor knew each other from extra-classroom
interaction. Sometimes a professor would call on a student
by name, adding, “I’m calling on you only because I know
your name.” In other words, he didn’t know others’ names,
though this occurred more than two months into the
semester. Further, unlike field notes from TAM
observations, field notes from the computer science courses
are characterized by identifying students as “F1,” “M2,”
“red hair,” and so on, even in courses with very small
enrollment (one of these had only 12 students by the end of
the semester). As observers, we try to remember names so
that we can observe patterns by student, but the lack of
name use made this difficult.
Self-disclosure is sharing information that others
would not usually know or discover. Self-disclosure
functions to cement interpersonal relationships by helping
people to predict others’ behavior and deepening mutual
trust [3]. It was very rare to hear a student disclose
personal information that was related to anything other than
work (a serious and important topic) even in their limited
before-class chitchat. Indeed, one CS instructor repeatedly
disclosed personal information such as his love of poetry,
music, and hiking, but students typically did not respond
and remained silent, violating an unspoken rule of self-
disclosure in American culture: disclosure is mutual.
Students rarely responded to instructors or even spoke
much in class, suggesting that the social environment was
very guarded. A few examples are the lack of or very
subdued student chatting before class, students sitting
isolated from each other, non-response to instructor
queries, silence when the instructor paused or erased the
board, and students not asking expected questions such as
“what was the average grade on the test?”
Computer grading of programming assignments is
employed to address the very real problems of scale.
However, this is another impersonal aspect of CS. Though
the grading program has a name and is talked about as if it
is a person, it cannot interact with students like a tutor or
teacher and the only feedback it gives is whether the
program compiled.
4.2 Informal Student Hierarchy
Hierarchy and status are characteristics of every social
situation and relationship, whether equal or unequal [1, 10].
Hierarchy may be formal or informal, or have elements of
both. Formal hierarchy occurs when certain persons have
the authority and duty to govern the interaction of others,
such as in teacher-student relationships. Informal hierarchy
is created through the acquisition and display of status by
participants in a social situation and is relevant to the
values shared by members. Individuals learn the values of
groups in subtle ways through interaction and present
themselves as members through the expression of shared
values; they make a bid to be treated as having higher
status when they talk in ways that suggest they excel at the
kind of skills or knowledge required for functioning in that
social context. In CS classrooms, status is informally
accorded to those who display technical skill or provide
valued information. Who belongs and where they belong
in the informal hierarchy are negotiated throughout the
semester in the courses we observed.
Even on the first day of class for first semester
freshmen, the process of identifying who belongs and who
does not begins. One professor explained to his class that
the course had no prerequisites and that all levels of
experience, “never programmed, a bit of programming, and
rocket scientists” are all in the same course. Thus all
students belong, but the status of different types of
belonging is already set up, with experience being
attributed to a term popularly used to mean ‘very smart’.
The instructor further defines the “rocket scientists” by
saying that they often compete to do more and to out-do
one another. He gives an example of a student who
designed a complex game for his final project and says,
“Did it help his grade [to go beyond the assignment]? No,
but he had fun.” Instructors reinforce views about
belonging both explicitly and implicitly. In one course, the
professor demonstrated a possible project for the final
component of the course (an extension of the peg-board
game) and asked “[who in the class] thinks it’s a cool one?”
When all of the students raised their hands, he said, “Good,
because if you don’t think it’s cool, you’re in the wrong
class. If you don’t think it’s cool, I won’t be able to
entertain you. This is about as good as it gets.”
Setting up hierarchy and status can help students to
understand the goals of courses and the major. For
example, a professor compared two versions of the same
code, telling the class, “don’t hesitate to write code like this
[indicates the beginner’s version], but eventually you’ll
write code like this [indicates the more compact, efficient
version].” However, problems can arise when students
confuse the source of knowledge that can lead to high
status: intelligence versus experience. This is especially
problematic for those with less experience, a group to
which most female CS students belong.
Students with programming experience are frequently
referred to as “smart,” both explicitly and implicitly. For
example, one instructor announced that “we have people in
this class who have never programmed and some who have
created game software. By the way, we have [TA] jobs for
smart students like that.” In fact, one professor described a
computer scientist as “a very smart person, who knows
how to create software.” Clearly, students who are
successful in the major come to believe that computer
scientist have knowledge which is superior in nature to
other types of knowledge. An undergraduate CS major
who worked with a group of non-majors said, “I tried to
make sure that ideas from non-technical people could be
heard by not making judgments.” He implies that he
deliberately chose not to express judgments. The judgment
of another person is a “one-down” move, a move which
shows a perception of, in this case, intellectual superiority.
Over time, students become aware of whether they
belong as well as where they fit in the CS social hierarchy.
That is, they are developing their identity as “computer
scientists” – or not – through interaction with each other,
their instructors, and TAs. Prior to the deadline for the first
assignment for a junior-level course, one TA spent the
entire recitation session telling students how ‘easy’ the
assignment would be: “You won’t have any problem with
[the assignment]. It will be simple.” When a student
asked, “did you already do this project?” the TA replied
with a wave of his hand, “No. I spent about an hour putting
together [this presentation for class] and I’ve written five
languages commercially – this is all scraps to me.” Only
26 out of more than 80 students received passing grades on
the assignment. Likewise, in a lower-division course, the
instructor repeatedly told the class that “this [lab] test is a
slam dunk; you’re all going to get 100 percent.” Those
who made the average grade 87 percent must have
wondered, like the 54 students who failed the assignment
above, whether they were “smart,” like the other computer
scientists (i.e., experienced students).
Through self-presentation as “smart,” students also
contribute to the construction of hierarchy in the classroom.
For example, a male freshman made a point of telling one
of us about his web design business and extensive
programming experience. He explained his presence in the
introductory class by saying that he did not want to place
out of it so that he could have a more ‘relaxed’ semester.
He said all of this before being reminded that the researcher
wasn’t another student in the class and was later over-heard
sharing the same information with other students in the
class.
In many cases, students ask questions that do not
appear to be seeking information, but to be displays of their
own knowledge. Students tend to use question forms such
as, “You can do _____, right?” and “Isn’t it true that ____ ”
“But doesn’t it work [this way] in Java?” These are voiced
not as questions, but as statements. The strategy seems to
persuade at least some students in their classes. In a
recitation, a slightly older female student said to a male
student, “why are you taking this class? From what you
said the other day, it sounds like you already know this
stuff.” One day later in the semester, the same male
student brought up another way of programming an
operator. The instructor agreed that there is more than one
way to do it and called on him to explain to the rest of the
class. The student could not articulate an explanation, but
instead said “that’s what I get for opening my mouth.”
Interestingly, when we tested our belief that students were
posturing in discussions with three CS professors, all
agreed that students often do that. To people who consider
themselves to be outsiders to the CS classroom, however,
such posturing seems unusual.
While students rarely speak in class relative to other
majors in our experience, some ‘experienced’ programmers
seem to be compelled to show off their knowledge by
pointing out mistakes in syntax that they see on professor’s
slides and/or on any work written on the blackboard.
Students frequently interrupt lecture with comments like,
“Shouldn’t ‘expression’ and ‘term’ be the other way
around?” and “you’ve made a mistake in ______ [on that
slide].” These comments frustrate the professors. As
several told us in informal interviews, they feel that
students who publicly challenge their knowledge and who
point out minor mistakes on slides are interfering with
lectures simply to make the point that they are experts.
These professors felt that such attention-drawing strategies
took away from the real point of the lectures. One
described it as focusing too much on details and not on the
concepts.
However, professor reactions to such challenges and
displays of knowledge as they take place in the classroom
suggest that they feel forced to respond to such comments.
They consistently either offer ‘good reasons’ for having
made a mistake (e.g., “that comes from doing things at the
last minute”) and/or attempt to make light of the mistakes
in a way that indicates acute embarrassment (e.g.,
“obviously, I believe in text readers”). Accounts such as
those offered by the instructors acknowledge and attempt to
mitigate some behavior seen as dispreferred in a particular
community. After a series of such corrections, one
professor began discovering his own mistakes as he
lectured and hurried to correct them live as he joked about
making the corrections “so [that] people who have me next
time will benefit from these debugged slides.” Over time
and in conjunction with other similar messages, such as a
grading system that penalizes students a full 80 percent of
their grade if the program doesn’t compile (regardless of
the correct planning and steps indicated in their programs),
these sorts of reactions indicate that it is not reallyokay to
make trivial mistakes – especially not in public – and that
judging others’ knowledge and abilities and defending your
own is an expected part of interaction.
5 The Creation of a Defensive Social Climate
The interactions described above all work together to
create, maintain, and reinforce a learning environment
characterized by a defensive social climate, as discussed by
Gibb [5]. No single person and no one course create a
defensive climate nor did we see all the types of defensive
communication Gibb identified. Rather, a series of
interactions over extended periods of time lead to such a
climate. In the case of the CS courses examined for this
study, it is important to note that CS faculty members, as is
the case in most Science, Mathematics, Engineering, and
Technology (SMET) education, are actively seeking to find
ways to encourage interaction in their classes and to re-
enfranchise those students who have traditionally become
disenfranchised from the CS major. Be that as it may, the
types of interaction we saw in these courses, impersonal
communication, guardedness, and jockeying for superior
status, lead to and lend their support to the creation and
maintenance of a defensive communication climate which
works against these goals.
The impersonal environment and guarded behavior
we describe is characterized by neutral, as opposed to
empathetic, communication. The depersonalization of
students through a failure to use their names and an
environment that discourages self-disclosure of anything
other than work-related information can be perceived as a
lack of concern for others, which violates the normal
human desire to be perceived as important, someone who
matters, someone for whom others are concerned. This is a
particularly salient desire for women in that they tend to
define themselves in relation to others, as opposed to men,
who often define themselves in terms of their occupational
contributions to society [6].
This depersonalization is only reinforced and
enhanced by computerized grading practices. The neutral
and impersonal nature of many of the practices in the CS
courses observed can unintentionally and indirectly
communicate rejection rather than acceptance and therefore
support of the value of the individual. This neutral
communication style is further supported when teachers
repeatedly tell students that what they’re learning is “easy.”
In doing so, they implicitly deny the legitimacy of these
students’ concerns and fears about mastering what they
perceive to be new and difficult material. Again, women
are particularly sensitive to this sort of rejection and denial
of their concerns [8].
Much of the system of informal hierarchy described
here stems from communication that emphasizes
superiority rather than equality. Equating “smart” students
to experience in programming, implying that one must
think that extending programs, like the peg board game, is
“cool,” and describing students who compete to do more
and to out-do one another as “rocket scientists” (i.e.,
smart), all function to express and establish a social order
defining the value of different types of people. This in turn
leads to a competitive environment where students feel it
necessary to demonstrate their superiority, not just in the
execution of their assignments, but in the way they present
themselves and challenge their teachers publicly. In the
interrelated fashion of social construction, this behavior
from students contributes to a communication environment
in which teachers feel that they are being judged and
evaluated. In iterative fashion, this leads them to
communicative defensively, modeling behaviors that
suggest that mistakes are bad and must be justified. Yet a
learning environment should be a place where making a
mistake is an acceptable action. Once again, these
communicative practices can be discouraging to women,
who tend to be less competitive and more cooperative in
their approach to social interactions.
With SMET education’s trend toward collaborative
learning; ABET 2000’s focus on collaboration; industry’s
emphasis on team work; and the push for diversity in
SMET disciplines, institutions of higher education across
the nation are looking for ways to incorporate collaboration
and peer learning as well as to increase participation in
their classes. As one of the processes underlying the
competitive, rather than collaborative, nature of computer
science [2], a defensive communication climate works
against these goals.
As Gibb [5] points out, defensive communication is
endemic to most traditional learning environments. To
meet the needs of today’s students, it will be necessary to
understand the dimensions of the learning environment and
to be cognizant of the ways in which our communication
styles contribute to the creation and maintenance of the
climate associated with our learning environments. In this
article, we have presented some ways students and
instructors speak and behave to unconsciously create and
maintain defensive climates. Reflecting on typical
communication practices found in the classroom is the first
step to changing the culture and appeal of computer
science.
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