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Coimbra, Portugal September 3 – 7, 2007
International Conference on Engineering Education – ICEE 2007
Second Chance Learners, Supporting Adults
Learning Computer Programming
Cornelia Connolly
1
, Eamonn Murphy
2
, Sarah Moore
3
1
Cornelia Connolly, Dundalk Institute of Technology, Ireland, cornelia.connolly@ul.ie
2
Eamonn Murphy, Professor of Quality and Applied Statistics, University of Limerick, Ireland, eamonn.murphy@ul.ie
3
Sarah Moore, Dean of Teaching and Learning, University of Limerick, Ireland, sarah.moore@ul.ie
Abstract - The focus of this paper is adult learning, with
regard to understanding how adults learn computer
programming. Some computing students learning
programming for the first time often have ineffective
mental models for how a program operates and they fail
to transfer their programming knowledge beyond what is
taught. They lack appropriate cognitive skills that are a
prerequisite to learning computer programming, and
have a mental block when it comes to understanding the
abstract constructs involved. This can cause the students
to become anxious, or even fear programming. As
performance is negatively affected by anxiety, this
consequently impacts on their academic performance.
This paper explores programming anxiety and the
construction of mental schemas necessary for learning
computer programming.
Index Terms – Computer Programming, Mental Schema,
Anxiety.
I
NTRODUCTION
,
ADULT
LEARNING
Negative cognitions and attitudes to learning a new skill
generally accompany such feelings of anxiety, including
worry about embarrassment and looking foolish. It is
hypothesized that students’ introductory computer
programming courses are perceived by some first year
students as demanding and stressful because of the abstract
and complex components involved. Computer programming
is an ab-initio skill for the majority of first year
undergraduate students and their mental schemas necessary
in programming may not be developed sufficiently, but
particularly apparent for adult learners. Studies have
investigated the factors that indicate student’s ability to learn
programming which include mathematical ability, processing
capacity, analogical reasoning, conditional reasoning,
procedural thinking and temporal reasoning [1] and some of
these skills are underdeveloped prior to the student starting
their undergraduate computing degree programme, causing
them enter a state of apprehension and unease. It is felt that a
situation specific anxiety occurs for students when they have
to learn programming for the first time. This anxiety,
Programming Anxiety, is a constituent of computer anxiety
and occurs for students when a mistaken or dysfunctional
assessment of their ability to learn computer programming
occurs.
This paper will firstly explain anxiety and defines how
programming anxiety occurs for computing students. Results
from research conducted at Dundalk Institute of Technology
presents the prevalence of programming anxiety amongst
first year undergraduate students. The paper concludes in
examining how adults learn and the necessity for creating
learning strategies to overcome programming anxiety.
C
OMPUTER AND
P
ROGRAMMING
A
NXIETY
Anxiety is a feeling of apprehension or fear, it is a complex
phenomenon which may be a generalized personality trait for
some individuals, while for others it is quite clearly context
bound and stressful in particular situations [2, 3]. Anxiety
may be distinguished from fear in that the former is an
emotional process while fear is a cognitive one [4]. When
fear becomes activated one experiences anxiety, and
prolonged anxiety can lead to a state of stress [2].
Computer anxiety prevents students from learning the
simplest of computing task, as it has been found that
negative feelings and attitudes intrude on the development of
formal reasoning. It is suggested that in some circumstances
test anxiety and computer anxiety bear similar characteristics
[5]. It has been demonstrated that computer anxiety is an
important predictor of student achievement in computing
skills [6]. Furthermore, the higher the initial level of
computer anxiety, the lower the computer achievement [6].
In developing a standardized test of computer anxiety, the
Computer Anxiety Index (CAIN) similarly demonstrated that
students with higher computer anxiety scores had lower
scores on an achievement test of computer literacy [7].
Speier found significant correlation between high initial
levels of anxiety and decreased skills performance
throughout computer learning [8]. Honeyman concluded that
students perform more poorly and develop negative attitudes
as a result of computer anxiety [9].
Among the early literature on the psychological state of
individuals who have negative affective reactions to
computers, researchers in the area of computer anxiety
suggested that a major influence is the lack of familiarity
with computers [10], and with increased experience anxiety
should decrease. The subsequent research gave some support
to this hypothesis [11]. However Rosen et al. argued, in
contrast, that during repeated exposure to the computer, the
subject is being reconditioned at increased levels of anxiety
which, thus increases discomfort and anxiety [12-14]. In
conclusion, they found that experience with computer
interaction did not reduce computer anxiety nor improve
attitudes [13, 14]. Marcoulides concluded that computer
anxiety significantly influences the degree to which
computers can be utilized effectively by third level students
and that although computer experience does diminish the
Coimbra, Portugal September 3 – 7, 2007
International Conference on Engineering Education – ICEE 2007
anxiety to some extent, varying degrees of computer anxiety
remain [6]. Corroboration for such assertions comes from
Mahmood who found that even after an extensive computer
literacy course, initial negative attitudes and values towards
computer technology persisted, though somewhat diminished
[15]. Similarly Leso reported that in both computer
applications and programming courses, significant numbers
of students reported anxiety at the end of fourteen weeks,
one third in the former case, and over two-thirds in the latter
[16], despite the fact that most students had prior computer
experience. This affirmed simply but pointedly, that such
courses alone do not guarantee reduction in anxiety for all
individuals [16]. It is clear from this literature, that computer
anxiety is prevalent and can persist in individuals
irrespective of exposure to computers [17].
Meier believes that computer anxiety can be understood
within a social learning model and is a result of low
expectations of efficacy, outcome or reinforcement [18].
Therefore, anxiety and related components maybe made
better or more tolerable by enhancing self-efficacy through
skill building and success experiences. Another review was
presented by Rosen and Weil who perceived computer
anxiety as a clinical entity wherein anxiety may vary
anywhere from mild discomfort to severe ‘phobia’, [13, 14].
The cause of such phobia is prior uncomfortable computer
interactions which make future computer and even
mechanical experiences appear to be negative regardless of
their outcome [19] and may perhaps lead to withdrawal from
educational courses. An intervention for computer related
anxieties needs to be strategic and may include the use of
desensitization, relaxation and analytic interventions [20,
21]. In this research, it is hypothesized that students’
introductory computer programming courses would be
perceived by some first year students as demanding and
stressful especially due to the abstract and complex
components involved. As such, programming anxiety, a form
of computer anxiety would occur (as depicted in Figure 1).
For the purpose of this research, originating from
McInereny’s definition of computer anxiety, programming
anxiety is proposed as “a psychological state engendered
when a student experiences or expects to lose self-esteem in
confronting a computer programming situation.”
FIGURE 1
R
ELATIONSHIP BETWEEN
A
NXIETY
,
C
OMPUTER
A
NXIETY AND
P
ROGRAMMING
A
NXIETY
Anxiety is maintained by mistaken or dysfunctional
appraisal of a situation and therefore programming anxiety
occurs for students because of a mistaken assessment of their
ability to learn computer programming. This mistaken
assessment can be because the process of activation cannot
take place, and the students’ mental schemas cannot form the
foundation from which they will deconstruct the
programming problem and develop a solution. The cognitive
model conceives that when people find themselves in
situations, automatic thoughts are activated, which are
directly influenced by their core and intermediate beliefs.
Automatic thoughts then influence reactions. A students
most fundamental beliefs impact their thoughts in given
situations. For a student susceptible of computer
programming anxiety, their core belief, a fear of learning
programming may commence when they first engage in
learning this new computer programming skill. Their
intermediate thoughts could arise as a fear of what other
students might think. The automatic thought occurs when the
student is in the influential environmental and combined with
their beliefs and trigger negative thoughts and reactions.
FIGURE 2
T
HE
C
OGNITIVE
M
ODEL
[4]
AMENDED FOR
P
ROGRAMMING
A
NXIETY
This notion of a mismatch between internal/individual
demands and resources is central to the majority of anxiety
conceptualizations. The subjective appraisal of a demanding
environment, a realization that demands may outstrip
resources and that the consequences of not coping, are
important in defining programming anxiety in the higher
educational environment. Corresponding to the mismatch
between skill and challenge relationship in gaining ‘optimal
experience’ [22]. It is key to ensure that the students are
anxious to learn programming but not anxious about
learning.
P
ROGRAMMING
A
NXIETY
P
REVALENCE AMONG
F
IRST
Y
EAR
C
OMPUTING
S
TUDENTS
Research carried out at Dundalk Institute of Technology,
Ireland shows that there are high levels of programming
anxiety evident amongst the first year undergraduate
computing cohort [23].
The evaluation cycles took place during the 2005/2006
Academic Year and 79% of the first year total participated in
the initial Pre-CPAQ, (N = 86). Of the sample from whom
data was collected 74 were male and 12 female. While many
respondents used their personal computer for a variety of
applications, programming was selected by only 7% of the
students. 52.3% of students indicated that they were
Intermediate in terms of computer experience and 46.5%
said they were Advanced. There wasn’t a significant
relationship between PC ownership and computer
experience, with the majority of students who did not own a
computer claiming they were Intermediate in terms of
computing experience. Of the 12 female students, 11
indicated they were either Intermediate or Advanced, with
one selecting Beginner. Students indicated that they were
performance rather than learning oriented. 64% of students
Coimbra, Portugal September 3 – 7, 2007
International Conference on Engineering Education – ICEE 2007
(N=55) had chosen the course they were registered on as
their first choice of degree programme at higher education.
Of the 36% who had not chosen the course as their first
preference, 50% had intended registering on a different
computing degree course. The student demographics indicate
their interest in computers and the range of experience in use
of computers is vast across a broad range of applications.
The first scale of the Computer Programming Anxiety
Questionnaire administered, Gaining Initial Computer Skills,
refers to experiences related to computers, and students were
asked to indicate the extent to which the situations described
would make them anxious at this point in their life. It is clear
that all students at the start of their third level education
express considerable anxiety, with the greatest anxiety
shown in the area of demonstrating Competence with
Computers, which decreased considerably by the end of the
semester.
Two factors relating to Positive and Negative Sense of
Control when using a computer were identified. The factors
reflect an individual’s sense or lack of personal control, as
indicated in their cognitions. Students Positive Sense of
Control in computing situations decreased by the end of their
first year at college. Their Negative Sense of Control on the
other had increased, shown in Table 1.
With regard to Computer Self Concept, and for each of
the two factors Positive Computing Self-Concept and
Negative Computing Self Concept, questions assessed
different responses in relation to student self-efficacy or
confidence in computing. Students positive Computing Self
Concept decreased at the end of the year and their Negative
Computing Self Concept decreases, indicating that they have
more negativity with regard to self confidence in a
computing situation at the end of the year.
The fourth scale, ‘State of Anxiety in Computing
Situations’ examined the cognitive, emotional and
physiological states of anxiety students may face in computer
programming situations and the results reflect an individual’s
level of state anxiety. The difference in pre and post results
of the student cohort is interesting. All students indicated that
their sense of Worry increased in the post-CPAQ. With
regard to Happiness students answers in the post-CPAQ were
slightly more negative compared to their answers in the pre-
CPAQ. Students Physiological Symptoms and Distractibility
remained the same with minimal changes in the distribution.
T
ABLE
1
M
EDIAN AND
I
NTERQUARTILE
R
ANGE FOR
C
OMPUTER
P
ROGRAMMING
A
NXIETY
Q
UESTIONNAIRE
,
P
RE AND
P
OST RESULTS
PRE POST
Median IQR Median IQR
GAINING INITIAL COMPUTING SKILLS
Competence with
Computers 2.28 1.14 1.71 1.28
Handling Computer
Equipment 1.50 3.00 1.25 2.50
Receiving Feedback on
Computing Skills 1.80 1.80 1.40 2.00
Learning about
Computer Functions 2.08 1.66 1.58 2.83
SENSE OF CONTROL
Positive Control 3.92 1.10 3.50 3.32
Negative Control 1.27 0.55 1.50 0.77
COMPUTING SELF CONCEPT
Computing Self
Concept (positive
items) 1.75 0.75 1.66 1.66
Computing Self
Concept (negative
items) 4.60 1.00 4.20 1.70
STATE OF ANXIETY IN COMPUTING SITUATION
Worry 1.04 0.37 1.16 0.68
Happiness 4.00 0.87 3.50 0.93
Physiological
Symptoms 1.00 0.35 1.00 0.20
Distractibility 1.00 1.00 1.00 0.37
The results from the research show students entering
first year undergraduate computing courses have computer
programming anxiety tendencies at the start of term, some of
which diminish throughout their first year at college. Rather
surprisingly student’s negative sense of control or self-talk
increases and their fear increases and their negative self-
concept becomes more apparent by the end of first year.
Anxiety in computing situations doesn’t improve, with the
student’s sense of worry increasing and their sense of
happiness decreasing. Student’s positive self-concept
improves in post analysis, but their positive sense of control
(positive cognition) doesn’t improve. These findings
highlight important information with regard to the
psychological stance of the students and their reaction to
programming.
A
DULT
L
EARNERS
L
EARNING
P
ROGRAMMING
The basic principles of learning applied to children are as
relevant in relation to adults learning new skills/material, as
children. The differences are of emphasis rather than
fundamental principle. Research has shown the two
distinguishing characteristics of adult learning most
frequently advanced by theorists are firstly the adults
autonomy of direction in the act of learning and secondly the
use of personal experience as a learning resource [24].
Effective self-regulated learning is linked to an adult’s
subscription to a self-concept of themselves as a learner. In
his overview on self-regulated learning and achievement,
Zimmerman, defines self-regulated learners as
metacognitively, motivationally, and behaviorally active
participants in their own learning. In terms of motivational
processes, these learners report high self-efficacy, self-
attributions and intrinsic task interest [25]. As a rule, adult
learners like their learning activities to be problem centered
and meaningful to their life situation, and they want the
learning outcomes to have some immediacy of application.
One therefore can assume that adults seem to learn best when
they do not rely on memorizing, but when they can learn
through activity at their own pace, with material that is
relevant to their daily lives and can utilise their own
experience. It is also important to recognize however that
self-direction in learning is not an empirically verifiable
association of adulthood and that there are many individuals
who are chronologically adult, but who show a reluctance to
behave in a self-directed manner.
The past experiences of adults affect their current
learning, sometimes serving as an enhancement or hindrance
[26]. In higher education it is vital that the students past
Coimbra, Portugal September 3 – 7, 2007
International Conference on Engineering Education – ICEE 2007
experiences and prior knowledge are encompassed in their
learning. Prior knowledge is also referred to as ‘declarative’
knowledge [27], and refers both to the quantity of knowledge
(what is known) and the quality of knowledge (how well it is
known, organized and structured) [28]. Of importance to this
research, is the way in which students’ prior knowledge is
organized and structured. Bransford suggests that the
effective use of cognitive and metacognitive strategies can
assist in the appropriate organization of knowledge and
therefore in its effective retrieval and application [29]. Well
structured knowledge is easily and spontaneously accessed,
supported by many internal and external connections [30]
and through the activity of schemas and scripts, act as a
guide to comprehension, inference, reasoning and problem
solving.
I
NFORMATION
P
ROCESSING AND
M
ENTAL
M
ODELS
Information Processing is a theory of learning that explains
how stimuli enter one’s memory system, are selected and
organized for storage and retrieved from memory [30, 31]. In
order to design and develop an appropriate approach for
students susceptible of programming anxiety, to construct a
mental model for learning programming, an awareness of
how students process information is important. Information
processing, a common theoretical approach used by
cognitive psychologists, is not simply a unified theory, but
rather an approach to understanding human knowledge and
action. The approach analyses cognitive processes in a
sequence of ordered stages; each stage reflecting an
important step in the processing of cognitive information
[32]. Meaningful learning occurs during information
processing when the student connects new material with
knowledge already existing in memory. The existing
knowledge in memory is called a schema [33, 34].
As experience is acquired, one is forced to adapt to
function effectively. Adaptation is the process of adjusting
schemas and experiences of each other to maintain
equilibrium, and consists of two reciprocal processes:
accommodation and assimilation. Accommodation is a form
of adaptation in which an existing schema is modified and a
new one is created in response to the experience. The latter
assimilation is the process of connecting new information to
an existing schema [33, 34]. If new experiences are only
assimilated into existing schemas, the schemas won’t change
and development doesn’t occur. On the other hand, if
existing schemas can’t be made to work, a person faces
constant disequilibrium.
The concept of mental schemas has been used in a
number of research areas as an effective and insightful
approach to studying the behaviors and beliefs of individuals
and organizations. Schemas are abstract mental records that
serve as guides to action, as structures for remembering and
interpreting information, and as organized frameworks for
solving problems [35]. Piaget used the concept of schemas to
refer to a narrow range of abstract operations and which form
content perspectives [36]. All the contents, principles, rules
and procedures that students learn are organized into
schemes that allow them to make sense of the world.
Humans adopt a vast range of schemas, enabling us to make
sense and place any new information or experiences into
context. Once formed, the hierarchical schemas guide our
information processing and behavior [37]. In computer
programming students translate a program specification into
programming language code, drawing heavily on abstraction
skills and developed schemas in memory.
The practice of describing people’s beliefs and actions
in terms of mental schemas has been used extensively in
cognitive psychology and cognitive science, for phenomena
as diverse as how people solve brainteasers to how they
troubleshoot steam boilers [38]. In the case of technology
and organizations “individuals mental models tend to be
oriented around established practices and norms, and may
limit perception and understanding of an innovation” (p.23).
D
ISCUSSION
In the developed countries worldwide there has been a major
increase in the number of adults returning to third level
education in recent years. These adults are enrolling in
courses varying from the social sciences to engineering
disciplines. Many such adults enroll on computing courses
and the prospect of studying programming can be
overwhelming. This is especially the case in relation to
Ireland whose government is pursuing an economic
development strategy based on the knowledge society.
Developing learning strategies is very important not
alone for the traditional student who enters higher education
after finishing their second level education, but also for those
students re-entering the education system after, or while,
working in industry. As governments invest in knowledge
economies and support life-long learning, structures and
support systems to facilitate the up-skilling and professional
development of the workforce at all levels is crucial and need
to be develop within education. The findings presented in
this paper highlight once again that the psychological needs
of the individual should be recognized and supported within
the higher education system. The results from the Computer
Programming Anxiety Questionnaire re-emphasizes that
education needs to be individualized, supported and ensure
that student perceptions are met.
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