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Second Chance Learners, Supporting Adults Learning Computer Programming

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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.
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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.
R
EFERENCES
[1] Pea, R.D. and D.M. Kurland, On the Cognitive and Educational
enefits of Teaching Children Programming: A Critical Look.
New Ideas in Psychology, 1984. 2: p. 147-168.
[2] Malim, T., et al., Introductory Psychology. 1998, London:
Palgrave MacMillan.
[3] Phillips, B.N., R.P. Martin, and J. Meyers, Interventions in
Relation to Anxiety in School, in Anxiety: Current Trends in
Theory and Research, C.D. Speilberger, Editor. 1972, Academic
Press: New York. p. 410-464.
[4] Beck, A., Anxiety Disorders and Phobias. A Cognitive
Perspective. 1985, New York: Basic Books.
[5] McInereny, V., Computer Anxiety: Assessment and Treatment.
1997, The University of Western Sydney Macarthur.
[6] Marcoulides, G.A., The Relationship Between Computer Anxiety
and Computer Achievement. Journal of Educational Computing
Research, 1988. 4: p. 151-158.
[7] Simonson, M.R., et al., Development of A Standardized Test of
Computer Literacy and A Computer Anxiety Index. Journal of
Educational Computing Research, 1987. 3: p. 231-247.
Coimbra, Portugal September 3 – 7, 2007
International Conference on Engineering Education – ICEE 2007
[8] Speier, C., M.G. Morris, and C.M. Briggs, Attitudes Toward
Computers: The Impact on Performance. 1996.
[9] Honeyman, D.S. and W.J. White, Computer Anxiety In
Educators Learning To Use The Computer: A Preliminary
Report. Journal of Research on Computing in Education, 1987.
20: p. 129-138.
[10] Loyd, B.H. and C.P. Gressard, Reliability and Factorial Validity
of Computer Attitude Scales. Educational and Psychological
Measurement, 1984. 44: p. 501-505.
[11] Howard, G.S. and R. Smith, Computer Anxiety in Management:
Myth or Reality? Communications of the ACM, 1986. 29: p.
611-615.
[12] Weil, M.M., L.D. Rosen, and D.C. Sears, The Computerphobia
Reduction Program: Year 1. Program Development and
Preliminary Results. Behavior Research Methods,
Instrumentation and Computers, 1987. 19: p. 180-184.
[13] Rosen, L.D., D.C. Sears, and M.M. Weil, Computerphobia.
Behavior Research Methods. Instrumentation and Computers,
1987a. 19: p. 167-179.
[14] Rosen, L.D., D.C. Sears, and M.M. Weil, Computerphobia
Measurement. A Manual for the Administration and Scoring of
Three Instruments: Computer Anxiety Rating Scale (CARS),
Attitudes Toward Computers Scale (ATCS) and Computer
Thoughts Survey (CTS). 1987b, California State University,
Dominguez Hills: California.
[15] Mahmood, M.A. and J.N. Medewitz, Assessing The Effects of
Computer Literacy on Subjects' Attitudes, Values, and Opinions
Toward Information Technology: An Exploratory Longitudinal
Investigation Using the Linear Structural Relations (LISREL)
Model. Journal of Computer-Based Instruction, 1989. 16: p. 20-
28.
[16] Leso, T. and K.L. Peck, Computer anxiety and different types of
computer courses. Journal of Educational Computing Research,
1992. 8: p. 469-478.
[17] Marcoulides, G., B.T. Mayes, and R.L. Wiseman, Measuring
Computer Anxiety in the Work Environment. Educational and
Psychological Measurement, 1995. 55: p. 804-810.
[18] Meier, S., Computer Aversion. Computers in Human Behavior,
1985. 12: p. 327-334.
[19] Rosen, L.D. and P. Maguire, Myths and Realities of
Computerphobia: A Meta-Analysis. Anxiety Research, 1990. 3:
p. 175-191.
[20] Weil, M., L. Rosen, and S. Shaw, Computerphobia Reduction
Program: Clinical Resource Manual. 1988, Dominguez Hills:
California State University: California.
[21] Heinssen, R.K., C.R. Glass, and L.A. Knight, Assessing
Computer Anxiety: Development and Validation of the Computer
Anxiety Scale. Computers in Human Behavior, 1987. 3: p. 49-59.
[22] Csikszentmihalyi, M., Flow: The Psychology of Optimal
Experience. 1990, New York: Harper&Row.
[23] Connolly, C., E. Murphy, and S. Moore, Programming Anxiety
Amongst Undergraduate Computing Students – A Key in the
Retention Debate? IEEE Transactions in Education, 2007.
[24] Simpson, E.L., Adult Learning Theory: A State of the Art, in
Adult Development and Approaches to Learning, H. Lasker, J.
Moore, and E.L. Simpson, Editors. 1980, National Institute of
Education: Washington D.C.
[25] Zimmerman, B.J., Self-Regulated Learning and Academic
Achievement: An Overview. Educational Psychologist, 1990. 25:
p. 3-18.
[26] Worsley, H., Problem-based Learning (PBL) and the Future of
Theological Education: A Reflection Based on Recent PBL
Practice in Medical Training Compared to Emerging Trends in
Residential Ministerial Training for Ordination. 2005. 2(1): p.
71-81.
[27] Paris, S.G., M.Y. Lipson, and K.K. Wixon, Becoming a Strategic
Reader. Contemporary Educational Psychology, 1983. 8: p. 293-
316.
[28] Pintrich, P., R. Marx, and R. Boyle, Beyond Cold Conceptual
Change: The Role of Motivational Beliefs and Classroom
Contextual Factors in the Process of Conceptual Change.
Review of Educational Research, 1993. 63: p. 167-199.
[29] Bransford, J.D., Anchored Instruction: Why We Need It and How
Technology Can Help., in Cognition, Education and
Multimedia., D. Nix and R. Sprio, Editors. 1990, Erlbaum
Associates.: Hillsdale, NJ.
[30] Mayer, R., Learners as Information Processors: Legacies and
Limitations of Educational Psychology's Second Metaphor.
Educational Psychologist, 1996. 31(4): p. 151-161.
[31] Mayer, R., Cognitive Theory for Education: What Teachers Need
to Know, in How Students Learn: Reforming Schools Through
Learner-Centred Instruction, N. Lambert and B. McCombs,
Editors. 1998, American Psychological Association: Washington
DC. p. 353-378.
[32] Anderson, J.R., Cognitive Psychology and Its Implications. 1985,
New York: W.H. Freeman and Company.
[33] Mayer, R., The Psychology of how Novices Learn Computer
Programming. Computing Surveys, 1981. 13(1): p. 121-141.
[34] Piaget, J., Language and Thought of the Child. 1959, New York:
Humanities Press.
[35] Curven, B., S. Palmer, and P. Ruddell, Brief Cognitive Behaviour
Therapy. 2000, London: Sage Publications.
[36] Piaget, J., Origins of Intelligence in Children. 1952, New York:
International Universities Press.
[37] Bartlett, F.C., Remembering: A Study in Experimental and Social
Psychology. 1932, London: Cambridge University Press.
[38] Orlikowski, W.J. Learning from Notes: Organizational Issues in
Groupware Implementation. in CSCW 1992 Proceedings. 1992.
Toronto, Canada.
... Since learners' self-belief plays a fundamental role in intellectual development (Berland & Lee, 2011;Pajares, 1992), Jiang, Zhao, Wang, and Hu (2020) believe that this trauma happens when students lose their self-efficacy in programming, which negatively affects learning outcomes. Connolly et al. (2007) propose a cognitive model to explain how programming anxiety influences students' emotional, behavioral and physiological reactions (see Figure 1). The mental model asserts that students' automatic thoughts are activated in programming situations, directly influenced by their core and intermediate beliefs. ...
... Eventually, automatic thoughts affect their emotional, behavioral, and physiological reactions. According to Connolly et al. (2007), a fear of programming may commence caused by core beliefs for a student sensitive to programming anxiety. Then, intermediate thoughts of students could emerge as a fear of what other students might think about their performance and ability. ...
... At the same time, peers, teaching methodology, timing, lectures, and tutors constitute external factors. (Connolly et al., 2007) International Journal of Computer Science Education in Schools, April 2022, Vol. 5, No. 3 ISSN 2513 The number of studies on programming anxiety has risen dramatically in the last decade. Some of these studies examined factors associated with programming anxiety, while others investigated the impact of programming anxiety on student performance and motivation. ...
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The main goal of the current study is to develop a reliable instrument to measure programming anxiety in university students. A pool of 33 items based on extensive literature review and experts' opinions were created by researchers. The draft scale comprised three factors applied to 392 university students from two different universities in Turkey for exploratory factor analysis. The number and character of the underlying components in the scale were determined using exploratory factor analysis. After exploratory factor analysis, confirmatory factor analysis was conducted on the draft scale using a sample of 295 university students. Confirmatory factor analysis was carried out to ensure that the data fit the retrieved factor structure. The internal consistency coefficient (Cronbach's alpha) was calculated for the full scale and each dimension for reliability analysis. For convergent validity, the factor loading of the indicator, the average variance extracted, composite reliability, and maximum share variance values were calculated. Additionally, convergent validity was tested through (1) comparison of mean values of factors and total programming anxiety depending on gender and (2) correlation analysis of factors, total programming anxiety, and course grade of students. The Fornell & Larcker criterion and the Heterotrait-Monotrait correlation ratio were utilized to assess discriminant validity. According to analysis results, the Programing Anxiety Scale (PAS) comprised 11 items in two factors: classmates and self-confidence. Similarly, results revealed that The PAS has good psychometric properties and can be used to assess the programming anxiety of university students.
... Based on the problems identified, it can be stated that the competence aspect needs more strengthening, as relatedness and autonomy are partially addressed in the ENVS course ( Fig. 1). Incompetency in programming can be caused by not having adequate mental schemas, which properly deconstruct programming problems and form solutions (Connolly, Murphy, & Moore, 2007, 2008. Cognitive process occurs in a sequence of ordered stages, and learning occurs when the student makes linkages between new and existing knowledge or mental models, drawing from the long-term memory (Shih & Alessi, 1993). ...
... In programming, the failure to transfer knowledge beyond what is taught is one of the causes of programming anxiety and low competence (Connolly et al., 2007;Stachel et al., 2013). A study in Ireland amongst computer science students showed that students have greatest anxiety in showing competence with computer programming (Connolly et al., 2007). ...
... In programming, the failure to transfer knowledge beyond what is taught is one of the causes of programming anxiety and low competence (Connolly et al., 2007;Stachel et al., 2013). A study in Ireland amongst computer science students showed that students have greatest anxiety in showing competence with computer programming (Connolly et al., 2007). The study did a before and after measure and showed that students show negative sense of control (low selfconfidence) even at the end of the course. ...
Preprint
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This scholarship of learning and teaching (SoTL) piece will explore how non-computer science students learn programming as part of their primary degree. Computer programming requires the understanding of various concepts such as language syntax, logic, and assemblage of many abstract notions together. For a novice student, this may be overwhelming and can significantly increase the cognitive load, channel into low information processing, and cause lack of motivation in a learner. Therefore, in this SoTL piece, self-determination theory will be applied
... Programming language concepts expressed in a foreign language, and inexperience on programming can cause students to carry on with learning process in negative feelings, even to quit it (Garner, 2002;Gomes & Mendes, 2007;Kelleher & Pausch, 2005;Salleh et al., 2018;Tsai, 2019). This situation may create computer programming anxiety on students and prevent them to acquire programming skills (Chang, 2005;Connolly et al., 2007;Freeman et al., 2004;Owolabi et al., 2014). Programming languages which has simple syntax, programming tools facilitating algorithmic thinking, and programming tasks from easy to difficult can help reduce novice programmers' anxiety which discourages from them learning computer programming (Chang, 2005;Connolly et al., 2007;Tsai, 2019). ...
... This situation may create computer programming anxiety on students and prevent them to acquire programming skills (Chang, 2005;Connolly et al., 2007;Freeman et al., 2004;Owolabi et al., 2014). Programming languages which has simple syntax, programming tools facilitating algorithmic thinking, and programming tasks from easy to difficult can help reduce novice programmers' anxiety which discourages from them learning computer programming (Chang, 2005;Connolly et al., 2007;Tsai, 2019). ...
... Negative feeling of novice programmers toward Programming language (Kelleher & Pausch, 2005;Tsai, 2019) may create computer programming anxiety on them and prevent improve programming skills (Chang, 2005;Connolly et al., 2007). But, some studies in literature have investigated computer anxiety instead of computer programming anxiety (Chang, 2005;Owolabi et al., 2014). ...
Article
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In this study, based on quasi-experimental research, was investigated the effects of teaching Python programming language via Blockly tool, which had hybrid interface, on students’ computer programming anxiety, cognitive load level, and achievement. Participants were 90 high school students, 44 of them in experimental group (hybrid interface) and 46 of them in control group (non-hybrid interface). According to results, there was a meaningful difference between programming achievement scores of students in favor of experimental group while there was no difference in terms of computer programming anxiety between groups. Moreover, after 10-week implementation process, students’ anxiety increased in each group. It was found out cognitive load levels of both groups in the first week were higher than final week. Although both weekly and 10-week intrinsic, extraneous, germane, and total cognitive load levels of experimental group were lower than control group, there was no significantly difference between groups. Consequently, it can be said that programming via hybrid interface, using Blockly, has not an effect on students’ computer programming anxiety positively whereas it helps to keep cognitive load at low level and to increase students’ programming success more. It is recommended that considering these results to make computer programming education is more efficient in high schools and administrators encourage the teachers to use programming tool had hybrid interface such as Blockly.
... The andragogy focuses rather on the strengths of the learner (adult in their learning and in regulating their learning). Questions could be asked about how BLEs deal with adults that do not possess these characteristics, for example second chance learners (Connolly, Murphy, & Moore, 2007). ...
... Although research stresses the suitability of BLEs for adults (Brookfield, 1986;Caffarella & Merriam, 2000;Tough, 1978), research on second chance education suggests that such learners are not necessarily able to regulate their own learning (Connolly et al., 2007). Research on self-regulation in blended-learning environments regularly reports the importance of specific self -regulatory abilities learners need, to be able to benefit from BLEs (e.g., Lynch & Dembo, 2004a). ...
... Although research stresses the suitability of BLEs for adults (Brookfield, 1986;Caffarella & Merriam, 2000;Tough, 1978), research on second chance education shows that such learners are not necessarily adult learners as described by some authors (Connolly et al., 2007). Research on self-regulation in blended-learning environments regularly reports the importance of self-regulatory abilities learners need, to be able to benefit from BLEs (e.g., Lynch & Dembo, 2004a). ...
Technical Report
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Blended forms of learning in adult education have become increasingly popular. Learning activities within these environments are supported by large varieties of online and face-to-face interventions. However, it remains unclear under what conditions these environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet, little is known about (1) which self-regulatory behaviours learners exhibit, (2) which environmental attributes support self-regulation and so (3) how blended learning environments (BLEs) can be designed to impact learners’ self-regulatory behaviour. The main objective of this PhD project is to develop and validate an instructional design model for the support of learners’ self-regulation in BLEs at the micro (course) level. The target group for this project is vulnerable ‘second-chance’ learners in adult education. Four studies are planned in a design-based research approach. The first two were undertaken prior to this report, study three is currently in progress and study four still needs to take place. The first study investigated which attributes of BLEs support learners’ self-regulation. Based on a systematic literature review, seven attributes that support self-regulation were identified and defined. A descriptive framework for the description of BLEs was developed and validated in different contexts. Based on these actions, the current instructional state of six BLEs designed for the target group was described. The second study examined the self-regulatory behaviour learners exhibit in BLEs and how this behaviour relates to the design of such environments. Traces were collected from the online learning environments. Three self-regulatory profiles could be determined. The results showed a relation between the design of BLEs and the self-regulatory behaviour learners exhibit in them. The two design attributes that occurred least often in the BLEs described were cues for reflection and calibration. Evidence showed that in environments that had some reflection cues, significantly fewer mis-regulators were observed compared to environments that did not include such cues. Based on the results of studies one and two, a third and fourth study will be undertaken to investigate the integration of reflection cues in BLEs. Study three examines the hypotheses that (a) learners’ performance is better in environments with extra reflection cues than in environments that do not have such cues, (b) the self-regulatory behaviour of learners will differ between the two environments and (c) a change in learners’ self-regulatory behaviour reflects a change in the learners’ characteristics rather than an ad-hoc behavioural change. Both studies take a quasi-experimental design-based research approach, including pre- and post-tests and experimental and control conditions. Through two iterative design cycles entailing (a) the description of the current states, (b) a redesign of the BLE, and (c) a final description of the current states, changes in the learners’ self-regulation will be investigated. While studies three and four have the same goal, study four will attempt either to target a different attribute (calibration) or to maximize the effectiveness of study three. These research actions facilitate the development of a model for the design of BLEs that support learners’ self-regulation. Such a model would enable (1) the systematic description of existing BLEs and self-regulatory behaviours exhibited by the learner, (2) an informed analysis of the relationships between design and behaviour, and, subsequently, (3) the (re)design of BLEs that support self-regulation. The project also aims to contribute to two research areas. On the one hand, it strengthens the educational psychology field by identifying and defining attributes that support learners’ self-regulation in BLEs. It proposes an instrument for describing such environments. Finally, it proposes a more refined methodology for investigating learners’ self-regulatory behaviour, using ecological trace data. On the other hand, it strengthens the educational technology field by providing design guidelines for the implementation of environmental attributes to support learners’ self-regulatory behaviour in both online and offline components of blended learning environments.
... Another of the challenges facing programming teaching is programming anxiety. (Jenkins, 2002;Akhu-Zaheya et al., 2012) stated that the students who were worried had problems in learning, Gürcan (2005) stated that students with high programming anxiety were less likely to write programs, Connolly et al. (2007) reported that students had difficulties in understanding the discrete structure of programming and this causes inquietude and McInerney (1990) stated that the anxiety level of the students who took the programming course and completed it without any problem was lower than the other students. ...
... However, although there is an increase in the level of anxiety in the theory integrated group, this increase is not statistically significant. Connolly et al. (2007) supported this finding in their study, students have difficulty in understanding and embody discrete and complex structures, and have experienced stress and anxiety especially in the introductory course in computer programming, Baloğlu and Çevik (2008) reported that students have computer anxiety and, consequently, may experience anxiety in programming teaching; Fesakis and Serafeim (2009) showed that educational programming languages reduce the percentage of stress and anxiety; Tzavara and Komis (2003) stated that participation in courses will help to lower the stress levels of students; Bishop-Clark et al. (2007) supported this conclusion with the findings that educational programming languages increase confidence in programming and reduce anxiety. Gürcan-Namlu (2003) examined the effect of computer programming anxiety on success. ...
Article
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The abstract structure, logic, negative perceptions, and anxiety of programming are seen as obstacles to novice programmers. The importance of educational programming languages is increasing day by day in overcoming these obstacles. In this study, it was aimed to investigate the effect of educational programming language integration on academic achievement and programming anxiety level. The pretest–posttest test design without control group, which is one of the experimental methods, was used in the study, which was carried out on three groups consisting of the theory, practice and integration of the course into both theory and practice part. The groups determined by random sampling method consist of 87 people, 61 boys and 26 girls. Pretest–posttest method was used to determine academic success. During the application process, five performance tests were used to determined the change in success. The scale developed by Cheung (1990) in determining computer programming anxiety was adapted to Turkish by the validity and reliability study by the researcher and was used as pre-test and post-test. Variance and covariance analyzes were used to determine anxiety about academic success and programming, and the results of Kruskal–Wallis test analyzes were used for analysis of performance tests. It is concluded that educational programming languages can be used by integrating both the theory and practice of the course in order to increase academic success and in-class performance and reduce anxiety about computer programming.
... Others have stressed for example autonomy, selfdirection, and affinity for real-life learning as key characteristics of adult learners (see e.g., Brookfield 1986;Caffarella and Merriam 2000;Tough 1978). Questions could be asked about how BLEs deal with adults that do not have these characteristics, for example second chance learners (Connolly et al. 2007). The andragogy focuses rather on the abilities of the learner (adult in their learning and in regulating their learning). ...
... Although research stresses the suitability of BLEs for adults (Brookfield 1986;Caffarella and Merriam 2000;Tough 1978), research on second chance education shows that such learners are not necessarily typical 'adult learners' (Connolly et al. 2007). Research on self-regulation in blended-learning environments regularly reports the importance of specific self-regulatory abilities learners need, to be able to benefit from BLEs (e.g., Lynch and Dembo 2004b). ...
Article
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Blended forms of learning have become increasingly popular. However, it remains unclear under what circumstances blended learning environments are successful. Studies suggest that blended learning challenges learners’ self-regulation. Yet little is known about what self-regulatory behaviour learners exhibit in such environments. This limited understanding is problematic since this insight is needed for effective designs. Therefore, the aim of this study was to identify learners’ self-regulatory behaviour profiles in blended learning environments and to relate them to designs of blended learning environments. Learners’ (n = 120) self-regulatory behaviour in six ecologically valid blended learning courses was captured. Log files were analysed in a learning analytics fashion for frequency, diversity, and sequence of events. Three main user profiles were identified. The designs were described using a descriptive framework containing attributes that support self-regulation in blended learning environments. Results indicate fewer mis-regulators when more self-regulatory design features are integrated. These finding highlights the value of integrating features that support self-regulation in blended learning environments.
... On the other hand, consistent with the former findings (Connolly, Murphy, & Moore, 2007;Owolabi, Olanipekun, & Iwerima, 2014), one sub-scale of the programming anxiety scale was correlated with achievement test posttest scores. In addition, the Significant Others and Ability Anxiety sub-scales of the computer programming anxiety scale were negatively associated with participants' programming self-efficacy perceptions. ...
Article
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Computer games are effective instructional tools used in programming courses to increase students' motivation and engagement. This participatory action research aims to redesign the Object-Oriented Programming course in which the first author is both the instructor and researcher to make it more effective and efficient. In the first step of the action research, data were collected for the definition and solution of the problem through questionnaires and semistructured interviews. After this step, an action plan was created, and the ObjectOriented Programming course was redesigned as part of the action plan. In line with the objectives of the action plan, The Karting Microgame Template, a game prototype prepared by Unity 3D, was integrated into the course, and students were expected to add various game components (bonus collection system, a scoring system, collision mechanisms, etc.) to this game prototype using C # programming language. After the action plan creation phase, an action plan was implemented. The implementation phase was conducted in the 2019-2020 spring semester with 29 post-secondary students enrolling in Computer Technology Department at a vocational college in Turkey. After the implementation phase, data were collected through the Object-Oriented Programming achievement test, student and researcher diaries, and focus group interviews on measuring this implementation's effectiveness. This paper describes the difficulties encountered during the study, the students' views on this implementation, and the researchers' experiences in this process.
... Dolayısıyla uzaktan eğitimle verilen programlama eğitiminin, öğrencilerin bilgisayar programlama kaygısını değiştirmediği söylenebilir. Alanyazında öğrencilerin programlama kaygısını tetikleyen etmenler; programlamaya karşı olumsuz algı ve kalıplaşmış düşünceler, programlama dillerindeki karmaşık söz dizimi ve programlamada yaşanan zorluklar olarak ifade edilmiştir (Connolly, Murphy & Moore, 2007;Ünal, 2019;Saeli, Perrenet, Jochems, & Zwaneveld, 2011;Zainal ve diğ., 2012). Uzaktan eğitim dışında, genel olarak öğrencilerin bilgisayar programlamaya yönelik kaygılarını konu alan çalışmalara rastlanılmıştır. ...
... These learners manage and plan their learning activities well over time and reach every deadline. Although research stresses the suitability of BLEs for adults [5], it is often suggested that such learners are not necessarily able to regulate their own learning [6]. Research on self-regulation in BLEs regularly reports the importance of specific self-regulatory abilities learners need, to be able to benefit from BLEs [4]. ...
Conference Paper
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Blended forms of learning in adult education have become increasingly popular. Learning activities within these environments are supported by large varieties of online and face-to-face interventions. However, it remains unclear under what conditions these environments are successful. Studies suggest that blended learning challenges learners' self-regulation. Yet, little is known about (1) what self-regulatory behaviors learners exhibit in blended learning environments (BLEs), (2) what environmental attributes support self-regulation and so (3) how BLEs can be designed to impact learners' self-regulatory behavior. By identifying and investigating the relationship between the design of BLEs, learners' (cognitive, motivational, and metacognitive) characteristics and ecologically valid sequenced log file data of learners' self-regulatory behavior, this PhD project aims to develop and validate an instructional design model for the support of learners' self-regulation in BLEs at the course level.
Thesis
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Oyun geliştirmeye dayalı öğrenme stratejisi, öğrencilerin oyunlara karşı olan ilgilerini sıfırdan bir oyun geliştirmeye veya mevcut bir oyuna eklentiler yapmaya yönlendirerek programlamayı öğrenmelerini sağlamayı amaçlamaktadır. Bu stratejide öğrenciler yazılım mühendisliği yöntem ve tekniklerini oyun geliştirme projeleri vasıtasıyla deneyimlemektedir. Bu tez çalışmasında araştırmacının kendisinin vermekte olduğu Nesne Yönelimli Programlama dersinde yaşanan sorunları en aza indirebilmek ve dersin verimliliğini artırabilmek için oyun geliştirmeye dayalı programlama öğretiminin mevcut derse bütünleşmiş edildiği bir eylem araştırması yürütülmüştür. Bu bağlamda araştırmanın amacı; mevcut Nesne Yönelimli Programlama dersinin sorunlarının tespit edilmesi; mezun öğrencilerin, uzmanların ve alanyazındaki çalışmaların önerileri ışığında mevcut dersin oyun geliştirmeye dayalı öğretim stratejisini temel alarak yeniden tasarlanması; geliştirilen dersin uygulanması ve bu süreçte yaşanan deneyimlerin raporlanması olarak belirlenmiştir. Belirlenen amaç ve hedefler doğrultusunda bu tez çalışması, iki araştırma döngüsünü kapsayacak şekilde tasarlanmış ve uygulanmıştır. Birinci döngü analiz, tasarım, uygulama ve değerlendirme basamaklarını içerirken ikinci döngü tasarım, uygulama ve değerlendirme basamaklarını içermiştir. Birinci döngünün analiz aşamasında daha önce nesne yönelimli programlama dersini almış ve okullarından mezun olmuş 59 katılımcı ile nesne yönelimli programlama dersini vermekte olan altı öğretim elemanından veriler toplanarak mevcut dersin sorunlarının detaylı bir şekilde tespit edilmesi sağlanmıştır. İlave olarak analiz aşamasında öğrencilerin derste geliştirmek istedikleri yazılım projesi ve oyun türleri nedenleriyle incelenmiştir. Tasarım aşamasında; analiz aşamasından elde edilen verilerin çözümlenmesinden ve alanyazından yararlanılarak mevcut nesne yönelimli programlama dersi Morrison, Ross ve Kemp öğretim tasarım modeli ışığında oyun geliştirmeye dayalı öğretim stratejisini temel alacak şekilde yeniden tasarlanmıştır. Birinci döngünün uygulama aşaması sekiz hafta sürecek şekilde Türkiye’deki bir meslek yüksekokulunun bilgisayar teknolojisi programında öğrenim görmekte olan 29 önlisans öğrencisi ile yürütülmüştür. Birinci döngünün uygulama aşamasından sonra uygulanan eylem planının etkinliği değerlendirilmiş ve birinci döngüde karşılaşılan sorunların giderilmesi amacıyla ikinci döngünün tasarım aşamasında bazı revizyonlar gerçekleştirilmiştir. Revize edilen nesne yönelimli programlama dersi acil uzaktan öğretim yöntemi kullanılarak 15 hafta sürecek şekilde Türkiye’deki bir meslek yüksekokulunun bilgisayar teknolojisi programında öğrenim görmekte olan 30 önlisans öğrencisi ile yürütülmüştür. Bu aşamadan sonra uygulanan eylem planının değerlendirilmesine yönelik yansıtma yapılmıştır. Araştırmada hem nitel hem de nicel araştırma tekniklerine uygun olarak toplam 14 adet veri toplama aracı kullanılmıştır. Araştırmanın birinci döngü bulgularına göre oyun geliştirmeye dayalı stratejisi temel alınarak sunulan öğretimin katılımcıların nesne yönelimli programlama bilgi ve becerilerini anlamlı şekilde geliştirdiği tespit edilmiştir. Bunun yanında katılımcıların en çok çokbiçimlilik, kurucu metot ve kapsülleme konularında zorlandıkları da ortaya çıkmıştır. İkinci döngüde gerçekleştirilen revizyonlarla birlikte bu konularda gelişim sağlanmıştır. Araştırmanın diğer sonuçlarına göre oyun geliştirmeye dayalı programlama öğretiminin her iki döngüde de katılımcıların çoğunun programlama dersine yönelik motivasyonlarını ve programlama öz yeterlilik algılarını olumlu etkilediği görülmüştür. Ancak programlama kaygısı bağlamında değerlendirildiğinde, katılımcıların programlama kaygılarının çalışmanın başlarında arttığı ancak süreç içinde azaldığı; yine de programlama kaygılarının devam ettiği sonucuna varılmıştır. Bu çalışma kapsamında gerçekleştirilen öğretim tasarımın ve uygulama sonucunda elde edilen deneyimlerin, geliştirilen “Programlama Kaygı Ölçeğinin” alanyazına katkı sunması açısından önemli görülmektedir. Oyun geliştirmeye dayalı öğretim stratejisinin nesne yönelimli programlama dersine entegrasyonu açısından değerlendirildiğinde, mevcut çalışmanın öğrencilerin nesne yönelimli programlama dersinde karşılaştıkları sorunları en aza indirmeye çalışması; öğrencilerin programlamaya yönelik ilgi ve motivasyonlarını artırarak programlama öz yeterlilik algılarında olumlu değişimler yaratmayı amaçlaması bakımından güncel, işlevsel ve özgündür. Anahtar Kelimeler: Nesne Yönelimli Programlama, Oyun Geliştirmeye Dayalı Programlama Öğretimi, Oyun Programlama, Programlama Dersine Yönelik Motivasyon, Programlama Öz Yeterliliği, Programlama Kaygısı.
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Definitions of the three components of computer literacy and of computer anxiety were used in a nationwide survey of instructional computing educators to develop a list of seventy competencies of the computer-literate person. This list was used to develop an eighty-question multiple-choice examination. This test was divided into three parts, one part for each of the three components of the definition of computer literacy. Normative data were collected from 341 college students from six different universities. The examination was found to have a reliability estimate of .86. A computer anxiety index (CAIN) was also developed. This instrument was designed to be used to determine a person's level of computer anxiety. Normative data from 1943 students were collected. The CAIN was found to have a reliability of approximately .90. Both the eighty-item achievement test and the twenty-six item CAIN were sent to a nationwide selection of instructional computing specialists who evaluated them. This evaluation was used to revise the two tests. In summary, this article describes the process used to develop two examinations, an achievement test of computer literacy, and a computer anxiety index.
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