A Theory of the Relationships between Cognitive Requirements of Computer Programming Languages and Programmers Cognitive Characteristics

Journal of Information Systems Education, Vol 13(1)

A Theory of the Relationships between Cognitive
Requirements of Computer Programming Languages
and Programmers’ Cognitive Characteristics


Garry L. White, Ph. D.
GW06@business.swt.edu

Marcos P. Sivitanides, Ph.D.
Department of Computer Information Systems
College of Business Administration
Southwest Texas State University
San Marcos, TX 78666


ABSTRACT

This paper formulates a theory that investigates the possible effects of two human cognitive characteristics, on the
difficulties of learning specific programming languages. The two human cognitive characteristics are Piaget’s cogni-
tive development and McCarthy’s cognitive hemispheric style. This paper consolidates prior research and accepted
cognitive theory. It then presents a formulation of a theory that relates cognitive requirements of different computer
programming languages and programmers’ cognitive characteristics. If the cognitive requirements for a programming
language are beyond the cognitive characteristics of a programming student, the student may burn out. If the cognitive
requirements are below the student’s cognitive characteristics the student may be bored. If they are similar to them,
the student is able to meet the challenges. Motivation, interest, self-esteem and success may thus be optimized. Differ-
ent programming languages are more suited for different cognitive characteristics. This theory extends prior research in
cognitive theory and cognitive requirements of computer programming.

Keywords: Cognitive development, Cognitive style, Programming languages, Script Programming, Procedural
programming, Object-oriented programming, Visual programming


1. INTRODUCTION
learning style in the studies of academic success at the

college level" (Hudak 1990). This type of research
"There is a need to understand how people learn, not
just aptitude. Such understanding may influence
can enhance academic teaching and industry training.
productivity in various programming languages"
(Rosson 1990; Scholtz 1993; Sheetz 1997).
(Myers 1996). Research is needed to improve under-

standing of the learning process and identify the
Why do some students take computer programming
underling cause of students' difficulties with pro-
courses and fail, while others succeed? Research has
gramming languages. "Study of the language-learning
shown that novice college computer science students
process is necessary to understand how the process
experience more difficulty with concepts involving
can be improved" (Myers 1996). A research study
mathematical logic, than they do with other concepts
with computer science courses emphasized "the need
(Almstrum 1994). Cafolla (1987) found that "... some
to examine students' cognitive maturity and learning
people of college age have difficulty in learning
style -- factors often ignored in research aimed at
procedural programming. This suggests that the
ascertaining the reasons for academic success at the
cognitive skills needed to learn procedural program-
college level." The findings of that study "highlight
ming develop later or perhaps never, in some". Is it
the need to examine both cognitive maturity and
possible that these students lack the required cognitive

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Journal of Information Systems Education, Vol 13(1)

characteristics to learn programming? This begs the
son 1983). This is significant for procedural pro-
question: Which hemispherical cognitive style and
gramming. Procedural programming logic uses the
which stage of cognitive development are better suited
biconditional reasoning of “if and only if” logic.
for different computer programming language para-

digms?
Children younger than 11 or 12 find it difficult to
This paper focuses on two human cognitive character-
learn procedural programming (Becker 1982).
istics: (1) cognitive development and (2) cognitive
This suggests there is some type of cognitive
hemispheric dominance (cognitive style). The
development that allows older children above this
different programming language paradigms, whose
age range to learn procedural programming. Since
cognitive requirements are considered in this paper,
procedural programming skills are related to
are: procedural, object-oriented, visual, and script.
logical reasoning (Folk 1973; Fletcher 1984;

Cafolla 1987), it is not surprising that younger
It should be noted that the impact of these cognitive
children are unable to do programming in light of
factors can vary in strength due to differences in
Piaget's theory of cognitive development.
course content. For example, a programming

paradigm may involve concepts that favor the left side
Piaget's theory fosters the notion that formal opera-
of the brain, while another one may involve concepts
tional thinking abilities develop around age 11-12
that favor the right side. One programming paradigm
(Chiapetta 1976). It is at this age that students begin to
may focus on object manipulation, while another may
move from concrete thinking to logic/abstract think-
focus on problem solving skills and the flow of logic
ing. Research has shown that these formal operations,
through the program.
such as thinking in abstractions and logically, occur

much later in some people or not at all (Griffiths
2. COGNITIVE CHARACTERISTICS
1973; Schwebel 1975; Pallrand, 1979).


Research has shown that cognitive development (what
Research has shown that 17% of 7th graders, 23%
can be learned), cognitive styles (how one learns), and
of 8th graders, and 34% of 12th graders reach
prior experiences are factors in learning procedural
formal operational thinking abilities (Renner
programming languages (Losh 1984; Fletcher 1984;
1978). Similar findings were made by Epstein
Little 1984; Ott 1989; Monfort 1990). Myers (1996)
(1980), when he showed that development through
showed that different learning styles were significant
Piaget's stages was by degree. For example, while
predictors of achievement between Imperative
20% of 13 year olds (8th graders) were at the
(Procedural) and Functional (Non-Procedural)
formal operational stage, 78% were at the concrete
programming methods. Bishop-Clark (1995) found
operational stage and 2% were at the pre-
that cognitive style affected programming perform-
operational stage of cognitive development.
ance.


Several studies show that a majority of adults, includ-
2.1 Cognitive Development
ing college students and professionals, fail at many
Piaget’s cognitive development theory deals with
formal operational tasks (Sund 1976; Petrushka 1984).
three stages of development (Piaget 1972; Epstein
Many college students fail to attain full formal
1990), pre-operational, concrete, and formal opera-
operational thinking (Griffiths 1973; Schwebel 1975).
tions. Pre-operational cognitive level involves the
There are adults who’s cognitive development is at the
mental age from age 2 years to age 7 years.
concrete level, mental age of 7 years to 12 years.


The concrete level person, mental age of 7 years to 12
Different people develop their formal operational
years, understands conservation of matter and classifi-
thinking abilities at different rates and may reach
cation/generalization (conclude that all dogs are
different maximum levels. Why do so many, never
animals and not all animals are dogs). However, such
reach the formal level of thinking? The reason has
a person is unable to comprehend mathematical ratios
been identified to be dependant upon the maturing
(Barker 1983).
neural fibers between the left and right cerebral

hemispheres (Kraft 1976). The advancement of people
Formal operations is the highest cognitive develop-
through the development of Piagetian stages is an
ment level defined by Piaget. It is the ability to deal
indication of such maturation. Ross (1982) found that
with abstractions, form hypotheses, solve problems
Epstein's descriptions of growth spurts and plateaus
systematically, and engage in mental manipulations.”
corresponded to Piaget’s learning stages.
(Biehler and Snowman 1986). A precondition to

formal operations development is to understand
2.2 Cognitive Style
biconditional reasoning, “if and only if” logic (Law-
Different people process the same information in

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Journal of Information Systems Education, Vol 13(1)

different ways using different areas of the brain,
from the instruction code.

depending upon their cognitive style. Hemisphericity

is a term used to describe how the brain processes
3.1.1 Cognitive Development
specific information, and research suggests that one
Some research suggests that programming involves
side predominates over the other (Losh 1984). The left
important higher cognitive abilities (Hudak 1990)
brain functions differently from the right brain (Saleh
such as problem solving and Piaget's formal opera-
1995; Supprian 1997). Examples of some left
tions. Other studies have shown that formal opera-
hemispheric characteristics are: talking/writing and
tional reasoning ability is necessary for success in
rational, objective judgments. Examples of some right
procedural computer programming/logic (Fletcher
hemispheric characteristics are: intuitive, subjective
1984; Little 1984; Azzedine 1987; Hudak 1990).
judgment, and drawing/manipulating physical objects

(McCarthy 1986).
Azzedine (1987) tested 203 students from the 6th

grade to college level with the Langeot Test of
Electroencephalograms (EEG's) have shown that
Cognitive Development. This research investigated
different cognitive styles use different sides of the
the implications of Piaget's cognitive developmental
brain (Riding 1997). This leads to further hemispheric
theory and the intellectual prerequisite of learning
differences (Gordon 1988), because the right and left
procedural programming. The results showed that
cerebral hemispheres process information differently.
cognitive development predicted programming
Which hemispherical cognitive style is best for
performance.
different computer programming languages? Studies

using EEG measurements have shown that cognitive
Cafolla (1987) did a similar study with students from
tasks activate different parts of the brain (Jausovec
a community college. Each student was given the
1997). EEG measurements have shown that the left
Inventory of Piaget's Development Tasks (IPDT) to
brain deals with Piagetian tasks of logic (Kraft 1976)
measure his or her cognitive development level. The
and EEG measurement showed increased activity in
results were the same as for Azzedine (1987): cogni-
the left hemisphere when subjects performed
tive development predicted programming perform-
arithmetic (Rotenberg 1997).
ance.


Geschwind & Galaburda (1985) found many studies
Little (1984) found that students who tested high in
showing that each hemisphere is usually superior over
formal operations, Piaget's high level of cognition,
the other in certain cognitive functions and that the
scored higher on programming and logical thinking
left hemisphere matures later than the right. The right
measures than those students who were concrete
side of the brain seems to handle concrete experiences
operational thinkers (a Piaget's lower level of cogni-
and the left side of the brain seems to process abstract
tion). This cognitive developmental level is a factor in
conceptions (Diehl 1986). Another study showed that
determining one's ability to learn procedural pro-
the left brain is the logical cognitive side and that the
gramming (Folk 1973). This finding is also supported
right brain is the creative cognitive side (Herrmann
by Hudak & Anderson (1990). They determined that
1981). Other studies have shown that the left side of
people who have reached Piaget's formal operational
the brain also deals with logical cognition (Lawson
stage, would have the tools needed to understand
1975). A more recent study found some cooperation
programming. They also have a greater abstract
between the hemispheres involving reasoning. The left
learning style that helps them learn programming.
brain dealt with probabilistic reasoning and the right

brain dealt with deductive reasoning (Osherson 1998).
3.1.2 Cognitive Style

Students who are successful in procedural
3. COGNITIVE CHARACTERISTICS AND
programming have been found to be significantly left
PROGRAMMING LANGUAGES TYPES
hemispheric brain dominant for cognitive style (White

2001). This was true at public, post-secondary and
3.1 Procedural Languages
vocational-technical schools where "Your Style of
Most programming languages are Procedural. Such a
Learning and Thinking-Form C" inventory forms were
language is "characterized by these three properties:
used (Losh 1984). A later study found Computer
the sequential execution of instructions, the use of
Science and Mathematics students also to be left brain
variables representing memory locations and the use
dominant while music, art, oral communication and
of assignment to change the values of variables"
journalism students were found to be right brain
(Louden 1993). The data is kept separately from the
dominant. Brain hemisphere dominance was inferred
procedures within the same program. An example of
from Human Information Processing Survey scores
such a language is COBOL. The definitions of data
(Monfort 1990).
used in the program are placed in separate code away


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A dissertation by Ott (1989) supports the above
concrete component, it may be that those who are pre-
findings. She found that left brain dominance in high
formal operation thinkers would be able to handle this
school students, correlated significantly with grades in
challenge of visual objects on a screen and be success-
procedural programming courses (r = .30 & .34).
ful. Formal operation thinkers might find it an easy
Brain dominance was determined by the Herrmann
task, since the cognitive characteristic of visual
Participant Survey Form.
programming has a concrete component. Empirical

research that deals with Visual programming and
3.2 OOP Languages
cognitive development is lacking in the literature.
Object oriented programming "is based on the notion
Empirical research is warranted to support or reject
of an object, which can be loosely described as a
this hypothesis.
collection of memory locations together with all the

operations that can change the values of these memory
3.3.2 Cognitive Style
locations" (Louden 1993). Data declarations, data
Since there are OOP characteristics/concepts with
definitions and program instructions are all under one
Visual Programming, it is speculated that it would be
identifier, known as an object. Examples of this type
cognitive (hemispheric) style friendly. Empirical
of paradigm language are C++ and Java.
research that deals with Visual programming and

cognitive style is lacking in the literature. Empirical
Most research dealing with the cognitive aspects of
research is warranted to support or reject this hypothe-
programming dealt with Procedural programming
sis.
languages, such as COBOL, BASIC, Pascal and

FORTRAN. There is very little research dealing with
3.4 Script Languages
cognitive characteristics required for OOP.
3.4.1 Cognitive Development

What about those who are at a lower level of cognitive
3.2.1 Cognitive Development
development such as concrete operational thinkers as
What is known about OOP indicates that development
defined by Piaget? A solution might be script pro-
of a program uses problem solving skills, a high
gramming languages, such as HTML, XML and other
cognitive level (Kim 1997). A recent research study
web page development languages. Such programming
did show that OOP also involved Piaget’s formal
languages develop formats and layouts of visual
operational cognitive level (White 2001). More
objects and text on the computer screen. Script
research in this area is warranted.
programming may be an alternative for those who find

procedural programming or OOP difficult. Script
3.2.2 Cognitive Style
languages lack substantial logic and abstract proce-
Cognitive style appears to be hemispheric friendly.
dures. The user indicates how things are to be dis-
All hemispheric styles appear to be able to learn OOP
played on the screen. Instead of using logic and
(White 2001). This may be due to the fact that user
abstract algorithms to query and process data, English
cognition has shown Object Oriented properties of
like statements could be used to tell the computer
cognitive economy and limited storage space (Krovi
what is to be done. Empirical research that deals with
1998). More research in this area is warranted.
Script programming and cognitive development is

lacking in the literature. Empirical research is war-
3.3 Visual Languages
ranted to support or reject this hypothesis.
There is a lack of research describing required

cognitive characteristics for Visual Programming.
3.4.2 Cognitive Style
What follows is a formulation of a hypothesized
Since the right side of the brain seems to handle
theory based on Piaget’s theory and characteristics of
concrete experiences and creativity while the left side
the language. Empirical research is warranted, to
of the brain seems to process abstract and logic
support or refute this new hypothesized theory.
conceptions (Diehl 1986; Herrmann 1981; Lawson
1975), it is hypothesized that Script programming is
3.3.1 Cognitive Development
right hemispheric cognitive style.
The language characteristic of Visual programming is

the manipulation of visual objects on a computer
However, subjects with mixed hemispheric domi-
screen. An example is Visual Basic by Microsoft.
nance, based on eye-hand preference, have shown low
Some Visual programming languages have OOP and
performance when using HyperCard software. The
procedural characteristics. Therefore, it is suspected
subjects who were more symmetrical in laterality, left
that formal operation cognitive level would be
hand-left eye or right hand-right eye, exhibited better
required. However, instead of manipulating abstract
performance when designing a sales presentation
objects found in C++ or Java, visual objects on a
using HyperCard software (McCluskey 1997).
computer screen are manipulated. Since this is a


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Table 1. Programming Languages and Cognitive Development/Style

Programming

Piaget’s Cognitive Development Levels
Cognitive Style
Pardigm

Pre-Oper Concrete Pre-Formal Formal (Hemisphericity)

Procedural (COBOL,
Burnout Burnout Burnout P & M
Left Brain
logic sequence)

Object Oriented (C++,
Burnout Burnout Burnout P & M
Either Hemisphere
Java, concepts)

Visual (Visual Basic,
Burnout Burnout P & M Bored
Either Hemisphere
on screen)

Script (HTML,

Burnout P & M Bored
Bored
Right Brain
Web Pages)
P & M: Productive and Motivated

Empirical research that deals with Script programming
programming courses taught in schools.
and cognitive style based on hemispheric dominance

is lacking in the literature. Empirical research is
5. EDUCATIONAL IMPLICATIONS
warranted to support or reject this hypothesis.


If a teacher uses subject material that caters to the left
4. SUMMARY
side of the brain, right dominant brain students will

have trouble (Creswell 1988). If the content level
The literature has shown that formal operational
exceeds the cognitive level of the students, the
cognitive development is a required cognitive
students will burnout. There is the risk that the
characteristic of people for learning procedural
students’ self-esteem will be damaged. As shown in
programming. The majority of adults and many
Table 1, if the students’ cognitive level exceeds the
college students fail to develop to full formal
course content level, the students will be bored. The
operational thinking skills. Research has also
students’ interest and motivation will be hindered.
supported logical thinking skills (a component of

formal operational cognitive development) as a
It is recognized that individuals learn differently and
required characteristic for learning procedural
have different instructional needs (Sonnier 1976). To
programming.
be most effective, teaching styles and content level

must be compatible with the cognitive development
Research has shown that procedural and object
and style of an individual. It is beneficial to the
oriented programming, require the cognitive charac-
students that computer programming courses have
teristic of formal operations. Those at this cognitive
prerequisites that place them in a course that best fits
level would be “productive and motivated” (P & M),
their cognitive characteristics. Motivation, interest,
able to handle the challenge of procedure program-
self-esteem, and success may thus be optimized.
ming and OOP. They would have the mental tools to

be successful. Table 1 shows a conjecture that those
A way to implement some type of prerequisites, is to
students who are below this cognitive level would
use standardize math scores from the ACT and SAT.
“burnout” in such a programming class. The required
The research literature supports the relationship
cognitive characteristic of the language is beyond the
between mathematic scores and success with
cognitive development of the student.
procedural programming languages (Ricardo 1983;

Ignatuk 1986; Renk 1987; Ott 1989). If the learner is
The literature has shown left hemispheric thinking
weak in mathematics, the placement would be with
style of learners as another characteristic necessary for
Script or Visual programming. If the learner is strong
success with procedural programming. Since schools
in mathematics, the placement would be with
tend to teach to the left hemispheric thinking style
procedural or OOP programming. Again, research to
(Hatcher 1983; Walden 1995), this may explain why
show relationships between mathematic scores and
many right brain thinkers have problems with
success with Script, Visual, and OOP programming

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adolescence to adult. Human Development, 15, 1-
Sund, R. B. [1976], “Piaget for educators: a
12.
multimedia program.” In Brooks, R (1978) “The
relationship between Piagetian Cognitive

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Journal of Information Systems Education, Vol 13(1)

development and cerebral cognitive asymmetry.”
are in the areas of Computer Programming, Systems
ERIC(ED160224, Trans.). Columbus: Charles E.
Analysis and Design, Database Design and Manage-
Merrill.
ment, and Computer Networks. His research interests
Supprian, T. and E. Hofmann [1997], “The fornix of
and work are in the areas of Decision Theory, Com-
the human brain: Evidence of left/right asymmetry
puter Education, and Curriculum Development and
on axial MRI scans.” Surgical and Radiologic
Design. He has published papers and abstracts in
Anatomy, 19(2), 105.
journals such as Decision Sciences and the Journal of
Walden, U. [1995], “The neuropsychological
Information Systems Education and conferences such
implications of hemispheric learning and teaching
as the Decision Sciences Institute, and the Information
preferences on the achievement of college prep
Systems Educational Conference.
students: In search of brain based education.”

Dissertation Abstracts, A55(9), 2780

White, G. L. [2001], “Cognitive Characteristics for

Learning Java, an Object Oriented Programming

Language.” Unpublished Dissertation, University of

Texas at Austin, Texas





AUTHOR BIOGRAPHIES



Garry L. White is a faculty member in the

Computer Information
Systems depart-ment at

Southwest Texas State

University (SWT) in San

Marcos Texas. He holds a MS

in Computer Sciences from

Texas A & M University –

Corpus Christi and a PhD in

Science Education, emphasis

in Information Systems, from

The University of Texas at Austin. Professional

Certifications from the Institute of Certified Computer

Professionals (ICCP) include C.D.P, C.C.P., and

C.S.P. He has been on the SWT faculty since 1997.

His teaching interests are in the areas of Computer

Programming, Data Communications, Systems

Analysis, and Computer Networks. His research

interests and work are in the areas of Computer

Education and the Internet. He has published papers

and abstracts in journals such as the Journal of

Computer Information Systems. Proceeding

publications have been with the Decision Sciences

Institute and the Information Systems Educational

Conference.



Marcos P. Sivitanides is a tenured Associate Profes-

sor of Computer Information

Systems at Southwest Texas

State University (SWT) in San

Marcos Texas. He holds a BA

(Honors) in Computer Sciences,

an MBA and a PhD in Man-

agement Information Systems,

all from The University of

Texas at Austin. He has been

on the SWT faculty since 1989. His teaching interests

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