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Modelling the development of affective and cognitive processes in computer programming and their interrelationships
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Type
Thesis
Author
Mooi, Lee Choo
Supervisor
Soh, Kay Cheng
Abstract
In order to promote liking and ameliorate computer programming anxiety, teachers need to understand the cognitive processes underlying these affective traits and the affective processes underlying computer programming competence. Interest in this interplay of affect and cognition led to the proposition of models to explain (i) problem-solving processes; (ii) inter-relationships among liking for, anxiety and competence in computer programming; and (iii) computer programming understanding. To validate these models, cognitive and affective responses were collected from Grade 11 Computing students via three assessment instruments: Computer Programming Algorithm Test, Computer Programming Anxiety Scale, and Liking for Computer-related Activities Scale; and analysed using systemic networks, IRT and Dual Scaling techniques.
Model I uses a systematic network to show the component steps of four stages of problem solving that would emphasis thinking processes. In this view, the stages are (1) problem perception, (2) problem representation, (3) problem execution, and (4) problem evaluation. The problem-solver first understands the surface features of the problem statement well enough to derive the deep structure implied so as to construct a representation of the task and to translate this representation into a sequence of computer operations to perform the task reliably. Model II, the loop model of affect-cognition in computer programming, involves the development of affect and cognition in a feedback manner. Computer programming anxiety has debilitative effects on problem-solving competence while liking for computer programming has facilitative effects on competence and anxiety. An increase in computer programming anxiety is associated with a decrease in competence and in liking for computer programming resulting in further increases in anxiety in a feedback manner. Changes in computer programming competence, liking and anxiety may occur at any stage of problem solving. Model III, the model of computer programming understanding, proposes three dimensions of knowledge structure developing in orchestration. They are the conceptual/procedural, data structure/program constructs and semantic/syntax dimensions. This model represents not only the "expert" knowledge required for programming but also the possible difficulties, errors and misconceptions. A student may be at different points along each dimension.
It was found that a minimally competent student was at least able to initialise a variable, read a value, represent a single loop structure, assign values to variables, and produce a plan to solve simple or standard programming tasks. Students' problem-solving processes were in accordance with the steps proposed in Model 1 and computer programming understanding comprised the different competencies distributed along separate developmental frameworks as proposed in Model III. students found it most difficult to like doing computer programming assignments and having to debug computer programmes caused the most anxiety. However, learning to use programming software was easy to like. It was found that activities believed to be worthy of time, effort and money and having relevance to passing examinations caused them less anxiety , were liked and resulted in more competence in solving computer programming problems thus validating the interplay of affect and cognition proposed in Model II.
Model I uses a systematic network to show the component steps of four stages of problem solving that would emphasis thinking processes. In this view, the stages are (1) problem perception, (2) problem representation, (3) problem execution, and (4) problem evaluation. The problem-solver first understands the surface features of the problem statement well enough to derive the deep structure implied so as to construct a representation of the task and to translate this representation into a sequence of computer operations to perform the task reliably. Model II, the loop model of affect-cognition in computer programming, involves the development of affect and cognition in a feedback manner. Computer programming anxiety has debilitative effects on problem-solving competence while liking for computer programming has facilitative effects on competence and anxiety. An increase in computer programming anxiety is associated with a decrease in competence and in liking for computer programming resulting in further increases in anxiety in a feedback manner. Changes in computer programming competence, liking and anxiety may occur at any stage of problem solving. Model III, the model of computer programming understanding, proposes three dimensions of knowledge structure developing in orchestration. They are the conceptual/procedural, data structure/program constructs and semantic/syntax dimensions. This model represents not only the "expert" knowledge required for programming but also the possible difficulties, errors and misconceptions. A student may be at different points along each dimension.
It was found that a minimally competent student was at least able to initialise a variable, read a value, represent a single loop structure, assign values to variables, and produce a plan to solve simple or standard programming tasks. Students' problem-solving processes were in accordance with the steps proposed in Model 1 and computer programming understanding comprised the different competencies distributed along separate developmental frameworks as proposed in Model III. students found it most difficult to like doing computer programming assignments and having to debug computer programmes caused the most anxiety. However, learning to use programming software was easy to like. It was found that activities believed to be worthy of time, effort and money and having relevance to passing examinations caused them less anxiety , were liked and resulted in more competence in solving computer programming problems thus validating the interplay of affect and cognition proposed in Model II.
Date Issued
1997
Call Number
QA76.6 Moo
Date Submitted
1997