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Characterizing Student Proficiency In Software Modeling In Terms of Functions, Structures, and BehaviorsPaul JoseKutty Thomas (10711266) 06 May 2021 (has links)
<p>Software modeling is an integral
practice for software engineers especially as the complexity of software
solutions increase. There is precedent in industry to model information systems
in terms of functions, structures, and behaviors. While constructing these
models, abstraction and systems thinking are employed to determine elements
essential to the solution and how they are connected. However, both abstraction
and systems thinking are difficult to put in practice and difficult to teach
due to the, often, ill-structured nature of real-world IT problems. Unified
Modeling Language (UML) is the industry standard for software modeling but
unfortunately it is often used incorrectly and misunderstood by novices. This
has also been observed in educational contexts where students encounter
difficulty in employing the appropriate level of abstraction in modeling and
programming contexts and not necessarily being able to view or treat software
systems as being interconnected. </p>
<p>The researcher detailed a
multi-methods approach, through the lens of pragmatism, towards understanding
patterns of student proficiency with abstraction and software modeling in terms
capturing the functional, structural, and behavioral aspects of an information
system, as given by the Structures-Behaviors-Function framework. The
quantitative strand involved the development of rubrics to analyze functional,
structural, and behavioral models given by UML activity diagrams, class
diagrams, and sequence diagrams, respectively. The subjects of this study were
students enrolled in a sophomore-level systems analysis and design class. Descriptive
analysis revealed patterns of modeling proficiency. Students were generally
proficient in modeling the system in terms of functions but there was an
overall drop-off in proficiency when modeling the system in terms of structures
and behaviors. The results of the clustering analysis revealed underlying profiles
of students based on abstract thinking and systems thinking ability. Two
distinct clusters – high performing students and moderate performing students –
were revealed with statistically significant differences between the groups in
terms of abstract thinking and systems thinking ability. Further correlational
analysis was performed on each cluster. The results of the correlational
analyses pointed to significant positive associations between software modeling
proficiency and the constructs of abstract thinking and systems thinking. Logistic
regression analysis was then performed, and it could be inferred from the
regression model that abstract thinking in terms of behaviors and systems
thinking in terms of aligning sequence diagrams with activity diagrams were the
most important predictors of high performance. </p>
The qualitative strand of this study involved a
case study approach using the think-aloud protocol centered around exploring
how students utilized abstract thinking and systems thinking while constructing
software models. The participants of this study were students who had completed
the sophomore-level systems analysis and design course. Thematic analysis was
utilized to identify themes of abstract thinking and systems thinking within
the epistemic games of structural, functional, and process analyses. Two
different approaches towards modeling information systems were identified and
chronological visualizations for each approach were presented. Overall, it
could be inferred from the results and findings of the study that the learning
design of the sophomore-level course was successful in equipping students with
the skills to proficiently model information systems in terms of functions.
However, the students were not as proficient in modeling information systems in
terms of structures and behaviors. The theoretical contribution of this study was
centered around the application of the SBF framework and epistemic forms and
games in the context of information systems. The methodological contributions
pertain to the rubrics that were developed which can be used to evaluate
software modeling proficiency as well as abstract thinking and systems
thinking. Abstract thinking and systems thinking were successfully
characterized in the context of information systems modeling. The results of
this study have implications in computing education. The suggested
instructional approaches and scaffolds can be utilized to improve outcomes in
terms of structural and behavioral modeling proficiency.
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