Design Readiness: An Exploratory Model of Object-Oriented Design Performance
The available literature supports the fact that some students experience difficulty learning object-oriented design (OOD) principles. Previously explored predictors of OOD learning difficulties include student characteristics (cognitive activities, self-efficacy), teaching methodologies (teacher cen...
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Virginia Tech
2014
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| Online Access: | http://hdl.handle.net/10919/28545 http://scholar.lib.vt.edu/theses/available/etd-08062004-115926/ |
| Summary: | The available literature supports the fact that some students experience difficulty learning object-oriented design (OOD) principles. Previously explored predictors of OOD learning difficulties include student characteristics (cognitive activities, self-efficacy), teaching methodologies (teacher centered, course complexity), and student experiences (prior programming experience). Yet, within an extensive body of literature devoted to OOD, two explanations of student difficulty remain largely unexplored: (1) varying conceptualizations of the underlying principles/strategies of OOD, and (2) preparedness or readiness to learn OOD.
This research also investigated the extent to which individual differences impacted DRAS and OOD performance. The individual difference measures of interest in this study included college grade point average, prior programming experience, cognitive abilities (spatial orientation, visualization, logical reasoning, flexibility, perceptual style), and design readiness. In addition, OOD performance was measured using two constructs: course grade (exams, labs, programs, overall), and a specially constructed design task.
Participants selected from the CS2 course from two southeastern state universities were used within this study, resulting in a sample size of 161 (School A, n = 76; School B, n = 85). School A is a mid-sized comprehensive university and School B is a large research-intensive university. If was found that the schools significantly differed on all measures of prior computer science experience and cognitive abilities.
Path analysis was conducted to determine which individual differences were related to design readiness and OOD performance.
In summary, this research identified that instructors can not ignore individual differences when teaching OOD. It was found that the cognitive ability visualization, prior OO experience, and overall college grade point average should be considered when teaching OOD. As it stands, without identifying specific teaching strategies used at the schools within this study, this research implies that OOD may require a certain level of practical computer experience before OOD is introduced into the curriculum. The cognitive ability visualization was found to have a significant indirect relationship with overall course grade through the mediating variable design readiness. Further, the results suggest that the DRAS may serve as a viable instrument in identifying successful OOD students as well as students that require supplemental OOD instruction. === Ph. D. |
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