Does construct overload truly overload the performance? : an experimental study of experienced data modeler = 컨스트럭트 오버로드가 진정으로 모델 퍼포먼스에 악영향을 미치는가?

다국어 초록 (Multilingual Abstract)

A principal activity in information systems development involves building a conceptual model of domain that an information system is intended to support. Such models are created using a conceptual-modeling grammar fundamental means to specifying information systems requirement. However, the actual usage of grammar is poorly understood and some issues regarding conceptual grammar such as construct overload still remain unsolved. With regard to construct overload in conceptual modeling, past studies have had some deficiencies in research methods and even have presented contradicting results. In this paper, we experimented to test whether construct overload enables conceptual models users to understand a domain more efficiently. To acquire a more complete and accurate understanding of construct overload, our study focused on three major points; the evaluation of conceptual modeling grammar semantics, research participants and domain familiarity. This paper’s key contribution is that it is one of the first studies to investigate practitioner’s aspects of construct overload employing different degrees of domain familiarity by investigating the cognitive processes of practitioner. In addition, this research reconciles conflicting outcomes by examining practical directions for model variation. The result of study will broaden the perspective on usability in the context of the conceptual model and may serve as an ontological guidance to construct overload when modelers create a conceptual model.

목차 (Table of Contents)

• 1. Introduction 2
• 2. Theory and Related Work 5
• 2.1. Theory 6
• Theory of Ontological Clarity 7
• Feynman-Tufte Principle 7
• Mayer’s Cognitive Theory of Multimedia Learning 8
• Information Processing Theory 8
• Theory of Visual Attention 9
• 2.2. Related Work 9
• Ontological Clarity 13
• Domain Familiarity 13
• 3. Proposition Development 14
• 4. Research Method 18
• 4.1. Design and Measures 19
• 4.2. Materials 20
• Personal Profile and Training Materials 20
• Conceptual Models 21
• Understanding Task Materials 27
• 4.3. Participants 31
• 4.4. Procedures 32
• 4.5. Results 33
• Data Scoring 33
• Quantitative Data Analysis 33
• 5. Cognitive Process Tracing Study 36
• 5.1. Design and Measures 36
• 5.2. Materials 37
• 5.3. Participants 38
• 5.4. Procedures 38
• 5.5. Coding Scheme 39
• 5.6. Analysis of Protocol Data 40
• 5.7. Analysis of Eye-tracking Data 45
• Scan Path 48
• Focus and Heat Map 52
• Quantitative Data Analysis of Key Performance Indicators 56
• 6. Discussion 63
• 6.1. Conclusion 63
• 6.2. Implication 63
• 6.3. Limitations and Future Research Directions 65
• Reference 66
• Appendix A 73
• Summary of Information Processing Coding Typology 73
• Appendix B 75
• Glossary of Eye Tracking Technique 75
• Focus Map of Unfamiliar Domain (Waste Processing System) 75