Conduct Rigorous and Scientific Research. Chang Xu Department of Computer Science and Technology Nanjing University Sep 21, 2018
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1 Conduct Rigorous and Scientific Research Chang Xu Department of Computer Science and Technology Nanjing University Sep 21, 2018
2 Outline I. Writing and Presentation II. Research Formulation III. Experimentation 2
3 III. Experimentation 1. Questions and subjects 2. Experimental design 3. Threats to validity
4 General Experimentation Is not merely a description of the experimental procedure and a list of experimental results Should have a careful design (questions and variables) and discussion of potential threats (construct validity, internal validity, external validity, and theoretical reliability) 4
5 Experimentation and Case Study Experimentation In a lab environment Variables (factors) can be isolated and controlled Case study Under an industrial (real-world) setting Hard to repeat We mostly conduct controlled experiments 5
6 Key Points (1) Questions to be answered Is Tool A better than Tool B? Why would we expect it to be better? Better at doing what? Why do we need to know? Better in what way? What will we do with the answer? Better in what situations? 6
7 Key Points (2) Subjects selected Sample of what population? Consider the representativeness Variables and threats to validity Variables: See the next page Threats to validity: See an example 7
8 Variables Independent variables (factors) Dependent variables Controlled variables Independent variable Treatment1 Treatment2 Independent variable Treatment1 Treatment2 Controlled variables Fixed levels Experiment Dependent variable 8
9 Example Name Stuart Bean ("stu") Topic Merging stakeholder views in model driven development Status 2 years into his PhD study Has built a tool Needs evaluation 9
10 Stu s Evaluation Plan Experiments Independent variable: Stu-merge vs. Rational Architect (RA) Dependent variables: correctness, speed, assessment Controlled variables: task (merging class diagrams from two different stakeholders models), subjects (graduate students in software engineering) Hypotheses H1: Stu-merge produces correct merges more often than RA H2: Subjects produce merges faster with Stu-merge than RA H3: Subjects prefer using Stu-merge to RA H1 accepted (strong evidence), H2 & H3 rejected 10
11 Threats to Validity Analysis 3 construct validity 2 internal validity 4 external validity 1 theoretical reliability 11
12 Threats to Validity (1) 3 Construct validity What do we mean by a merge? What is correctness? 0-5 point scale for subjective assessment - insufficient discriminatory power (both tools scored very low) Task (merging class diagrams) and subjects (graduate students) Stu-merge vs. Rational Architect Correctness, speed, assessment 12
13 Threats to Validity (2) 2 Internal validity Confounding variable: time taken to learn the tool (subjects were all familiar with RA, not with Stumerge) Task (merging class diagrams) and subjects (graduate students) Stu-merge vs. Rational Architect Correctness, speed, assessment 13
14 Threats to Validity (3) 4 External validity (representativeness) Task: Class diagram models were of a toy problem Subject: Graduate students as sample of what population? Task (merging class diagrams) and subjects (graduate students) Stu-merge vs. Rational Architect Correctness, speed, assessment 14
15 Threats to Validity (4) 1 Theoretical reliability (conclusion validity) Bias: Subjects knew Stu-merge was Stu s own tool Task (merging class diagrams) and subjects (graduate students) Stu-merge vs. Rational Architect Correctness, speed, assessment 15
16 Take-home Messages When you design your experiments Questions to be answered Subjects to select Independent variables, dependent variables, and controlled variables (no confounding variable) When you interpret your experimental results Threats to construct validity, internal validity, external validity, and theoretical reliability Why do they not affect your conclusion? 16
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