The effect of Inappropriate Research Design for Software Development Project:
From Data Gathering Tools To Choosing A Research Design
Cooper and
Schindler (2003) report that statistical studies attempt to capture a
population’s characteristics by making inferences from a population sample’s
characteristics. The quality of inferences to address the research problem and
solution depends on the quality of research tools such as data gathering and
statistical analysis. The significance of this paper lies in the fact that 40%
of software development project failed (Mandell, 1997) because of using
inappropriate research design for data gathering and analysis. The determinant
of good research is therefore based on: (a) design (e.g., quantitative,
qualitative, or mixed); (b) sample/population characteristics; and (c) data
gathering tools/instrumentation. The finding is that researches on software
development projects use more quantitative methodology and less qualitative and
mixed methodologies. However, future research is recommended to confirm this
findings.
Table of Contents
Abstract
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Problem Statement
PAGEREF _Toc120370474 \h 8
Purpose of the Paper
PAGEREF _Toc120370475 \h 8
Research Guidelines
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Quantitative versus Qualitative Research Methodologies.
PAGEREF _Toc120370477 \h 10
Quantitative design
PAGEREF _Toc120370478 \h 11
Qualitative design
PAGEREF _Toc120370479 \h 11
Sample/Population Characteristics.
PAGEREF _Toc120370480 \h 12
Sampling as a process
PAGEREF _Toc120370481 \h 13
Sampling plan
PAGEREF _Toc120370482 \h 13
Target population
PAGEREF _Toc120370483 \h 14
Sampling frames
PAGEREF _Toc120370484 \h 15
Eligibility criteria
PAGEREF _Toc120370485 \h 15
Sampling design
PAGEREF _Toc120370486 \h 16
Sample size
PAGEREF _Toc120370487 \h 16
Significance and Power
PAGEREF _Toc120370488 \h 17
Sample Recruitment
PAGEREF _Toc120370489 \h 18
Data Gathering Tools/Instrumentation.
PAGEREF _Toc120370490 \h 19
Literature searches
PAGEREF _Toc120370491 \h 19
Talking with people
PAGEREF _Toc120370492 \h 20
Focus group
PAGEREF _Toc120370493 \h 20
Formal interview
PAGEREF _Toc120370494 \h 21
Telephone survey
PAGEREF _Toc120370495 \h 21
Mail survey
PAGEREF _Toc120370496 \h 21
E-mail survey
PAGEREF _Toc120370497 \h 22
Internet survey
PAGEREF _Toc120370498 \h 23
Analysis of Data Gathering Tools.
PAGEREF _Toc120370499 \h 23
Validity
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Reliability
PAGEREF _Toc120370501 \h 24
Data types and statistics
PAGEREF _Toc120370502 \h 25
Contemporary IS/IT Research Literature Review..
PAGEREF _Toc120370503 \h 26
IBM Uses Mixed Methodology
PAGEREF _Toc120370504 \h 26
COCOMO-II Uses Bayesian Statistical
PAGEREF _Toc120370505 \h 27
Chulani’s Research Uses Multiple Regression
PAGEREF _Toc120370506 \h 29
Germany Uses Test driven software development (TDD)
PAGEREF _Toc120370507 \h 30
Test Driven Software Development Reliability.
PAGEREF _Toc120370508 \h 30
Test Driven Software Development Validity.
PAGEREF _Toc120370509 \h 30
Test Driven Software Development Qualitative Analysis.
PAGEREF _Toc120370510 \h 31
Test Driven Software Development Statistical tools.
PAGEREF _Toc120370511 \h 31
Test Driven Software Development Findings.
PAGEREF _Toc120370512 \h 31
Pros and cons of quantitative & qualitative designs.
PAGEREF _Toc120370513 \h 34
Conclusion.
PAGEREF _Toc120370514 \h 37
References.
PAGEREF _Toc120370515 \h 41
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