This document outlines a research design process for architecture, engineering, construction, and operations management applications. It recommends using a mixed methods design to holistically explore research problems from multiple perspectives. The process involves first drafting a problem statement and collecting quantitative data. Qualitative data is then collected to develop the problem space and hypothesis. The data sets are aligned within the problem space to create a final hypothesis. Technical writing standards are provided for presenting the research in an objective, third-person style with appropriate sections.

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Built Environment Advanced Research, Theories and Technologies Institute
RESEARCH DESIGN
+
TECHNICAL WRITING
FOR AECO APPLICATION

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RESEARCH DESIGN
When identifying a problem for research in Architecture,
Engineering, Construction, or Operations Management
(AECO) a Mixed Methods Design (MMD) should be
implemented as it allows for holistic exploration of the subject
from multiple perspectives.
MMD is both quantitative and qualitative, using the integration
of data sets and observations to effectively:
• Interpret, organize or categorize, and explain information.
• Develop and test new instruments or tools.
• Complement strengths, and overcome weaknesses, in both
problem and solution spaces.

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RESEARCH DESIGN - APPROACH
identify data need (s)
STEP 1 - QUANTITATIVE (QUAN) DATA SET
identify data source (s)
identify data collection tool (s)
1.a DRAFT PROBLEM STATEMENT

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RESEARCH DESIGN - APPROACH
develop data collection tool (s)
implement tool (s) / collect data
organize / categorize data
1.b FINE TUNE PROBLEM STATEMENT
STEP 1 - QUAN (continued)

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RESEARCH DESIGN - APPROACH
project data collected onto
research problem space
STEP 2 - QUALITATIVE (QUAL) DATA SET
organize research solution space
2.b DRAFT HYPOTHESIS
2.a DRAFT THE PROBLEM SPACE

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RESEARCH DESIGN - APPROACH
STEP 3 - ITERATION (QUAN + QUAL)
An Iteration may or may not be a requirement, but it can be
implemented to either one or both data sets, to improve the
clarity of the Problem Statement, the quality of the Problem
Space, and the accuracy of the Hypothesis; an iteration works
as a Leaning Tool that can effectively:
• Eliminate waste, or unnecessary, data.
• Eliminate deficiencies in data collection tools and process.
• Mitigate deficiencies in the problem space, therefore reduce
deficiencies in the solution space.

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RESEARCH DESIGN - APPROACH
STEP 4 - ALIGNMENT
ALIGN BOTH DATA SETS
WITHIN PROBLEM SPACE
TO CREATE FINAL HYPOTHESIS

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TECHNICAL WRITING
• Stay clear, concise, and precise with your content.
• Present, clearly, both QUAN and QUAL data sets.
• Present, clearly, both problem and solution spaces.
• Stay impersonal, and always objective.
• Use complete sentences, and appropriate terminology.
• Always use citations, when citations are required.
STEP 5 - PRESENTING THE RESEARCH

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TECHNICAL WRITING
• Must never be written in first person; must be written in third
person and remain consistent.
• Must be written in present tense, and must remain
consistent; only use past or future tenses when necessary.
• Must incorporate both text and graphics.
• Must include both a cover page and a references page, in
addition to the following sections at minimum : Abstract,
Data Sets, Exploration, and Hypothesis.
STEP 5 - PRESENTING THE RESEARCH

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IN SUMMARY,
• When conducting research for AECO use Mixed Methods Design.
• Draft your Problem Statement.
• Create your QUANtitative Data Set.
• Fine tune your Problem Statement.
• Draft your Problem Space, and a Hypothesis.
• Project your QUAN into your QUALitative Data Set.
• Implement Iteration, when necessary or required.
• Align Data Sets Within Problem Space to Create Final Hypothesis.
• Use Technical Writing to present your Research.

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Built Environment Advanced Research, Theories and Technologies Institute
Colorado, USA
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