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– ## UnitIVAssignment.docx
– ## UnitIVStudyGuide.pdf
**## UnitIVAssignment.docx**
Unit IV
This assignment measures your mastery of ULOs 2.1, 2.2, 3.1, and 3.2.
**Research Strategy Analysis**
Locate a primary research article in an academic journal from the CSU Online Library where the researcher(s) used a quantitative research strategy, a survey instrument, and inferential statistics. After reading the article, explain the following elements:
· purpose of the study,
· population of interest,
· research questions,
· constructs and variables being tested,
· hypotheses,
· research design,
· analytical approach,
· data analysis procedures used,
· sampling frame,
· sampling design (i.e., sampling type),
· data collection method,
· statistically significant inferences that are generalizable to the population of interest.
Your assignment should consist of a minimum of two pages in length, not counting the required references page. Please thoroughly address all required elements listed above. Responses should be written in a narrative format rather than being formatted as short bullet points.
Please use APA-compliant headings and sub-headings that align with the individual assignment elements and please respond to the assignment elements in the same sequence they are requested in the instructions. Do not combine elements within a section. Each assignment element should have its own section with APA heading. Adhere to all other APA Style and formatting guidelines, including in-text citations and references for all sources that are used. Include at least the article used as a source, but other credible sources may be used as needed.
**Resources**
The following resource(s) may help you with this assignment.
·
[Citation Guide](https://www.columbiasouthern.edu/downloads/pdf/success/citation-guide)
·
[CSU Online Library Research Guide](https://libguides.columbiasouthern.edu/researchmethods)
·
[Submit Writing Center Request](https://mycsu.columbiasouthern.edu/student/forms/courses/writing-center-request)
**## UnitIVStudyGuide.pdf**
RCH 5301, Research Design and Methods 1
Course Learning Outcomes for Unit IV
At the end of this unit, you should be able to:
2. Discriminate among the characteristics of qualitative and quantitative research methods.
2.1 Deduce differences between a quantitative methodological research strategy and
qualitative research strategy.
2.2 Identify a primary research article in an academic journal where the researcher or
researchers used a survey instrument and inferential statistics.
3. Evaluate research designs.
3.1 Differentiate between descriptive, explanatory, and exploratory research designs based on
their unique characteristics.
3.2 Analyze an academic study’s research design, analytical approach, data analysis
procedures, data collection method, and sampling design.
Required Unit Resources
Chapter 3: The Use of Theory (ULOs 3.1 and 3.2)
Read the following sections from this chapter:
Quantitative Theory Use
Chapter 4: Writing Strategies and Ethical Considerations (ULOs 3.1 and 3.2)
Article: Research Methods: Quantitative Observation (ULOs 3.1 and 3.2)
This article discusses using observation for quantitative data collection. (2 pages).
Unit Lesson
Lesson: Don’t Look Now, but You’re Being Observed (ULOs 3.1 and 3.2)
Introduction
Most of the focus of data collection in this course has been on the survey or self-completion questionnaire.
While the survey is the most often used quantitative data collection method in research, there are other non-
experimental methods for collecting data, such as structured observation, content analysis, and utilizing
secondary data.
Structured Observation
As the name implies, structured observation is a process where the researcher systematically and visually
examines and quantifies phenomena as they occur. While observation research is often associated with the
qualitative research methodology, structured observation is decidedly quantitative. Characteristics of
observation research that make it a positivist’s tool are that the variables to be studied are predetermined
through the structure, and the variables are quantifiable. These are two conditions that are foreign to
qualitative research.
Variables under structured observation are varied. Virtually anything that can be counted can be studied
through structured observation, including objects, time, events, words, clicks, people, and behavior. Even
nonverbal communication can be observed and quantified, including facial expressions, body language, eye
UNIT IV STUDY GUIDE
Quantitative Research Using Naturally
Occurring Data, Secondary Data, and
Official Statistics
RCH 5301, Research Design and Methods 2
UNIT x STUDY GUIDE
Title
movements, personal space, gestures, and manners. For example, assume medical patients are under
observation in a health care facility, and the predetermined variables to measure are facial expressions, body
language, eye movements, personal space, manners, time, objects, demographics, and actions. The
researcher might devise an observation schedule that includes the variables below.
Was the purpose of the patient’s visit to:
• seek treatment for a new medical concern (event)?
• seek treatment for an existing medical condition (event)?
When approached by the medical provider, did the patient:
• smile, frown, or remain unchanged (facial expression)?
• stand still, back away, or lean into the medical provider (personal space)?
• shake the provider’s hand (manners)?
• fold their arms or keep them dangling in a relaxed manner (body language)?
• make steady eye contact or avoid looking at the provider directly (eye movement)?
• mention the current condition that is being treated (words)?
How much time did the patient:
• speak with the provider (timing)?
• engage in conversation with other patients (timing)?
• spend in common areas (timing)?
• isolate in their room (timing)?
• handle common area activities, such as books (timing)?
Which items did the patient handle while in the common area?
• Educational literature (object)?
• Magazines (object)?
• Books (object)?
• Board games (object)?
What was the patient’s:
• gender (demographics)?
• age (demographics)?
RCH 5301, Research Design and Methods 3
UNIT x STUDY GUIDE
Title
Structured observation can take place in a controlled environment (i.e., contrived observation), such as a
laboratory, but observation most often occurs in the participants’ natural environment, such as a field location
or facility, which was used in the example above. Research outside of a lab has the potential for a more
realistic and unbiased accounting of behavior since participants are unlikely to modify their actions to meet
researcher expectations. In either case, the structured observation takes place without researcher
intervention, although the research can be conducted overtly (i.e., undisguised observation) or covertly (i.e.,
disguised observation). If conducted overtly, the participants are aware they are the subject of research. This
can create bias since the participants are likely to modify their behavior to conform to how they think the
researcher expects them to behave. This is known as reactivity. This is also known colloquially as the
Hawthorne effect. The name originates from a series of 1920s industrial experiments conducted at Western
Electric’s large Hawthorne plant in Cicero, Illinois. Although there were four different studies, the Illumination
Experiments (1924–1927) were the most illuminating (pun intended) about the phenomenon called reactivity
(Perera, 2021; Price et al., 2017).
In the Illumination Experiments, researchers were seeking to determine if there was a relationship between
the variables of illumination levels and factory productivity. They hypothesized that the relationship would be
positive, meaning the variables would move in the same direction. For example, they guessed as illumination
levels decreased, productivity would decrease, and as illumination levels increased, productivity would
RCH 5301, Research Design and Methods 4
UNIT x STUDY GUIDE
Title
increase. The researchers were surprised to find, however, that no matter the change in illumination,
productivity increased. As illumination increased, productivity increased. As illumination decreased,
productivity increased. It was determined that the workers’ awareness of being studied was severely biasing
results. Interestingly, reactivity begins to wane over time as participants become desensitized to the presence
of researchers, and their behaviors begin to normalize. This is precisely what occurred at the Hawthorne
factory (Perera, 2021).
To avoid bias from reactivity, observation research can be conducted covertly so that the participants are
unaware that they are the subjects of research. While this can eliminate the risk of bias, it can potentially
increase ethical risks. However, researchers generally accept covert observation as ethical if participants’
anonymity is preserved, and the observation is performed in public where there is no expectation of privacy
(Cooper & Schindler, 2014).
Structured observation is very similar to naturalistic observation and participant observation, which are
qualitative data collection methods. The difference between structured observation, naturalistic observation,
and participant observation is that structured observation is intended to quantify a relatively small number of
variables rather than record and interpret all the behaviors that are taking place (Price et al., 2017).
It should be noted that everything that was discussed in previous units about sampling applies to structured
observation; however, probability sampling can be challenging since it is often difficult to develop a sampling
frame in observation studies. It then follows that making valid and reliable inferences about a population of
interest, or generalizing results, can be difficult to achieve (Price et al., 2017).
Structured Observation in Practice
In addition to structured observation that occurs in participants’ natural environments, there are many other
methods available to researchers to capture observation data. Many of these other methods use cutting-edge
technology. The following describes examples of structured observation in practice, but this is nowhere near a
complete list of all observation methods.
Mechanical Observation
It is not always possible or practical for researchers to observe the phenomena in real time in the participant’s
natural environment. In these instances, mechanical observation is an effective alternative. Traffic cameras
and other mechanical devices are commonly used to quantify usage of roadways and to identify traffic
patterns that may be problematic. Video cameras and time-lapse photography are used in busy warehouses
to improve the flow of product and safety for employees who are working around dangerous equipment.
Nielsen Media Research uses mechanical observation to collect data on which television shows are being
watched in households, on which television sets, who is watching them, and for how long. Arbitron performs
similar observation research on radio audiences. Scanner-based observation is another mechanical means of
capturing consumer purchase behavior data through scanned UPC codes. This is an easy way to collect large
amounts of data that can be used to analyze the relationship between consumer behavior and variables like
promotion and pricing (Cooper & Schindler, 2014).
Satellite Imagery
Observation from space is a unique example of observation research. Satellites are routinely used to observe
activity at ports, shipping terminals, oil refineries, retail establishments, and farms. This data enables the
quantification of shipping containers and vessel traffic in ports; supply of energy at oil refineries; consumer
traffic at retail establishments like Walmart, Lowes, and McDonalds; and crop yields. Satellite data is then
used to make inferences about economic activity (Eamon, 2010; Goldstein, 2010).
Eye Tracking
Eye tracking is a desirable observation method since it captures what subjects actually do rather than what
they say they do. Eye tracking uses infrared-enabled webcam and wearable technology to quantify research
participants’ conscious and unconscious eye movements to determine what they pay attention to (behavior)
and for how long (timing). Eye tracking is useful for capturing participant data and the attention paid to online
RCH 5301, Research Design and Methods 5
UNIT x STUDY GUIDE
Title
stimuli. It is especially beneficial in online environments since eye-tracking data can be linked directly to
behavior.
Heat Mapping
The purpose of heat mapping, like eye tracking, is to quantify human behavior using special technology. The
technology is used to measure variables like cursor movements, scrolling activity, clicks and click-through
rates, page views, and time per page for all website visitors. Activity is color coded, so high activity appears
visually in gradients of red, and low activity appears as gradients of green. Heat mapping technology can also
be used to create heat maps for consumer behavior and physical movements in retail establishments.
Regardless of whether heat mapping is used for creating a visualization of behavior in digital or non-digital
environments, the data can be used to make strategic decisions to improve the effectiveness of lower activity
areas (Perez, 2020).
Retail heat mapping (Soltani, 2015)
Neuromarketing
Neurofocus is a company that uses technology called quantified electroencephalography (QEEG) to measure
a subject’s brain activity in different parts of their brain. The data is captured through discreet electrodes
attached to the subject’s head and displayed in a format like a heat map. QEEG is like magnetic resonance
imaging (MRI) technology, but it is mobile and allows the capture of data in dynamic environments. For
example, electrodes can be attached to consumers to observe the alpha-wave brain activity as they engage
in surfing the web. As their alpha-wave activity is triggered by interest in different websites, the researcher will
observe their brain images that light in hotter gradients of red. As subject interest wanes, researchers will
observe areas of the brain’s lighting in cooler gradients of green.
Education
Observation research is routinely used in many domains of interest, including education. For example,
structured observation could be used in the classroom to quantify the number of questions asked by students
during class time to determine if a relationship exists with grade point average.
RCH 5301, Research Design and Methods 6
UNIT x STUDY GUIDE
Title
Time and Motion
Time and motion studies provide a great application for structured observation research. Quantifying the
number of movements and time required to make those movements can be helpful in reducing waste,
increasing efficiency, and raising safety awareness (Drew, 2022).
Safety, Health Care, and Medicine
Structured observation research in safety, health care, and medicine has been used to quantify the types,
frequency, and severity of negative events across various departments, including operations, pharmacy,
emergency, operating rooms, anesthesia, obstetrics, and intensive care. For example, the type, frequency,
and severity of incorrect drug administration is easily quantifiable through observation research. In addition to
improving operational efficiency, the most beneficial aspect of observation research in a safety or health care
setting is the reduction of workplace accidents and illnesses and the detrimental effects of adverse care,
including death (Carthey, 2003).
Content Analysis
Content analysis is like structured observation in that it is a quantitative process where the researcher
systematically and visually examines and quantifies existing words, titles, subjects, actors, and images within
published or unpublished print or digital media, including news articles, letters, emails, advertisements,
television shows, and websites. The content analysis may measure either the inclusion or exclusion of the
variable or variables under study. This should not be confused with the qualitative content analysis, which is
subjective. In the qualitative content analysis, the researcher interprets and constructs meaning from the print
or digital media. In quantitative content analysis, the researcher objectively quantifies what is found in the
media and does not interject their values or interpret meaning. Content analysis would be an incredibly time-
consuming and tedious exercise if it were done manually. Fortunately, there are technology solutions to
facilitate this process so researchers can spend most of their time on data analysis rather than data collection
(Zikmund et al., 2013).
Secondary Data Analysis
Secondary data analysis (i.e., archival research) is a quantitative approach to research using data that has
already been collected for other purposes, by other people and researchers, such as academic study data,
commercial and trade data, organizational data, and government data (Zikmund et al., 2013). For example,
the scanner data mentioned above in the discussion on mechanical observation is normally collected by
individual grocery store chains to monitor their own customers. However, the National Grocers Association
could aggregate scanner data from their association members to share with the entire association, even those
without access to their own scanner data. This would be a useful means of secondary data analysis.
In Closing
Many of the practical examples of structured observation make use of cutting-edge technology, and there is
no stopping it. Technology is pervasive in society and is often used to surreptitiously capture consumer
information through so-called surveillance products. See the examples below.
• Smartwatches capture health, exercise, and sleep data.
• Geolocation technology and GPS navigation apps track people’s activities and vehicle movements.
• Smartphones, tablets, and laptops listen to their users.
• Amazon’s Alexa and Apple's Siri capture user activity and listen to conversations.
• Smart refrigerators, washing machines, and other appliances have listening capabilities.
• Millions of users on social networking sites have no appreciation for privacy and gladly share their
most intimate details.
• Radio-frequency identification (RFID) chips used in toll passes, passports, payment mechanisms, and
reward fobs track owners’ movements.
Many consumers naively believe that marketers respect their privacy. Perhaps the most successful marketing
organization in history, Amazon, has been caught collecting user conversations through Alexa without
their knowledge. Since being caught with their hand in the cookie jar, Amazon now allows users to opt
RCH 5301, Research Design and Methods 7
UNIT x STUDY GUIDE
Title
out of this functionality, but many users are still unaware of this option or are simply unconcerned.
Similarly, users of Gmail and Google Calendar open personal, business, and contact information that
is available to Google to peruse at will, without requiring permission, and with no explanation required.
Many other users are willing to trade privacy and confidentiality for convenience or productivity. Still, others
are willing to swap their privacy for “free” services from companies like Google or Bing (Kelly, 2022).
Experts in the field warn the public that the danger from these means of observation has never been more
serious. The information that consumers share willingly and unwillingly with marketers can be accessed and
abused by governments, hackers, and others (Kelly, 2022). For consumers, privacy and confidentiality should
be a top concern, especially given the potential for search histories, location data, text messages, emails, and
other digital information to be accessed, analyzed, and sold to third-party marketers and government
agencies. Some would say that George Orwell’s vision in 1984 is alive and well in today’s society, and it is
being facilitated through observation research technology. Researchers should enjoy the efficiency and
quality of data provided through observation research technology, but they should always be mindful to do no
harm.
References
Carthey, J. (2003). The role of structured observational research in health care. BMJ Publishing Group Ltd. &
The Health Foundation. https://qualitysafety.bmj.com/content/12/suppl_2/ii13
Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods
approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964
Drew, C. (2022, October 23). 10 observational research examples. The Helpful Professor.
https://helpfulprofessor.com/observational-research-examples/
Eamon, J. (2010, August 17). Spying for profits: The satellite image indicator. CNBC.
https://www.cnbc.com/2010/08/17/Spying-For-Profits:-The-Satellite-Image-Indicator.html?slide=1
Ellis, P. (2024). Research methods: Quantitative observation. Wounds UK, 20(2), 73-74.
https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire
ct=true&db=cul&AN=178268293&site=ehost-live&scope=site
Goldstein, J. (2010, August 19). With satellite images, Wall Street analysts spy on Wal-Mart. NPR.
https://www.npr.org/sections/money/2010/08/19/129298095/with-satellite-images-wall-street-analysts-
spy-on-wal-mart
Kelly, S. M. (2022, October 2). Amazon is always watching. CNN.
https://www.cnn.com/2022/10/02/tech/amazon-product-event/index.html
Perera, A. (2021, May 28). What is the Hawthorne effect? Simply Psychology.
https://www.simplypsychology.org/hawthorne-effect.html
Perez, J. (2020, May 20). What’s so hot about heat mapping? Pinckney.
https://pinckneymarketing.com/whats-so-hot-about-heat-mapping/
Price, P. C., Jhangiani, R., Chiang, I. A., Leighton, D. C., & Cuttler, C. (2017). 6.5 Observational research. In
Research methods in psychology. Pressbooks.
https://opentext.wsu.edu/carriecuttler/chapter/observational-research/
Soltani, A. (2016, April 30). Privacy trade-offs in retail tracking [Image]. Federal Trade Commission.
https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2015/04/privacy-trade-offs-retail-tracking
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage
Learning.
**## UnitIVStudyGuide.pdf**
RCH 5301, Research Design and Methods 1
Course Learning Outcomes for Unit IV
At the end of this unit, you should be able to:
2. Discriminate among the characteristics of qualitative and quantitative research methods.
2.1 Deduce differences between a quantitative methodological research strategy and
qualitative research strategy.
2.2 Identify a primary research article in an academic journal where the researcher or
researchers used a survey instrument and inferential statistics.
3. Evaluate research designs.
3.1 Differentiate between descriptive, explanatory, and exploratory research designs based on
their unique characteristics.
3.2 Analyze an academic study’s research design, analytical approach, data analysis
procedures, data collection method, and sampling design.
Required Unit Resources
Chapter 3: The Use of Theory (ULOs 3.1 and 3.2)
Read the following sections from this chapter:
Quantitative Theory Use
Chapter 4: Writing Strategies and Ethical Considerations (ULOs 3.1 and 3.2)
Article: Research Methods: Quantitative Observation (ULOs 3.1 and 3.2)
This article discusses using observation for quantitative data collection. (2 pages).
Unit Lesson
Lesson: Don’t Look Now, but You’re Being Observed (ULOs 3.1 and 3.2)
Introduction
Most of the focus of data collection in this course has been on the survey or self-completion questionnaire.
While the survey is the most often used quantitative data collection method in research, there are other non-
experimental methods for collecting data, such as structured observation, content analysis, and utilizing
secondary data.
Structured Observation
As the name implies, structured observation is a process where the researcher systematically and visually
examines and quantifies phenomena as they occur. While observation research is often associated with the
qualitative research methodology, structured observation is decidedly quantitative. Characteristics of
observation research that make it a positivist’s tool are that the variables to be studied are predetermined
through the structure, and the variables are quantifiable. These are two conditions that are foreign to
qualitative research.
Variables under structured observation are varied. Virtually anything that can be counted can be studied
through structured observation, including objects, time, events, words, clicks, people, and behavior. Even
nonverbal communication can be observed and quantified, including facial expressions, body language, eye
UNIT IV STUDY GUIDE
Quantitative Research Using Naturally
Occurring Data, Secondary Data, and
Official Statistics
RCH 5301, Research Design and Methods 2
UNIT x STUDY GUIDE
Title
movements, personal space, gestures, and manners. For example, assume medical patients are under
observation in a health care facility, and the predetermined variables to measure are facial expressions, body
language, eye movements, personal space, manners, time, objects, demographics, and actions. The
researcher might devise an observation schedule that includes the variables below.
Was the purpose of the patient’s visit to:
• seek treatment for a new medical concern (event)?
• seek treatment for an existing medical condition (event)?
When approached by the medical provider, did the patient:
• smile, frown, or remain unchanged (facial expression)?
• stand still, back away, or lean into the medical provider (personal space)?
• shake the provider’s hand (manners)?
• fold their arms or keep them dangling in a relaxed manner (body language)?
• make steady eye contact or avoid looking at the provider directly (eye movement)?
• mention the current condition that is being treated (words)?
How much time did the patient:
• speak with the provider (timing)?
• engage in conversation with other patients (timing)?
• spend in common areas (timing)?
• isolate in their room (timing)?
• handle common area activities, such as books (timing)?
Which items did the patient handle while in the common area?
• Educational literature (object)?
• Magazines (object)?
• Books (object)?
• Board games (object)?
What was the patient’s:
• gender (demographics)?
• age (demographics)?
RCH 5301, Research Design and Methods 3
UNIT x STUDY GUIDE
Title
Structured observation can take place in a controlled environment (i.e., contrived observation), such as a
laboratory, but observation most often occurs in the participants’ natural environment, such as a field location
or facility, which was used in the example above. Research outside of a lab has the potential for a more
realistic and unbiased accounting of behavior since participants are unlikely to modify their actions to meet
researcher expectations. In either case, the structured observation takes place without researcher
intervention, although the research can be conducted overtly (i.e., undisguised observation) or covertly (i.e.,
disguised observation). If conducted overtly, the participants are aware they are the subject of research. This
can create bias since the participants are likely to modify their behavior to conform to how they think the
researcher expects them to behave. This is known as reactivity. This is also known colloquially as the
Hawthorne effect. The name originates from a series of 1920s industrial experiments conducted at Western
Electric’s large Hawthorne plant in Cicero, Illinois. Although there were four different studies, the Illumination
Experiments (1924–1927) were the most illuminating (pun intended) about the phenomenon called reactivity
(Perera, 2021; Price et al., 2017).
In the Illumination Experiments, researchers were seeking to determine if there was a relationship between
the variables of illumination levels and factory productivity. They hypothesized that the relationship would be
positive, meaning the variables would move in the same direction. For example, they guessed as illumination
levels decreased, productivity would decrease, and as illumination levels increased, productivity would
RCH 5301, Research Design and Methods 4
UNIT x STUDY GUIDE
Title
increase. The researchers were surprised to find, however, that no matter the change in illumination,
productivity increased. As illumination increased, productivity increased. As illumination decreased,
productivity increased. It was determined that the workers’ awareness of being studied was severely biasing
results. Interestingly, reactivity begins to wane over time as participants become desensitized to the presence
of researchers, and their behaviors begin to normalize. This is precisely what occurred at the Hawthorne
factory (Perera, 2021).
To avoid bias from reactivity, observation research can be conducted covertly so that the participants are
unaware that they are the subjects of research. While this can eliminate the risk of bias, it can potentially
increase ethical risks. However, researchers generally accept covert observation as ethical if participants’
anonymity is preserved, and the observation is performed in public where there is no expectation of privacy
(Cooper & Schindler, 2014).
Structured observation is very similar to naturalistic observation and participant observation, which are
qualitative data collection methods. The difference between structured observation, naturalistic observation,
and participant observation is that structured observation is intended to quantify a relatively small number of
variables rather than record and interpret all the behaviors that are taking place (Price et al., 2017).
It should be noted that everything that was discussed in previous units about sampling applies to structured
observation; however, probability sampling can be challenging since it is often difficult to develop a sampling
frame in observation studies. It then follows that making valid and reliable inferences about a population of
interest, or generalizing results, can be difficult to achieve (Price et al., 2017).
Structured Observation in Practice
In addition to structured observation that occurs in participants’ natural environments, there are many other
methods available to researchers to capture observation data. Many of these other methods use cutting-edge
technology. The following describes examples of structured observation in practice, but this is nowhere near a
complete list of all observation methods.
Mechanical Observation
It is not always possible or practical for researchers to observe the phenomena in real time in the participant’s
natural environment. In these instances, mechanical observation is an effective alternative. Traffic cameras
and other mechanical devices are commonly used to quantify usage of roadways and to identify traffic
patterns that may be problematic. Video cameras and time-lapse photography are used in busy warehouses
to improve the flow of product and safety for employees who are working around dangerous equipment.
Nielsen Media Research uses mechanical observation to collect data on which television shows are being
watched in households, on which television sets, who is watching them, and for how long. Arbitron performs
similar observation research on radio audiences. Scanner-based observation is another mechanical means of
capturing consumer purchase behavior data through scanned UPC codes. This is an easy way to collect large
amounts of data that can be used to analyze the relationship between consumer behavior and variables like
promotion and pricing (Cooper & Schindler, 2014).
Satellite Imagery
Observation from space is a unique example of observation research. Satellites are routinely used to observe
activity at ports, shipping terminals, oil refineries, retail establishments, and farms. This data enables the
quantification of shipping containers and vessel traffic in ports; supply of energy at oil refineries; consumer
traffic at retail establishments like Walmart, Lowes, and McDonalds; and crop yields. Satellite data is then
used to make inferences about economic activity (Eamon, 2010; Goldstein, 2010).
Eye Tracking
Eye tracking is a desirable observation method since it captures what subjects actually do rather than what
they say they do. Eye tracking uses infrared-enabled webcam and wearable technology to quantify research
participants’ conscious and unconscious eye movements to determine what they pay attention to (behavior)
and for how long (timing). Eye tracking is useful for capturing participant data and the attention paid to online
RCH 5301, Research Design and Methods 5
UNIT x STUDY GUIDE
Title
stimuli. It is especially beneficial in online environments since eye-tracking data can be linked directly to
behavior.
Heat Mapping
The purpose of heat mapping, like eye tracking, is to quantify human behavior using special technology. The
technology is used to measure variables like cursor movements, scrolling activity, clicks and click-through
rates, page views, and time per page for all website visitors. Activity is color coded, so high activity appears
visually in gradients of red, and low activity appears as gradients of green. Heat mapping technology can also
be used to create heat maps for consumer behavior and physical movements in retail establishments.
Regardless of whether heat mapping is used for creating a visualization of behavior in digital or non-digital
environments, the data can be used to make strategic decisions to improve the effectiveness of lower activity
areas (Perez, 2020).
Retail heat mapping (Soltani, 2015)
Neuromarketing
Neurofocus is a company that uses technology called quantified electroencephalography (QEEG) to measure
a subject’s brain activity in different parts of their brain. The data is captured through discreet electrodes
attached to the subject’s head and displayed in a format like a heat map. QEEG is like magnetic resonance
imaging (MRI) technology, but it is mobile and allows the capture of data in dynamic environments. For
example, electrodes can be attached to consumers to observe the alpha-wave brain activity as they engage
in surfing the web. As their alpha-wave activity is triggered by interest in different websites, the researcher will
observe their brain images that light in hotter gradients of red. As subject interest wanes, researchers will
observe areas of the brain’s lighting in cooler gradients of green.
Education
Observation research is routinely used in many domains of interest, including education. For example,
structured observation could be used in the classroom to quantify the number of questions asked by students
during class time to determine if a relationship exists with grade point average.
RCH 5301, Research Design and Methods 6
UNIT x STUDY GUIDE
Title
Time and Motion
Time and motion studies provide a great application for structured observation research. Quantifying the
number of movements and time required to make those movements can be helpful in reducing waste,
increasing efficiency, and raising safety awareness (Drew, 2022).
Safety, Health Care, and Medicine
Structured observation research in safety, health care, and medicine has been used to quantify the types,
frequency, and severity of negative events across various departments, including operations, pharmacy,
emergency, operating rooms, anesthesia, obstetrics, and intensive care. For example, the type, frequency,
and severity of incorrect drug administration is easily quantifiable through observation research. In addition to
improving operational efficiency, the most beneficial aspect of observation research in a safety or health care
setting is the reduction of workplace accidents and illnesses and the detrimental effects of adverse care,
including death (Carthey, 2003).
Content Analysis
Content analysis is like structured observation in that it is a quantitative process where the researcher
systematically and visually examines and quantifies existing words, titles, subjects, actors, and images within
published or unpublished print or digital media, including news articles, letters, emails, advertisements,
television shows, and websites. The content analysis may measure either the inclusion or exclusion of the
variable or variables under study. This should not be confused with the qualitative content analysis, which is
subjective. In the qualitative content analysis, the researcher interprets and constructs meaning from the print
or digital media. In quantitative content analysis, the researcher objectively quantifies what is found in the
media and does not interject their values or interpret meaning. Content analysis would be an incredibly time-
consuming and tedious exercise if it were done manually. Fortunately, there are technology solutions to
facilitate this process so researchers can spend most of their time on data analysis rather than data collection
(Zikmund et al., 2013).
Secondary Data Analysis
Secondary data analysis (i.e., archival research) is a quantitative approach to research using data that has
already been collected for other purposes, by other people and researchers, such as academic study data,
commercial and trade data, organizational data, and government data (Zikmund et al., 2013). For example,
the scanner data mentioned above in the discussion on mechanical observation is normally collected by
individual grocery store chains to monitor their own customers. However, the National Grocers Association
could aggregate scanner data from their association members to share with the entire association, even those
without access to their own scanner data. This would be a useful means of secondary data analysis.
In Closing
Many of the practical examples of structured observation make use of cutting-edge technology, and there is
no stopping it. Technology is pervasive in society and is often used to surreptitiously capture consumer
information through so-called surveillance products. See the examples below.
• Smartwatches capture health, exercise, and sleep data.
• Geolocation technology and GPS navigation apps track people’s activities and vehicle movements.
• Smartphones, tablets, and laptops listen to their users.
• Amazon’s Alexa and Apple's Siri capture user activity and listen to conversations.
• Smart refrigerators, washing machines, and other appliances have listening capabilities.
• Millions of users on social networking sites have no appreciation for privacy and gladly share their
most intimate details.
• Radio-frequency identification (RFID) chips used in toll passes, passports, payment mechanisms, and
reward fobs track owners’ movements.
Many consumers naively believe that marketers respect their privacy. Perhaps the most successful marketing
organization in history, Amazon, has been caught collecting user conversations through Alexa without
their knowledge. Since being caught with their hand in the cookie jar, Amazon now allows users to opt
RCH 5301, Research Design and Methods 7
UNIT x STUDY GUIDE
Title
out of this functionality, but many users are still unaware of this option or are simply unconcerned.
Similarly, users of Gmail and Google Calendar open personal, business, and contact information that
is available to Google to peruse at will, without requiring permission, and with no explanation required.
Many other users are willing to trade privacy and confidentiality for convenience or productivity. Still, others
are willing to swap their privacy for “free” services from companies like Google or Bing (Kelly, 2022).
Experts in the field warn the public that the danger from these means of observation has never been more
serious. The information that consumers share willingly and unwillingly with marketers can be accessed and
abused by governments, hackers, and others (Kelly, 2022). For consumers, privacy and confidentiality should
be a top concern, especially given the potential for search histories, location data, text messages, emails, and
other digital information to be accessed, analyzed, and sold to third-party marketers and government
agencies. Some would say that George Orwell’s vision in 1984 is alive and well in today’s society, and it is
being facilitated through observation research technology. Researchers should enjoy the efficiency and
quality of data provided through observation research technology, but they should always be mindful to do no
harm.
References
Carthey, J. (2003). The role of structured observational research in health care. BMJ Publishing Group Ltd. &
The Health Foundation. https://qualitysafety.bmj.com/content/12/suppl_2/ii13
Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods
approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964
Drew, C. (2022, October 23). 10 observational research examples. The Helpful Professor.
https://helpfulprofessor.com/observational-research-examples/
Eamon, J. (2010, August 17). Spying for profits: The satellite image indicator. CNBC.
https://www.cnbc.com/2010/08/17/Spying-For-Profits:-The-Satellite-Image-Indicator.html?slide=1
Ellis, P. (2024). Research methods: Quantitative observation. Wounds UK, 20(2), 73-74.
https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire
ct=true&db=cul&AN=178268293&site=ehost-live&scope=site
Goldstein, J. (2010, August 19). With satellite images, Wall Street analysts spy on Wal-Mart. NPR.
https://www.npr.org/sections/money/2010/08/19/129298095/with-satellite-images-wall-street-analysts-
spy-on-wal-mart
Kelly, S. M. (2022, October 2). Amazon is always watching. CNN.
https://www.cnn.com/2022/10/02/tech/amazon-product-event/index.html
Perera, A. (2021, May 28). What is the Hawthorne effect? Simply Psychology.
https://www.simplypsychology.org/hawthorne-effect.html
Perez, J. (2020, May 20). What’s so hot about heat mapping? Pinckney.
https://pinckneymarketing.com/whats-so-hot-about-heat-mapping/
Price, P. C., Jhangiani, R., Chiang, I. A., Leighton, D. C., & Cuttler, C. (2017). 6.5 Observational research. In
Research methods in psychology. Pressbooks.
https://opentext.wsu.edu/carriecuttler/chapter/observational-research/
Soltani, A. (2016, April 30). Privacy trade-offs in retail tracking [Image]. Federal Trade Commission.
https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2015/04/privacy-trade-offs-retail-tracking
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage
Learning.
**## UnitIVAssignment.docx**
Unit IV
This assignment measures your mastery of ULOs 2.1, 2.2, 3.1, and 3.2.
**Research Strategy Analysis**
Locate a primary research article in an academic journal from the CSU Online Library where the researcher(s) used a quantitative research strategy, a survey instrument, and inferential statistics. After reading the article, explain the following elements:
· purpose of the study,
· population of interest,
· research questions,
· constructs and variables being tested,
· hypotheses,
· research design,
· analytical approach,
· data analysis procedures used,
· sampling frame,
· sampling design (i.e., sampling type),
· data collection method,
· statistically significant inferences that are generalizable to the population of interest.
Your assignment should consist of a minimum of two pages in length, not counting the required references page. Please thoroughly address all required elements listed above. Responses should be written in a narrative format rather than being formatted as short bullet points.
Please use APA-compliant headings and sub-headings that align with the individual assignment elements and please respond to the assignment elements in the same sequence they are requested in the instructions. Do not combine elements within a section. Each assignment element should have its own section with APA heading. Adhere to all other APA Style and formatting guidelines, including in-text citations and references for all sources that are used. Include at least the article used as a source, but other credible sources may be used as needed.
**Resources**
The following resource(s) may help you with this assignment.
·
[Citation Guide](https://www.columbiasouthern.edu/downloads/pdf/success/citation-guide)
·
[CSU Online Library Research Guide](https://libguides.columbiasouthern.edu/researchmethods)
·
[Submit Writing Center Request](https://mycsu.columbiasouthern.edu/student/forms/courses/writing-center-request)
**## UnitIVStudyGuide.pdf**
RCH 5301, Research Design and Methods 1
Course Learning Outcomes for Unit IV
At the end of this unit, you should be able to:
2. Discriminate among the characteristics of qualitative and quantitative research methods.
2.1 Deduce differences between a quantitative methodological research strategy and
qualitative research strategy.
2.2 Identify a primary research article in an academic journal where the researcher or
researchers used a survey instrument and inferential statistics.
3. Evaluate research designs.
3.1 Differentiate between descriptive, explanatory, and exploratory research designs based on
their unique characteristics.
3.2 Analyze an academic study’s research design, analytical approach, data analysis
procedures, data collection method, and sampling design.
Required Unit Resources
Chapter 3: The Use of Theory (ULOs 3.1 and 3.2)
Read the following sections from this chapter:
Quantitative Theory Use
Chapter 4: Writing Strategies and Ethical Considerations (ULOs 3.1 and 3.2)
Article: Research Methods: Quantitative Observation (ULOs 3.1 and 3.2)
This article discusses using observation for quantitative data collection. (2 pages).
Unit Lesson
Lesson: Don’t Look Now, but You’re Being Observed (ULOs 3.1 and 3.2)
Introduction
Most of the focus of data collection in this course has been on the survey or self-completion questionnaire.
While the survey is the most often used quantitative data collection method in research, there are other non-
experimental methods for collecting data, such as structured observation, content analysis, and utilizing
secondary data.
Structured Observation
As the name implies, structured observation is a process where the researcher systematically and visually
examines and quantifies phenomena as they occur. While observation research is often associated with the
qualitative research methodology, structured observation is decidedly quantitative. Characteristics of
observation research that make it a positivist’s tool are that the variables to be studied are predetermined
through the structure, and the variables are quantifiable. These are two conditions that are foreign to
qualitative research.
Variables under structured observation are varied. Virtually anything that can be counted can be studied
through structured observation, including objects, time, events, words, clicks, people, and behavior. Even
nonverbal communication can be observed and quantified, including facial expressions, body language, eye
UNIT IV STUDY GUIDE
Quantitative Research Using Naturally
Occurring Data, Secondary Data, and
Official Statistics
RCH 5301, Research Design and Methods 2
UNIT x STUDY GUIDE
Title
movements, personal space, gestures, and manners. For example, assume medical patients are under
observation in a health care facility, and the predetermined variables to measure are facial expressions, body
language, eye movements, personal space, manners, time, objects, demographics, and actions. The
researcher might devise an observation schedule that includes the variables below.
Was the purpose of the patient’s visit to:
• seek treatment for a new medical concern (event)?
• seek treatment for an existing medical condition (event)?
When approached by the medical provider, did the patient:
• smile, frown, or remain unchanged (facial expression)?
• stand still, back away, or lean into the medical provider (personal space)?
• shake the provider’s hand (manners)?
• fold their arms or keep them dangling in a relaxed manner (body language)?
• make steady eye contact or avoid looking at the provider directly (eye movement)?
• mention the current condition that is being treated (words)?
How much time did the patient:
• speak with the provider (timing)?
• engage in conversation with other patients (timing)?
• spend in common areas (timing)?
• isolate in their room (timing)?
• handle common area activities, such as books (timing)?
Which items did the patient handle while in the common area?
• Educational literature (object)?
• Magazines (object)?
• Books (object)?
• Board games (object)?
What was the patient’s:
• gender (demographics)?
• age (demographics)?
RCH 5301, Research Design and Methods 3
UNIT x STUDY GUIDE
Title
Structured observation can take place in a controlled environment (i.e., contrived observation), such as a
laboratory, but observation most often occurs in the participants’ natural environment, such as a field location
or facility, which was used in the example above. Research outside of a lab has the potential for a more
realistic and unbiased accounting of behavior since participants are unlikely to modify their actions to meet
researcher expectations. In either case, the structured observation takes place without researcher
intervention, although the research can be conducted overtly (i.e., undisguised observation) or covertly (i.e.,
disguised observation). If conducted overtly, the participants are aware they are the subject of research. This
can create bias since the participants are likely to modify their behavior to conform to how they think the
researcher expects them to behave. This is known as reactivity. This is also known colloquially as the
Hawthorne effect. The name originates from a series of 1920s industrial experiments conducted at Western
Electric’s large Hawthorne plant in Cicero, Illinois. Although there were four different studies, the Illumination
Experiments (1924–1927) were the most illuminating (pun intended) about the phenomenon called reactivity
(Perera, 2021; Price et al., 2017).
In the Illumination Experiments, researchers were seeking to determine if there was a relationship between
the variables of illumination levels and factory productivity. They hypothesized that the relationship would be
positive, meaning the variables would move in the same direction. For example, they guessed as illumination
levels decreased, productivity would decrease, and as illumination levels increased, productivity would
RCH 5301, Research Design and Methods 4
UNIT x STUDY GUIDE
Title
increase. The researchers were surprised to find, however, that no matter the change in illumination,
productivity increased. As illumination increased, productivity increased. As illumination decreased,
productivity increased. It was determined that the workers’ awareness of being studied was severely biasing
results. Interestingly, reactivity begins to wane over time as participants become desensitized to the presence
of researchers, and their behaviors begin to normalize. This is precisely what occurred at the Hawthorne
factory (Perera, 2021).
To avoid bias from reactivity, observation research can be conducted covertly so that the participants are
unaware that they are the subjects of research. While this can eliminate the risk of bias, it can potentially
increase ethical risks. However, researchers generally accept covert observation as ethical if participants’
anonymity is preserved, and the observation is performed in public where there is no expectation of privacy
(Cooper & Schindler, 2014).
Structured observation is very similar to naturalistic observation and participant observation, which are
qualitative data collection methods. The difference between structured observation, naturalistic observation,
and participant observation is that structured observation is intended to quantify a relatively small number of
variables rather than record and interpret all the behaviors that are taking place (Price et al., 2017).
It should be noted that everything that was discussed in previous units about sampling applies to structured
observation; however, probability sampling can be challenging since it is often difficult to develop a sampling
frame in observation studies. It then follows that making valid and reliable inferences about a population of
interest, or generalizing results, can be difficult to achieve (Price et al., 2017).
Structured Observation in Practice
In addition to structured observation that occurs in participants’ natural environments, there are many other
methods available to researchers to capture observation data. Many of these other methods use cutting-edge
technology. The following describes examples of structured observation in practice, but this is nowhere near a
complete list of all observation methods.
Mechanical Observation
It is not always possible or practical for researchers to observe the phenomena in real time in the participant’s
natural environment. In these instances, mechanical observation is an effective alternative. Traffic cameras
and other mechanical devices are commonly used to quantify usage of roadways and to identify traffic
patterns that may be problematic. Video cameras and time-lapse photography are used in busy warehouses
to improve the flow of product and safety for employees who are working around dangerous equipment.
Nielsen Media Research uses mechanical observation to collect data on which television shows are being
watched in households, on which television sets, who is watching them, and for how long. Arbitron performs
similar observation research on radio audiences. Scanner-based observation is another mechanical means of
capturing consumer purchase behavior data through scanned UPC codes. This is an easy way to collect large
amounts of data that can be used to analyze the relationship between consumer behavior and variables like
promotion and pricing (Cooper & Schindler, 2014).
Satellite Imagery
Observation from space is a unique example of observation research. Satellites are routinely used to observe
activity at ports, shipping terminals, oil refineries, retail establishments, and farms. This data enables the
quantification of shipping containers and vessel traffic in ports; supply of energy at oil refineries; consumer
traffic at retail establishments like Walmart, Lowes, and McDonalds; and crop yields. Satellite data is then
used to make inferences about economic activity (Eamon, 2010; Goldstein, 2010).
Eye Tracking
Eye tracking is a desirable observation method since it captures what subjects actually do rather than what
they say they do. Eye tracking uses infrared-enabled webcam and wearable technology to quantify research
participants’ conscious and unconscious eye movements to determine what they pay attention to (behavior)
and for how long (timing). Eye tracking is useful for capturing participant data and the attention paid to online
RCH 5301, Research Design and Methods 5
UNIT x STUDY GUIDE
Title
stimuli. It is especially beneficial in online environments since eye-tracking data can be linked directly to
behavior.
Heat Mapping
The purpose of heat mapping, like eye tracking, is to quantify human behavior using special technology. The
technology is used to measure variables like cursor movements, scrolling activity, clicks and click-through
rates, page views, and time per page for all website visitors. Activity is color coded, so high activity appears
visually in gradients of red, and low activity appears as gradients of green. Heat mapping technology can also
be used to create heat maps for consumer behavior and physical movements in retail establishments.
Regardless of whether heat mapping is used for creating a visualization of behavior in digital or non-digital
environments, the data can be used to make strategic decisions to improve the effectiveness of lower activity
areas (Perez, 2020).
Retail heat mapping (Soltani, 2015)
Neuromarketing
Neurofocus is a company that uses technology called quantified electroencephalography (QEEG) to measure
a subject’s brain activity in different parts of their brain. The data is captured through discreet electrodes
attached to the subject’s head and displayed in a format like a heat map. QEEG is like magnetic resonance
imaging (MRI) technology, but it is mobile and allows the capture of data in dynamic environments. For
example, electrodes can be attached to consumers to observe the alpha-wave brain activity as they engage
in surfing the web. As their alpha-wave activity is triggered by interest in different websites, the researcher will
observe their brain images that light in hotter gradients of red. As subject interest wanes, researchers will
observe areas of the brain’s lighting in cooler gradients of green.
Education
Observation research is routinely used in many domains of interest, including education. For example,
structured observation could be used in the classroom to quantify the number of questions asked by students
during class time to determine if a relationship exists with grade point average.
RCH 5301, Research Design and Methods 6
UNIT x STUDY GUIDE
Title
Time and Motion
Time and motion studies provide a great application for structured observation research. Quantifying the
number of movements and time required to make those movements can be helpful in reducing waste,
increasing efficiency, and raising safety awareness (Drew, 2022).
Safety, Health Care, and Medicine
Structured observation research in safety, health care, and medicine has been used to quantify the types,
frequency, and severity of negative events across various departments, including operations, pharmacy,
emergency, operating rooms, anesthesia, obstetrics, and intensive care. For example, the type, frequency,
and severity of incorrect drug administration is easily quantifiable through observation research. In addition to
improving operational efficiency, the most beneficial aspect of observation research in a safety or health care
setting is the reduction of workplace accidents and illnesses and the detrimental effects of adverse care,
including death (Carthey, 2003).
Content Analysis
Content analysis is like structured observation in that it is a quantitative process where the researcher
systematically and visually examines and quantifies existing words, titles, subjects, actors, and images within
published or unpublished print or digital media, including news articles, letters, emails, advertisements,
television shows, and websites. The content analysis may measure either the inclusion or exclusion of the
variable or variables under study. This should not be confused with the qualitative content analysis, which is
subjective. In the qualitative content analysis, the researcher interprets and constructs meaning from the print
or digital media. In quantitative content analysis, the researcher objectively quantifies what is found in the
media and does not interject their values or interpret meaning. Content analysis would be an incredibly time-
consuming and tedious exercise if it were done manually. Fortunately, there are technology solutions to
facilitate this process so researchers can spend most of their time on data analysis rather than data collection
(Zikmund et al., 2013).
Secondary Data Analysis
Secondary data analysis (i.e., archival research) is a quantitative approach to research using data that has
already been collected for other purposes, by other people and researchers, such as academic study data,
commercial and trade data, organizational data, and government data (Zikmund et al., 2013). For example,
the scanner data mentioned above in the discussion on mechanical observation is normally collected by
individual grocery store chains to monitor their own customers. However, the National Grocers Association
could aggregate scanner data from their association members to share with the entire association, even those
without access to their own scanner data. This would be a useful means of secondary data analysis.
In Closing
Many of the practical examples of structured observation make use of cutting-edge technology, and there is
no stopping it. Technology is pervasive in society and is often used to surreptitiously capture consumer
information through so-called surveillance products. See the examples below.
• Smartwatches capture health, exercise, and sleep data.
• Geolocation technology and GPS navigation apps track people’s activities and vehicle movements.
• Smartphones, tablets, and laptops listen to their users.
• Amazon’s Alexa and Apple's Siri capture user activity and listen to conversations.
• Smart refrigerators, washing machines, and other appliances have listening capabilities.
• Millions of users on social networking sites have no appreciation for privacy and gladly share their
most intimate details.
• Radio-frequency identification (RFID) chips used in toll passes, passports, payment mechanisms, and
reward fobs track owners’ movements.
Many consumers naively believe that marketers respect their privacy. Perhaps the most successful marketing
organization in history, Amazon, has been caught collecting user conversations through Alexa without
their knowledge. Since being caught with their hand in the cookie jar, Amazon now allows users to opt
RCH 5301, Research Design and Methods 7
UNIT x STUDY GUIDE
Title
out of this functionality, but many users are still unaware of this option or are simply unconcerned.
Similarly, users of Gmail and Google Calendar open personal, business, and contact information that
is available to Google to peruse at will, without requiring permission, and with no explanation required.
Many other users are willing to trade privacy and confidentiality for convenience or productivity. Still, others
are willing to swap their privacy for “free” services from companies like Google or Bing (Kelly, 2022).
Experts in the field warn the public that the danger from these means of observation has never been more
serious. The information that consumers share willingly and unwillingly with marketers can be accessed and
abused by governments, hackers, and others (Kelly, 2022). For consumers, privacy and confidentiality should
be a top concern, especially given the potential for search histories, location data, text messages, emails, and
other digital information to be accessed, analyzed, and sold to third-party marketers and government
agencies. Some would say that George Orwell’s vision in 1984 is alive and well in today’s society, and it is
being facilitated through observation research technology. Researchers should enjoy the efficiency and
quality of data provided through observation research technology, but they should always be mindful to do no
harm.
References
Carthey, J. (2003). The role of structured observational research in health care. BMJ Publishing Group Ltd. &
The Health Foundation. https://qualitysafety.bmj.com/content/12/suppl_2/ii13
Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods
approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964
Drew, C. (2022, October 23). 10 observational research examples. The Helpful Professor.
https://helpfulprofessor.com/observational-research-examples/
Eamon, J. (2010, August 17). Spying for profits: The satellite image indicator. CNBC.
https://www.cnbc.com/2010/08/17/Spying-For-Profits:-The-Satellite-Image-Indicator.html?slide=1
Ellis, P. (2024). Research methods: Quantitative observation. Wounds UK, 20(2), 73-74.
https://libraryresources.columbiasouthern.edu/login?url=https://search.ebscohost.com/login.aspx?dire
ct=true&db=cul&AN=178268293&site=ehost-live&scope=site
Goldstein, J. (2010, August 19). With satellite images, Wall Street analysts spy on Wal-Mart. NPR.
https://www.npr.org/sections/money/2010/08/19/129298095/with-satellite-images-wall-street-analysts-
spy-on-wal-mart
Kelly, S. M. (2022, October 2). Amazon is always watching. CNN.
https://www.cnn.com/2022/10/02/tech/amazon-product-event/index.html
Perera, A. (2021, May 28). What is the Hawthorne effect? Simply Psychology.
https://www.simplypsychology.org/hawthorne-effect.html
Perez, J. (2020, May 20). What’s so hot about heat mapping? Pinckney.
https://pinckneymarketing.com/whats-so-hot-about-heat-mapping/
Price, P. C., Jhangiani, R., Chiang, I. A., Leighton, D. C., & Cuttler, C. (2017). 6.5 Observational research. In
Research methods in psychology. Pressbooks.
https://opentext.wsu.edu/carriecuttler/chapter/observational-research/
Soltani, A. (2016, April 30). Privacy trade-offs in retail tracking [Image]. Federal Trade Commission.
https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2015/04/privacy-trade-offs-retail-tracking
Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage
Learning.
**## UnitIVAssignment.docx**
Unit IV
This assignment measures your mastery of ULOs 2.1, 2.2, 3.1, and 3.2.
**Research Strategy Analysis**
Locate a primary research article in an academic journal from the CSU Online Library where the researcher(s) used a quantitative research strategy, a survey instrument, and inferential statistics. After reading the article, explain the following elements:
· purpose of the study,
· population of interest,
· research questions,
· constructs and variables being tested,
· hypotheses,
· research design,
· analytical approach,
· data analysis procedures used,
· sampling frame,
· sampling design (i.e., sampling type),
· data collection method,
· statistically significant inferences that are generalizable to the population of interest.
Your assignment should consist of a minimum of two pages in length, not counting the required references page. Please thoroughly address all required elements listed above. Responses should be written in a narrative format rather than being formatted as short bullet points.
Please use APA-compliant headings and sub-headings that align with the individual assignment elements and please respond to the assignment elements in the same sequence they are requested in the instructions. Do not combine elements within a section. Each assignment element should have its own section with APA heading. Adhere to all other APA Style and formatting guidelines, including in-text citations and references for all sources that are used. Include at least the article used as a source, but other credible sources may be used as needed.
**Resources**
The following resource(s) may help you with this assignment.
·
[Citation Guide](https://www.columbiasouthern.edu/downloads/pdf/success/citation-guide)
·
[CSU Online Library Research Guide](https://libguides.columbiasouthern.edu/researchmethods)
·
[Submit Writing Center Request](https://mycsu.columbiasouthern.edu/student/forms/courses/writing-center-request)
**## UnitIVStudyGuide.pdf**
RCH 5301, Research Design and Methods 1
Course Learning Outcomes for Unit IV
At the end of this unit, you should be able to:
2. Discriminate among the characteristics of qualitative and quantitative research methods.
2.1 Deduce differences between a quantitative methodological research strategy and
qualitative research strategy.
2.2 Identify a primary research article in an academic journal where the researcher or
researchers used a survey instrument and inferential statistics.
3. Evaluate research designs.
3.1 Differentiate between descriptive, explanatory, and exploratory research designs based on
their unique characteristics.
3.2 Analyze an academic study’s research design, analytical approach, data analysis
procedures, data collection method, and sampling design.
Required Unit Resources
Chapter 3: The Use of Theory (ULOs 3.1 and 3.2)
Read the following sections from this chapter:
Quantitative Theory Use
Chapter 4: Writing Strategies and Ethical Considerations (ULOs 3.1 and 3.2)
Article: Research Methods: Quantitative Observation (ULOs 3.1 and 3.2)
This article discusses using observation for quantitative data collection. (2 pages).
Unit Lesson
Lesson: Don’t Look Now, but You’re Being Observed (ULOs 3.1 and 3.2)
Introduction
Most of the focus of data collection in this course has been on the survey or self-completion questionnaire.
While the survey is the most often used quantitative data collection method in research, there are other non-
experimental methods for collecting data, such as structured observation, content analysis, and utilizing
secondary data.
Structured Observation
As the name implies, structured observation is a process where the researcher systematically and visually
examines and quantifies phenomena as they occur. While observation research is often associated with the
qualitative research methodology, structured observation is decidedly quantitative. Characteristics of
observation research that make it a positivist’s tool are that the variables to be studied are predetermined
through the structure, and the variables are quantifiable. These are two conditions that are foreign to
qualitative research.
Variables under structured observation are varied. Virtually anything that can be counted can be studied
through structured observation, including objects, time, events, words, clicks, people, and behavior. Even
nonverbal communication can be observed and quantified, including facial expressions, body language, eye
UNIT IV STUDY GUIDE
Quantitative Research Using Naturally
Occurring Data, Secondary Data, and
Official Statistics
RCH 5301, Research Design and Methods 2
UNIT x STUDY GUIDE
Title
movements, personal space, gestures, and manners. For example, assume medical patients are under
observation in a health care facility, and the predetermined variables to measure are facial expressions, body
language, eye movements, personal space, manners, time, objects, demographics, and actions. The
researcher might devise an observation schedule that includes the variables below.
Was the purpose of the patient’s visit to:
• seek treatment for a new medical concern (event)?
• seek treatment for an existing medical condition (event)?
When approached by the medical provider, did the patient:
• smile, frown, or remain unchanged (facial expression)?
• stand still, back away, or lean into the medical provider (personal space)?
• shake the provider’s hand (manners)?
• fold their arms or keep them dangling in a relaxed manner (body language)?
• make steady eye contact or avoid looking at the provider directly (eye movement)?
• mention the current condition that is being treated (words)?
How much time did the patient:
• speak with the provider (timing)?
• engage in conversation with other patients (timing)?
• spend in common areas (timing)?
• isolate in their room (timing)?
• handle common area activities, such as books (timing)?
Which items did the patient handle while in the common area?
• Educational literature (object)?
• Magazines (object)?
• Books (object)?
• Board games (object)?
What was the patient’s:
• gender (demographics)?
• age (demographics)?
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Structured observation can take place in a controlled environment (i.e., contrived observation), such as a
laboratory, but observation most often occurs in the participants’ natural environment, such as a field location
or facility, which was used in the example above. Research outside of a lab has the potential for a more
realistic and unbiased accounting of behavior since participants are unlikely to modify their actions to meet
researcher expectations. In either case, the structured observation takes place without researcher
intervention, although the research can be conducted overtly (i.e., undisguised observation) or covertly (i.e.,
disguised observation). If conducted overtly, the participants are aware they are the subject of research. This
can create bias since the participants are likely to modify their behavior to conform to how they think the
researcher expects them to behave. This is known as reactivity. This is also known colloquially as the
Hawthorne effect. The name originates from a series of 1920s industrial experiments conducted at Western
Electric’s large Hawthorne plant in Cicero, Illinois. Although there were four different studies, the Illumination
Experiments (1924–1927) were the most illuminating (pun intended) about the phenomenon called reactivity
(Perera, 2021; Price et al., 2017).
In the Illumination Experiments, researchers were seeking to determine if there was a relationship between
the variables of illumination levels and factory productivity. They hypothesized that the relationship would be
positive, meaning the variables would move in the same direction. For example, they guessed as illumination
levels decreased, productivity would decrease, and as illumination levels increased, productivity would
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increase. The researchers were surprised to find, however, that no matter the change in illumination,
productivity increased. As illumination increased, productivity increased. As illumination decreased,
productivity increased. It was determined that the workers’ awareness of being studied was severely biasing
results. Interestingly, reactivity begins to wane over time as participants become desensitized to the presence
of researchers, and their behaviors begin to normalize. This is precisely what occurred at the Hawthorne
factory (Perera, 2021).
To avoid bias from reactivity, observation research can be conducted covertly so that the participants are
unaware that they are the subjects of research. While this can eliminate the risk of bias, it can potentially
increase ethical risks. However, researchers generally accept covert observation as ethical if participants’
anonymity is preserved, and the observation is performed in public where there is no expectation of privacy
(Cooper & Schindler, 2014).
Structured observation is very similar to naturalistic observation and participant observation, which are
qualitative data collection methods. The difference between structured observation, naturalistic observation,
and participant observation is that structured observation is intended to quantify a relatively small number of
variables rather than record and interpret all the behaviors that are taking place (Price et al., 2017).
It should be noted that everything that was discussed in previous units about sampling applies to structured
observation; however, probability sampling can be challenging since it is often difficult to develop a sampling
frame in observation studies. It then follows that making valid and reliable inferences about a population of
interest, or generalizing results, can be difficult to achieve (Price et al., 2017).
Structured Observation in Practice
In addition to structured observation that occurs in participants’ natural environments, there are many other
methods available to researchers to capture observation data. Many of these other methods use cutting-edge
technology. The following describes examples of structured observation in practice, but this is nowhere near a
complete list of all observation methods.
Mechanical Observation
It is not always possible or practical for researchers to observe the phenomena in real time in the participant’s
natural environment. In these instances, mechanical observation is an effective alternative. Traffic cameras
and other mechanical devices are commonly used to quantify usage of roadways and to identify traffic
patterns that may be problematic. Video cameras and time-lapse photography are used in busy warehouses
to improve the flow of product and safety for employees who are working around dangerous equipment.
Nielsen Media Research uses mechanical observation to collect data on which television shows are being
watched in households, on which television sets, who is watching them, and for how long. Arbitron performs
similar observation research on radio audiences. Scanner-based observation is another mechanical means of
capturing consumer purchase behavior data through scanned UPC codes. This is an easy way to collect large
amounts of data that can be used to analyze the relationship between consumer behavior and variables like
promotion and pricing (Cooper & Schindler, 2014).
Satellite Imagery
Observation from space is a unique example of observation research. Satellites are routinely used to observe
activity at ports, shipping terminals, oil refineries, retail establishments, and farms. This data enables the
quantification of shipping containers and vessel traffic in ports; supply of energy at oil refineries; consumer
traffic at retail establishments like Walmart, Lowes, and McDonalds; and crop yields. Satellite data is then
used to make inferences about economic activity (Eamon, 2010; Goldstein, 2010).
Eye Tracking
Eye tracking is a desirable observation method since it captures what subjects actually do rather than what
they say they do. Eye tracking uses infrared-enabled webcam and wearable technology to quantify research
participants’ conscious and unconscious eye movements to determine what they pay attention to (behavior)
and for how long (timing). Eye tracking is useful for capturing participant data and the attention paid to online
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stimuli. It is especially beneficial in online environments since eye-tracking data can be linked directly to
behavior.
Heat Mapping
The purpose of heat mapping, like eye tracking, is to quantify human behavior using special technology. The
technology is used to measure variables like cursor movements, scrolling activity, clicks and click-through
rates, page views, and time per page for all website visitors. Activity is color coded, so high activity appears
visually in gradients of red, and low activity appears as gradients of green. Heat mapping technology can also
be used to create heat maps for consumer behavior and physical movements in retail establishments.
Regardless of whether heat mapping is used for creating a visualization of behavior in digital or non-digital
environments, the data can be used to make strategic decisions to improve the effectiveness of lower activity
areas (Perez, 2020).
Retail heat mapping (Soltani, 2015)
Neuromarketing
Neurofocus is a company that uses technology called quantified electroencephalography (QEEG) to measure
a subject’s brain activity in different parts of their brain. The data is captured through discreet electrodes
attached to the subject’s head and displayed in a format like a heat map. QEEG is like magnetic resonance
imaging (MRI) technology, but it is mobile and allows the capture of data in dynamic environments. For
example, electrodes can be attached to consumers to observe the alpha-wave brain activity as they engage
in surfing the web. As their alpha-wave activity is triggered by interest in different websites, the researcher will
observe their brain images that light in hotter gradients of red. As subject interest wanes, researchers will
observe areas of the brain’s lighting in cooler gradients of green.
Education
Observation research is routinely used in many domains of interest, including education. For example,
structured observation could be used in the classroom to quantify the number of questions asked by students
during class time to determine if a relationship exists with grade point average.
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Time and Motion
Time and motion studies provide a great application for structured observation research. Quantifying the
number of movements and time required to make those movements can be helpful in reducing waste,
increasing efficiency, and raising safety awareness (Drew, 2022).
Safety, Health Care, and Medicine
Structured observation research in safety, health care, and medicine has been used to quantify the types,
frequency, and severity of negative events across various departments, including operations, pharmacy,
emergency, operating rooms, anesthesia, obstetrics, and intensive care. For example, the type, frequency,
and severity of incorrect drug administration is easily quantifiable through observation research. In addition to
improving operational efficiency, the most beneficial aspect of observation research in a safety or health care
setting is the reduction of workplace accidents and illnesses and the detrimental effects of adverse care,
including death (Carthey, 2003).
Content Analysis
Content analysis is like structured observation in that it is a quantitative process where the researcher
systematically and visually examines and quantifies existing words, titles, subjects, actors, and images within
published or unpublished print or digital media, including news articles, letters, emails, advertisements,
television shows, and websites. The content analysis may measure either the inclusion or exclusion of the
variable or variables under study. This should not be confused with the qualitative content analysis, which is
subjective. In the qualitative content analysis, the researcher interprets and constructs meaning from the print
or digital media. In quantitative content analysis, the researcher objectively quantifies what is found in the
media and does not interject their values or interpret meaning. Content analysis would be an incredibly time-
consuming and tedious exercise if it were done manually. Fortunately, there are technology solutions to
facilitate this process so researchers can spend most of their time on data analysis rather than data collection
(Zikmund et al., 2013).
Secondary Data Analysis
Secondary data analysis (i.e., archival research) is a quantitative approach to research using data that has
already been collected for other purposes, by other people and researchers, such as academic study data,
commercial and trade data, organizational data, and government data (Zikmund et al., 2013). For example,
the scanner data mentioned above in the discussion on mechanical observation is normally collected by
individual grocery store chains to monitor their own customers. However, the National Grocers Association
could aggregate scanner data from their association members to share with the entire association, even those
without access to their own scanner data. This would be a useful means of secondary data analysis.
In Closing
Many of the practical examples of structured observation make use of cutting-edge technology, and there is
no stopping it. Technology is pervasive in society and is often used to surreptitiously capture consumer
information through so-called surveillance products. See the examples below.
• Smartwatches capture health, exercise, and sleep data.
• Geolocation technology and GPS navigation apps track people’s activities and vehicle movements.
• Smartphones, tablets, and laptops listen to their users.
• Amazon’s Alexa and Apple's Siri capture user activity and listen to conversations.
• Smart refrigerators, washing machines, and other appliances have listening capabilities.
• Millions of users on social networking sites have no appreciation for privacy and gladly share their
most intimate details.
• Radio-frequency identification (RFID) chips used in toll passes, passports, payment mechanisms, and
reward fobs track owners’ movements.
Many consumers naively believe that marketers respect their privacy. Perhaps the most successful marketing
organization in history, Amazon, has been caught collecting user conversations through Alexa without
their knowledge. Since being caught with their hand in the cookie jar, Amazon now allows users to opt
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out of this functionality, but many users are still unaware of this option or are simply unconcerned.
Similarly, users of Gmail and Google Calendar open personal, business, and contact information that
is available to Google to peruse at will, without requiring permission, and with no explanation required.
Many other users are willing to trade privacy and confidentiality for convenience or productivity. Still, others
are willing to swap their privacy for “free” services from companies like Google or Bing (Kelly, 2022).
Experts in the field warn the public that the danger from these means of observation has never been more
serious. The information that consumers share willingly and unwillingly with marketers can be accessed and
abused by governments, hackers, and others (Kelly, 2022). For consumers, privacy and confidentiality should
be a top concern, especially given the potential for search histories, location data, text messages, emails, and
other digital information to be accessed, analyzed, and sold to third-party marketers and government
agencies. Some would say that George Orwell’s vision in 1984 is alive and well in today’s society, and it is
being facilitated through observation research technology. Researchers should enjoy the efficiency and
quality of data provided through observation research technology, but they should always be mindful to do no
harm.
References
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The Health Foundation. https://qualitysafety.bmj.com/content/12/suppl_2/ii13
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Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods
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Drew, C. (2022, October 23). 10 observational research examples. The Helpful Professor.
https://helpfulprofessor.com/observational-research-examples/
Eamon, J. (2010, August 17). Spying for profits: The satellite image indicator. CNBC.
https://www.cnbc.com/2010/08/17/Spying-For-Profits:-The-Satellite-Image-Indicator.html?slide=1
Ellis, P. (2024). Research methods: Quantitative observation. Wounds UK, 20(2), 73-74.
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Soltani, A. (2016, April 30). Privacy trade-offs in retail tracking [Image]. Federal Trade Commission.
https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2015/04/privacy-trade-offs-retail-tracking
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