The Importance of Triangulation in Data Collection

The provided assignment discusses the importance of using multiple data collection methods to ensure reliability and validity in research studies. It highlights the limitations of individual data collection techniques and the benefits of employing triangulation, a methodology that combines different approaches to enhance report quality. The assignment emphasizes the need for researchers to critically examine their data collection methods and consider using triangulation to minimize differences and improve overall test quality.

PASS - EXAMPLE THREE
FRONT COVER:
Course title: Msc International Business
Module title: Applied Research Skills
Word count is 4478 words (excluding cover page, table of Contents , references)
OUTCOME:
PASS - 19% SIMILARITY
COMMENTS (EXAMPLE)
To improve, you must significantly increase your referencing. Your grade would have been much
higher if you had provided in text citations to support all your key points and if you had also provided
examples from referenced research studies to demonstrate your understanding of how the covered
research methods work in practice.
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Task -1
1. Purpose and Pros and Cons of the Research Data
The system used to collect data on individuals and processes in a natural environment is a
participating data system. Researchers consider participant assessment as the most effective and
straightforward form of data collection since it does not require scientific expertise. A contextual
methodology for gathering and interpreting data inside a natural system is a way of evaluating
data processing. As such, work plays an essential role in helping researchers to examine how the
participants behave in a natural environment. Clearly stated, the data collection observation
approach applies to a systematic explanation of activities, actions and objects in a natural setting

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chosen for a particular analysis. The data collection technique helps researchers to identify
current circumstances utilizing five senses of the condition or scenario being examined.
A participant data network is a method used to gather data on individuals and activities in the
natural world. Researchers see participant assessment as the easiest, more straightforward
process of data collection, as technical knowledge is not necessary. The way data analysis may
be measured by a relational approach to collect and analyze data within a natural environment.
Therefore, work plays a crucial role in helping researchers to examine the behaviour of
participants in a natural setting. A structured interpretation of events, practices and artefacts in
the natural world identified for a specific study is explicitly demonstrated by the data collection
analytical method. The technique of data collection helps researchers to identify current
situations, which are examined using five senses of the condition or scenario. Unlike other data
processing methods, the usage of audience assessment systems provides several benefits. For
example, the approach offers a straightforward interpretation of the situation under study, which
allows the researcher to clarify incidents, behaviours or scenarios(Sekaran&Bougie, 2016).
Often, the data collection strategy helps participants access unplanned activities. In this way, new
testing questions or theories are further enhanced by data analysis, evaluation and formulation
through improved precision. The other advantage of observational research is that it can help
complete a study by putting a hypothesis issue into the real world. It offered the participants a
better description in this regard; therefore, the process is less hypothesized than other data
collection methods. However, observational evaluation enables scientists not to use evidence to
predict what would happen in the course of experiments, but to identify and assess real
circumstances and incidents, thus validating actual findings.

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In contrast with other data gathering techniques, there are many benefits of utilizing audience
evaluation processes. For example, a clear explanation of a condition under analysis is given by
the methodology, which allows the researcher to explain incidents, acts or scenarios. The data
collection strategy often helps participants to access activities which are not planned. As such,
the data analysis, evaluation and the formulation of new testing questions or theories are
enhanced by enhancing the accuracy as well. The other benefit of observational research is that it
can help to complete a study by bringing a question of hypothesis into the real world. In this
connection, it offered the participants a better description; therefore, compared to other methods
of data collection, the process is less hypothetical. However, evaluation by observers allows
scientists not to use evidence to forecast what would happen in the context of experiments but
establish and evaluate real circumstances or incidents and the method validates the actual results
in this way.
The participant's assessment as a data collection tool has many drawbacks. Of starters, academics
might not be involved in activities taking place in the natural landscape or in the context of the
public. In order to facilitate the data collection, the researchers would focus on primary
informants. However, there is a debate about whether various studies interpret what they find and
whether the primary subjects or respondents interested in the analysis draw the results. Problems
relating to key behaviors and associated expectations may emerge, however, when researchers
pick key participants or informants they meet, or if the primary informants are vulnerable
participants or representatives of the community(Saunders, Lewis &Thornhill, 2016). In
addition, where participant expertise is used by researchers to gather information, the assessment
was described as an essential source or inappropriate concept, particularly when used in conduct
studies. The gathered evidence cannot be accurate because the details obtained by the inspectors

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may be used dependent on the investigator's curiosity in the situation or behaviour. The
information mentioned cannot reflect in certain cases what can be seen in the natural world.
2. Four Dimensions that Distinguish various Approaches to Observation
1. Controlled vs Uncontrolled Observation Studies
There is a disparity in results in simulated conditions or in natural settings. This should be
remembered, though, that findings typically arise in natural settings. Observations may also be
rendered as a form of data collection in managed or experimental settings. The participant
observation studies are usually limited under regulated conditions engineered by the researcher.
In addition, participants are exposed to other circumstances, such as the types of employment.
This is critical as it allows scientists to analyze the numerous behavioral responses to a specific
circumstance. On the opposite, controlled experiments, for instance in a model shop or on the
field, in a research setting and, in a laboratory, atmosphere can be performed. The other aspect is
that a controlled experiment takes place, mainly if observational work takes place in a situation
or condition that is carefully monitored. An uncontrolled discovery happens, on the other hand,
when an investigator is not attempting to influence and control the situation. In this case, the
activities are conducted in the natural environment without actually interacting with the location
in the real world. The researchers observe the events. Participants' most significant benefit is that
unregulated learning can be conducted in their natural environment, including working areas.
The downside of uncontrolled observation is that a complicated scenario is generally not easy to
distort or manipulate, as the scientists have little influence over a particular aspect. This is why
the triggers of participant behaviour, or incidents are so challenging to understand and discern. A
good thesis includes information from different sources, and this is a fact. And some
methodologies, such as triangulation, qualitative and quantitative methodologies may be used for

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such an accounting study(Guest, 2013). As such, a thesis should differentiate between research
approaches and procedures such that confusion cannot be eliminated throughout the review.
Nonetheless, the simplest explanation is that virtually all data processing approaches are
associated with certain tacit premises. As a consequence, the legitimacy of the observational
methods used by multiple sources and through particular data collection strategies can arise
where findings from a standard variable show significant correlations. Furthermore, the data
obtained from discarded devices, by using specific data recovery methods and tools, may even be
improved to some precision.
It is also a fact that each data processing technique used by analysis has its unique features.
Which is that the findings align with perceptions and interviewees as interviews are used.
Nevertheless, if details are collected and linked from various sources if the ties between the
specific methods of knowledge collection are established through separate sources, and there are
a definite correlation and confidence between them. The reliability of evidence and accuracy of
the results might be starting to be questioned by researchers on the other side because there is no
relatively clear connection between responses. The methods used to gather data would be
carefully investigated in all situations. When participants say for example that they are highly
pleased with their present work when tested, if a concept or feature is measured utilizing many
elements found in the questionnaire, the results should be deemed acceptable, while information
obtained from different studies that include the same mix. In the other side, there may be severe
concerns for the accuracy or quality of the data collected or on the instrument's unreliability as
the data collection methods are different.
Obviously, all scientists believe that triangulation is the best approach to reduce the variations in
data collected. The triangulation process is the system by which scientists use various strategies

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to analyze such phenomena. Therefore, both quantitative and graphical methods can be utilized
by a researcher in the same study by triangulation. Triangulation methods are specifically aimed
at reducing or decreasing the variations and enhancing both theoretical accuracy and validity
(Quinlan et al., 2019). For instance, if a researcher cannot obtain and estimate the sample size,
the method of triangulation is used to increase the consistency of the overall study by reviewing
exam results
2. Participant vs Nonparticipant Observation
By gathering empirical evidence, researchers may assume the role of a non-participant or
observer. Therefore, in the case of a non-participant sample, the researcher is not interested
directly in actors' activities or acts. However, the experiment aims at subjects outside the
perceptual horizons. Measurement by samples, though, is a process also utilized in a variety of
studies. Therefore, the researcher gathers information through the everyday life of people,
societies or organizations in the study of topics. Furthermore, the degree of engagement depends
on the case. The lowest amount of participation is a voluntary engagement that helps researchers
to collect the knowledge they need without being an association leader. Moderate engagement
occurs where the researcher does not actively engage but meets frequently with the researchers
or the study organization.
The researcher engages or participates entirely in all that the community or company does. The
researcher is considered a member of the association or a social group under review in a full
evaluation of the sample. Therefore, full participation is intended to build an understanding from
an insider’s viewpoint or point of view of the company or social group (Noble & Smith, 2015).
Beynon joined the Form Motor Company, was considered a member of the company under
investigation and is an example of full involvement.

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3. Structured vs Unstructured Observation Studies
A formal observational study occurs when a researcher has established a collection of activities
or categories that should be studied. For these instances, the formats used to capture the data
should be developed explicitly and tailored to each study to ensure that they fulfil the research
objective. Structured observational studies are, therefore, generally of a quantitative nature. Of
example, issues relating to the workplace may also be noted, such as working conditions and
improvements in the climate. Unstructured quantitative studies include observations of events, as
well as ways of exploratory and qualitative analysis, which may also be part of a program. Thus,
almost everything observed will be recorded by the researcher. Unstructured quantitative studies
are nevertheless known as the fundamental foundation of qualitative research. Besides, informal
observation studies can lead to a collection of conclusions that are deductive in nature and can be
checked in subsequent analysis(Zohrabi, 2013).
4. Concealed vs Unconcealed Observation
While making hidden observations, it is necessary to consider whether the mechanism leading to
the study advises or tells participants or members of a social group about the research intent. The
main benefit of a covert observational study is that there is no knowledge that participants or test
subjects are tested or examined. On the other hand, unnoticed findings are considered more
obstructive, because they contribute to an alteration of the validity of the actions of the studied
subjects. The Hawthorne effect is an example of the subject's uncontrolled reaction. The other
case is when researchers try to prevent reactivity, dressing themselves up as shoppers to gather
data on how salespeople approach. Cloaked observations are therefore employed because
uncloaked considerations could influence the validity of the results.

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3. Ways of Minimizing Observer Bias
When researchers use representation to collect data, they often discount information gathered in
the first few days, particularly if it seems to be distinct from what they later experience. The
evidence obtained from the investigator's point of view is most likely correlated with or subject
to observational bias in these situations. It is possible that a possible problem with the study of
the student will disappear or disappear as a result of the student position in a group of subjects,
and that the investigator becomes native. This can result in partiality or faulty accounting. For
example, the researcher may report errors when analyzing such tasks, events, actions and non-
verbal signs. Consequently, the observer could have regular observations of events over long
periods and this could result in partiality, particularly if the observations are documented. For
example, before data collection techniques are implemented, the questionnaire will be tested for
genuineness and consistency of the measurement, whether the results have been compiled via a
questionnaire. Next, to calculate the item that is to be measured, it is essential to test the validity
of the equation that suits the precision measurement or instrument used to calculate details. The
relevance and importance of knowledge obtained from the collection of the questions or from the
issues to be examined were included in the analysis (Leung, 2015). As such, a series of questions
identified by the representative sample and the community, the legitimacy and efficacy of the
questionnaire will be calculated.
There are two essential requirements for a questionnaire to be correct and valid. For example, the
survey is assumed to be accurate if the questions primarily reflect the questionnaire query. If the
respondents are given time-conforming answers, a questionnaire is claimed to be precise (Leung
2015, p. 325). The inquiry is, therefore, correct. Furthermore, the quality and efficiency of the
method used to capture the data are taken into consideration as several ways are used to compile

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data from various outlets. Besides, the results will be more confident when data collection from
different sources is closely linked, such as interviews, questionnaires and observations.
The usage of other forms of data processing is a method for evaluating them. Typically, there are
thus two big questions concerning any variation in data collection approaches (Leung 2015, p.
324). Both are mainly associated with the implementation and combination of various
knowledge sets. In this way, the analysis of data is focused on experiments and the
understanding of results, such that a researcher can consider the topic entirely. On the other hand,
the use of multiple data collection methods is based on the assumption that the researchers are
prepared to resolve the prejudices that correlate with each process. This can be expected to
properly analyze the process studied as the different techniques of data collection are still
producing the same findings(Suen&Ary, 2014).
When biases arise as findings are registered, there are mainly ways to mitigate them. Training on
techniques of observation and what events to record from view are usually offered to researchers,
for example. As such, it would be best if adequate observational studies established the reliability
of the inter-observer. They can be further developed, in particular during observatory training,
which can be accomplished by tape video, which can also help to establish interobserver
reliability. The best formula for dividing or categorizing the number of agreements between
trainees by several negotiations as well as disagreements can be used for the production of the
reliability coefficient.

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4. Proceed with a thorough Review of the Ethics used as a Testing tool by
Discreet Observation
Work that would ensure that the security of privacy and the psychological well-being of research
respondents are taken into consideration in the natural conditions has been acknowledged. As
such, the ethical concern to be taken into account should ensure that consent is respected, mainly
when a rigorous observational study is applied. For such cases, scientists will not tell the
respondents that certain people are investigating what is deemed unethical. Besides, other
societies, as well as local traditions, should be taken into account, as the privacy of individuals
may be compromised when making occulted findings even though they feel they are not
investigated.
If respondents assume that they are not examined in a study setting, it has been proposed that this
may be affected by what the researchers expect. It is also essential to ensure the researcher
follows the social desirability factors that can contribute to the actions of the participant to
ensure their expectations have been fulfilled. As such, some ethical concerns separate
observational studies from a recognized research concern. For example, during the analysis,
there are some unexpected errors. Some researchers try, without making them aware of the intent
of the study, the social life of those who are disadvantaged. It is seen as a difficulty focused on
ethical considerations in particular when using the blurred quantitative methods (Hewsonv &
Stewart, 2014). Such studies are usually sensitive. Some experiments can stigmatize or apply to
various human behaviors. Therefore, if the subjects are not told about the intent of the
operations, they may be deemed unethical as the privacy rights will be violated.

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Task -2
1. Mechanisms for Handling Electronic Questionnaires and Explaining the
Potential Benefits and Drawbacks
The use of web surveys and email surveys is one of the most common ways to obtain
information via the Internet. These online surveys collect information from the audience by
inviting the respondents and completing the survey via the Internet. Throughout recent years,
several scholars have used the Internet to perform work throughout different areas of the world.
In comparison with other methods of surveys, the online survey was considered the best way to
collect information from respondents.
Pros
The usage of electronic polls provides many benefits. First, data from several people around the
globe can be easily collected. For example, web-based surveys and an email can lead to an
enquiry that requires more respondents. Besides, online surveys involve minimal costs, as they
facilitate low cost associated with the rapid collection of data from respondents. For example,
sending an inquiry and web-based investigation is more affordable than other data collection
methods (Leung, 2015). It is also a fact that online surveys enable respondents, utilizing Web-
based platforms to provide their answers. Feedback is conveniently stored in error-free sample
repositories. Also, the response rate is faster because online surveys are more convenient for
respondents, as they can answer the questionnaires themselves at their chosen time. The other
advantage of the electronic polls is that the sample questions can be crafted flexibly and
accessible to both respondents and researchers.

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Cons
In addition to the drawbacks of utilizing the electronic polls, the lack of an interviewer is
undermined. They are therefore not suitable for surveys which concentrate primarily on open-
ended questions, as the respondents are not equipped with qualified staff to provide advice
(Fetters, Curry & Creswell, 2013). The other downside to electronic polls is that they cannot
meet or communicate with interviewees. The approach is also not sufficient for surveys
involving many that have no internet connection. E.g., older people or people live in rural places
without Internet access.
2. Wording Principles, how important they are in the Design of Questionnaires,
not in the Book, Citing Examples
While constructing a questionnaire, the wording concept is primarily implemented to define the
reasons appropriate for the respondents to interpret the survey quickly. Different aspects to
address include concerns about the compliance quality and how queries and the degree of
vocabulary for the design of the questionnaire will be taken into account. The nature and form of
questions posed, the sequence of questions and the way they were addressed in the poll, and
external elements used to construct the questionnaire. For a fact, they may provide sensitive
details submitted by the questionnaire respondents.
a. Scope and Goals of the Queries
Different factors, such as the type of questions to be put (Noble and Smith 2015, p. 35) must be
taken into account for the development of the questionnaire. Thus, for instance, the levels of
satisfaction and commitment of the variables are subjective where the respondents are convinced
that they measure the views and attitudes of the dimensions of the query and the element.

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Therefore, the intent of the questions to be carefully answered must be emphasized in
constructing the questionnaire to ensure that all factors are calculated.
b. Using Expression
When developing the questionnaire, participants would understand the vocabulary used.
Consequently, the formulation of the survey will be the knowledge standard of the respondents.
Moreover, in particular in the culture and context of the interlocutors, use of words and idioms
should be consistent. For e.g, if English is the official language used by respondents and used by
their relatives, it is chosen instead as it may not be popular to the culture of the respondents.
c. Issue Form
The query type is whether the queries are available or locked to build the questionnaire. If free
objects are used to build the sample, respondents are encouraged to react best. Instead, as closed
questions are included, answerers will be seen on a very simplified size. A questionnaire of God
is thus arranged to deal with both helpful and dangerous subjects. Double usage of words like no
negative or replicated cannot be avoided though as respondents tend to be fooled in a bad
way(Albright, Gechter&Kempe, 2013).
3.Data Processing Processes, including the Precision and Quality of
Measurements from Various Sources
For example, whether the data are obtained by the use of a questionnaire, the questionnaire
would be checked for the validity as well as precision of calculation before the testing methods
are used to collect data. Next, the validity of the calculation which corresponds to the precision
measurement, or of the instruments used for measuring information should be checked to the

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analysis of the element to be calculated. To order to analyze the knowledge gathered from the
collection of questions or from the subjects to be questioned, both their relevance and
significance were included. As such, the questionnaire's legitimacy and efficacy will be
calculated from a collection of questions that the applicants, identified by the representative
sample and the community, have filled out in the questionnaire.
To be accurate and correct, there are two essential conditions specific to a questionnaire. For e.g.,
whether the questions primarily reflect the query the survey is to be calculated, the investigation
is assumed to be accurate. Thus, if the respondents have responses which are deemed to conform
with time, a questionnaire is claimed to be correct (McDaniel & Gates, 2013). In addition, the
validity and reliability of the measure to manage the data shall be considered if multiple sources
are used to collect data and to collect multiple sources. In addition, if the collection of data from
various sources, including interviews, questionnaires and observations, are closely related, the
results will be more confident. A practice of doing the analysis is the usage of many types of data
collection. Therefore, there are typically two big questions regarding any variety of approaches
used to gather data. Both are mainly linked to how various sets of knowledge are implemented
and how they are combined. The logic of data appears in this regard to rely on testing and data
interpretation to enable a researcher to achieve a full understanding of the topic. The usage of
multiple data collection techniques, on the other hand, is focused on the premise that the
investigator is willing to overcome the prejudices correlated with each process. Thus, such the
process being studied may be assumed to be correctly analyzed because different data collection
techniques continue to yield the same findings.
Additionally, it was shown that interpersonal partnerships were identified and remembered
throughout the research by utilizing different methods of data collection. There are some

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qualitative analysis standards focused on the idea that relevance is a question of the reliability of
the techniques protected by them as various methodologies are implemented (Sekaran&Bougie,
2016). Therefore, whether this analysis is a calculation or assesses what is supposed to be
calculated concerns explicitly the validity. Reliability, on the other hand, is a critical aspect of
the testing method which seeks to produce identical, accurate, replicable which effective results.
4. Each Method of Data Collection has its own incorporated Preferences. Giving
Access to a Multiplicity of Data Collection Approaches would just render Tastes
much Worse
It is a reality that a successful analysis thesis needs knowledge from different sources. And such
an accounting-based analysis, a variety of methodologies may be used, such as triangulation,
qualitative and quantitative methodologies. As such, a study can create a distinction between
testing techniques and procedures to prevent ambiguity when doing analysis. The most
persuasive interpretation of the argument is, however, that almost all methods to data collection
are correlated with such implicit assumptions. As a consequence, if results from a single variable
contain strong similarities, it will lead to the legitimacy of the analysis instruments utilized by
various outlets and by specific data collection techniques. Furthermore, it may also add to the
absolute reliability of the data collected from used instruments utilizing many data collection
techniques and devices.
This is also a reality that each of the techniques of data processing used by analysis has its
unique characteristics. Of one, as interviews are used, the assumptions are correlated with
interviewer stereotypes and interviewees. However, where the data is obtained and associated
from multiple sources, where the associations between the various data collection methods are

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formed across different sources. Specific data collection methods are healthy, then the
association and trust are large(Saunders, Lewis &Thornhill, 2016). At the other side, the
researchers may begin to doubt the reliability of data and the consistency of the findings because
the interaction between responses is not entirely healthy. For these instances, the techniques used
to gather data should be carefully examined. For example, when participants claim that, when
they are considered, they are incredibly pleased with their current job, whether a term or attribute
is evaluated using multiple things in the questionnaire, the findings can be deemed appropriate.
However, the same association can be formed with the details gathered from various studies. At
the other side, the precision or the reliability of the obtained data can be strongly doubted, or the
instrument can become unreliable or not accurate because there is no link with the data collection
methods used.
Many scientists agree that the only way to reduce the differences in obtained data is by utilizing
the triangulation method. The triangulation cycle is the mechanism that scientists use to research
a particular phenomenon by combining different methodologies. Therefore, a researcher should
use both quantitative and quantitative techniques in the same analysis by utilizing triangulation.
Triangulation approaches are mainly designed to eliminate or minimize differences and improve
both the precision and the validity of the report (Quinlan et al., 2019). Of example, if a
researcher cannot collect or approximate the sample size, the triangulation procedure will be
utilized to enhance the quality of the overall test by verifying the findings of the examination.

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References
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