practical research 2 (q2)
TRANSCRIPT
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Practical Research 2 (Q2)
Ella Cañas Ansay
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Table of Contents
Module 3: Learning from Others
Introduction 57
Learning Objectives 57 Lesson 1: Review of Related Literature 58
Lesson 2: Ethical Standards in Writing 68 Lesson 3: Citation and Referencing 70
Assessment 73 Summary 81
References 82
Module 4: Methodology
Introduction 83 Learning Objectives 83
Lesson 1: Hypothesis 84 Lesson 2: Data Collection 86
Lesson 3: Instrument Development 89 Lesson 4: Establishing Validity and Reliability 96
Lesson 5: Description of Sample 99
Lesson 6: Ethical Considerations 107 Lesson 7: Data Analysis 109
Assessment 115 Summary 127
References 129
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MODULE 3 LEARNING FROM OTHERS
Introduction
Now that we already discussed the introductory parts of your research paper,
obtaining narrative from others to support your study comes next. Some researchers used the
term “Review of Related Literature” for this section while others prefer to use the term “Literature
review” instead. Regardless of the label, this section is known to be derived from previous works
of several authors. This consequently requires critical reading skills and acknowledgment to the
authors you acquired sources from.
It is important to understand the role that a literature imparts with the research process
before getting started on sourcing it as this will place your own findings in context. After all, your
literature review will demonstrate how familiar you are with your topic.
In this module, we will give an extensive discussion on the review of related literature. This
includes the definition, ethics in standard writing, and citation and referencing.
Learning Outcomes
At the end of this module, the learners should be able to:
1. presents written review of related literature;
2. follow ethical standards in writing related literature; and
3. cite related literature using the APA style.
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Lesson 1. Review of Related Literature
Bordonaro (2010) defined the review of related literature as a way to relate the
explored area of a certain study along with the topic that the researcher is still investigating. Ridley
(2008) added that literature review includes theories and related research that is connected to
your paper. This is also where you place your argument on the subject of your research.
When doing the literature review, you may experience revising your research questions
for many times since literature review involves the process of defining the research question to
make your research more valid and reliable. Students writing literature review frequently wonder
how many articles they should cite and how long they should make the review. Often, standards
regarding this matter will vary, depending on the nature of the topic, the amount of literature on it,
or the instructions of your teacher.
We should establish two main goals for your literature review. First, attempt to provide a
comprehensive and up-to-date review of the topic. Second, try to demonstrate that you have a
thorough command of the field you are studying. The level of accuracy expected in a paper is
quite high (Galvan, 2002). This will require that you edit your writing to a level that far exceeds
what may be expected in a term paper.
In Dr. Villanueva’s (2018) lecture, she pointed out that a good literature review shows
where prior studies and research agree and disagree, plus where major questions that require
answers remains. It presents what is currently known studies in your chosen research topic and
gives direction to researcher in the future. A good literature review presents new techniques,
procedures, or even research design that is worth emulating to gain new useful insights and to
have a better focus in hypothesis.
Types of Review of Related Literature
Since literature reviews are pervasive throughout various academic disciplines, various
approaches can be adopted to effectively organize it. This means that the type of review that you
write will depend on your research topic. The University of Southern California (2015) created a
summarized list of the various types of literature review.
1. Self-study reviews
This type of review increases your reader’s confidence in an area that is rarely published.
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2. Context reviews
This type of review places your project in the big picture.
3. Historical Reviews
This type of review includes studies about first time issues, concepts, theories or even
phenomena that rose from literature while examining the changes throughout time. The intention
of this type of literature is to put research in the context of history so that scholars can observe
the changes and developments and how it can lead future research.
4. Theoretical Reviews
This type of review refers to the extent of how much is already explored in a particular
theory. This is also used to check the relationships among the present theories to determine
whether they can contribute to explain an arising question or not.
5. Methodological Reviews
We can simply say that this type of literature review focuses on the researcher’s method
(i.e., survey or experimentation) in conducting the study. Since some researcher’s approach does
not consider ethical issues that may affect the validity and the reliability of the result, hence it is
important to be extra careful before adapting the claims of others. Instead of accepting other
researchers’ assertions right away, it is more important to examine “how” those people came up
with that claim.
6. Integrative Reviews
This type of review combines the existing studies that may have the same hypothesis or
claims. From consolidating them altogether, new knowledge can be generated. A good integrative
review should be clear, accurate, and can be duplicated just like a primary research.
Purpose of Review of Related Literature
When one plans a research, he/she has to build the plan on positions provided by a theory
or observation from experience. One cannot do research without review of related literature since
research is a disciplined, systematic, controlled, empirical and critical study of relationship among
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some defined variables in natural phenomena (Ong Kian Koc, 1999). The following are the
importance of conducting review of related literature as enumerated by Villanueva (2018).
1. Limits the problem area. To apply enough and competent analysis, the problem should be
specific so that the treatment to be used is also specific. Consulting reliable research articles will
help you to improve your research more.
2, Avoid unnecessary repetition. If all the existing research uses all the same methods to carry
out their study, it does not mean that it is the only proper way to tackle the problem you are
focused to. Sometimes, it depends on your situation and variables—which should be considered
first before adapting other researcher’s methods.
3. Search for new approaches. Try to consider other researcher’s point of view before considering
the viewpoint of a single researcher especially if a particular field lacks research or studies.
4. Recommend suitable methods. Try to check on how other researchers utilize different methods
such as their research instruments and designs, sampling techniques, data collection, and data
interpretation. This is helpful so that the appropriate method for your problem can be applied.
5. Sample current opinions. Check and read newspapers, non-technical articles or even
magazines to acquire fresh ideas or problems that other researches have not touched on yet.
Conducting the Review of Related Literature
At this juncture, it is expected and presumed that you have already chosen your topic,
written your research questions, and stated the problem. You cannot proceed to select and review
your literature without them. But if you did, then you can proceed to the next steps listed by
Jerusalem, Del Rosario-Garcia, Palencia, & Calilung (2017).
1. Finding Information
▪ You should know “what” information to look for and “where” to find them.
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▪ The “what” information to look for must be answered by your topic, research objectives,
and statement of the problem.
▪ The obvious places to look for the information you need are the library and the internet.
2, Evaluating the Content
▪ Include only credible scholarly and academic articles or sources by evaluating its quality
and scholarliness. Use the following guidelines to help you in your evaluation presented
in Table 1.
Table 3.1. Guidelines for evaluating the sources.
Authority What are the author’s credentials?
Can you identify their institutional
affiliations?
What is the author’s experience on the
subject?
Currency When was the source published? Last 5
years?
Is it outdated?
Does it meet the time needs for your
topic?
Documentation Does the author cite credible, authoritative
sources?
Is evidence of scholarly research present?
Do they properly cite their sources?
Intended Audience Who is the intended audience? Scholars?
Researchers? General audiences?
Objective/Purpose What is the author’s goal in writing it? To
entertain? To inform? To influence? How
objective is the source?
Relevancy Is it relevant to your topic?
Does it provide any new information about
your topic?
(Eastern University, 2017)
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▪ If you are using internet in searching for related literature, you must be mindful that not all
materials on the internet are credible.
3. Writing the Review
▪ When writing the literature review, you should show relevant issues and findings from your
research articles.
▪ Make your presentation of studies organize and coherent by making a pattern such as
presenting details by chronological, known to unknown, categorical, or general-to-specific.
▪ The models in the research articles and book descriptions of the past research you read
should be followed as very close as possible.
▪ If reading other research or study, do not include all information but instead take down
only those necessary in helping you to rationalize gaps and variables, to define, to
contextualize, to explain the arguments you are claiming in your research paper.
▪ Arguments should be clear, logical, and facts based (Galvan, 2002).
Structure of a Review of Related Literature
In quantitative research, the literature review is organized by sections: introduction, critical
review, and summary (Ong Kian Koc, 1999).
Introduction: It states the purpose or scope of the review. The purpose may be a
preliminary review in order to state a problem or develop a proposal, or it may be an exhaustive
review in order to analyze and critique the research-based knowledge on the topic or to strengthen
the link between the variables included to the study.
Critical review: The essence of the review is the criticism of the literature. The researcher
must arrange the literature review as it related to the selection of the variables and the significance
of the problem. Merely summarizing one study after another does not make sense for an
informative literature review. Studies should be classified, compared, and contrasted in terms of
the way they contribute or fail to contribute to the knowledge on the topic, including criticisms of
designs, sample size used and methods to obtain such knowledge.
Summary: It presents the status of knowledge on the topic and identifies gaps in it. The
gaps in knowledge may be due to methodology difficulties in gathering data, inadequate sampling
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techniques, lack of studies related to the knowledge, or inconclusive statements from the results
of the study. The summary should also provide similarities and differences between the study to
be undertaken by the researcher and those conducted by other researchers.
Utilizing the Internet for Research
With the presence of internet nowadays, you can find useful information using it after
identifying your problem for research.
▪ Google Scholar is a very useful tool, providing a search of scholarly literature across many
disciplines and sources including theses, books, abstracts, and articles.
o ELSEVIER: www.sciencedirect.com. is a Dutch publishing and analytics company
specializing in scientific, technical, and medical content (Physical Sciences and
Engineering, Life Sciences, Social Sciences and Humanities).
o EBSCO: www.sciencedirect.com (Agriculture, Biology, Education, Engineering,
Environmental Studies, Film, Government, History, Kinesiology and Sports,
Literature, Medicine and Health, Music and Performing Arts, Political Science,
Psychology, Sociology
o Springer: www.sciencedirect.com (Agriculture, Biology, Education, Engineering,
Environmental Studies, Film, Government, History, Kinesiology and Sports)
▪ Educational Resources Information Center (ERIC) is an internet-based digital library of
education research and information. It provides access to bibliographic records of journal
and non-journal literature from 1966 to present.
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Example of Review of Related Literature
Below is an excerpt taken from the literature review of Thornbury (2020) entitled “The
Relationship between Instructor Course Participation, Student Participation, and Student
Performance in Online Courses”.
Online learning developed and continues to grow in popularity out of a need to make
learning more accessible to individuals in various phases of life and with varying personal
situations, but with a desire to continue their professional and academic development
(Fedynich, 2014). The National Center for Education Statistics reported that adult learners
(ages 25+) made up over half the part-time undergraduate enrollments at 4-year institutions
in 2016. The traditional classroom is often unappealing or not an option for the adult learner
population due to access limitations or obligations such as employment and family (Fedynich,
2014). The growth in the adult learner population has contributed to the ubiquity of online
instruction at institutions of higher education (Allen & Seaman, 2016). As the popularity and
acceptance of online learning continues to grow, institutions of higher education are looking
for ways to meet the changing needs and expectations of today’s learners (Johnson et al.,
2015). Competition among colleges and universities for students, reduced state funding, and
the need to do more with less are fueling additional changes and innovations in post-
secondary institutions (Macfadyen & Dawson, 2010). (INTRODUCTION)
This chapter includes a review of two foundational frameworks for online learning;
(1) three types of interaction developed by Moore (1989), and (2) the community of inquiry
theoretical framework established by Garrison and Akyol (2013). Greater attention will be
given to the instructor-learner interaction and teaching presence components of these
frameworks as they relate to instructor participation in the learning environment. The current
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This chapter includes a review of two foundational frameworks for online learning; (1) three
types of interaction developed by Moore (1989), and (2) the community of inquiry theoretical
framework established by Garrison and Akyol (2013). Greater attention will be given to the
instructor-learner interaction and teaching presence components of these frameworks as
they relate to instructor participation in the learning environment. The current literature on
participation in the online classroom will also be reviewed. The chapter will close with an
exploration of the current use of LMS data by researchers to answer questions related to the
learning experience – more specifically the instructor’s impact on learning in the virtual
environment.
Teaching and Learning Online (VARIABLES INVOLVED)
Online instruction developed out of the availability of new technologies that could
support remote access and communication and the need to educate a new kind of workforce
– a knowledge-based workforce (Bates, 2015). The format and methods of the early online
classroom would mimic those of the traditional face-to-face classroom; some even requiring
synchronous meetings (Pittman, 2013). In starting the experimental high school, Benton
Harbor, the University of Nebraska indicated that their goal was to work within their existing
instructional resources to provide training that met their standards of quality for graduation
(Moore & Kearsley, 2011). Although the basic instructional premises are the same, the
realities of the technology being used to deliver instruction at a distance necessitated new
theories and frameworks for teaching and learning (Moore, 1989).
Three Types of Interaction (VARIABLES INVOLVED)
As one of the first researchers to focus on interaction in courses taught at a
distance, Moore developed the theory of transactional distance for distance education
(Garrison & Cleveland-Innes, 2005; Moore, 1993). The term “transactional” stems from
Dewey’s (1938) theory of knowledge as transaction, which asserted that knowledge is
influenced by the environment as well as an individual’s perceptions of the experience
(Giossos, Koutsouba, Lionarakis, & Skavantzos, 2009).
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Moore (1993) defined transactional distance as a “pedagogical concept” (p. 22) pertaining to
the altered relationships between instructor and learner when separated by space and time
in a distance learning setting. The original transactional distance education theory had three
variables: dialog, structure, and learner autonomy (Moore, 1993).
Moore suggests that the terms dialog and interaction are synonymous. Later he
further delineated interaction into three types: learner-instructor, learner-content, and learner-
learner (Garrison & Cleveland-Innes, 2005; Moore, 1989). Moore’s (1989) types of
interaction spurred much research into interaction in distance education (Battalio, 2007;
Garrison & Cleveland-Innes, 2005; Kuo, Walker, Belland, & Schroder, 2013; Macfadyen &
Dawson, 2010).
Community of Inquiry
Garrison et al. (2000) elaborated on Moore’s transactional distance theory to
incorporate what they termed, educational presence. They argued that educational presence
“is more than social community and more than the magnitude of interaction among
participants” (Garrison & Cleveland-Innes, 2005, p. 134). Garrison et al. (2000) argued that
an effective educational experience is “embedded in a community of inquiry” (p. 88)
regardless of the mode of delivery, although it calls for special considerations in distance
learning. The community of inquiry theoretical framework has three elements: cognitive
presence, social presence, and teaching presence (Garrison & Akyol, 2013). These three
elements are further delineated into categories for research purposes. Cognitive presence
consists of triggering events, exploration, and integration (Garrison & Akyol, 2013). Social
presence includes emotional expression, open communication, and group cohesion
(Garrison & Akyol, 2013). Lastly, examples of teaching presence are categorized as course
design and organization, facilitation of discourse, or direct instruction (Anderson et al., 2001).
Teaching Presence (VARIABLES INVOLVED)
Anderson et al. (2001) defined teaching presence as “the design, facilitation, and
direction of cognitive and social processes for the purpose of realizing personally meaningful
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and educationally worthwhile outcomes” (p. 5). Specifically, teaching presence is the
selection and organization of course content, presentation of course content, “intellectual and
scholarly leadership” (Anderson et al., 2001), subject matter expertise, directing knowledge,
directing attention, confirming understanding, diagnosing misconceptions, and “encouraging
active discourse and knowledge construction” (Garrison et al., 2000, p. 93). Cognitive
presence and the social presence that supports it, are dependent on teaching presence
(Garrison & Akyol, 2013; Shea & Bidjerano, 2009).
Participation as Visible Evidence of Interaction, Teaching Presence, and Learning
The concepts of participation, interaction, and engagement often overlap and are
operationalized in a variety of ways in the literature (Beer et al., 2010; Henrie, Halverson, &
Graham, 2015; Hrastinski, 2008, 2009; Morris, Finnegan, & Wu, 2005; Ravenna, Foster, &
Bishop, 2012). Morris et al. (2005) defined participation as “student engagement in specific
learning activities” (p. 224) including page views, discussion posts read, and original
discussion postings. Henrie et al. (2015) operationalized engagement as frequency of logins,
number of postings, responses and hits, frequency of posts or views, participation, and time
spent online or a combination therein (p. 43), where participation is an observable indicator
of engagement.
LMS: Changing Learning
Just as online learning has become ubiquitous in higher education, so too has the
use of LMSs (Beer et al., 2010; Joksimović et al., 2015; You, 2016). Today’s LMSs help
universities and colleges meet the demand of a virtual student body (Macfadyen & Dawson,
2010), and provide the technologies necessary to facilitate social and constructivist learning
methodologies in the online classroom (Beer et al., 2010; Macfadyen & Dawson, 2010; Wei,
Peng, & Chou, 2015). However, as a result of the wide spread adoption of LMSs, the
development of learning experiences has become somewhat prescriptive because these
applications force course development into predefined molds around particular technologies
or LMS functionality (Beer et al., 2010). Beer et al. (2010) argued that LMSs are changing
teaching strategies and that the change is likely affecting how students engage in learning.
For example, in online learning environments students are often required to interact with
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Lesson 2: Ethical Standards in Writing
A general principle underlying ethical writing is the notion that the written work of an author
represents an implicit contract between the author and the readers (Jerusalem et al., 2017). This
means that the reader always assumes that the author is the sole originator of the written work
with or without credits. Thus, understanding the basic ethical norms for a scientific conduct is
important before writing a paper, specifically the literature review. There are three important and
relevant ethical issues to students who will be conducting research projects as follows:
1. Plagiarism
According to Neville (2017), plagiarism is a term used to describe a practice that involves
knowingly taking and using another person’s work and claiming it, directly or indirectly, as your
own.
Types of Plagiarism
or LMS functionality (Beer et al., 2010). Beer et al. (2010) argued that LMSs are changing
teaching strategies and that the change is likely affecting how students engage in learning.
For example, in online learning environments students are often required to interact with
content and other learners without any prompting from an instructor, a process which can
affect motivation and engagement.
Conclusions and Gaps in Current Research (SUMMARY)
Technology has evolved since the initial development of the theories and
frameworks of Moore (1989, 1993) and Garrison et al. (2000). However, the core principles
of their ideas, and the findings of research they have spurred to this day, persist. Current
research using available LMS activity log data has continued to show positive correlations
between student participation and academic achievement (You, 2016).
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a. Blatant Plagiarism. This is also known as intentional plagiarism. It happens when you
claim to be the sole author of a work written completely by someone else (Jackson State
Community College, n.d.). This includes the act of letting someone else write part of a
paper for you, making up bogus citations, turning in work done as a group that you
participated in as yours alone.
b. Technical Plagiarism. This is also known as unintentional plagiarism. It occurs when the
writer is not trying to cheat but fails to abide with the accepted methods of using and
revealing sources.
If you commit a blatant plagiarism, it might result to your failure in course or worst, you
might get dismissed from the school. Committing technical plagiarism might not drop you out of
school but it will your teacher may give you low grades on submitted paper.
Ideas of other people can be use as long as you properly cite them and do not claim
ownership on other researchers’ ideas. As a part of the academic field, you are expected to read,
to properly analyze and to respond to all the scholarly papers and ideas when writing your paper.
In short, you should cite properly to avoid accusations of plagiarism and it is your way of showing
respect to others works.
2. Language Use
Aside from plagiarism, another ethical consideration in writing is the use of language. A
writer must avoid racially charged, sexist, offensive language and tendencies. In other words, it
is an ethical responsibility of the writer to be sensitive to the sensibilities of his audience. Here are
some guidelines for language use in writing:
a. Avoid hasty generalizations about an ethic minority, any other category of people including
people’s sex and gender.
b. Use accurate and politically correct terminology when you are discussing about racial
groups.
c. Write first the subject then write the description after when discussing about people with
disabilities. Example: the man who is blind rather than the blind man.
3. Fraud
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Aside from plagiarism, another temptation that is ever present among students who are
conducting research is to fabricate data and results just to get over the coursework. This is done
for a variety of reasons, but foremost is due to the workload involved in gathering or collecting
data. Hence a researcher must observe the following to avoid fraud.
a. Honesty. Do not try to fabricate, misinterpret or falsify data. Do not lie to your colleagues,
to your research sponsor and to the public. Report all your results and data, methods and
procedure with honesty.
b. Objectivity. When creating your experimental design, conducting data analysis, or
interpreting data where being objective is required, avoid biases. Divulge personal interest
or financial interest that can affect your research.
c. Integrity. Show consistency and sincerity in action and thoughts because keeping
promises and agreements is not enough.
d. Carefulness. Be careful and critical when inspecting your work and your colleague`s
works. Keep track of your progress in research like in data collection, data analysis,
research design and transactions with journal agencies in a record book to avoid careless
mistakes and negligence.
LESSON 3: Citation and Referencing
It was emphasized in the previous lesson to cite your references to avoid committing
plagiarism. Several written works have various styles in doing this. In this course, however, the
guidelines for citation and preparing reference list should be consistent with the principles in the
Publication Manual of the American Psychological Association (APA) 7th edition.
You can use the following format summarized by Saint Mary’s College of California Library
(2020):
Table 3.2. APA guide for referencing
Sources In-text Citation Reference List
Book with one author (Gonzales, 2019) Author(s) last name, first and middle
initial. (Year of publication), Title of
the book (in italics). Publisher name.
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Book with two authors (Gonzales & Jones, 2019)
e.g. Gonzales, M. (2019). The
gendered Society. Oxford
University Press.
Book with 3 or more
authors
(Gonzales et al., 2019)
Journal Articles (Klimonske & Palmer,
1993)
Authors Last name. (Initial Year of
Publication). Article Title. Journal
Title in italics. Volume (issue), page
numbers. Digital object identifier
(doi)
e.g Klimonske, R., & Palmer, S.
(1993). The ADA and the hiring
process in organizations.
Consulting Psychology Journal:
Practice and Research, 45(2), 10-
36. https://doi.org/10.1037/1061-
4087.45.2.10
Websites (Sparks, 2018) Author. (Date). Title in italics.
Website. URL
e.g. Sparks, Dana. (2018,
September 12). Mayo mindfulness:
Practicing mindfulness exercises.
Mayo Clinic.
https://newsnetwork.mayoclinic.org.
Newspaper Article Online (Cieply, 2013) Article Author Last Name, First
Initial. (Year, Month, Date of
Publication). Article Title.
Newspaper in italics.
e.g. Cieply, M. (2013, November
11). Gun Violence in American
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movies is rising, study finds. New
York Times.
The list of references is not limited with the four sources mentioned in Table 3.2. For more
quick reference formatting guide, you can visit the APA website.
As a meticulous researcher, accurate citation is a part of the process. You should also
make sure that the content from the cited sources is accurately reported (Day & Gastel, 2016).
Aside from keeping you from committing plagiarism, careful citation helps keep you from
alienating those evaluating your paper.
Preparing the Reference List
According to Walden University (2020), a reference list is the list of publication information
for the sources that were cited in the literature. It intends to give the readers the information they
need in case that they wanted to find those sources. Some publications refer it as bibliography.
Below are some guidelines provided by Bordonaro (2010) in preparing the reference list.
▪ If you write an uncited resource or material, it shouldn`t reflect in your list of references.
▪ List references alphabetically by author’s surname.
▪ When writing your references, make sure that you will use a hanging indent for the second
line and the next line should be aligned on the hanging indented second line.
Example:
Gambles. I. (2009). Making the business case: Proposals that succeed for projects
that work. Farnham, England: Ashgate.
▪ Double-check the by cross-checking the reference list against the citations in the body of
the review.
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Assessment Tasks
TASK NO. 1 (WRITTEN WORK)
Instructions: Encircle the letter of the correct answer.
1. What is a good review of related literature?
a. It points out where prior studies agree, where they disagree, and
where major question remains.
b. It collects what is known up to a point in time.
c. It hardly indicates the direction for future research.
2. Supposed a researcher wanted to examine the evolution of computers
throughout the time. What type of review should he conduct?
a. Context reviews
b. Theoretical reviews
c. Historical reviews
3. The researcher’s literature review mentioned the adverse effect of taking
multivitamins as opposed to the belief of majority that multivitamins are
good for the health. What purpose of review of related literature has been
served?
a. Unnecessary repetition was avoided.
b. New approaches were discovered.
c. The problem area was limited.
4. What guideline should you look for if you want to evaluate the timeliness
of a journal article you found on the internet?
a. Currency
b. Intended audience
c. Purpose
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5. What is the correct order of the structure of a literature review?
a. Critical review ⇾ Introduction ⇾ Summary
b. Introduction ⇾ Critical Review ⇾ Summary
c. Summary ⇾ Introduction ⇾ Critical Review
6. What tool provides a search of scholarly literature across many disciplines and sources
including theses, books, abstracts, and articles?
a. Google Scholar
b. Elsevier
c. Educational Resources Information Center
7. What is a practice that involves claiming an idea/work of someone else?
a. Fraud
b. Ethical Standards in Writing
c. Plagiarism
8. What do you call an act that fabricates data and results just to get over the coursework?
a. Plagiarism
b. Fraud
c. Objectivity
9. What referencing style is required to be used in your research?
a. MLA
b. APA
c. Chicago
10. If the researcher avoided biased in experimental design, what attitude was exhibited?
a. Honesty
b. Objectivity
c. Carefulness
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TASK NO. 2 (WRITTEN WORK)
Instructions: Use the APA 7th edition style to create a reference list for the following
information. Write your answers on the box provided.
1. Book Title: Philippine History and Government Through the Years
Authors: Francisco M. Zulueta and Abriel M. Nebres
Published by National Bookstore in Mandaluyong City
Date: June 2002
2. Journal Title: Reclaiming Instructional Design
Journal Publication: Educational Technology
Volume: 36
Issue: 5
Pages: 5-7
Date: August 5, 1996
Author: Mary Merrill
3. Author: National Institute of Mental Health
Retrieval Date: May 2015
Title: Anxiety Disorders
Website URL: http://www.nimh.nih.gov/health/topics/anxiety-disorders/index.s
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TASK NO. 3
Instructions: Write the review of related literature of the topic assigned to you. Observe
proper in-text citation.
REVIEW OF RELATED LITERATURE
TASK NO. 3 (CONTINUATION)
Instructions: Write the review of related literature of the topic assigned to you. Observe
proper citation.
REVIEW OF RELATED LITERATURE
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TASK NO. 3 (CONTINUATION)
Instructions: Write the review of related literature of the topic assigned to you. Observe
proper citation.
REVIEW OF RELATED LITERATURE
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TASK NO. 3 (CONTINUATION)
Instructions: Write the review of related literature of the topic assigned to you. Observe
proper citation.
REVIEW OF RELATED LITERATURE
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TASK NO. 4
Instructions: List the references you used in writing the review of related literature. Observe
proper guidelines.
REFERENCE LIST
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Summary
▪ A review of related literature is a place to make connections between what you are
investigating and what has already been investigated in your subject area.
▪ A good review points out areas where prior studies agree, where they disagree, and where
major question remain.
▪ There are six types of literature review: (1) Self-study reviews; (2) Context reviews; (3)
Historical reviews; (4) Theoretical reviews; (5) Methodological reviews; (6) Integrative reviews.
▪ To evaluate the content of a source, assess its authority, currency, documentation, intended
audience, objective, and relevancy.
▪ The review of related literature of a quantitative research is organized by sections—the
introduction, critical review, and summary.
▪ Google Scholar is a useful too to find relevant information about a research problem.
▪ Plagiarism is a term used to describe a practice that involves knowingly taking and using
another person’s work and claiming it.
▪ The two types of plagiarism are blatant and technical plagiarism.
▪ Blatant plagiarism is when someone claims to be the sole author of a work written by someone
else.
▪ Technical plagiarism happens when the writer failed to abide with the accepted methods of
writing.
▪ The guidelines for citation and preparing reference list should be consistent with the principles
in the Publication Manual of the American Psychological Association (APA) 7th edition.
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References
Bordonaro, K. (2010). How to Write a Literature Review: An Overview for International Students.
[PowerPoint Slide]. Brock University.
Day, R. & Gastel, B. (2016). How to Write and Publish a Scientific Paper. (8th ed.). California:
Greenwood.
Galvan, J. (2002). Writing Literature Review A Guide for Students of the Social and Behavioral
Sciences. (6th ed.). New York: Pyrczak Publishing.
Jackson State Community College. Intentional Plagiarism. Retrieved from:
https://www.jscc.edu/academics/programs/writing-center/plagiarism/intentional-
plagiarism.html.
Jerusalem, V., Del Rosario-Garcia M., Delos Reyes, A., Palencia, M., & Calilung, R. (2017).
Practical Research 2: Exploring Quantitative Research. (1st edition). Philippine Copyright.
Ong Kian Koc, B, (1999). EDSC 341 Research Seminar in Science Education. UP Open
University: Office of Academic Support and Instructional Services.
Ridley, D. (2008). The literature review: A step-by-step guide for students. London: Sage
Publications, p. 2.
Saint Mary’s College of California Library. (2020). APA Style 7th edition.
Thornbury, E. (2020). The Relationship Between Instructor Course Participation, Student
Participation, and Student Performance in Online Courses. [Doctoral dissertation,
University of Tennessee at Chattanooga]
University of Southern California. (2015, September 7). Organizing Your Social Sciences
Research Paper. Retrieved from USC Libraries:
https://libguides.usc.edu/writingguide/literaturereview
Villanueva, R. (2018). Session 7: What is Literature Review. [PowerPoint slides]. University of the
Philippines Los Baños.
Walden University. (2020). Q. What is a reference list? Retrieved from:
https://academicanswers.waldenu.edu/faq/72739
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MODULE 4
METHODOLOGY
Introduction
In the first section of your research paper, a little information about the methods to
be used should be stated. Reasons for choosing that specific method over others is discussed in
that chapter as well. This time, in the Methodology, all the procedures that will be used by the
researcher must be stated in complete details. This is the part where the researcher narrates the
necessary steps that he/she took to gather the data that need interpretation and analysis.
Research methodology, as defined by University of the Witwatersrand (2020), is the
specific procedures or techniques used to identify, select, process, and analyze information about
a topic. This section allows the reader to critically evaluate a study’s overall validity and reliability.
The main purpose of the methodology is to describe the experimental design so that another
researcher can repeat it if deemed necessary (Day & Gastel, 2016). The way these methods are
presented should be in chronological order.
In this module, we will discuss the methodology including the hypothesis, sampling
procedures, data collection, and data analysis.
Learning Outcomes
At the end of the lesson, the students shall be able to:
1. formulate research hypothesis;
2. plan data collection procedure;
3. construct an instrument and establish its validity and reliability;
4. describe sampling procedure and sample;
5. describe the ethical considerations in conducting methodology;
6. plan data analysis using statistics and hypothesis testing; and
7. present written research methodology
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Lesson 1. Hypothesis
The word hypothesis came from two Greek roots which mean that it is some sort of ‘sub-
statements’. This is often referred to as an ‘explanation’ of the facts someone has observed
(Singh, 2006). Simply put it, someone has a ‘theory’ about a particular thing. The word hypothesis
consists of two words:
Hypo + thesis = Hypothesis
‘Hypo’ means tentative of subject to the verification while ‘thesis’ means statement about
the solution of a problem (Singh, 2006).
Basically, a hypothesis is “an educated and testable guess about the answer to your
research question.” Making a prediction is one key feature of hypothesis formulation (DeMatteo
et.al, 2005). These predictions are then tested by gathering and analyzing data, to determine
whether they can be supported or rejected. In their simplest form, hypotheses are typically
phrased as “if-then” statements. For example, a researcher may hypothesize that “if someone
studied for four hours everyday, then his exam scores will be high.” This hypothesis makes a
prediction about the effects of studying on the exam scores, and this prediction can either be true
or false after the data gathered has been analyzed.
Since hypotheses propose a tentative solution to a problem, supposed one of your good
friends did not show up on your birthday celebration. A possible problem will be “What are the
factors that contribute to the absence of your friend on your birthday celebration?”
To solve this problem, you enumerated the possible explanations for the problem:
▪ Your friend is sick
▪ An emergency came up in the family
▪ There was an accident along the way
▪ Your friend decided to ditch the celebration
▪ Your friend was not able to buy you a gift
▪ Others
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Some of these explanations can be outright rejected. The guess that your friend ditched the
celebration can be rejected knowing that she is a good friend. Finding out which among the
guesses are false can help you narrow down the hypothesis.
Problem solving in research requires hypothesis to direct us on how to go about solving a
problem (Ong Kian Koc, 1999). It should be testable, brief, consistent and clear.
Kinds and Forms of Hypothesis
Hypotheses can be classified into several forms. These forms are determined by functions
that is why your hypothesis must be the best guess with respect to the available evidences. In
other cases, the type of statistical treatment generates a need for a particular form of hypothesis
(Singh, 2006). There are three forms of hypotheses that we will discuss in this lesson as follows:
1. Declarative Statement. A hypothesis can be written as a declarative that provides
relationship or difference between variables. The assumption of having a difference between
variables imply that the researcher had enough evidence to claim it.
Example: There is a significant effect of classroom size on the students’ behavior. (This
is merely a declaration of the independent variable effect on the dependent variable.)
2. Directional Hypothesis. A hypothesis is directional if it suggests an expected direction in
the relationship or difference between variables.
Example: Bigger classroom size results to a manageable set of students whereas
smaller classroom size results to loud students.
3. Non-directional Hypothesis. A null hypothesis is a statement of no difference or an assertion
of no relationship. This is a testable form of hypothesis called statistical hypothesis.
Example: There is no significant effect of classroom size on the students’ behavior.
Relationship between Hypotheses and Research Design
Hypothesis can be stated in different forms depending on the what type of research you
are conducting. If your study is about relationship between variables, then your hypothesis should
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be stated as a relationship between that two variables. In a correlational research for example,
you are trying to formulate a hypothesis if there is a relationship between decision-making ability
of an individual and alcohol intoxication. The case is different if you are using an experimental
design. The hypothesis should be if the intoxication of alcohol is the cause of poor decision-
making ability of an individual. We can say that the hypothesis testing depends on what kind or
type of research design you are going to use (De Matteo et al., 2005).
Lesson 2. Data Collection
Data
One thing that we should remember as a researcher is that we should not treat data as an
absolute reality but instead a manifestation of that reality only. To further understand this
statement, we can see what other people are doing and the behaviors they are showing, the
things that they are creating, and how this action affects their environment or other people, but
we will never know the actual people “inside” those individuals. Using the data, the researcher
collected, the researcher can seek the underlying truth on these events.
Research instruments are administered on the sample subjects for collecting evidences
or data. These tools must provide objective data for interpretation of results achieved in the study.
The data collection is the accumulation of specific evidence that will enable the researcher to
properly analyze the results of all activities by his research design and procedures. The main
purpose of data collection is to verify the research hypotheses.
When you undertake a research study, you need to collect the required information.
However, sometimes the information requires is already available and only need to be extracted.
Based upon these broad approaches to information gathering, data can be categorized as:
primary and secondary data.
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Figure 4.6 Methods of Data Collection
The information collected from determining the community’s health needs, assessing a
certain social program, determining employees job satisfaction of a certain organization, and
determining the service quality showed by the worker are examples of data or information
collected from primary sources. Examples of secondary sources are the following: using data
census to acquire data on the population`s age-sex structure, using the records of a hospital to
find if there is a pattern on the mortality and morbidity of a certain community, and obtaining data
from sources such as research articles, research/academic journals, magazines, and books.
Measurement of Data
As you go along solving your research problem, you will probably discover that you must
pin down your observations by measuring them in some way. In some cases, you will be able to
use one or more existing instruments—perhaps a published personality test to measure a
person’s tendency to be either shy or outgoing. In other situations, you may need to develop your
own measurement—perhaps a pencil-and-paper test to measure what students have learned
from a particular instructional unit.
Measurement instruments provide a basis on which the entire research effort rests. It is
limiting the data of any phenomenon so that those data may be interpreted and compared to a
particular standard. The variables that were discussed in the first module can undergo through
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the process of quantification to yield data and scores. In this case, the concept of measurement
is applied.
Measurement Scales / Types of Data
When we consider the statistical interpretation of data in later procedures, you may want
to refer to Table 4.1 in determining whether the type of measurement instrument you have used
will support the statistical operation you are contemplating.
Table 4.1 A summary of measurement scales
Measurement Scale Characteristics of the Scale Statistical Possibilities of the
Scale
Nominal Scale “A scale that “measures” only
in terms of names or
designations of discrete units
or categories”
“Enables one to determine the
mode, percentage values, or
chi-square”
Ordinal Scale “A scale that measures in
terms of such values as
“more” or “less, “larger” or
“smaller”, but without
specifying the size of the
intervals”
“Enables one also to
determine the median,
percentile rank, and rank
correlation”
Interval Scale “A scale that measures in
terms of equal intervals or
degrees of difference, but with
an arbitrarily established zero
point that does not represent
“nothing” of something”
“Enables one also to
determine the mean, standard
deviation, and product
moment correlation; allows
one to conduct most
inferential statistical analyses”
Ratio Scale “A scale that measures in
terms of equal intervals and
an absolute zero point”
“Enables one also to
determine the geometric
mean and the percentage
variation; allows one to
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conduct virtually any
inferential statistical analysis”
Lesson 3. Instrument Development
Research Instrument
Research instruments are the tools you use to collect data on the topic of interest to
transform it into useful information. There are several possible approaches to carry out your
research. Based on the research question, the researcher decides which type of instrument he
can use. These include survey, case study and experiment. The survey is concerned with
gathering data from a large number of people called respondents. The data gathered from these
respondents usually focus on the views, ideas, and attitudes of those respondents in relation to
the research topic. The case study draws on a specific environment such as school, and explores
the research topic in relation to that school. This may involve obtaining the views of the teachers,
children and parents. Experimental research is concerned with establishing the effect of some
action upon two groups or situations. All of these approaches to research draw upon a variety of
instruments. The range of research instruments used for each of these strategies are as follows”
(Hinds, 2001).
1. Questionnaires
The main instrument to collect data through survey is questionnaires. It is a set of
standard questions, often called items, which follow a fixed scheme in order to collect individual
data about one or more specific topics (Lavraska, 2008). Questionnaires seem so simple, but
one false step can lead to uninterpretable data or an abysmally low return rate (Leedy &
Ormrod, 2013).
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Type of Questions
The questions in a questionnaire will either be open or closed questions.
a. In an open question types of questionnaire, the respondents are allowed to comment
his or her suggestions or ideas about the question asked (See Figure 4.1).
b. In a closed question type of questionnaire, the respondents are required to answer the
question by picking one or more answer from the set of pre-defined choices (See
Figure 4.2)
When to use a questionnaire?
▪ Information is sought from a large number over a relatively large geographical
area.
▪ The information being sought is not complex.
▪ You are seeking information about facts, either in the present or in the recent
past.
▪ You want to study particular groups, or people in a particular problem area
because you want to generalize about them, make comparisons with other
groups or use their response and comparisons for development.
▪ You are certain that a questionnaire will produce the type of information you
need.
▪ You are certain that barriers such as language and literacy do not apply to your
target group.
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Figure 4. 1 Example of Open Question
Figure 4.2 Example of Close Question
Constructing Questionnaires
Leedy & Ormrod (2010) prepared a list of guidelines for developing questionnaires as follows:
1. “Keep it short.” Your questionnaire should be brief as possible. As a general rule of
thumb, a questionnaire should take no more than about twenty minutes to complete
(Wilkinson & Birmingham, 2003)
2. “Keep the respondent’s task simple and concrete.” Remember that you are the one
asking for people’s time. They are most likely to respond to a questionnaire if they
perceived it to be quick and easy to complete.
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3. “Provide straightforward, specific instructions.” Communicate exactly how you want the
respondents to respond. Do not assume that they are already familiar with Likert scales.
4. “Use simple, clear, unambiguous language.” When writing questions for your survey,
be exact on what you really want to find out. Avoid as much as possible obscure words or
technical jargons since some of your respondents may not understand the meaning of
your choice of words.
5. “Give a rationale for any items whose purpose may be unclear.” Give them a reason to
want to do the favor.
6. “Check for unwarranted assumptions implicit in your question.” Consider a very simple
question: “How many cigarettes do you smoke each day?” It seems to be a clear and
unambiguous question, especially if it is accompanied with certain choices so that all the
respondents have to do is to check one of them:
How many cigarettes do you smoke each day? Check one of the following:
__More than 25 __25-16 __15-11 __10-6 __5-1 __none
One underlying assumption in that question is that a person is likely to be
a smoker rather than nonsmoker, which is not necessarily the case. A second
assumption is that a person smokes the same number of cigarettes each day, but
for many smokers this assumption is not applicable. When the pressure is on for
some people, they may be chain smokers. But on weekends and holidays, they
may relax and smoke only one or two cigarettes a day or go without smoking at
all. This may confuse the respondents with that kind of smoking habits if they are
to answer the question using the scale previously mentioned. Had the author of
the question considered the assumptions on which the question was predicated,
he or she might first have questions such as these:
Do you smoke cigarettes?
___Yes
___No (If you mark “no”, skip the next two questions).
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Are your daily smoking habits reasonably consistent; that is, do you smoke
about the same number of cigarettes each day?
___Yes
___No (If you mark “no”, skip the next question)
7. “Word your question in ways that do not give clues about preferred or more desirable
responses.” This also means that you should not ask leading questions at all. Take
another question: “What strategies have you used to try to quit smoking?” By implying that
the respondent has, in fact, tried to quit, it may lead him or her to describe strategies that
have never been seriously tried at all.
8. “Determine in advance how you will code the responses.” Plan ahead on how you are
going to record the participant’s responses as a numerical data in order for you treat it with
statistical analysis. You can do this before and while writing your questionnaire.
9. “Check for consistency.” Some questions in your questionnaire form may touch
controversial and sensitive issues, and because of that, the respondent may give answers
that are acceptable and favorable in society rather than what the respondents really think
or perceive. To check for their consistency on their answer, try to ask the same question
in other part of the questionnaire but use different words or wording style.
10. “Conduct one or more pilot tests to determine the validity of your questionnaires.”
Before using newly constructed questionnaires, professional and experienced
researchers conduct a series of test runs to check the validity and reliability of the
questionnaires. This is done because researchers want the questions asked to be clear
and will give a valid and desired information.
11. “Scrutinize the almost-final product one more time to make sure it addresses your
needs.” Check the quality of your questionnaire by checking item by item again and again
to obtain results that are precise, objective, relevant, and probability of favorable reception
and return.
12. “Make the questionnaire attractive and professional looking.” Your final instrument
should have clean lines, crystal-clear printing (and clearly no typographical errors). It
should not be colorful. It should ultimately communicate that the author of it is a careful,
well-organized professional.
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2. Interviews
According to Kumar (2011), interviewing is a commonly used method of collecting
information from people. Interviews are not an easy option. They are often likened to a
conversation between two people, though it requires orchestrating, directing, and controlling to
varying degrees (Wilkinson & Birmingham, 2003).
Interviews are classified into different categories according to the degree of flexibility as shown in
Figure 4.3.
Figure 4.3 Types of Interview (Kumar, 2011)
▪ “Unstructured Interview is a very flexible approach. The areas of interest are established
by the researcher but the discussion should be guided by the interviewee. The researcher
has the utmost freedom in terms of content and structure. However, unstructured
interviews can be difficult to plan (in terms of the time to be given to the event). They are
difficult to steer if the discussion gets away from the key subject matter, and they can
prove extremely difficult to analyze.”
When to use interviews?
▪ “In-depth information is required”
▪ “Where the subject matter is potentially sensitive”
▪ “The issues under examination would benefit from development or
clarification”
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▪ “Structured Interview is where the researcher asks a predetermined set of questions, using
the same wording and order of questions as specified in the interview schedule. Some
see the structured interview as no more than a questionnaire that is competed face-to-
face. One of the main advantages of this interview is that it provides uniform information,
which assures the comparability of data. This also requires fewer interviewing skills than
does unstructured interviewing.”
3. Focus Groups
“Focus groups are formally organized, structured groups of individuals brought together
to discuss series of topics during a specific period of time. They are typically composed of several
participants (usually 6 to 10 individuals) and a trained moderator. Focus groups are also typically
made up of individuals who share a particular characteristics, demographic, or interest that is
relevant to the topic being studied. Overall, focus groups should attempt to cover no more than
two to three major topics and should last no more than 1 ½ to 2 hours.”
Regarding Scales of Measurement
There are other types of research tools which are used to collect the data. For example, the
observation technique is most frequently used to collect the data which yields the data at nominal
scale and also at interval scale. Table 4.2 provides a classification of instruments to use with in
relation to the scale of measurement.
When to use focus groups?
▪ “To gain information relating to how people think.”
▪ “To explain perceptions of an event, idea, or experience.”
▪ “When there is a desire for more understanding of the human
experience.”
▪ “When seeking the perspective of the client.”
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Table 4.2. A Classification of Scales of Measurement with Reference to the Traits
Trait Tool Scale of Measurement
1. Intelligence Psychological Tests Interval
2. Achievement Educational Tests Interval
3. Aptitude Psychological Tests Interval
4. Attitude Scales Ordinal
5. Interest Inventories Interval
6. Personality Inventories Interval
7. Adjustment Inventories Interval
8. Opinions or feelings Questionnaire Nominal
Lesson 4. Establishing Validity and Reliability
Regardless of the type of scale a measurement instrument involves, the instrument must
have both validity and reliability for its purpose. In your research report, you should provide
evidence that the instruments you use have a reasonable degree of validity and reliability.
However, validity and reliability take different forms, depending on the nature of the research
problem, the methodology being used to address the problem, and the nature of the data that are
collected.
The Concept of Validity
To examine the concept of validity, let us take a very simple example. Supposed that you
have designed a study to determine the health needs of a community. You decided to use
interview schedule for it. Most of the questions you constructed pertains to the attitude of the
community towards the health services being provided to them. However, note that your aim was
to determine the health needs of that community. Thus, the instrument you used is not measuring
what it was designed to measure.
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Certainly, no one would question the premise that a thermometer measures temperature,
but to what extent does an intelligence test actually measures a person’s intelligence? How
accurately do people’s annual incomes reflect their social class? Therefore, when we say validity,
it is the extent to which the instrument measures what it intends to measure. Conceptually, validity
seeks to answer the following question: “Does the instrument or measurement approach measure
what it is supposed to measure? Validity is determined by considering the relationship between
the test and some external, independent event.” The most common methods for demonstrating
validity are referred as follows:
1. “Face Validity. It is the extent to which, on the surface, an instrument looks like it is measuring
a particular characteristic. Face validity is often useful for ensuring the cooperation of people who
are participating in a research study. But because it relies entirely on subjective judgment, it is
not a dependable indicator that an instrument is truly measuring what the researcher wants to
measure. “
2. Content Validity. “It is the extent to which a measurement instrument is a representative sample
of the content being measured. The researcher defines the construct and the attempts to develop
item content that will accurately capture it. For example, an instrument designed to measure
anxiety should contain item content that reflects the construct of an anxiety.”
3. Criterion Validity, “It is determined by the relationship between the measure and performance
on an outside criterion or measure. The outside criterion must be related to the construct of
interest, and it can be measured at the same time the measure is given. If the measure is
compared to an outside criterion that is measured at the same time, it is then referred to as
concurrent validity. If the measure is compared to an outside criterion that will be measured in the
future, it is then referred to as predictive validity. For example, a personality designed to assess
a person’s shyness or outgoingness has criterion validity if its scores have a relationship with
other measures of a person’s general sociability.”
4. Construct Validity. “It is the extent to which an instrument measures a characteristic that cannot
be directly observed but is assumed to exist based on patterns in people’s behavior. Motivation,
creativity, racial prejudice, love—all of these are constructs, in that none of them can be directly
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observed and measured. When researchers ask questions, they should obtain some kind of
evidence that their approach does, in fact, measure the construct in question.”
The Concept of Reliability
We use the word ‘reliable’ very often in our lives. When we say that a person is reliable,
we infer that he is dependable, consistent, predictable, stable and honest. The concept of
reliability in relation to a research instrument has a similar meaning. If a research tool is said to
be consistent and stable, hence predictable and accurate, it is said to be reliable. Imagine that
you are concerned about your growing waistline and decide to go on a diet. Everyday, you put a
tape measure around your waist and pull the two ends together snugly to get a measurement.
But just how tight is “snug”? Quite possibly, the level of snugness might differ from one day to the
next. In fact, you might even measure your waist with different level of snugness from one minute
to the next. To the extent that you are not measuring your waist in a consistent fashion. Despite
the fact that you use the same tape everyday, you have a problem with reliability,
Therefore, reliability refers to the “consistency or dependability of a measurement
technique, and it is concerned with the consistency or stability of the score obtained from a
measure or assessment over time and across settings or conditions. If the measurement is
reliable, then there is less chance that the obtained score is due to random factors and
measurement error.”
Let us consider an example. In psychology, personality is a construct that is thought to be
relatively stable. If we were to assess a person’s personality traits using an objective,
standardized instrument, we would not expect the results to change significantly if we
administered the same instrument a week later. If the results did vary considerably, we might
wonder whether the instrument that we used was reliable. Reliability can be determined through
a variety of methods.
1. Interrater reliability. “It is the extent to which two or more individuals evaluating the same
product or performance give identical judgment. For example, assume you have two evaluators
assessing the acting-out behavior of a child. You measured “acting-out behavior” as the number
of times that the child refuses to do his or her schoolwork in class. The extent to which the
evaluators agree on whether or when the behavior occurs reflect this type of reliability.”
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2. Test-retest reliability. “This is a commonly used method for establishing the reliability of a
research tool. This is where an instrument is administered once, and then again, under the same
or similar conditions. For example, administering the same measure of academic achievement on
two separate occasions 6 months apart is an example of this type of reliability. The main
disadvantage of this method is that a respondent may recall the responses that s/he gave the first
round.”
3. Parallel form of same test. “It is the extent to which two different versions of the same instrument
that were administered at different times yield similar results. The two forms must cover identical
content and have a similar difficulty level. The two test scores are then correlated.”
4. Internal consistency reliability. “It is the extent to which all of the items within a single instrument
yield similar result. Even if you randomly select a few items or questions out of the total pool to
test the reliability of an instrument, each segment of questions thus constructed will reflect
reliability more or less to the same extent. It is based upon the logic that if each item or question
is an indicator of some aspect or phenomenon, each segment constructed will still reflect different
aspects of the phenomenon even though it is based upon fewer items. It is often measured with
Cronbach’s Alpha.
Validity and Reliability
Reliability is directly related to the validity of the measure. There are several important
principles. First, a test can be considered reliable, but not valid. Consider the National
Achievement Test (NAT) used as a predictor of success in college. It is a reliable test (high scores
relate to high GWA), though only a moderately valid indicator of success (due to lack of structured
environment—class attendance, parent-regulated study, and sleeping habits—each holistically
related to success).
Second, validity is more important than reliability. Using the above example, college
admissions may consider the NAT a reliable test, but not necessarily a valid measure of other
quantities colleges seek, such as leadership capability, altruism, and civic involvement. The
combination of these aspects, alongside the National Achievement Test (NAT), is a more valid
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measure of the applicant’s potential for graduation, later social involvement, and generosity
(alumni giving) toward the alma mater.
Finally, the most useful instrument is both valid and reliable. Proponents of the National
Achievement Test argue that it is both. It is a moderately reliable predictor of future success and
a moderately valid measure of a student’s knowledge in Mathematics, Critical Reading, and
Writing.
Lesson 5. Description of a Sample
The Concept of Sampling
Let us take a very simple example to explain the concept of sampling. Suppose you want
to estimate the average income of families living in city. There are two ways of doing this. The
first method is to contact all the families in your target city, find out their incomes, add them up,
and then divide this by the number of families. The second method is to select a few families from
the city, ask them their ages, add them up and then divide by the number of families. From this,
you can make an estimate of the average of the income of the families living in a city. Imagine the
amount of effort and resources required if you visit each and everyone’s household when you can
select a few and generalize from it.
Sampling, therefore, is the “process of obtaining a few (aka sample) from a bigger group
(aka population) to become the basis for estimating or predicting the prevalence of an unknown
piece of information regarding the bigger group.”
Sample
“A sample is a selection which is taken from a group; it is usually considered to be
representative of that group. As a result, the findings from the sample can be generalized
back to the group.”
Population
“A population is a group who shares the same characteristics. For example, a population
could be members of a club, nurses, students or children.”
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Randomization
Randomization is a “method of sampling in which each of the population has the equal
chance or probability of selection of the individuals for constituting a sample. The choice of one
individual is in no way tied with other. Randomization can be used when selecting the participants
for the study and for assigning those participants to various conditions within the study. These
two approaches are referred to as random selection and random assignment.”
a. Random Selection. “It is a process of selecting participants at random from a defined
population of interest. Random selection helps control for extraneous influences because
it minimized the impact of selection biases. In other words, using random selection would
ensure that the sample was representative of the population as a whole.”
Figure 4.4. A graphic example of random selection
b. Random assignment. “This is concerned with how participants are assigned to
experimental and control conditions within the research study. The basic principle of
random assignment is that all participants have an equal likelihood of being assigned to
any of the experimental or control groups.”
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Methods of Randomization
The following are main methods of randomization:
a. Lottery method of randomization. This is a simple technique wherein the researcher can
pick from the pool of population.
b. Tossing a coin. This is to randomly assign a decision that traditionally involves throwing
the coin in the air and see which side of the coin landed.
c. Throwing a dice. This involves throwing the dice in the air to see which side of it lands.
d. Blind folded method. This procedure requires that only the researcher be kept “blind” or
“naïve” regarding which treatment or control conditions that participants are in.
e. Double-blind technique. The most powerful method for controlling researcher
expectancy and related bias, this procedure requires that neither the participants nor the
researcher know which experimental or control condition research participants are
assigned to.
Sampling Design
Different sampling designs may be more or less appropriate in different situations. Figure 4.5
shows the type of sampling designs
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Figure 4.5. Types of Sampling Design
A. Probability Sampling
“In probability sampling, every part of the population has the potential to be represented
in the sample. The sample is chosen from the overall population by random selection—that is, it
is chosen in such a way that each member of the population has an equal chance of being
selected. When such a random sample is selected, the researcher can assume that the
characteristics of the sample approximate the characteristics of the total population.”
Random sampling can be selected using two different systems—sampling without
replacement and sampling with replacement. In sampling without replacement, each sample unit
of the population has only one chance to be selected in the sample. For example, the researcher
draws a simple random sample such that no unit can occur one or more times in the sample
(Lavraskas, 2008). If the unit can be chosen again at another draw, then it is sampling with
replacement.
1. Simple Random Sampling, “Simple random sampling is exactly the process just
described. Every member of the population has an equal chance of being selected. Such
approach is easy when the population is small and all of its members are known. To illustrate,
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supposed you want to sample a class. There are 80 students in the class, and so the first step is
to identify each student by a number from 1-80. Suppose you decide to select a sample of 20
using this technique. Use the lottery method or any randomization method to select the 20
students. These 20 students become the basis of your enquiry”
2. Stratified Random Sampling. “Think of grade 4, grade 5, and grade 6 in a public school.
This is a stratified population by which means that it has different groups called “strata” (singular:
stratum) that share distinct characteristics from each other. The population within a stratum must
be homogeneous. If we were to sample a population of fourth-, fifth-, and sixth-graders in
particular school, we would assume that the three strata are roughly equal in size (i.e., there are
similar numbers of children at each grade level), and so we would take equal samples from each
of the three grades.” The sampling procedure is shown in Figure 4.6.
Figure 4.5. Stratified Random Sampling Procedure
2.a. Proportionate Stratified Sampling. “In a simple stratified random sampling, all strata of the
population are essentially equal in size. But it is different in proportionate stratified sampling such
that the number of elements from each stratum in relation to its proportion in the total population
is selected. To illustrate, imagine a survey situation where a local researcher wanted to sample
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people in different religion in a community. There are 1,000 Jewish People, 2,000 Catholics, and
3,000 Protestants. In this situation, the researcher chooses his sample in accordance with the
proportions of each religious group. For every Jewish person, there should be 2 Catholics, and 3
Protestants.”
2b. Disproportionate Stratified Sampling. “In a disproportional stratified sample, the size of each
stratum is not proportional to its size in the population. The researcher may decide to sample half
of married people within female graduate students and one-third of married people within male
graduate students.”
3. Cluster Sampling. “Sometimes the population of interest is spread out over a large area. It may
not be feasible to make up a list of every person living within the area and, from the list, select a
sample for study through normal randomization procedures. Cluster sampling is based on the
ability of the researcher to divide the sampling population into groups (based upon visible or easily
identifiable characteristics), called clusters, and then select elements within each cluster, using
Simple Random Sampling technique. It is important that the clusters be as similar to one another
as possible, with each cluster containing an equally heterogeneous mix of individuals”
B. Non-probability Sampling
In non-probability sampling designs, the researcher has no way of predicting or
guaranteeing that each element of the population will be represented in the sample. Some
members of the population have little or no chance of being sampled. Non-probability sampling
designs are used when the number of elements in a population is either unknown or cannot be
individually identified.
1. Quota Sampling. “One consideration of quota sampling is the researcher’s ease of access to
the sample population. For example, suppose you are a reporter for a television station. At noon,
you positioned yourself with microphone and television camera in the middle of street of a
particular city. As people pass, you interview them. The fact that people in the two categories may
come in clusters of two, three, or four is not a problem. All you need are the opinions of 20 people
from each category. Quota sampling is the least expensive way of selecting a sample; you do not
need any information, such as sampling frame, the total number of elements, their location, or
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other information about the sampling population. It guarantees the inclusion of the type of the
people you need. However, the findings using this design cannot be generalized to the total
sampling population.”
2. Accidental Sampling or Convenience Sampling. “This sampling technique is also based upon
convenience in assessing the sampling population. It takes people or other units that are readily
available and you stop collecting data once you reach the required number of respondents you
decided to have in your sample. To illustrate, suppose you own a small restaurant and want to
sample the opinions of your patrons on the quality of food and service at your restaurant. You
open for breakfast at 6:00 am, and on five consecutive weekdays you question the first 40 patrons
who arrive. Customers who have on one occasion expressed an opinion are eliminated on
subsequent arrivals. The opinions you eventually obtained are from 36 mean and 4 women. It is
heavily in favor of men, perhaps because the people who arrive at 6:00 am are likely to be in
certain occupations that are predominantly male. The data from this convenience sample give
you the thoughts of robust, hardy men about your breakfast menu. Yet such information may be
all you need for your purpose.”
3. Judgmental or Purposive Sampling. “The primary consideration in purposive sampling is your
judgment as to who can provide the best information to achieve the objectives of your study. You
as a researcher only go to those people who in your opinion are likely to have the required
information and be willing to share it with you. Pollsters who forecast elections frequently use
purposive sampling. They may choose a combination of voting districts that, in past elections, has
been quite useful in predicting the final outcomes.”
4. Snowball Sampling, “It is the process of selecting a sample using networks. To start with, a few
individuals in a group are selected and the required information is collected from them. They are
then asked to identify other people in the group or organization, and the people selected by them
become part of the sample. This process is continued until the required number or a saturation
point has been reached, in terms of the information being sought.”
C. Systematic Sampling
“Systematic sampling has been classified as a mixed design because it has the characteristics of
both random and non-random sampling designs. Systematic sampling involves selecting
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individuals according to a predetermined sequence. The sequence must originate by chance. For
instance, we might create a randomly scrambled list of units that lie within the population of
interest and then select every 10th unit on the list.”
Sample Size Determination
Researchers often ask, How big of a sample should I select? A basic rule in sampling is: “The
larger the sample, the better.” But such a generalized rule is not very helpful to a researcher who
must make a practical decision about a specific research situation. Gay, Mills, and Airasian (2009)
have offered the following guidelines for selecting a sample size as restated by Leedy.
▪ “For smaller populations, say, 𝑁 = 100 or fewer, there is little point to sample. Just survey
the entire population”
▪ “If the population size is around 500, 50% should be sampled.”
▪ “If the population is around 1,500, 20% should be sampled.”
To some extent, the size of an adequate sample depends on how homogeneous or
heterogeneous the population is. If the population is markedly heterogeneous, a larger sample
will be necessary than if the population is fairly homogeneous. Statisticians have developed
formulas for determining the desired sample size for a given population. In determining the size
of your sample, the following should be considered:
▪ “At what level of confidence do you want to test your results, findings or
hypotheses?”
▪ “With what degree of accuracy do you wish to estimate the population
parameters?”
▪ “What is the estimated level of variation (standard deviation), with respect to the
main variable you are studying in the study population?”
Answering these questions is necessary regardless of whether you intend to determine the
sample size yourself or have an expert do it for you.
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Lesson 6. Ethical Considerations in Data Collection
All professions are guided by a code of ethics that has evolved over the years to accommodate
the changes happening over time in accordance with society’s needs and expectations. There
are certain behaviors in research—such as causing harm to individuals, breaching confidentiality,
using information improperly and introducing bias—that are considered unethical in any
profession.
Ethical Issues to consider concerning Research Participants
1. Seeking consent. “In every discipline it is considered unethical to collect information without
the knowledge of participants, and their expressed willingness and informed consent. Informed
consent implies that subjects are made adequately aware of the type of information you want from
them, why the information is being sought, what purpose it will put to, how they are expected to
participate in the study, and how it will directly affect them. It is important that the consent is
voluntary and without pressure of any kind.”
2. Providing incentives. “Some researchers provide incentives to participants for their participation
in a study, feeling this to be quite proper as participants are giving their time. Other think that the
offering of inducements is unethical. Most of the time, people do not participate in a study because
of incentives, but because they realize the importance of the study. Therefore, giving a small gift
after they participated, as a token of appreciation, is in the author’s opinion not unethical.
However, giving a present before collecting the data is unethical.”
3. Seeking sensitive information. “Certain types of information can be regarded as sensitive or
confidential by some people and thus an invasion of privacy. Asking for this information may upset
or embarrass a respondent. However, if you do not ask for the information, it may not be possible
to pursue your interest in the area and contribute to the existing body of knowledge. The dilemma
you face as a researcher is whether you should ask sensitive and intrusive questions.”
4. The possibility of causing harm to participants. “Harm includes not only hazardous medical
experiments but also any social research that might involve such things as discomfort, anxiety,
harassment, invasion of privacy, or demeaning or dehumanising procedures.”
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5. Maintaining Confidentiality. “Sharing information about a respondent with others for purposes
other than research is unethical. It is unethical to identify an individual respondent and the
information provided by him/her.”
Ethical issues to consider relating to the Researcher
1. Avoiding bias. “Bias on the part of the researcher is unethical. Bias is different from subjectivity
as bias is a deliberate attempt either to hide what you have found in your study or to highlight
something disproportionately to its true existence. It is the bias that is unethical and not the
subjectivity.”
2. Provision or deprivation of a treatment. “It is usually accepted that deprivation of a trial treatment
to a control group is not unethical as, in the absence of this, a study can never establish the
effectiveness of a treatment which may deprive many others of its possible benefits. This
deprivation of the possible benefits, on the other hand, is considered by some as unethical.”
3. Using inappropriate research methodology. “It is the researcher’s obligation to use appropriate
methodology. It is unethical to use a method inappropriate to prove or disprove something that
you want to, such as by selecting a highly-biased sample, using an invalid instrument or by
drawing wrong conclusions.”
4. Incorrect reporting. “To report the findings in a way that changes them to serve your own or
someone else’s interest is unethical.”
5. Inappropriate use of the information. “The use of information in a way that directly or indirectly
affects respondents adversely is unethical.”
Lesson 7. Data Analysis
All research requires logical reasoning. Quantitative researchers tend to rely more heavily
on deductive reasoning, beginning with certain premises (e.g., hypotheses, theories) and then
drawing logical conclusions from them. They also try to maintain objectivity in their data analysis,
conducting predetermined statistical procedures and using objective criteria to evaluate the
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outcomes od those procedures. By the time you reach this part, you should have your data neatly
collected and piled up waiting for analysis. The role of analysis is to bring data together in a
meaningful way and enable the researchers to interpret or make sense of it.
It is critical to remember that your methods of analysis must align with your chosen
research methodology (Bloomberg & Volve, 2018). In most type of research studies, the process
of data analysis involves following three steps: (1) preparing the data for analysis, (2) analyzing
the data, and (3) interpreting the data (i.e., testing the research hypotheses and drawing valid
references.
Since research data can be seen as the fruits of researchers’ labor, the data will serve as
a clue to answer the researchers’ questions given that the study has been conducted in a
scientifically rigorous manner. To unlock these clues, the researcher typically rely on a variety of
statistical procedures. These procedures allow researchers to describe groups of individuals and
events, examine the relationships between different variables, measure differences between
groups and conditions, and examine and generalize results obtained from a sample back to the
population from which the sample was drawn
There are two major areas of statistical procedures. The first one is called descriptive
statistics and the second one is called inferential statistics.
Descriptive Statistics
Descriptive statistics are used to describe the data collected in research studies and to accurately
characterize the variables under observation within a specific sample. It is frequently used to
summarize a study sample prior to analysing a study’s primary hypotheses. This provides
information about the overall representativeness of the sample, as well as the information
necessary for other researchers to replicate the study, if they so desire.
1. Central Tendency
The central tendency of a distribution is a number that represents the typical or most
representative value in the distribution. Measures of central tendency provide researchers with a
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way of characterizing a data set with a single value. The most widely used measures of central
tendency are mean, median, and mode.
▪ Mean
“It is commonly known as the average. The mean is quite simple to calculate. Simply add
all the numbers in the data set and then divide by the total number of entries. The result
is the mean of the distribution. For example, let us say that we are trying to describe the
mean age of a group of 10 study participants with the following ages:”
34 27 23 23 26 27 28 23 32 41
The summed ages for the 10 participants is 284. Therefore, the mean age of the sample
is 284/10 = 28.40.
The mean is quite accurate when the data set is normally distributed. Unfortunately, the
mean is strongly influenced by extreme values or outliers. Therefore, it may be misleading
in data sets in which the values are not normally distributed, or where there are extreme
values at one end of the data set.
▪ Median
“It is the middle value in a distribution of values. To calculate the median, simply sort all of
the values from lowest to highest and then identify the middle value. The middle value is
the median. For example, sorting the set of ages in the previous example would result in
the following:”
23 23 23 26 27 27 28 32 34 41
In this instance, the median is 27. If the two values were different, you would simply get
the average of the two values.
▪ Mode
“It is the value that occurs most frequently in a set of values. To find the mode, simply
count the number of times (frequency) that each value appears in a data set. The value
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that occurs most frequently is the mode. For example, we could easily see from the
previous example that the most prevalent age in the sample is 23, which is therefore the
mode.”
23 23 23 26 27 27 28 32 34 41
2. Dispersion
“Measures of central tendency, like the mean, describe the most likely value, but they do not tell
is anything about how the values vary. For example, two sets of data can have the same mean,
but they may vary greatly in the way that their values are spread out. Another way of describing
the shape of a distribution is to examine this spread. The spread, more technically referred to as
the dispersion. The most widely used measures of dispersion are range, variance, and standard
deviation.”
▪ Range
“The range of a distribution tells us the smallest possible interval in which all the data in a
certain sample will fall. Quite simply, it is the difference between the highest and lowest
values in a distribution. Using our previous example, the range of ages for the study
sample would be:”
41-23= 18
▪ Variance
“Variance gives us a sense of how closely concentrated a set of values is around its
average value, and is calculated in the following manner:
1. Subtract the mean of the distribution from each of the values.
2. Square each result.
3. Add all the squared results.
4. Divide the result by the number of values minus 1.”
The variance of a distribution gives us an average of how far, in squared units, the values
in a distribution are from the mean, which allows us to see how closely concentrated the scores
in a distribution are.
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▪ Standard Deviation
“Basically, the standard deviation is the square root of the variance. The variance and the
standard deviation of distributions are the basis for calculating many other statistics that
estimate the association and differences between variables.”
3. Measures of Association
“In addition to describing the shape of variable distributions, another important task of descriptive
statistics is to examine and describe the relationships of associations between variables.
Correlations are perhaps the most basic and most useful measure of association between two or
more variables. Expressed in a single number called a correlation coefficient (r), correlations
provide information about the direction of the relationship and the intensity of the relationship.
Furthermore, tests of correlations will provide information on whether the correlation is statistically
significant. There is a wide variety of correlations that, for the most part, are determined by the
type of data being analyzed. One of the most commonly used correlations is the Pearson product-
moment correlation, often referred to as the Pearson r.”
Inferential Statistics
In addition to describing and examining associations of variables within our data sets, we often
conduct research to answer questions about the greater population. Because it would not be
feasible to collect data from the entire population, researchers conduct research with
representative sample (as mentioned in the previous lessons) in an attempt to draw inferences
about the population from which the samples were drawn. The analyses used to examine these
inferences are appropriately referred to as inferential statistics.
Inferential statistics help us to draw conclusions beyond our immediate samples and data. For
example, inferential statistics could be used to infer, from a relatively small sample of
employees, what the job satisfaction is likely to be for a company’s entire work force. Basic
overview of several of the most widely used inferential statistical procedures, including the t-test,
analysis of variance (ANOVA), chi-square, and regression.
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▪ T-test
“T-tests are used to test mean differences between two groups. In general, they require
a single dichotomous independent variable (e.g., an experimental and control group) and
a single continuous dependent variable. For example, t-tests can be used to test for
mean differences between experimental and control groups in a randomized experiment,
or to test for mean differences between two groups in a nonexperimental context (such
as whether cocaine and heroin users report more criminal activity). When a researcher
wishes to compare the average (mean) performance between two groups on a
continuous variable, he should consider the t-test.”
▪ Analysis of Variance (ANOVA)
“ANOVA is also a test of mean comparisons just like T-test. In fact, one of the only
differences between a t-test and an ANOVA is that the ANOVA can compare means
across more than two groups or conditions.”
▪ Chi-square (2)
“The inferential statistics that we have discussed so far (i.e., t-tests and ANOVA) are
appropriate only when the dependent variables being measured are continuous (interval
or ratio). In contrast, the chi-square allows us to test hypothesis using nominal or ordinal
data. Similarly, chi-square analysis is often used to examine between-group differences
on categorical variables such as gender, marital status, or grade level.”
▪ Regression
“Linear regression is a method of estimating or predicting a value on some dependent
variable given the values of one or more independent variables. Like correlations,
statistical regression examines the association of relationship between variables. Unlike
with correlations, however, the primary purpose of regression is prediction.”
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Assessment Tasks
TASK NO. 1 (WRITTEN WORKS)
Instructions. Complete the following statements by filling the blanks with
appropriate answers. (50 points)
1. The word hypothesis consists of two words: hypo which means
___________________ and thesis which means _______________. (2pts)
2. One salient feature of hypothesis is that they must make a ________________.
3. ____________________ is a form of statistical hypothesis that is testable.
4. The main purpose of data collection is to verify ______________________.
5. ________________________ is an example of primary source.
6. ________________________ is a scale that measures in terms of names or
designations of discrete units.
7. Research instruments are the tools you use to _________________ on the topic
of interest to transform it into useful information.
8. Questionnaires can be used when certain barriers such as ________________
and literacy do not apply to your target group.
9. __________________ require the respondents to choose one or more from a
pre-defined category of ‘answers’ to the questions.
10. Interviews can be used when _______________________________.
11. In unstructured interview, the researcher have the _____________________ in
terms of content and structure.
12. Structured interview is where the researcher asks a ____________________
set of questions.
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TASK NO. 1 (WRITTEN WORKS)
13. Focus groups can be used when _______________________________________.
14. Validity is the extent to which the __________________ measures what it intends to
measure.
15. Face validity , _____________________, ___________________, ____________________, are
the most common methods for demonstrating validity. (3pts)
16. ________________, ___________________, _________________, _______________, are the
methods that can determine reliability. (4pts)
17. The process of selecting a representative sample from a target population is called
__________________.
18. _____________________ is considered to be a representative of a group.
19. A population is a group who shares the same ________________.
20. Randomization is a method of sampling in which each of the population has the
_____________ chance or probability of selection of the individuals for constituting a sample.
21. _____________ and ___________ are the two approaches in randomization. (2pts)
22. In _______________________, each sample unit of the population has only one chance to
be selected in the sample.
23. The groups that share distinct characteristics from each other is called
_________________.
24. The division of the sampling population into groups based upon visible or easily
identifiable characteristics is called _____________________.
25. In ______________________, the researcher has no way of predicting or guaranteeing that
each element of the population will be presented in the sample.
26. Quota sampling is the ____________ expensive way of selecting a sample.
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TASK NO 1. (WRITTEN WORKS)
27. __________________ is a sampling technique that takes people or other units that are
readily available.
28. The primary consideration in purposive sampling is your judgment as to who can
provide the _______________ to achieve the objectives of your study.
29. Snowball sampling is the process of selecting a sample using _________________.
30. The _______________ the sample, the better.
31. __________________ implies that subjects are made adequately aware of the type of
information you want from them, why the information is being sought, what purpose it will
put to, how they are expected to participate in the study, and how it will affect them.
32. Descriptive Statistics are used to _____________ the data collected in research studies
and to accurately characterize the variables under observation within a specific sample.
33. The most widely used measures of central tendency are _______, ________, and
___________.
34. The most widely used measures of dispersion are ___________, ___________, and
_____________. (3pts)
35. _______________ help us to draw conclusions beyond our immediate samples and data.
36. The most widely used inferential statistical procedures are _________, ____________,
_____________, and _____________. (4pts)
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TASK NO. 2
Instructions: Provide hypothesis for the following topic on the box provided.
1. Hypothesis 1: About Climate Change
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
2. About Public Transportation
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
3. About Education
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
4. About your assigned topic
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
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TASK NO. 3.
Instructions: Teacher Sarah is in-charge of preparing an annual report on the school’s
performance. She collected pertinent data on the variables below. Identify whether the
variables are qualitative or quantitative. Moreover, identify the measurement scale of the
data.
Data Type Scale
1. Nutritional status of a
student (underweight, normal,
overweight, obese)
2. Percentage of students who
leave school during the year of
any reason
3. Rank of school in the region
based on students’
performance on the National
Achievement Test
4. Town or city of students
enrolled in the current school
year.
5. Total number of students
enrolled in the current school
year.
6. Total number of textbooks
in the school that are not
already in good condition.
7. Whether or not the student
participated in the district,
division, regional or national
athletic meets.
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TASK NO. 3
Instructions: In each of the scenarios in this exercise, a researcher encounters a
measurement problem. Some of the scenarios reflect a poblem with the validity of a
measure. Others reflect a problem with a measure’s reliability—a problem that indirectly also
affects the measure’s validity. For each scenario, choose the most obvious problem from
among the following alternatives. Provide justification for your choice on the box provided.
∘ Face validity ∘ Interrater reliability
∘ Content validity ∘ Test-retest reliability
∘ Criterion validity ∘ Parallel form of same test
∘ Construct validity ∘ Informal consistency reliability
___________________1. “After using two different methods for teaching basic tennis skills to
non-tennis-playing adults, a researcher assess the effectiveness of the two methods by
administering a true-false test regarding the rules of the game.”
___________________2. “A researcher writes 120 multiple-choice questions to assess middle
school students’ general knowledge of basic word geography. To minimize the likelihood that
students will cheat on the test by copying one another’s answers, the researcher divides the
questions into three different sets to create three 40-item tests. In collecting data, the
researcher distributes the three tests randomly to students in any single classroom. After
administering the tests to students at many different middle schools, the researcher
computes the students’ test scores and discovers that student who answered one particular
set of 40 questions scoreed an average of 3 points higher than students who answered
either of the other two 40-question sets.”
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_________________3. “In order to determine what kinds of situations provoke aggression in
gorillas, two researchers observe montain gorillas in the Virunga Mountains of northwestern
Rwanda. As they watch a particular gorilla family and take notes about family members’
behaviors, the researchers often disagree about whether certain behaviors consitute
“aggression” or, instead, reflect more peaceful “assertiveness””
__________________4. “A researcher uses a blood test to determine people’s overall energy
level after drinking or not drinking a can of a high-cafferine cola drink. Unfortunately, when
two research assistants independently rate people’s behaviors for energy level for a 4-hour
period after drinking the cola, their results do not seem to have any correlation with the
blood-test results.”
__________________5. “In a two-week period during the semester, a researcher gains entry
into several college classrooms in order to administer a short survey regarding college
students’ beliefs about climate change. The survey consists of 20 statements about climate
change to which students voluntarily put their names on their surveys. Thanks to the names
on many survey forms, the researcher discovers that a few students were in two of the
classes surveyed and this completed the survey twice. Curiously, however, these students
sometimes gave different responses to particular statements on the two different occassions,
and hence their overall scores were also different.”
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_________________7. “A researcher develops and uses a questionnaire intended to measure
the extent to which college students dusplay tolerance woward a particular religious group.
However, several experts in the researcher’s field of study siggest that the questionnaire
measures not how tolerant students actually are, but what students would like to believe
about their tolerance for people of a particular religion.”
_________________8. “Students in an introductory college psychology course must satisfy
their “research methods” requirement in one of several ways; one option is to participate in a
research study called “Intelligence and Motor Skill Learning.” When students choosing this
option report to the laboratory, one of their tasks is to respond as quickly as possible to a
series of simple computer-generated questions. Afterward, the researcher debrief the student
about the nature of the study and tells them that the reaction-time measure was designed to
be a simple measure of intelligence. Some of the students object, saying, “That’s not a
measure of intelligence! Intelligence isn’t how quickly you can do something, it’s how well
you can do it.””
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TASK NO. 4
Instructions: Identify which among the sampling designs is the most appropriate to use in the
given scenarios. Write your answer on the space provided.
_____________________1. In evaluating certain teacher training institutes during the summer
of 1992, the researcher sampled from 300 people attendees of the seminar who he
happened to recognize.
______________________2. To determine the psychological effects of stress on gender, the
researcher decided to group the population of Poblacion II into male and female.
______________________3. The researcher wanted to investigate the attitude of college
students in the Philippines towards problems in higher education in the country. Higher
education institutions are spread out in every region of the country. In addition, there are
different types of institutions that exist. Within that institution, various courses are being
offered.
_____________________4. The researcher selected a sample of 20 male students in order to
find out the average age of the male students in the class. He decided to stand at the
entrance of the room, and whenever a male student enters the room, he ask sfor his age.
____________________5. A researcher wanted to know if his constructed learning material for
Trigonometry is effective to apply in a classroom. Instead of trying it out to students, he
decided to ask several Trigonometry teachers to evaluate his material.
____________________6. The researcher wanted to conduct a study involving previously
illegal immigrants who were never caught. To gather respondents, he asked his friend who
happened to know illegal immigrants.
____________________7. There are 50 students in a class and the researcher wants to select
10 students. After calculating the width of the interval, he selected the third element for every
five students.
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TASK NO. 5
Instructions: Construct your own research questionnaire for your assigned topic. Make sure
to follow the guidelines discussed in the lesson.
125
TASK NO. 6
Instructions: Write your tentative research methodology on your assigned topic.
RESEARCH METHODOLOGY
126
TASK NO. 7
Instructions: Write your tentative research methodology for your assigned topic.
127
Summary
▪ Hypothesis is an educated and testable guess about the answer to your research
question.
▪ Three kinds and forms of hypothesis are declarative, directional, non-directional.
▪ The hypothesis being tested by a researcher is largely dependent on the type of
research design being used.
▪ Research seeks to discover underlying truths through data.
▪ Data can be categorized into primary and secondary data.
▪ Measurement limits the data of any phenomenon so that those data may be interpreted
and compared to a particular standard.
▪ Research instruments are administered on the sample subject for collecting evidences
or data.
▪ Research instruments are the tools you use to collect data on the topic of interest to
transform it into useful information.
▪ The main instrument to collect data through survey is questionnaires.
▪ Questionnaire is a set of standard questions, often called items, which follow a fixed
scheme in order to collect individual data about one or more specific topics.
▪ Open questions allow the respondent to insert his or her views, ideas, or suggestions
about the question posed.
▪ Closed questions require the respondents to choose one or more from a pre-defined
category of answers to the question.
▪ Interviews are often likened to a conversation between two people, though it requires
orchestrating, directing, and controlling to varying degrees.
▪ Focus groups are formally organized, structured groups of individuals brought together
to discuss series of topics during a specific period of time.
▪ Validity is the extent to which the instrument measures what it intends to measure.
▪ Face validity is the extent to which an instrument looks like it is measuring a particular
characteristic.
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▪ Content validity is the extent to which a measurement instrument is a representative
sample of the content being measured.
▪ Criterion validity is determined by the relationship between the measure and
performance on an outside criterion or measure.
▪ Construct validity is the extent to which an instrument measures a characteristic that
cannot be directly observed but it is assumed to exist based on patterns in peoples’s
behavior.
▪ Reliability refers to the consistency or dependability of a measurement technique, and it
is concerned with the consistency or stability of the score obtained from a measure or
assessment over time and across setting or conditions.
▪ Interrater reliability is the extent to which two or more individuals evaluating the same
product or performance give identical judgment.
▪ Test-retest reliability is where an instrument is administered on two separate occasions.
▪ Parallel form of same test is the extent to which two different versions of the same
instrument that were administered at different times yield similar results.
▪ Internal consistency reliability is the extent to which all of the items within a single
instrument yield similar result.
▪ A test can be reliable but not valid.
▪ Validity is more important that reliability.
▪ The most useful instrument is both valid and reliable.
▪ Sampling is the process of obtaining a few from a bigger group to become the basis for
estimating or predicting the prevalence of an unknown piece of information regarding the
bigger group.
▪ Randomization is a method of sampling in which each of the population has an equal
chance or probability of selection of the individuals for constituting a sample.
▪ Probability sampling is the extent to which every part of the population has the potential
to be represented in the sample.
▪ Simple random sampling is a process such that every member of the population has an
equal chance of being selected.
▪ Stratified random sampling involves sampling from different groups called strata.
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▪ Cluster sampling is based on the ability of the researcher to divide the sampling
population into groups.
▪ Quota sampling is a type of non-probability sampling is the researcher’s ease of access
to the sample population.
▪ Accidental sampling takes people or other units that are readily available and the
collection of data only stops when you reach the required number of respondents you
decided to have in the sample.
▪ Judgmental sampling is a non-probability sampling with a consideration as to who can
provide the best information to achieve the objectives of your study.
▪ Snowball sampling is the process of selecting a sample using networks.
▪ Systematic sampling involves selecting individuals according to a predetermined
sequence.
▪ The basic rule in sampling is the larger the sample, the better.
▪ There are certain behaviors in research that are considered unethical.
▪ The role of data analysis is to bring data together in a meaningful way and enable the
researchers to interpret or make sense of it.
▪ There are two major areas of statistical procedures—descriptive statistics and inferential
statistics.
▪ Descriptive statistics are used to describe the data collected in research studies and to
accurately characterize the variables under observation within a specific sample.
▪ The central tendency of a distribution is a number that represents the typical or most
representative value in the distribution.
▪ Measures of dispersion is another way of describing the shape of a distribution.
▪ Inferential statistics help us to draw conclusions beyond our immediate samples and
data.
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