Ideas behind classifying quantitative research
Summary
TLDRThis video focuses on how to classify quantitative research by considering multiple perspectives. The speaker emphasizes understanding research as both an activity and an object, exploring three key perspectives: time, structure, and goal. The time perspective involves cross-sectional, longitudinal, and retrospective studies. The structure perspective distinguishes between experimental and observational research. The goal perspective divides research into descriptive or analytical. The video also discusses how to classify research based on whether it involves interventions and comparisons, helping viewers grasp the foundational concepts needed for future exercises.
Takeaways
- 😀 Classifying research requires adopting multiple perspectives.
- 📊 Time, structure, and goal are three key perspectives for understanding research.
- ⏱️ Time-based research includes cross-sectional, longitudinal, and retrospective approaches.
- 🛠️ Structure-based research is divided into experimental (involving interventions) and observational (observing activities).
- 🎯 The goal of research can be descriptive or analytical, with analytical research further classified into prediction, exploration, explanation, and causation.
- 🔍 Cross-sectional research captures a snapshot of a specific moment.
- 📅 Longitudinal research tracks changes over time, either from now onward (prospective) or looking back (retrospective).
- 🔬 Quantitative research focuses on experimental or observational studies, while qualitative research will be covered later.
- 📈 Analytical research seeks to establish relationships between variables, distinguishing between correlation and causation.
- 🧠 Understanding research classification is essential for mastery and success in the course.
Q & A
What is the main purpose of the video script?
-The main purpose of the video script is to explain a better way of classifying quantitative research using multiple perspectives, focusing on aspects like time, structure, and goal.
Why are perspectives important in classifying research?
-Perspectives are important because they influence how we interpret and classify research. Different perspectives can lead to different categorizations and understanding of the research objectives and outcomes.
What are the three perspectives used to classify research in the video?
-The three perspectives discussed in the video are time, structure, and goal.
How is the 'time' perspective used to classify research?
-The 'time' perspective classifies research into cross-sectional, longitudinal, and retrospective categories. Cross-sectional research provides a snapshot at a single point in time, longitudinal research follows a subject over time, and retrospective research looks backward to analyze past data.
What is the difference between experimental and observational research from the structure perspective?
-In experimental research, the researcher administers an intervention or treatment, directly influencing the study. In observational research, the researcher observes without intervening, allowing subjects to go about their regular activities.
What are the main goals of research classified under the 'goal' perspective?
-The main goals of research under the 'goal' perspective are descriptive and analytical. Descriptive research aims to describe characteristics or phenomena, while analytical research involves more complex analyses, such as prediction, exploration, explanation, and causation.
Can you provide an example of cross-sectional research?
-An example of cross-sectional research is studying the statistical literacy scores of nursing students at a specific point in time to assess their current level of knowledge.
What is the difference between prediction and causation in analytical research?
-Prediction establishes a relationship between an exposure and an outcome but does not imply causation. Causation aims to demonstrate a strong link where the exposure directly influences the outcome.
How can one differentiate between correlation and causation?
-Correlation indicates a relationship between two variables but does not imply that one causes the other. Causation suggests that one variable directly affects or determines the outcome of another variable, supported by strong evidence.
What is the significance of understanding experimental designs in research classification?
-Understanding experimental designs is crucial for correctly classifying research. It helps distinguish between experimental and observational studies, ensuring accurate identification of research types and avoiding misinterpretation of the study's findings.
Outlines
🧠 Understanding Research Perspectives
The speaker introduces the concept of classifying research by exploring multiple perspectives. They emphasize how human classification depends on the perspective taken and how shifting perspectives can be challenging. The goal is to teach how to view research not just as an activity but also as an object through three main perspectives: time, structure, and goal. Time includes cross-sectional, longitudinal, and retrospective research, structure covers quantitative and qualitative types, and goal examines descriptive versus analytical research.
⏳ Time, Structure, and Goal in Research
This section expands on the perspectives of time, structure, and goal. Cross-sectional research looks at a current 'snapshot,' longitudinal research examines changes over time, and retrospective research investigates past events. The structure of research is divided into experimental, where the researcher intervenes, and observational, where the researcher merely observes. Finally, the goal perspective differentiates descriptive research (focused on characteristics or phenomena) from analytical research (which includes prediction, exploration, and causation).
🔍 Experimental and Observational Research
The speaker delves deeper into the structure of research. Experimental research involves the researcher administering an intervention, like a treatment or activity, whereas observational research involves logging or monitoring participants' natural behavior. The focus here is primarily on observational research for this course, with experimental research left for future exercises. There’s an explanation of the distinction between descriptive and analytic research, with descriptive focusing on ‘who, where, when,’ while analytic research investigates exploratory, predictive, or causal relationships.
📊 Comparing and Understanding Causation
The speaker emphasizes the importance of distinguishing correlation from causation. They explain how researchers seek to establish links between variables in analytical research. This includes exploring relationships between exposure and outcome (independent and dependent variables) and differentiating between prediction and causation. The example provided highlights the challenge of demonstrating that one factor (e.g., piano playing) causes another (e.g., better math skills) rather than just correlating with it.
Mindmap
Keywords
💡Perspective
💡Cross-sectional
💡Longitudinal
💡Experimental research
💡Observational research
💡Descriptive research
💡Analytic research
💡Causation
💡Correlation
💡Randomization
Highlights
The classification of quantitative research requires adopting multiple perspectives, including time, structure, and goal.
Humans often face challenges when switching perspectives, which is crucial for classifying research effectively.
Research can be seen not only as an activity but also as an object, allowing for classification from different viewpoints.
Time perspective introduces three types of research: cross-sectional (a snapshot), longitudinal (prospective or retrospective).
The structure perspective focuses on experimental and observational research, with the first involving active researcher intervention.
In observational research, the researcher observes activities without interfering, allowing the subject to follow their regular life.
Goals of research are categorized as either descriptive (to describe) or analytical (to analyze and establish relationships).
Analytical research includes prediction, exploration, explanation, and causation, each with distinct purposes in linking variables.
Examples of time perspective include statistical literacy scores analyzed from cross-sectional, prospective, and retrospective views.
Quantitative research structures involve experimental studies with assigned interventions and observational studies where no intervention occurs.
Descriptive research aims to describe characteristics or phenomena within a population, addressing questions of 'who,' 'where,' and 'when.'
Analytical research often seeks to predict or explain relationships between variables, exploring causation and correlation.
Experimental research involves treatment and control groups, with the researcher assigning interventions to participants.
Observational research can still include treatment and control groups, but there is no researcher intervention in assigning participants.
Students must focus on mastering experimental research classification early to successfully classify various types of research.
Transcripts
hello um I'm attempting
to come up with a better way of uh
classifying or helping you classify
quantitative research and to do that
we're going to do a little little bit of
uh learning about multiple perspectives
so that's kind of going to be the key
key approach here so first of
all perspectives it's a way of
humans
uh sorry the way humans classify objects
is dependent on the perspective we take
so we have the power to switch
perspectives and we often get caught up
in a perspective of the world and when
we're asked to switch that's when we
have difficulties so classifying
research is going to require that you
take
on perspectives and we're going to take
we're going to look at research from
multiple
perspectives and now in order to to do
this we have to think of research not as
an
activity Al but also as an object and so
that's going to be really important to
uh that's again taking a
perspective all right three useful
perspectives I'm going to go right
through time structure and
goal okay so from time we have
cross-sectional which is a
snapshot a slice of life so to speak and
those are written up in your notes
longitudinal which could be perspective
the research Starts Now moves forward or
retrospective and we start at the end
and we collect data about things that
went on
already okay so that's the idea of
retrospective looking back structure
from the structure perspective we have
either research that's quantitative or
qualitative and I said as I said before
the first 12 or 13 weeks of this uh
course are focused on quanti research we
will look at qualitative research as
multiple uh types you can we'll
introduce them on the chart
quickly uh but in quantitative research
we're in terms of structure we're just
interested in experimental or
observational research we'll talk a
little bit about more than that in the
next
slides and exercise five coming up is
focused on quantitative research just so
you know and the goal uh perspective
helps us see whether the research is
descriptive or analytical
so in analytical well descriptive as it
sounds analytical we're doing some sort
of analysis so the subtypes are
prediction
exploration explanation SL causation
which are kind of the same
thing all right so let's get into the
weeds a little bit so time
cross-sectional so here's an example
what is a statistical literacy score of
him versus nud nursing students
today okay Slice of Life looking at
What's Happening Now perspective will a
statistical literacy score of hm
students improve before graduation so
we're looking
forward and we're collecting some data
now collecting data later and seeing if
there's any change retrospective has a
statistical statistical literacy score
of hm grads improved over the last 10
years so this gives you an example of
flavor some of the language that's used
without getting into the definitions now
with structure we're going taking a
little bit of a different approach
because we're examining
the way the structure works experimental
research the researcher is involved in
administering the interventions we've
talked about that in class already that
uh so administering the intervention the
treatment or the activity the key thing
is that the researcher is involved in
administering
that okay so it's not you going about
your regular life it's like you coming
in somewhere and getting a pill that's
an intervention or a treatment or
getting assigned to an to do exercises
which is an activity so if you're
assigned that means the research is
involved observational the researcher
observes activities so you're going
about your regular life and you're
either logging things or the researchers
observing you somehow in
that okay many possible structures are
under the observational umbrella we're
just going to be focusing on
observational as a group in this course
in the subsequent courses we'll look at
cohort and case control among
others descriptive so now well
descriptive we're focusing on goal as a
perspective so what is the goal of
research is it to
describe okay so describe what kind of
things do we describe we describe a
characteristic of a population or the
existence of a phenomena in a population
so incidents of disease incidence of
Lottery
winnings uh death case Fatality and kind
of the the broad questions we're asking
is who where when so if we're describing
the population right or or the phenomena
analytic research we either do
exploration that's preliminary
research secondary data small samples so
that's very early stage when we're just
kind of feeling our way around maybe
with our eyes half closed prediction is
when we're already trying to get a more
formal establish some sort of formal
relation between exposure some sort of
exposure and outcome also known as
independent and dependent
variable causation goal is to establish
an undeniable link or at least a very
convincing link between exposure and
outcome okay so that's an explanation
this
exposure or this outcome is explained by
this exposure more than just predicted
okay so there's something more going on
than
just a connection all right and we have
a
couple yes no this is an extra slide in
here yes we've got that already okay I
apologize for that slide it shouldn't
have been in there another set of
perspectives so this is from an article
by
elaka and so from here we can see there
is application
objectives inquiry
mode as viewpoints or perspectives and
so we see pure versus applied research
so basic
versus um and so in the Health Sciences
we wouldn't use that well there is some
pure research in health sciences as well
and so the objectives so goals
descriptive or exploratory correlational
versus explanatory so explanatory is
more like causation correlation is more
like
prediction all right inquiry mode
quantitative versus qualitative so that
I call that structure so some similar
similar approach with a little bit
different language and this is a slide
you saw already in the first weeks of
the course or the first week of the
course so you can see the qualitative
versus quantitative divide and some of
the
sub types of
each so we're not classifying abstracts
so this is preparing you for exercise 5
which we'll be taking a look at next uh
this
week process of
elimination okay so again I've talked
about process lination I'm I'm I'm
tweaking it a little bit here so in the
very simple approach what I want you to
look at you have two
steps there's the third step but it's
not on the slide we'll get to it
structure and goal so first you look at
eliminating experimental
is there an assigned treatment versus
control group and if there uh if you can
eliminate experimental then that means
it's observational once you establish
the structure is
experimental uh with Goal you can still
you can you probably not going to be
descriptive but is there a comparison
group if it's experimental there will be
an experimental group there will be a
comparison group but if it's
observational then it might be
correlation not a comparison of means or
rates
okay and this this next slide we'll get
into the details of this so we have the
structure and um I'll let you guys read
through this yourself I don't need to
read all these words out loud so we can
see step goal I've broken it up uh step
one into if experimental if not
experimental step two is the goal if
it's um you try to eliminate descriptive
if you uh can eliminate descriptive then
the goal must be exploration or
prediction okay step three try to
eliminate perspective First Look for
data collection description to get a
sense of
time and here's a little flowchart that
kind of gets across the same ideas that
we're talking about here right so we
start with uh is there an assigned
intervention so I've used the word
assigned as well yes then it's an
experimental study is it randomly
assigned yes or no you have two
different types of
experiments if it's not
assigned then it's
observational okay so that's our our
structure established do we have a
comparison group no there's only one
thing we're studying there's not we're
not doing any comparison it's a
descriptive study otherwise it's anal
analytic study and then we end either
end up with one of these okay so that's
the direction of the exposure exposure
before
outcome uh sorry flowchart here that's a
a perspective is the first one second
one is retrospective and a
cross-sectional study take place at the
same
time all
right so we have that's a flowchart that
that could be useful for you it doesn't
have all of the
different perspectives built in here but
it's pretty
useful yeah okay the
details true experiment okay so these
terms treatment versus
control so treatment is also known as
intervention okay control often is
either some sort of placebo but again
because we in an observational study we
also could have treatment and control we
use that language so it's not only for
experiments so that those words get uh
used in various settings but in the in
an
experiment these are very
um strongly present and then the next
part is randomization how do we assign
group people to the treatment versus
control group flip of a coin is a really
good way of um kind of imagining or
grounding the idea of Random
uh random assignment to
groups uh true experiment picture so the
gold standard we have
here shows random
assignments right you go either to the
treatment group control
group data collection
one then we administer the treatment
Placebo no treatment and then we end up
with observation two and we see if
there's any change so that's a
perspective obviously it has to be a
perspective design because we need to
assign people to treatment or control
group how do iy an experiments Step One
is there a treatment and control group
if yes then go to step two if no then
not an experiment you're done step two
does the researcher desde decide which
participants get treat treatment and
which do not if yes then experiment if
no then
observational okay then not experiment
now you I seem to be repeating myself
maybe to for you here over and over
about this experiment but I find that
the students that kind of focus on this
and use this will be successful in
classifying research because it's really
helpful and the experiment if you can't
get your mind around how the experiment
works then that's going to really hurt
you in terms of the classifying research
and we want you to achieve Mastery as
early as possible so that you can focus
on other parts of the course and other
uh courses that you're taking and so
that's it's worth spending the time with
that some statements indicating goals
cause Okay so this is important to
differentiate between cause and not
cause so if you see words like
effect impact um that's an indication
of uh causation so does consumption of
400 Mig G of caffeine per
day uh increase their GPA
so does a increase B so that means if
you if you give a you're going to get
more or less B in this case both
increase right
um in the second our children who play
piano is children better at math that's
not really showing does playing piano
impact because maybe those people
playing piano those children playing
piano are ones that also have parents
who help them with their math homework
or maybe they're gra they gravitate
towards piano and so maybe it's the same
sort of mindset in children that
gravitates them towards piano also has
them better math so we don't we're not
saying that a causes B um or playing
piano causes being better at math if
that is even true so relation versus
causation uh very important too often
times students uh and humans out in the
world in the non-math discourse world or
non- stats discourse World we'll use the
word proof and so we don't want to use
that unless we we have some evidence for
it so now you can understand the
following statement this observational
correlation study found that an increase
in Reading assigned material is strongly
associated with Higher Learning outcomes
and so with that I send you to actually
send you to the last slide um but and
but also to the readings and so I've
adjusted some of the ways I've
discussed the classifying research in
the readings booklets
but I think that you'll still gain
something from spending time with the
readings there okay so data types
perspective you have you have you have
either compare rates compare means or
correlation if you have two variables or
more so we talked about that in class
data collection it's either observation
or survey OBS word observation comes up
twice so observation in this case under
data collection means that I'm observing
I'm collecting data from
observations or I can collect data by
doing surveys so again two different
approaches to the uh to data collection
so again two different perspectives on
classifying research so just because you
see the word we observed XY z um that
could still be an
experiment okay so if you imagine I'm
I'm um assigning you to treatment a
versus treatment B and then I observe
you in the next few weeks and see how
your behavior changes or something like
that then I'm still doing an
observation from data collection
perspective but from the structural
perspective you're doing an experiment
okay so this is where we breaking up and
from the perspectives will help you say
okay which perspective am I using here
so that's going to be very useful hope
you get something out of this video I'm
not sure whether you're going to enjoy
it it's at what are we timing wise at oh
16 minutes a lot longer than I wanted to
and I'm feel like I'm speaking very
quickly thank you for watching
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