1.
Basic Classroom Research
Dr. Carlo Magno, PhD
De La Salle University, Manila
Lasallian Institute of Development and
Educational Research
2.
Objectives
Consider the basic research paradigm in
conceptualizing classroom research.
Conceptualize a classroom research anchored on a
conceptual or theoretical framework
Plan a research following an appropriate deign
3.
Research Process
Problem Identification
and Hypothesis
Formulation
Data Analysis,
Interpretation and
Drawing Conclusions
Design Formulation
Coding and data
Processing
Data Collection
4.
Phases of a Research Study
Idea-generating phase: Identify a topic of
interest to study.
Problem-definition phase: Refine the vague and
general idea that was generated in the previous
step.
Procedures-design phase: Decide on the
specific procedures to be used in the gathering
and statistical analysis of the data.
5.
Phases of a Research Study
Observation phase: Using the procedures
devised in the previous step, collect your
observations from the participants in your study.
Data-analysis phase: Analyze the data collected
above using appropriate statistical procedures.
Interpretation phase: Compare your results with
the results predicted on the basis of your theory.
Do your results support the theory?
Communication phase: Prepare a written or oral
report of the study for publication or other
presentation to colleagues. The report should
include a detailed description of all of the above
steps.
6.
Focus
Research Designs that will test specific classroom
phenomena
Correlational Studies
Group Comparison studies
Effectiveness of an intervention on a set of measure
Limited to quantitative approach in doing research
Variables are measured
Instruments are limited to obtaining quantitative data
Surveys
Questionnaires
Tests
Checklists
Structured observations (scores are obtained)
7.
Correlational Studies
Involves two variables where one increases with the
other
Examples:
Grades and motivation: Does student motivation increase
with students’ grades?
Attitude in Math and Math performance: Does students’
attitude in math increase with their performance in math
achievement test?
Math anxiety and test in math: Does anxiety decrease
math test scores?
The choice between the variables should be guided
by a theory (theoretical or conceptual framework).
Both variables should be quantitatively measured.
8.
Correlational Studies
Linear Regression
There is a straight line relationship between variables X
and Y
When X increases, Y also increases-positive relationship
When X increases, Y decreases or vice versa – negative
relationship
9.
Correlational Studies
Problem: Is there a significant relationship between
achievement and aptitude?
Hypothesis: There is a significant relationship
between achievement and aptitude
11.
Regression Line between achievement and
aptitude
S ca tte rp lo t: X vs. Y
Y = 1 4 .3 7 9 + .8 5 6 3 3 * X
C o rre la tio n : r = .9 8 9 6 6
4 0 5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0
X
5 5
6 0
6 5
7 0
7 5
8 0
8 5
9 0
9 5
1 0 0
1 0 5
Y
9 5 % co n fid e n ce
13.
Relationship between Laziness and
Perseverance S ca tte rp lo t: Y vs. X
X = 1 3 9 .9 4 - 1 .1 3 8 * Y
C o rre la tio n : r = -.9 9 5 9
3 0 4 0 5 0 6 0 7 0 8 0 9 0
Y
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
1 1 0
X
9 5 % co n fid e n ce
14.
Correlational Studies
Analysis
2 variables that are interval or ratio: Pearson r
2 variables are ordinal: Spearman rho
2 variables and each is a dichotomy: phi coefficient
High
Satisfaction in
teaching
Low satisfaction
in teaching
High teaching
performance
50 21
Low teaching
performance
12 48
• A significant relationship occurs if scores are extreme enough
to surpass the probability of error.
•If p value is < obtained value: reject the null hypothesis
•If the obtained value > critical value : reject the null hypothesis
15.
Group Comparison Studies
Involves group formed in categories (2 or more) and
these categories are compared on an characteristic.
The groups are called as the independent variable
The characteristics of where the groups are
compared on are called as the dependent variable.
Examples:
Is there a significant difference between males and
females on their math performance?
Is there a significant difference between public and private
school students in their study habits?
Are there a significant differences among the school
ability of students from across three years (2010, 2011,
2012)?
Are there significant differences among teachers,
administrators, and staff on their attitude towards the RH
16.
Group Comparison Studies
Take note that the IV...
is categorical
can have two or more levels
can also be more than one....
Example: Can gender and socio-economic status
differentiate students general intelligence?
A theoretical or conceptual framework is needed to
justify the comparison.
17.
Group Comparison Studies
Case: Third year high school males and females
are tested in their Mathematical Ability
Males Females
26 38
24 26
18 24
17 24
18 30
20 22
18
18.
Group Comparison Studies
Males: Mean = 20.14 SD=3.48
Females: Mean = 27.33 SD = 5.89
19.
Mean of Males and females in Math
B ox & W hisker P lo t: V a r2
M e a n
± S D
± 1 .9 6*S D
M a le s F em ale s
V ar1
1 2
1 4
1 6
1 8
2 0
2 2
2 4
2 6
2 8
3 0
3 2
3 4
3 6
3 8
4 0
Var2
20.
Group Comparison Studies
H0= There is no significant difference between
males and females in their math scores
H1= There is a significant difference between
males and females in their math scores
2. =.05
df = N1 + N2 –2
df = 7 + 6 –2
df = 11
t critical value = 2.201
22.
Group Comparison Studies
4. Decision and Interpretation
Since the t obtained which is – 2.73 is greater than
the t-critical which is 2.201, the null hypothesis is
rejected.
This means that there is a significant difference
between males and females in their math scores.
Females (M=27.33) significantly scored higher in
math as compared to the males (M=20.14)
23.
Group Comparison Studies
4. Decision and Interpretation (another way using p
values)
Since the p value obtained which is 0.0195 is less
than the alpha level which is .05, the null
hypothesis is rejected.
This means that there is a significant difference
between males and females in their math scores.
Females (M=27.33) significantly scored higher in
math as compared to the males (M=20.14)
24.
Factorial Design
Independent
Variable B
A1 A2 A3
B1 A1 B1 A2 B1 A3 B1 B1 Mean
Main
Effect
for BB2 A1 B2 A2 B2 A3 B2 B2 Mean
A1 Mean
A2 Mean A3 mean
Main Effect for A
Main effect of A
Main Effect of B
Interaction effect of A and B (A X B)
25.
Talent
Achievement
Effect of Achievement and Type of school on Talent
Low
Achievers
High
Achievers
Type of school
Public
school
Private
School
26.
Ho:
Achievement does not have a significant main
effect on talent
(there is no significant difference between high and
low achievers on talent)
Type of school does not have a significant main
effect on talent
(there is no significant difference between public
and private school students in their talent)
There is no significant interaction effect between
achievement and type of school
(there are no significant differences among high
achievers in public, high achievers in private, low
achievers in public, and low achievers in private in
their talent
Effect of Achievement and Type of school on Talent
27.
H1:
Achievement have a significant main effect on
talent
(there is a significant difference between high and
low achievers on talent)
Type of school have a significant main effect on
talent
(there is a significant difference between public
and private school students in their talent)
There is a significant interaction effect between
achievement and type of school
(there are significant differences among high
achievers in public, high achievers in private, low
achievers in public, and low achievers in private in
their talent
Effect of Achievement and Type of school on Talent
28.
Group Comparison Studies
Analysis
If two categories are compared on one DV: t-test for two
independent samples
If three or more categories (one IV) are compared on one
DV: One way Analysis of Variance (ANOVA)
If two IV are investigated on one DV: two way ANOVA
If two or more IV are investigated on two or more DV:
Multivariate Analysis of Variance (MANOVA)
29.
Effectiveness of an intervention on a set of
measure (Experimental Study)
The effect of a treatment is tested on a specific
change on a characteristic.
The treatment that is given to participants are called
as the independent variable.
The independent variable should be manipulated.
Ex. Groups are randomly assigned to listening and
watching stimulus.
Ex. Groups are randomly assigned to reading a text or
watching a news.
The characteristic that changes dues to the variation
or manipulation of the IV is called as the dependent
variable.
30.
Experimental Study
How is the IV manipulated?
Presence of absence
Amount
Type
31.
Presence vs. absence
The effect of adrenocorticotropin (ACTH) on the
attention enhancement of schizophrenic patients.
1st group: received the ACTH drug
2nd group: received a placebo drug
32.
Amount manipulation
The effect of ACTH drug on the excessive grooming
of rats.
1st group: 0 nanograms of ACTH
2nd group: 20 nanograms of ACTH
3rd group: 50 nanograms of ACTH
4th group: 80 nanograms of ACTH
5th group: 1,000 nanograms of ACTH
33.
Type manipulation
The effect of labeling on the teachers conduct
assessment of students
Results
Trouble makers low conduct
Average Average conduct
Ideal students High conduct
34.
Experimental Study
In an experiment done by dela Cruz, Cagandahan
and Arciaga (2004), the effect of nonbehavioral
intervention techniques was investigated on the
computational abilities of fourth year high school
students. The non-behavioral intervention
techniques has three levels, bibliotherapy, small
group interaction and games. These techniques
were used as a teaching strategy in a lesson in a
math class for three sections. Each of the strategy
was used for each section. One section did not
receive any strategy which served as the control
group. After undergoing the strategy, the students
were tested where they answered a series of
computation items.
35.
Experimental Study
Bibliotherapy Small group
interaction
Games Control Group
X1 X2 X3 X4
X1 X2 X3 X4
X1 X2 X3 X4
X1 X2 X3 X4
36.
Experimental Study
1. H0: The non-behavioral intervention techniques
have no significant effect on computational ability
H0: There are no significant differences among the
groups receiving bibliotherapy, small group
interaction, games and control in their computational
ability.
2. 2=.05
df between = groups – 1 = (4-1=3)
df within = (N – 1) – df between ((209-1)-3)=205
df total = df between + df within (3 + 205)
F ratio critical value = 2.65
37.
ANOVA Hypothesis Testing
3. Computation
F ratio computed = 4.62
4. Decision and Interpretation
Since the F ratio obtained which is 4.62 is greater
than the F ratio critical which is 2.65, the null
hypothesis is rejected. The non-behavioral
intervention techniques have a significant effect
on computational ability.
38.
ANOVA Hypothesis Testing
In te rve n tio n te ch n iq u e s; L S M e a n s
C u rre n t e ffe ct: F (3 , 2 0 5 )= 4 .6 8 1 9 , p = .0 0 3 4 7
E ffe ctive h yp o th e sis d e co m p o sitio n
V e rtica l b a rs d e n o te 0 .9 5 co n fid e n ce in te rva ls
co n tro l
G a m e s
B ib lio th e ra p y
S m a ll g ro u p in te ra ctio n
In te rve n tio n te ch n iq u e s
3 .5
4 .0
4 .5
5 .0
5 .5
6 .0
6 .5
7 .0
7 .5
8 .0
8 .5
computation
The group who received the small group interaction
significantly scored the highest among other intervention
techniques.
39.
Experimental Designs
Research Design – Refers to the outline, plan or
strategy specifying the procedure to be used in
seeking an answer to the research question
True Research Designs - Answers the research
questions or adequately tests hypothesis.
Extraneous variables are controlled
Inclusion of a control group
External validity - Generalizability
40.
Experimental Designs
1. After-Only Design
Dependent variable is measured only once and this
measurement occurs after the experimental conditions
have been administered to the experimental group.
Treatment Response
Measure
Experimental Condition X Y
Control Condition Y
Between Subjects Design – If different subjects are used
in each experimental treatment condition.
Within Subjects Design – If the same subjects are used
in each experimental condition.
41.
Experimental Designs
1.1 Between-Subjects After Only Design
subjects are randomly assigned to the experimental
and control group.
42.
Simple Randomized Subjects Design
Includes more than one level of the independent
variable
43.
Experimental Designs
Factorial Design
Two or more independent variables are
simultaneously studied to determine their
independent and interactive effects on the
dependent variables.
Main effect – influence of one independent variable
Interaction effect – Influence that one independent
has on another
44.
Experimental Designs
Within Subject After-Only Design
Same subjects are repeatedly assessed on the
dependent variable after participating in all
experimental treatment conditions
45.
Experimental Designs
Combined Between- and Within-Subjects Designs
Factorial Design Based on a mixed Model
Two independent variables have to be varied in two
different ways.
One independent variable requires a different group
of subjects for each level of variation.
The other independent variable is constructed in
such a way that all subjects have to take each level
of variation.
47.
Experimental Designs
2. Before-After Design
The treatment effect is assessed by comparing the
difference between the experimental and control
groups’ pre- and posttest scores.
48.
The Solomon Four-Group Design
- Designed to deal with a potential testing threat.
- Testing threat occurs when the act of taking a test
affects how people score on a retest or posttest.
- The design has four groups
- Two of the groups receive the treatment and two
does not.
- Two of the groups receive a pretest and two does
not.
- By explicitly including testing as a factor in the
design, we are able to assess experimentally
whether a testing threat is operating.
49.
Experimental Designs
Switching Replications Design
- There is a need to deny the program to some
participants through random assignment.
- A two group design with three waves of measurement.
- The implementation of the treatment is repeated or
replicated.
- In the repetition of the treatment, the two groups switch
roles:
- The original control group becomes the treatment group
in phase 2
while the original treatment acts as the control.
By the end of the study all participants have received the
treatment.
50.
Experimental Designs
Randomized Block Design
- Constructed to reduce noise or variance in the data
- Requires that the researcher to divide the sample
into relatively homogeneous subgroups or blocks.
- Then, the experimental design desired is
implemented within each block or homogeneous
subgroup.
- The key idea is that the variability within each block
is less than the variability of the entire sample. Thus
each estimate of the treatment effect within a block
is more efficient than estimates across the entire
sample
52.
Recap
What are the three approaches in conducting a
study?
53.
Activity
Construct a plan for your classroom research
Research Question
Hypothesis
What conceptual/theoretical framework will be used? (be
ready to explain)
Why is this research question relevant
Method
Design
Participants (who and how many)
Instruments used (how will you measure the DV?)
Procedure
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