MathDali Research Project Evaluation Report

MATHDALI RESEARCH PROJECT
Evaluation Report
Prepared by:
Chona Sandoval
Donna Batongbacal
KNOWLEDGE CHANNEL FOUNDATION, INC.
J u n e , 2 0 1 8

i
Table of Contents
Introduction.................................................................................................................................................. 1
Part 1: Research Background and Method.................................................................................................. 1
I. Rationale and Objectives of the MathDali Project............................................................................ 1
II. Mathdali Research Framework and Objectives................................................................................. 3
III. Method.............................................................................................................................................. 4
IV. Observations on the Research Method........................................................................................... 12
Part 2: Data Analysis .................................................................................................................................. 16
I. Results and Interpretation............................................................................................................... 16
II. Summary of Findings ...................................................................................................................... 25
Part 3: Recommendations for Future Research........................................................................................ 27

1
MATHDALI RESEARCH PROJECT
EVALUATION REPORT
INTRODUCTION
This report details the assessment findings conducted for the MathDali Research Project of the
Knowledge Channel Foundation, Inc. (KCFI).
The document is composed of three parts. The first part covers the MathDali Research Background and
Method. The write-up is based on the written documents provided by KCFI and the interviews with KCFI
officers and project staff. An assessment of the research method is provided at the end of this section.
The second part of the document focuses on Data Analysis and Summary of Findings for the studies
conducted in three areas – San Jose Del Monte (SJDM), Bulacan; Teresa and Morong, Rizal; and Bago
Bantay, Quezon City.
Recommendations for future research comprise the third part of the report.
PART 1: RESEARCH BACKGROUND AND METHOD
I. Rationale and Objectives of the MathDali Project
A. Problem Statement/Rationale for Project Implementation
 The country’s demand for graduates who possess skills in the field of Science, Technology,
Engineering and Mathematics (STEM) is not being met.
 Low Grade 6 NAT score in Math persists nationwide.
B. Project Goals and Objectives
 The MathDali Project’s goal is to increase enrollment in the STEM track by generating
interest in Math among grade schoolers. Specifically, it aims to:
1. develop in the students a positive attitude towards learning Math, and
2. contribute to better learning outcomes in Math
C. Project Strategy
 To achieve the project goals and objectives, the following strategies were identified:
1. Focus on Grade 4 students, the phase when Math performance in school starts to decline.

2
2. Develop a growth mindset among [Grade 4] Math teachers and students by introducing to
them Boaler’s1
mathematical mindset norms.
3. Make Math more meaningful and fun to learn by using the constructivist approach to
learning (Vygotsky, 1978).
4. Facilitate easier understanding of Math concepts through scaffolding (Vygotsky, 1978)
5. Enlist parents in supporting the children’s Math learning.
D. Intervention Components
 Based on the strategies identified, the MathDali Program was developed. MathDali is a
supplementary learning program for Grade 4 students, their Math teachers, and their
parents. The program includes the following components:
1. Math video program – 36 episodes of video shows with supplementary materials: 9
episodes per quarter corresponding to Grade 4 Math lessons based on the K-12 curriculum;
the videos incorporate the mathematical mindset norms by Boaler (2015) – 2 norms are
presented per video; the supplementary materials include (a) session guides on how to
incorporate the video to the Math lessons, and (b) Math worksheets that can be used for
skills practice of the students
2. Teacher training program – a one-day program given at the beginning of each school
quarter (total of 4 sessions for the whole school year). Each 1-day session consists of 5
modules: (1) Learning Theory: LEEP-Math which focuses on the constructivist approach to
learning; (2) Content: Grade 4 Math competencies per quarter (based on the K-12
curriculum); (3) use of the MathDali videos in the classroom (4) integration of learning
technology (computer-based Math games); and (5) orientation on Mathematical mindset
(Boaler, 2015)
3. Math computer games - Math games loaded on tablet computers to serve as learning aid in
the classroom; one tablet can be shared by 3-5 students
4. Parenting seminar – includes an orientation on the growth/mathematical mindset, tips on
how to guide children in studying Math, how to nurture children's potentials, and some
mathematical techniques that can be used in teaching children in the home
1
Boaler (2015) in Ramos, et. al (n.d.), The MathDali Project: Cycle 1 Full Report
Teacher Training
Parent Training
MathDali Videos
MathDali Games
Project

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All four components of the MathDali Program (video, teacher training, games, parenting
seminar) aim to bring about a growth mindset in students and increase Math performance.
II. MathDali Research Framework and Objectives
To determine the effectiveness of the MathDali Program, research was conducted parallel to its
implementation.
A. Conceptual Framework
An illustration of the initial MathDali research framework is shown below.
The video program, teacher training, computer games, and parent training served as the
Independent Variables (IVs). Learning Outcome (based on performance in a Math test) and
Attitude towards Math (based on the result of the Mathematical Mindset questionnaire) were
the two Dependent Variables (DVs).
The Math Computer Games and Parent Training components of the study were included in the
SJDM, Bulacan research. However, due to implementation issues (i.e. very few attended the
parent training, students expressed feelings of being overwhelmed by the use of the gadget,
teachers lacked compliance in using the games as a learning aid, etc.), it was decided that these
two components would not be included anymore in the Rizal and Quezon City studies. Thus,
only two IVs – namely, the MathDali videos and Teacher Training - were included in the Rizal and
Quezon City studies. The framework shown below illustrates the design of the Rizal and
Quezon City studies.
A
Videos/ Episodes
B
Teacher Training
Learning Outcomes
Attitudes towards Math

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B. Research Objectives
Over-all Objective
Determine which combination of the MathDali program component brings about more
improved learning outcomes and a more positive attitude towards learning Math.
Specific Objective
Describe changes in students’ Math performance resulting in the integration of MathDali
components in classroom instruction in selected Grade 4 classes. Specifically,
1. Compare pre-test and post-test score differences between experimental and control classes,
and across experimental classes.
2. Compare attitude towards Math at the start and end of MathDali project implementation.
3. Cull
opinions and insights on the usefulness of Math videos and interventions from teachers,
parents, and students.
C. Research Questions
If public school grade 4 classes are provided with the components contained in the Mathdali
Program (IVs), which group of students will show significant differences in learning outcomes
and attitude towards Math (DVs)?
III. Method
A. Research Design
 Quasi-experimental, pre-test/post-test/control group design
BULACAN
This study seeks to determine which combination of MathDali components will bring about
change in Math performance and attitude towards learning Math: (a) video alone, (b) video and
teacher training, or (c) video, teacher training, computer games, and parenting seminar.
 Experimental Group 1 – teacher
training, Math video, computer games,
and parent training
 Experimental Group 2 – teacher training
and Math video
 Experimental Group 3 – Math video
 Control group – no intervention
RIZAL
change in student Math performance and attitude towards learning Math: (a) video alone or (b)
video and teacher training

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 Experimental Group 1 – teacher training
and Math video
 Experimental Group 2 – Math video
 Control group – no intervention
QUEZON CITY
change in Math performance and attitude towards learning Math: (a) teacher training or (b)
video and teacher training.

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 Experimental Group 1 – teacher
training and Math video
 Control group – teacher training
The researchers did not provide clear hypotheses as to which program component or
components are expected to bring about improved performance in Math among Grade 4
students.
B. Sampling Method and Design
 In general, the non-probability sampling method (i.e. convenience sampling and
purposive sampling) were used in choosing participants for the study.
 Convenience sampling was used in choosing the school or schools division because the
main consideration was the willingness of the participants to partner with KCFI in
implementing the study.
 Purposive sampling was used at the school level and in the selection of teachers to
ensure comparability of participants’ characteristics (e.g. school performance in Math on
Grade 6 NAT, teacher competencies, etc.)
Bulacan:
 Schools Division Level: Convenience sampling - basis is the willingness of the schools
division to partner with KCFI on the research project
 School Level: Purposive Sampling - Based on Math NAT scores, 4 schools in SJDM with
comparable scores were chosen. The schools were then assigned as the experimental
and control groups (basis for the assignment of groups not known at the time of
evaluation).
San Jose Del Monte Central School – Experimental Group 1
Bagong Buhay E – Experimental Group 2
Bagong Buhay I – Experimental Group 3
Bagong Buhay F – Control Group
 Grade 4 Classes: Purposive Sampling - based on time slot to coincide with the MathDali
show, two Grade 4 sections in each school were chosen. A total of 8 classes, and 362
students, were included in the study. The control group has 99 students, experimental
group 1 has 84 students, experimental group 2 has 91 students, and experimental group
3 has 88 students.
 Teacher Level: The Math teachers of the chosen Grade 4 sections/classes automatically
became participants of the study
Rizal:

7
 Schools Division Level: Convenience sampling - basis is the willingness of the schools
division to partner with KCFI on the research project
 Teacher Level: Purposive Sampling - based on a diagnostic test (STAAR) conducted by
KCFI for ALL Grade 4 teachers in Rizal, four teachers (who happened to be Math
teachers) were selected from the list of test passers. These four teachers were also
recommended by the Division Superintendent based on their performance on the
teaching demonstration conducted.
 School Level: The schools where the selected four teachers teach were automatically
chosen to be part of the study. The schools were then assigned as the experimental and
control groups (basis for the assignment of groups not known at the time of evaluation.
Teresa ES – Experimental Group 1
Bombongan ES – Experimental Group 2
Maybancal ES – Experimental Group 2
Quiterio San Jose ES – Control Group
 Grade 4 Classes: The grade 4 classes/sections handled by the chosen teachers were
automatically selected as participants of the study. Experimental group 1 has 144
students, experimental group 2 has 126 students, and the control group has 134
students.
 Student Level: Students of the selected Grade 4 sections were given a diagnostic test
(Grade 3 Math test). All students who scored 5 points and above were selected as
participants of the study (around 2/3 of the class). Cut-off point was determined based
on the required number of participants per group.
In terms of implementation, the entire class watched the MathDali video but only the
selected participants took the MAT and Mathtitude test.
Quezon City:
 School Level: Convenience Sampling - based on the willingness of the Bago Bantay
Elementary School (BB ES) to partner with KCFI
 Teacher Level: There were only two Grade 4 Math teachers in BB ES so they were
automatically selected as participants of the study.
 Grade 4 Classes: The advisory class of the two Grade 4 Math teachers and the Grade 4
coordinator were purposively chosen as the experimental groups. The remaining Grade
4 sections automatically became part of the control group.
Experimental Groups (3): Sections Laurel, Quirino, and Aguinaldo (121 students)
Control Groups (4): Sections Roxas, Garcia, Osmena, and Magsaysay (157 students)
 Student Level: All students of these sections were included in the study.
C. Assessment Tools
 To assess the effectiveness of the intervention, assessment tools were either developed
or adapted by KCFI:
1. For Teachers:

8
(a) Math test for Grade 6 (STAAR) – diagnostic test on Math content recommended by a
Math expert. According to data and information provided, this was not tested for
validity and reliability.
(b) Mathtitude for Teachers – assessment of Growth/Math Mindset (7 norms)
- A 30-item, 4-point scale assessment adapted from Dweck’s (2008) growth
mindset questionnaire
- Pre-piloted to a set of Math teachers (number of teachers not specified); factor
analysis was conducted to test validity
2. For Students:
(a) Math test for Grade 3 – diagnostic test to assess learning level in Math. This was
developed by the KCFI staff based on the K-12 curriculum. According to data and
information provided, this was not tested for validity and reliability.
(b) Quarterly Math Assessment Test (MAT) – quarterly pre- and post-tests consisting of
lessons for the given period/quarter; content is based on the video lessons for the
period/quarter; pre-tests and post-tests are equivalent
- According to KCFI, MAT underwent validity and reliability testing
(c) Mathtitude for Students – assessment of Growth/Math Mindset (7 norms)
- 12 items from the Mathtitude for Teachers were adapted for student use
- The 4-point scale was turned into a 4-point smiley face scale
- The questionnaire was translated into Filipino and back-translated for
consistency
- The questionnaire was used as pre-test for the SJDM study
(d) Revised Mathtitude for Students
- The 12-item questionnaire was edited and additional items were included. The
revised 20-item Mathtitude questionnaire measures four concepts: (a) self-
efficacy (items 1-5); (b) perseverance (items 6-10); practical importance (items
12-16); and motivation (items 11, 17-20). The items were phrased either
positively (i.e. adhering to the growth mindset) or negatively (i.e. adhering to a
fixed mindset).
- According to KCFI, the 20-item Mathtitude questionnaire was tested for validity
and reliability
- The 20-item revised questionnaire was used as post-test for the SJDM, Bulacan
study and as pre-test/post-test tool for the Rizal and QC studies
(e) Student Demographic profile – a Demographic and Individual Data (DID) was
developed
(f) Secondary data: Phil-IRI, Math grades on report cards
D. Implementation Procedure
1. Needs assessment:
 Prior to the implementation of the research, a Needs Assessment was conducted
with the teachers and principal of the schools involved in the SJDM, Bulacan study.
The result of the assessment was used as input in the development of the video and
in the design of the teacher training program.

9
 Also, based on the participants’ evaluation of the teacher training program, program
designers and facilitators introduced revisions in the program design and/or
content.
2. Interventions:
BULACAN
a. Parent training: conducted on the 1st
week/start of each school quarter
b. Teacher training: conducted on the 1st
week/start of each school quarter
c. MathDali videos: Teachers of the 3 experimental groups were instructed to show
the video (corresponding to their lesson) as a learning resource during Math class.
The teachers were also instructed to use the supplementary materials to guide
them in integrating the video to their lesson.
Note: For the 1st
quarter, students of the Bulacan study experimental groups were
made to watch the TV airing of the MathDali program. For the 2nd
-4th
quarter, TV
sets and flash drives of the video programs were provided to the teacher of the
experimental groups.
d. Use of collaborative activities: For experimental groups 1 & 2, teachers were
instructed to incorporate their learning from the training program in their
classroom instruction, in particular the use of collaborative learning activities.
e. Math Mindset: For experimental groups 1 & 2, Teachers were “expected to exhibit
an attitude (in speech and in action) that promotes growth/math mindset in their
classroom. For instance, they should allow their students to learn from their
mistakes.”
f. Video games: For experimental group 1, teachers were instructed to use the tablets
loaded with games as learning aids for their Math class.
RIZAL
a. Orientation on the Research: conducted for the school principals and teachers prior
to the training
b. Teacher training: conducted for experimental group 1 on the 1st
week/start each of
quarter
c. MathDali videos: Teachers of the 2 experimental groups were instructed to show
the video (corresponding to their lesson) as a learning resource during Math class.
The teachers were also instructed to use the supplementary materials to guide them
in integrating the video to their lesson. (The experimental groups were each given a
TV set and external hard drive of the videos.)
d. Use of collaborative activities: For experimental group 1, the teachers were
instructed to incorporate their learning from the training program in their classroom
instruction, in particular the use of collaborative learning activities.
e. Math Mindset: For experimental groups 1 & 2, Teachers were “expected to exhibit
an attitude (in speech and in action) that promotes growth/math mindset in their
classroom. For instance, they should allow their students to learn from their
mistakes.”

10
QUEZON CITY:
a. Orientation on the Research: conducted for the school principals and teachers prior
to the training
b. Teacher training: given to the two Math teachers at the start of quarters 3 & 4
c. MathDali videos: For experimental group classes, the teachers were instructed to
show the MathDali video (corresponding to their lesson) as a learning resource
during Math class. Teachers were also instructed to incorporate their learning from
the training program in their classroom instruction. (The experimental groups were
given a TV set and external hard drive of the videos.)
d. Use of collaborative activities: For the control group, teachers were instructed to
incorporate their learning from the training program but not use the video in their
Math class.
e. Math Mindset: Because the teachers teach both experimental and control groups,
it is assumed that teachers exhibit in the classroom whatever positive attitude they
have learned in the training program.
3. Monitoring of Project Implementation:
BULACAN RIZAL QUEZON CITY
1. Teachers of
experimental groups 1
& 2 were provided with
viewing log sheets to
monitor the frequency
by which they use the
videos in class.
2. A separate log sheet
was also provided to
experimental group 1
to monitor the use of
the online game.
3. The KCFI staff
conducted weekly visits
to the schools and once
a month classroom
observation to monitor
implementation.
Random interviews
with students were also
conducted.
4. Attendance of
teachers/use of
substitute teachers not
monitored
1. Teachers of
experimental groups 1 &
2 were provided with
viewing log sheets to
monitor the frequency
by which they use the
videos in class.
2. The KCFI staff conducted
weekly visits to the
schools and once a
month classroom
implementation.
Random interviews with
students were also
conducted. An informal
survey was likewise
conducted.
3. Attendance of
teachers/use of
monitored
1. Teachers were
provided with viewing
log sheets to monitor
the frequency by which
they use the videos in
the experimental
groups.
2. The KCFI staff
conducted weekly visits
to the schools and once
a month classroom
implementation.
Random interviews
with students were also
conducted.
3. Attendance of
teachers/use of
monitored
4. Assessment

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For Teachers:
 Mathtitude for Teachers:
- Bulacan study: assessment conducted at the start of the project
- Rizal and Quezon City studies: assessment conducted at the end of the project
 Focus Group Discussion: For Bulacan, FGDs were conducted at the end of the program
to validate the quantitative data.
For Students:
 Math Assessment Test (MAT): Pre-test and post-test conducted for both experimental
and control groups at the beginning and end of each school quarter). The pre-test is
administered on the 1st
week of the quarter while the post-test is administered at the
end of the quarter before the schedule of the school quarterly exam.
 Mathtitude for Students: administered at the beginning and end of the research project.
 Focus Group Discussion: For SJDM, Bulacan, FGDs were conducted at the end of the
program to validate the quantitative data gathered
 End of Project Evaluation: For the Rizal and Quezon City, end of project evaluation were
conducted. This consists of written assessment for the teachers and focus group
discussion with the teachers and school principal.
5. Procedure for Data Analysis
SJDM, BULACAN
Statistical test used not specified in the UPCMC report itself, but it seems the analysis was
conducted as follows:
 To determine the effects of the MathDali video, computer games, and teacher training
components on MAT scores
1. Test of difference between groups (t-test) was applied and computed per quarter:
a. All Experimental Groups versus Control Groups
- Pre-Test Scores and Post Test Scores
b. Experimental Group 1 versus Control Group
c. Experimental Group 2 versus Control Group
d. Experimental Group 3 versus Control Group
2. Analysis using descriptive information: Trends seen from Q1 to Q4, based on
transmuted MAT Posttest mean scores

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 To determine MathDali effects on learning specific Math skills
Same as in #1, test of difference between groups (t-test), with items grouped according
to Math skills tested
 Predictor variables affecting student learning: Regression analysis
 Did MathDali improve attitudes toward Math? Statistical test used was unspecified, may
have been t-test
 What do teachers, parents and students say about MathDali as learning interventions?
Qualitative Analysis
RIZAL and QUEZON CITY
 To determine the effects of the MathDali video & teacher training components on MAT
scores, the following statistical test will be applied and computed per quarter:
(1) Two-way Mixed ANOVA. It's two-way because there are two IVs – treatment group
(experimental vs. control) and time (pretest vs. posttest). It's mixed because it's a
repeated-measures ANOVA, but with 2 groups (for QC, 3 groups for Rizal) undergoing
different treatments -- the analysis will not only be within-subjects but between-
subjects. Results will show whether subjects perform differently (that is, from pretest to
posttest) in different experimental conditions.
Pretest Posttest
Experimental 1 Experimental 1 Pre Experimental 1 Post
Experimental 2 Experimental 2 Pre Experimental 2 Post
Control Control Pre Control Post
 To investigate whether MathDali video & teacher training are effective in teaching all
Math skills, or for certain skills only
Topic scores analysis to see pattern of scores per Math skills/topics. T-tests will be done
to test significance of difference between groups in gain scores (posttest minus pretest
scores)
 To determine whether there is an improvement in attitudes towards Math
Two-way mixed ANOVA, same with assessment of change in MAT scores
IV. Observations on the Research Method
A review of related literature by KCFI points to the importance and effectiveness of teacher-
student interaction and use of multimedia resources in improving student performance. Given
this, investing in a program that (1) advocates the use of videos, games, and collaborative
activities in teaching Math; and (2) inculcates the value of having a growth mindset in teaching
and learning Math can be considered as a significant initiative and an excellent way to support
the public school system.

13
KCFI’s effort to assess the impact of the MathDali program through the conduct of research is
crucial in making sure that that the needs of the teachers and students are appropriately
addressed by the program. However, an assessment of the research methods used revealed
that several factors considered as extraneous variables appear to have influenced the result of
the studies conducted.
Research Validity
Extraneous variables are variables that may compete with the IV in explaining the outcome of a
study. A confounding variable is an extraneous variable that is related to the IV and affects the
DV. Extraneous and confounding variables serve as threats to the validity of a research. Threats
to internal validity make it difficult for a researcher to claim that a relationship exists between
the IV and the DV. Threats to external validity, on the other hand, lower the researcher’s
confidence in stating whether the results of the study are applicable to other groups.
In general, public schools are considered as open systems. As such, there are too many variables
present in its environment and inherent to the teachers and students that will be difficult to
control. Conducting an experimental or quasi-experimental study in public schools therefore,
opens the researcher to numerous elements that may confound the study being conducted.
In addition to the realities of the public school system, appropriateness of the research methods
used and adherence to implementation procedures are also factors that need to be evaluated to
ensure the validity of a research.
Based on the assessment conducted for the MathDali Research project, below are some factors
that may serve as extraneous or confounding variables in the Bulacan, Rizal, and Quezon City
studies.
A. Measure of Growth Mindset:
 Based on the information gathered, it appears that the hypothesis for the Mathtitude is
that students will develop a growth mindset through regular exposure (a) to the Math
videos, and (b) to teachers with a Mathematical mindset
 Since the teachers who participated in the study were not given a Mathtitude
assessment test, there must be one or several of the following for this hypothesis to
work:
(a) The teachers of the experimental group [with teacher training component] either
possess the growth mindset at the start of the project, or were able to imbibe the
growth mindset presented during the teacher training.
(b) The teachers of the experimental group [with teacher training component] were
able to effectively use/practice the growth mindset principles/norms when they
teach Math.
(c) The teachers of the experimental and control groups [with no teacher training
component] do not exhibit a growth mindset when they teach Math.
 These are risky assumptions that may lead to the presence of confounding variables in
assessing the impact of teacher training in the students’ growth mindset.

14
 One way to address this problem is to assess growth mindset using qualitative research.
For instance, the researcher can assess students’ knowledge of the 7 norms, determine
where they acquired the knowledge, and ask how these norms helped them in learning
Math.
B. Assessment Tools/Instrumentation
1. Validity: The assessment tools have to be tested for content or construct validity
2. Reliability: The assessment tools need to be pre-tested for all 3 studies conducted. Since
the characteristics of the subjects differ across research groups, it is important to do this
to ensure the reliability of the tools
3. Interaction Effect of Testing: Administering similar pre-test and post-test may pose as a
threat to the test’s internal validity. One way to address this is for the researcher to use
the Randomized Solomon Four-Group Research Design:
(a) 2 experimental groups: 1 group is given a pre-and post-test, the other group is
given only a post-test
(b) 2 control groups: 1 group is given a pre-and post-test, the other group is given
only a post-test
(c) Treatment is given to both experimental groups
4. Mathtitude Questionnaire
 The questionnaire was changed midway into the implementation of the Bulacan
study.
5. Use of Smiley Face Likert Scale (SFLS)
 There is a need to review the Mathtitude questionnaire to determine whether the
Smiley Face Likert Scale (SFLS) is an appropriate scale to use (e.g. sad face
representing “strongly disagree”; happy face representing “strongly agree”). Are
Grade 4 students truly able to make the value judgments required by the
questionnaire? Perhaps it is worth investigating whether it would be better to use
the five degrees of happiness scale instead of the traditional SFLS considering too
that children are prone to social desirability bias2
.
C. Sampling Design/Selection of Participants
 For SJDM, Bulacan study, Grade 4 sections were chosen based on time slot (i.e. class
schedule coinciding with the MathDali TV airing). Similarly, teacher competency was
not tested. Experimental and control groups, therefore, may not be comparable.
 In the Quezon City study, two teachers were assigned to handle classes in both the
control and experimental groups. It seems it was meant to control the teacher
factor. However, having two teachers within an experimental group and within a
control group can be potentially problematic. Varying teaching styles, personalities,
and so on serve as extraneous factors that can affect students’ performance. One
2
Read & Fine, 2005, cited in Hall (2017), Five Degrees of Happiness: Effective smiley face Likert scale for
evaluating children,
https://www.researchgate.net/publication/305726958_Five_Degrees_of_Happiness_Effective_Smiley_Face_Li
kert_Scales_for_Evaluating_with_Children

15
possible solution is to analyze the datasets separately. In this case, care should also
be taken in ensuring the comparability of the sections (under each teacher) prior to
combining them in one experimental group.
 For the Rizal study, two schools were combined to form part of Experimental Group
2 in order to attain the desired sample size. However, combining two different
schools in one treatment group is not recommended as it increases the possibility of
having extraneous variables (e.g. differing school environments, teaching styles,
teacher personalities etc.), as in the case of the Quezon City. The simplest solution
then would be to exclude one of the two schools from the experimental group.
D. Implementation of Teacher Training:
 Lack of standardization in the conduct of the teacher training
(a) Content and design of the training – based on the data gathered, changes in the
design of the training program were introduced midstream to respond to the needs
of the participants (e.g. addition of Math content in the program which was initially
not part of the design)
(b) Length of training - some of the research participants underwent a three-day LEEP
training (i.e. Rizal teachers), others underwent a two-day training program, while
still others participated in the 1-day training designed for the MathDali project)
(c) Size and profile of the training participants - there were teachers who were trained
together with a group who were not part of the research study. The way the
training is conducted and the type of instructions given in terms of using the videos
(e.g. for the LEEP participants, the videos were distributed randomly and teachers
were instructed to share them to other teachers) may differ in this case.
(d) Training venue - some were conducted in the schools and some were conducted in
the KCFI office
(e) Attendance – interview data also revealed that in certain cases, not all teachers who
were selected as research participants attended all the quarterly teacher training
E. Orientation of Participants on the Research Process
 The manner of orienting the research participants, more particularly the teachers, on
the research procedure apparently varied across research participants. According to
the data gathered, “Teachers were briefed, e-mailed, texted” to inform them about the
process and procedures for implementation.
F. Integration of the MathDali Video in Classroom Instructions
 Based on the data gathered, it appears that teachers tended not to use the MathDali
video session guides and accompanying activity worksheets.
G. Discontinuation of Intervention Component
 The introduction and eventual removal of the computer game may have had an effect
on the performance of experimental group 1, SJDM Central School.
H. Reactive Effects of Experimental Arrangements and Compensatory Rivalry

16
 Because research participants (teachers and students) know that they are being
assessed, there is a tendency for them to perform better than they would do in normal
circumstances (Hawthorne Effect).
 Research participants (teachers and students) in the control group may tend to compete
with the experimental group to prove that they can perform at par or better than the
experimental group even without the interventions which, in this case, are the MathDali
program components (John Henry Effect). This appears to be present in the Rizal study.
 Related to this, it was also found that teachers of both experimental and control groups
in the Rizal study use Math videos either downloaded from the internet or provided by
DOST.
I. Experimental Mortality
 Some of the teachers who were initially identified to participate in the study “dropped
out” of the program as they were given other assignments in school or had to take a
leave of absence. Because of this, new teachers had to be assigned to teach the
experimental group/class. The replacement teachers also did not have the benefit of
undergoing a complete training program.
 This occurred for both the SJDM, Bulacan study and the Rizal study (teacher of Teresa
ES)
 Interview data also revealed that as a result of the drop-out of teachers from the
Bulacan study, students of the group under the said teacher had to be dispersed and
transferred to different sections.
J. History
 It is important to determine whether there were events that occurred during the
implementation of the study that could have affected the result of the study. For
example, in Rizal, it was found that TERESA ES receives support from the school alumni
in the form of school equipment, learning aids, and other school needs. The School
District also provided INSET on Singapore Math. It was not clear, however, who among
the research participants attended the Singapore Math training and if they were they
able to complete the program.
PART 2: DATA ANALYSIS
I. Results and Interpretation
A. San Jose Del Monte, Bulacan3
The researchers of the SJDM, Bulacan study concluded that, overall, MathDaliinterventions
contributeto learningwhenthe video lessons are supported by teacher training. Findings
were reportedly consistent in demonstrating the key role ofteacher training in Math
learning, while exposure to videos alone barely created any impact on the students’ Math
3
Based on the evaluation report of UP College of Mass Communication Foundation (June, 2017).

17
performance.
According to the report of the UP College of Mass Communication Foundation, experimental
classes in general produced significant differences compared to the control group in all test
quarters, with the MathDali videos+teacher training having the most consistent advantage
over Control classes for all four quarters, whatever the topic for each quarter. Adding other
interventions such as games and parent trainings did not bring about appreciable
improvements in performance. The researchers posited two possible explanations:
“crowding” of interventions that could have affected the effectiveness of the materials; and
lack of funding and resources from the schools to sustain such interventions.
In terms of math skills or topics, videos were found to be mosteffective inMeasurement. On
the other hand, none of the MathDali interventions reflected any changes in scores of
students when it comes to Geometry skills. No findings were presented regarding the other
math skills tested by the Math Assessment Test.
Findings on attitude towards learning Math were found to be positive. Students from the
experimental groups scored significantly higher posttest scores than the control group,
particularly those groups with both video+teacher training, indicating that they have better
overallattitude forMath.
B. Teresa & Morong, Rizal 4
For the Rizal data set, the entire sample from Bombongan ES was removed from
Experimental Group 2 because initially it was combined with Maybancal ES to form an
experimental group. Having two teachers from two different schools would lead to even
more extraneous and potentially confounding variables, so the decision was made to
remove one school from the group for the analysis.
A mixed ANOVA was done for each quarter, with treatment groups and time (i.e. Pretest and
Posttest) as independent variables, and MAT scores as dependent variable. A mixed ANOVA
was also done for testing the same independent variables, and Mathtitude scores as
dependent variable. One-way ANOVA was also used in some instances depending on the
results. For this discussion, the treatment groups are referred to as:
LD1: Experimental Group 1, Video and teacher training
LD2: Experimental Group 2, Video only
LD3: Control group, no intervention
[Note: Sample sizes differ from quarter to quarter for various reasons (missing data, removal
due to inconsistencies and apparent errors in encoding, deletion of extreme scores, etc.).]
4
For Rizal and Quezon City, refer to Appendix A: A Guide to Understanding and Interpreting Mixed ANOVA
Results. For readability, statistical figures are not mentioned in the main body of the report and are instead
located in Appendix B. Statistical Test Results.

18
Quarter 1
(LD1 N = 129; LD2 N= 81; LD3 N = 152)
Figure 1. Interaction of treatment group and time on MAT scores, Rizal Quarter 1.
There is no significant interaction effect, but both time and treatment groups have
significant effects on MAT scores. This shows that overall the increase from pretest to
posttest scores within-groups is significant. The difference between treatment groups
overall is significant as well, specifically between LD1 vs. LD2, and LD1 vs. LD3 . However in
terms of gains in scores based on a one-way ANOVA, it appears that there is no significant
difference between treatment groups, indicating that the change in scores cannot be
attributed to the treatment.
It should be noted that to begin with, the difference in pretest scores between groups was
statistically significant as well. This could possibly be due to other extraneous factors (for
instance, selection bias. Were there high-performing students in LD1 that affected the
result? If so, the change in scores from pretest to posttest could be due to characteristics
inherent in the LD1 group, and not due to introduction of any intervention).

19
Quarter 2
(LD1 N = 99; LD2 N = 67; LD3 N = 106)
There is a significant interaction between treatment groups and time. As depicted in the
graph above, treatment groups apparently changed at different rates. Pretest scores are
close together, and when tested, showed no significant differences between groups. Testing
for the simple effect of treatment groups on MAT scores by running a one-way ANOVA on
gain scores, it appears that there is a significant difference between LD1 vs. LD3, and LD2 vs.
LD3, but none between LD1 and LD2, the experimental groups. This indicates that both
video plus teacher training, and video alone, produced increases in MAT scores from pretest
to posttest. Further, a one-way ANOVA to test for the simple effect of time shows that the
increase in MAT scores from pretest to posttest is significant in LD1 and LD2, but not in LD3.
In this case therefore, we can say that the experimental groups’ scores grew over time but
the control group did not.

20
Quarter 3
(LD1 N = 58; LD2 N = 62; LD3 N = 100)
For this quarter there is also a significant interaction between treatment groups and time. As
with the previous quarter, the treatment groups appear to have changed at different rates
over time. A look into simple effects reveals that there is no difference between the
treatment groups in terms of pretest scores (as should be), but there is a difference in
posttest scores, specifically between LD1 vs. LD2, and LD1 vs. LD3. There is no difference
between LD2 and LD3, however, indicating treatment group that had only video had no
appreciable advantage over the control group. This suggests that teacher training with video
brought on the significant effect on MAT scores.

21
Quarter 4
(LD1 N = 99; LD2 N = 62; LD3 N = 100)
The change in scores over time varies depending on the treatment group, as a significant
interaction effect is again observed in the graph above. There is a significant difference
between LD1 vs. LD2, and LD1 vs. LD3, but not between LD2 vs. LD3. In terms of gain scores,
there is no difference between LD1 and LD2, the experimental groups, while the control
group differs from both the experimental groups. This indicates that the use of videos,
whether with or without teacher training, brings about a change in scores over time.
Mathtitude
(LD1 N = 120; LD2 = 68; LD3 = 129)
Figure 5. Interaction of treatment group and time on Mathtitude scores, Rizal.
A significant interaction between treatment groups and time exists, with time having a
significant main effect, but treatment groups having none on Mathtitude scores. Looking
further into the simple main effect of time, however, reveals that the experimental groups

22
LD1 and LD2 differed significantly from the control group LD3 in terms of pretest scores, but
not posttest scores as expected. In addition, an inspection of gain scores shows that
contrary to expectation, Mathtitude scores decreased substantial in each group: 47% in LD1,
22% in LD2 and 47% in LD3.
If one looks back to method, it was mentioned that hypotheses were not clearly presented
by researchers during the design phase of this study. While attitude towards learning Math
was identified as a secondary dependent variable (DV), as measured by a Mathtitude test
anchored on components of a growth/Math mindset, it is unclear exactly how that
growth/Math mindset is passed on to students in tangible terms, particularly where
experimental group LD1 (video and teacher training) is concerned. Is this intervention
supposed to have a greater impact on Mathtitude compared to the other one (LD2, video
only)? If so, how? Even with LD3, the control group which was supposed to have no
intervention, it cannot be ascertained that growth/Math mindset was completely absent.
C. Bago Bantay, Quezon City 5
For the Quezon City data set, there are only two treatments being compared, that is -
LD1: Experimental Group, Video and teacher training
LD2: Control Group, Teacher training only
Initially, the groups were set up such that each one had multiple sections taught by two
different teachers. In an effort to control the teacher factor, sections taught by only one
teacher were retained, and the others removed. Since the same teacher taught both the
experimental and control group, the possibility that differing teacher abilities may confound
the results is eliminated. The same procedure employed in the Rizal data set was used for
this part of the analysis, except that t-tests were done in place of one-way ANOVA to
supplement mixed ANOVA results.
[Note: Sample sizes differ from quarter to quarter for various reasons (missing data, removal
due to inconsistencies and apparent errors in encoding, deletion of extreme scores, etc.).]
5
For Rizal and Quezon City, refer to Appendix A: A Guide to Understanding and Interpreting Mixed ANOVA
Results. For readability, statistical figures are not mentioned in the main body of the report and are instead
located in Appendix B. Statistical Test Results.

23
Quarter 3
(LD1 = 77; LD2 = 77)
Figure 6. Interaction of treatment group and time on MAT scores, Quezon City Quarter 3.
Mixed ANOVA results showed significant results for the interaction between time and
treatment groups, and for the main effects of both time and group. (Note that if the lines of
the graph were to extend on the left side, they would most certainly cross each other.) It
appears that the two groups changed at varied increments from pretest to posttest. Gain
scores of the two groups are significantly far apart, and posttest scores are significantly
different too, with LD1 being greater than LD2. The use of videos in addition to teacher
training could possibly account for the improvement in MAT scores. However, a t-test on
pretest scores shows a significant difference between groups, so pre-existing characteristics
within the groups or such other factors cannot be completely ruled out.

24
Quarter 4
(LD1 = 78; LD2 = 67)
Figure 7. Interaction of treatment group and time on MAT scores, Quezon City Quarter 4.
Results are much the same for Quarter 4 and Quarter 3, showing a significant interaction
effect between time and treatment groups, and significant main effects for both time and
treatment groups. Pretest scores between the groups are also significantly different to begin
with, suggesting that there could possibly be another extraneous factor that could have
affected the varying posttest scores. As with the previous quarter then, the use of videos
along with teacher training could possibly have led to an increase in MAT scores, but other
factors within the groups could also have affected the results.

25
Mathtitude
(LD1 N = 69; LD2 N = 43)
Figure 8. Interaction of treatment group and time on Mathtitude scores, Quezon City.
Results for Quezon City are non-significant where Mathtitude scores are concerned. There
are no main effects and no interaction effects between time and treatment groups, even
with the lines intersecting in the graph. Contrary to hypothesis, a reduction in Mathtitude
scores occurred in the case of LD1 while LD2 shows a slight increase. A look at gain scores
reveals that 49% of students in LD1 had a decrease in Mathtitude scores, compared to 37%
in LD2. It is entirely possible that something else could have affected the posttest scores. No
other inferences can be made given these results. 6
The same problems present in the case of Rizal also apply here. In this case, even if the same
teacher taught both the experimental and control group, the question remains on what
amounts exactly was growth/Math mindset administered to each group. Was LD2 (teacher
training only) expected to have less of an impact on Mathtitude? If so then why does LD1
show a decrease in Mathtitude scores and LD2 an increase? Can it be ascertained that no
other input was given to LD2 that could have affected the students’ attitude in learning
Math? Or could there have been some other factor that accounts for the results (for
instance, test fatigue, the time of day the test was administered, the presence of stressors,
and so on)?
6
Reliability of the Mathtitude Questionnaire (based on Quezon City pretest scores, N = 250) was computed to
be at an acceptable level with  = 0.70.

26
Topic Scores Analysis
(LD1 N = 62; LD2 N = 64)
In order to examine performance on the Math Assessment Test based on specific skills, or
topics, gain scores were obtained per topic and treatment group. A t-test for each topic
shows a significant difference between groups in Geometry for Quarter 3 and 4. No such
difference is found for the rest of the topics: Patterns and Algebra (Q3), Measurement (Q3)
and Statistics and Probability (Q4). It is interesting to note that there appears to be a wide
disparity in gain scores between groups where Geometry is concerned. It could be possible
that videos and teacher training combined had an effect in the improvement in scores.
Considering that the scores were obtained across two quarters where two different forms of
MAT were used, one cannot make comparisons across quarters especially since equivalence
of the tests (i.e., in terms of difficulty) has not been demonstrated. It is reasonable to make
comparisons within quarters, however. Based on the graph below, Geometry for each
quarter shows the most improvement in scores. Perhaps the teaching of Geometry is
enhanced by the use of visual aids, and videos in particular, compared to topics like Algebra
or Statistics? It may be a question worth exploring in future studies.
Figure 9. MAT topic gain scores per treatment group, Quezon City.

27
II. Summary of Findings
The significant results of the three studies and relevant findings are summarized in the table
below.
Studies Findings
SJDM, Bulacan Overall, MathDali contributes to learning when video lessons are supported
by teacher training. Exposure to videos alone barely created any impact on
students’ math performance. In terms of Math skills/topics, videos were
found to be most effective in Measurement.
In terms of attitude towards Math, MathDali interventions, specifically those
that combine videos with teacher training, produced better overall attitude.
Rizal Q1 Improvements from pretest to posttest scores were significant within each
group but gains in scores were not between groups. Treatment groups also
differed in pretest scores to begin with, indicating that the change in scores
cannot be attributed solely to the Mathdali interventions.
Rizal Q2 Both experimental groups’ scores grew from pretest to posttest while
control group scores did not. Both video plus teacher training package, and
video alone, produced significant increases in Math performance.
Rizal Q3 The experimental group that received video plus teacher training exhibited a
significant improvement in Math performance, while the experimental
group that was given video only had no appreciable advantage over the
control group.
Rizal Q4 MAT scores significantly improved from pretest to posttest, with both
experimental groups showing greater increments compared to the control
group. This indicates the use of videos, whether supplemented with teacher
training or not, brings about a positive change in Math performance.
Rizal Mathtitude MathDali interventions did not produce significant improvements in
Mathtitude scores. The experimental group that received videos only had
the greatest observable increase in scores but its difference from the other
groups was not statistically significant. Contrary to expectation, scores
decreased in a substantial percentage of students no matter what
intervention was given.
QC Q3 The experimental group (videos with teacher training) showed a significantly
greater improvement in Math performance compared to the control group,
but the possible effect of other extraneous factors cannot be completely
ruled out.
QC Q4 As with Q3, the use of videos with teacher training could have led to an
improvement in Math performance, but extraneous factors could also have
affected the results.
QC Mathtitude Non-significant results were obtained. As with Rizal, contrary to expectation,
a substantial percentage of students in both groups manifested a decrease
in Mathtitude scores.
QC Topic Scores Significant differences between groups were found in Geometry for
Quarters 3 and 4, suggesting that videos with teacher training could be most
effective in these topics compared to others.
In almost all instances, experimental groups that received both videos and teacher training
produced greater improvements in Math performance. The SJDM, Bulacan study found that the

28
same brought positive changes in attitude towards Math, but the other studies in Rizal and
Quezon City obtained non-significant results. It should be noted that, despite the significant
results, these findings should not be considered conclusive given the internal validity concerns
discussed in the Observation and Results sections of this report. That is to say, there is not
enough strong, consistent evidence to support the findings across studies and across quarters.
PART 3: RECOMMENDATIONS FOR FUTURE RESEARCH
Following are the recommendations based on the observations and findings discussed in this
evaluation:
A. Provide SMART Program Goals and Objectives
At the start of any program or project, SMART (specific, measurable, attainable, relevant and
time-bound) goals and objectives should be set so that the outcome and impact of
interventions can be monitored and evaluated for the purpose of further improving the
program.
B. Clearly state research hypotheses
When conducting a research study, it is crucial that hypotheses are clearly stated at the
outset. This means not only explicitly stating assumptions and expected outcomes but
clearly defining all the variables being studied. In experimental or quasi-experimental
designs particularly, this process, called operationalization of variables, can be crucial in
every step, be it in the manipulation of independent variables, the measurement of
dependent variables, and even in the analysis of results. Clear hypotheses are essential in
determining the most appropriate method (research design, sampling design, statistical
analysis, etc.) for the research.
C. Use assessment tools that will produce enough variation in outcomes and result in a more or
less normal distribution
One specific observation that is also relevant where monitoring and evaluation are
concerned relates to the Math Assessment Test. Note for instance, in the analysis of the
Rizal and Quezon City data sets, how mean MAT scores ranged from 7 to 16 points (out of a
maximum 30 points). It is suggested that achievement tests, especially ones that are
intended to assess public school students, should not be overly difficult. The test should
have a reasonable number of easy as well as moderately difficult items, and not too many
difficult ones. The effect of having an overly difficult test is a skewed distribution, with
students scoring around the low end. There will also be a bias against low and average
performing students, in that the effects of interventions meant to improve performance may
still not result in substantial increases due to the inherent difficulty of the test. By the same
token, there is an added risk that only high performing students will show changes in
performance.

29
D. Find alternatives to experimental/quasi-experimental designs
Designing and conducting experiments involves a rigorous process that adheres to strict
standards. As such, there are certain requirements and measures that make them quite
difficult to implement in the real world. Even with quasi-experiments where random
assignment of subjects to treatment conditions is not carried out, having groups that are
comparable can prove to be a challenging task. In the educational setting, this means
matching participants at all levels depending on the scope of the research: comparable
students, comparable teachers, comparable schools, and comparable environments.
“Environments” in the context of the Philippine public school system refers to various
aspects: school type (whether central, non-central, satellite, etc.), area classification
(whether urban or rural), geographical location, income classification, and so on. The failure
to ensure comparability opens the quasi-experiment to a host of possible extraneous
variables which left unchecked, become threats to internal validity. Even when one finds
comparable participants at say, the school level, and somehow conducts a very well-
controlled experiment, the possible trade-off is a threat to external validity, i.e., the results
of the research might not be applicable to a substantial enough number of schools in the
country.
Instead of conducting quasi-experiments, other more practicable but worthwhile studies can
be done. The question should no longer be “Are videos effective?”, for the direction of
learning in the 21st
century seems to have gone past that question, with visual materials
being a must. The current issues now are interactivity, collaborative learning, and so on.
Perhaps a better question to ask is “Which videos of Knowledge Channel are the most
effective, and why?”. In the same vein, which videos do not seem to have the desired effect?
What about them can be improved to make them more effective? Certainly while the trend
is toward using more of technology, and in more advanced forms, the reality is that even the
most basic issues such as reading readiness are still problematic where the Philippine public
school system is concerned. Given this, the challenge is in finding ways to integrate videos
into more conventional methods of teaching: how can videos successfully aid learning? If the
findings of this evaluation and other research point to the crucial role of teacher training in
conjunction with the use of videos in lessons, then Knowledge Channel should provide the
interventions and monitor/assess systematically.
Further than these, efforts should continually be directed towards keeping in touch with the
changing demands of learning and finding ways to respond to them while adapting to the realities in
Philippine schools.

30
APPENDIX A
A Guide to Understanding & Interpreting Mixed ANOVA Results
The ANOVA design used for the Rizal and Quezon City studies are set up as a two-way mixed ANOVA.
Two-way meaning there are two independent variables (IV): treatment groups (experimental vs.
control) and time (pretest vs. posttest).
It's a mixed ANOVA because the same participants were used to manipulate one IV (time), but
different participants were used to manipulate the other IV (treatment groups). In the first instance,
it is said to be a repeated-measures or within-groups IV, and the other, a between-groups IV.
For the repeated-measures, measurement of the dependent variable (DV) – MAT scores in the first
round, and Mathtitude scores in the second) – was done prior to the intervention (Pretest), and
after the intervention (Posttest). This is the WITHIN-GROUPS part of the analysis.
For the BETWEEN-GROUPS analysis, the IV being manipulated is treatment groups. For Quezon City
there were 2 groups (teacher training, and video with teacher training), while for Rizal there were 3
groups (video only; video with teacher training; and no intervention).
The analysis described above can be illustrated thus -

31
The ANOVA analyzes differences between group means. For instance:
Group Pretest
(Mean Score)
Posttest
(Mean Score)
Experimental 1 10.79 11.75
Experimental 2 8.37 9.4
Control 9.02 10.13
The most important points that are being investigated are:
 The Experimental Group’s Posttest Scores vs. Control Group Posttest Scores
 Whether pretest scores are equivalent (or at least not significantly different)
 If the change in the Experimental Group from Pretest to Posttest is greater than in the Control
Group
 If there is more than one Experimental Group: which treatment brings about greater change?
Interpreting Profile Plots
 If the lines are parallel: no interaction
 If the lines cross or touch slightly, there may be an interaction which may or may not be significant
 The presence of an interaction implies that the IVs are not independent
 The degree to which the lines cross each other has an implication on whether or not they are
statistically significant
 If the lines do not cross or touch, as long as the slopes are different, there may still be a significant
interaction

32
 In a two-way ANOVA with 3 x 2 design (i.e., there are 3 levels in the first IV, and two levels in the
second IV), interpretation may be slightly more complicated. Main effects will have to be studied
further to avoid misleading conclusions. This sometimes means looking at simple main effects,
meaning the effect of the first IV at each level of the second IV.

33
APPENDIX B
STATISTICAL TEST RESULTS
A. MIXED ANOVA
RIZAL Quarter 1
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
10.79
3.97
11.75
4.17
129
LD2 Mean
S.D.
8.37
3.44
9.4
3.75
81
LD3 Mean
S.D.
9.02
3.35
10.13
3.71
152
Tests of Within-Subjects Contrasts
Measure: MATscore
Source Time
Type III Sum of
Squares df Mean Square F Sig.
Partial Eta
Squared
Time Linear 179.099 1 179.099 29.192 .000 .075
Time * Group Linear .730 2 .365 .060 .942 .000
Error(Time) Linear 2202.536 359 6.135
Tests of Between-Subjects Effects
Measure: MATscore
Transformed Variable: Average
Source
Type III Sum of
Partial Eta
Squared
Intercept 66249.835 1 66249.835 3017.206 .000 .894
Group 674.414 2 337.207 15.357 .000 .079
Error 7882.687 359 21.957

34
Multiple Comparisons
Measure: MATscore
(I) Group (J) Group
Mean
Difference
(I-J)
Std.
Error Sig.
95% Confidence
Interval
Lower
Bound
Upper
Bound
Tukey HSD LD1 LD2 2.39
*
.470 .000 1.28 3.49
LD3 1.70
*
.397 .000 .77 2.63
LD2 LD1 -2.39
*
.470 .000 -3.49 -1.28
LD3 -.69 .456 .286 -1.76 .38
LD3 LD1 -1.70
*
.397 .000 -2.63 -.77
LD2 .69 .456 .286 -.38 1.76
RIZAL Quarter 2
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
7.15
2.11
9.75
4.27
99
LD2 Mean
S.D.
6.76
2.26
9.37
3.95
67
LD3 Mean
S.D.
7.21
2.34
7.83
2.77
106

35
Measure: MATscore
Source Time
Type III Sum of
Squares df
Mean
Square F Sig.
Partial
Eta
Squared
Time Linear 493.251 1 493.251 54.528 .000 .169
Time * Group Linear 126.783 2 63.392 7.008 .001 .050
Measure: MATscore
Source
Type III Sum of
Partial Eta
Squared
Intercept 33528.774 1 33528.774 3567.293 .000 .930
Group 89.656 2 44.828 4.769 .009 .034
Error 2528.315 269 9.399

36
Measure: MATscore
(I) Group (J) Group
Mean
Difference
(I-J)
Std.
Error Sig.
95% Confidence Interval
Lower
Bound Upper Bound
Tukey HSD LD1 LD2 .38 .343 .506 -.43 1.19
LD3 .93
*
.303 .007 .22 1.64
LD2 LD1 -.38 .343 .506 -1.19 .43
LD3 .55 .338 .239 -.25 1.35
LD3 LD1 -.93
*
.303 .007 -1.64 -.22
LD2 -.55 .338 .239 -1.35 .25
RIZAL Quarter 3
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
9.86
3.38
16.48
5.27
58
LD2 Mean
S.D.
9.66
3.08
12.73
4.64
62
LD3 Mean
S.D.
10.6
2.73
11.91
4.38
100
Measure: MATscore
Source Time
Type III Sum of
Partial Eta
Squared
Time Linear 1393.745 1 1393.745 157.163 .000 .420

37
Measure: MATscore
Source
Type III Sum of
Partial Eta
Squared
Intercept 58512.377 1 58512.377 2625.880 .000 .924
Group 322.078 2 161.039 7.227 .001 .062
Error 4835.402 217 22.283

38
Measure: MATscore
(I) Group (J) Group
Mean
Difference
(I-J)
Std.
Error Sig.
Lower
Bound
Upper
Bound
Tukey HSD LD1 LD2 1.98
*
.610 .004 .54 3.42
LD3 1.92
*
.551 .002 .62 3.22
LD2 LD1 -1.98
*
.610 .004 -3.42 -.54
LD3 -.06 .540 .993 -1.33 1.21
LD3 LD1 -1.92
*
.551 .002 -3.22 -.62
LD2 .06 .540 .993 -1.21 1.33
RIZAL Quarter 4
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
8.81
3.16
13.09
4.67
99
LD2 Mean
S.D.
7.18
2.1
10.11
4.43
62
LD3 Mean
S.D.
8.76
2.47
10.01
3.29
100
Measure: MATscore
Source Time
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
Time Linear 989.680 1 989.680 120.256 .000 .318

39
Measure: MATscore
Source
Type III Sum of
Partial Eta
Squared
Intercept 46360.447 1 46360.447 2897.011 .000 .918
Group 461.439 2 230.720 14.417 .000 .101
Error 4128.737 258 16.003
Measure: MATscore
(I) Group (J) Group
Mean
Difference
(I-J) Std. Error Sig.
Lower
Bound
Upper
Bound
Games-Howell LD1 LD2 2.30
*
.472 .000 1.19 3.42
LD3 1.56
*
.409 .001 .60 2.53
LD2 LD1 -2.30
*
.472 .000 -3.42 -1.19
LD3 -.74 .414 .178 -1.72 .24
LD3 LD1 -1.56
*
.409 .001 -2.53 -.60
LD2 .74 .414 .178 -.24 1.72

40
RIZAL Mathtitude
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
64.94
6.71
65.84
6.32
120
LD2 Mean
S.D.
61.65
6.87
65.72
6.28
68
LD3 Mean
S.D.
64.22
6.64
64.57
6.0
129
Measure: Mathtitude
Source Time
Type III Sum of
Squares df
Mean
Square F Sig.
Partial Eta
Squared
Time Linear 459.996 1 459.996 15.924 .000 .048
Measure: Mathtitude
Source
Type III Sum of
Partial Eta
Squared
Intercept 2431377.905 1 2431377.905 44637.303 .000 .993
Group 274.681 2 137.340 2.521 .082 .016
Error 17103.468 314 54.470

41
QUEZON CITY Quarter 3
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
10.88
2.94
16.23
6.07
77
LD2 Mean
S.D.
9.66
2.37
12.04
4.05
77
Measure: MATscore
Source Time
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
Time Linear 1149.432 1 1149.432 107.133 .000 .413
Measure: MATscore
Source
Type III Sum of
Partial Eta
Squared
Intercept 45876.886 1 45876.886 1991.776 .000 .929
Group 564.575 1 564.575 24.511 .000 .139
Error 3501.039 152 23.033

42
QUEZON CITY Quarter 4
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
9.59
2.64
14.5
5.56
78
LD2 Mean
S.D.
7.73
2.32
9.15
3.26
67
Measure: MATscore
Source Time
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
Time Linear 721.651 1 721.651 74.064 .000 .341
Measure: MATscore
Source
Type III Sum of
Partial Eta
Squared
Intercept 30248.968 1 30248.968 1676.130 .000 .921
Group 936.568 1 936.568 51.896 .000 .266
Error 2580.708 143 18.047

43
QUEZON CITY Mathtitude
Treatment
Group
Pretest Posttest N
LD1 Mean
S.D.
67.0
5.25
66.10
6.87
69
LD2 Mean
S.D.
64.84
7.42
66.51
6.52
43
Measure: Mathtitude
Source Time
Type III Sum
of Squares df
Mean
Square F Sig.
Partial Eta
Squared
Time Linear 7.973 1 7.973 .261 .610 .002
Measure: Mathtitude
Source
Type III Sum of
Partial Eta
Squared
Intercept 926312.686 1 926312.686 17474.515 .000 .994
Group 40.686 1 40.686 .768 .383 .007
Error 5831.029 110 53.009

44
B. T-TEST, QUEZON CITY MAT TOPIC GAIN SCORES*
Topics LD1
(N = 62)
LD2
(N = 64)
Geometry (Q3) Mean
S.D.
4.44
3.15
1.38
2.46
Patterns & Algebra (Q3) Mean
S.D.
0.37
1.35
0.53
1.51
Measurement (Q3) Mean
S.D.
1.29
2.44
0.47
2.63
Geometry (Q4) Mean
S.D.
2.97
3.72
0.20
2.85
Statistics & Probability (Q4) Mean
S.D.
1.6
2.53
1.06
2.55
*Gain score = Posttest – Pretest Score

45
Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig.
(2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower Upper
Geometry Q3 Equal variances
assumed
3.575 .061 6.096 124 .000 3.060 .502 2.067 4.054
Equal variances not
assumed
6.073 115.452 .000 3.060 .504 2.062 4.059
Patterns &
Algebra Q3
Equal variances
assumed
1.467 .228 -.628 124 .531 -.160 .255 -.665 .345
Equal variances not
assumed
-.629 123.134 .530 -.160 .255 -.665 .344
Measurement
Q3
Equal variances
assumed
.124 .725 1.817 124 .072 .822 .452 -.074 1.717
Equal variances not
assumed
1.819 123.764 .071 .822 .452 -.073 1.716
Geometry Q4 Equal variances
assumed
11.868 .001 4.695 124 .000 2.765 .589 1.599 3.930
Equal variances not
assumed
4.675 114.418 .000 2.765 .591 1.593 3.936
Statistics &
Probability Q4
Equal variances
assumed
.000 .991 1.180 124 .240 .534 .453 -.362 1.431
Equal variances not
assumed
1.180 123.925 .240 .534 .453 -.362 1.430

46
C. QUEZON CITY PRETEST, MATHTITUDE RELIABILITY TEST (N = 250)
Reliability Statistics
Cronbach's
Alpha
Cronbach's Alpha Based
on Standardized Items N of Items
.701 .726 20
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
1R. Natataranta ako kapag
nakakakita ng Math problem
na mukhang mahirap
62.27 44.392 .046 .124 .712
2. May kumpiyansa ako sa
aking sarili kapag
sumasagot ng math. ( + )
61.71 43.340 .342 .213 .689
3. Pakiramdam kong
malikhain ako sa
paghahanap ng iba't ibang
paraan para mag-solve ng
math. ( + )
62.35 42.115 .259 .179 .691
4. Madali para sa akin ang
mag-solve ng mga tanong
sa Math. ( + )
62.37 41.223 .292 .311 .688
5. Mataas ang mga
nakukuha kong score sa
Math. ( + )
62.04 42.537 .265 .279 .691
6. Tumataas ang antas ng
katalinuhan kapag
nagsusumikap ang isang tao
sa math. ( + )
61.97 42.224 .293 .188 .689
7. Maraming natututunan
ang isang tao mula sa
kanyang mga pagkakamali
sa pag-solve ng math ( + )
62.94 43.241 .074 .158 .716

47
8. Di ako titigil sa pag-solve
ng isang math problem
hanggat 'di ko nakukuha ang
sagot. ( + )
62.17 40.946 .332 .221 .684
9R. Kapag hindi ko ma-
solve ang math problem,
susuko na lang ako.
61.87 41.333 .385 .247 .681
10. Kapag sinasauli ng guro
ang mga test paper,
tinitignan ko kung saan ako
nagkamali at aaralin ko kung
saan ako nagkamali at
aaralin ko kung bakit mali
ang pag-solve ko. (+)
62.16 41.508 .285 .220 .689
11R. Nag-aaral ako ng Math
para lamang makakuha ng
mataas na grade sa exam.
63.92 47.605 -.212 .150 .737
12.Nagagamit ko ang mga
pinag-aralan namin sa Math
kahit ako'y nasa labas ng
paaralan. ( + )
62.38 39.914 .356 .240 .681
13. Dahil sa Math, mas
mabilis na akong mag-isip at
sumagot ng mga tanong. ( +
)
62.11 39.377 .472 .353 .669
Item14 recode 61.91 41.406 .350 .249 .683
15. Ginagamit ang Math sa
lahat ng uri ng trabaho. ( + )
62.16 42.644 .178 .089 .700
16. Natutuwa ako kapag
ako'y nagsasagot ng
assignment sa Math. ( + )
61.87 41.657 .399 .259 .681
17. Gusto kong matuto ng
iba pang mga bagay tungkol
sa Math. ( + )
61.82 41.002 .506 .367 .674
18R. Hindi ako interesado
sa mga lesson na tinuturo sa
amin sa Math.
62.16 40.215 .345 .249 .682
19. Ang Math ang isa sa
pinaka-paborito kong
subject. ( + )
61.97 41.104 .397 .274 .680

48
20. Gusto kong pinag-
uusapan ang Math kasama
ang aking mga kaibigan at
kaklase. ( + )
62.04 40.741 .380 .263 .680

MathDali Research Project Evaluation Report

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