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The Impact of Project-Based Learning on Teacher Self-Efficacy

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Abstract and Figures

The expansion of project-based learning has been advocated for as a solution and reform measure to the problem of rote learning-based teaching practices in Korean schools, deemed unfit for the development of diverse skills needed in the 21st century. While the ultimate goal of initiating project-based learning is to affect students in positive ways, it is important to analyze how conducting project-based learning affects teachers, as they are the direct implementers of teaching practices and are bound to have immense influence on the overall learning experience of students. By using the OECD TALIS database, we show that conducting project-based learning is strongly and positively associated with teacher self-efficacy. Such results are in line with an analysis using data obtained from a field experiment on teacher training of project-based learningconducted on Daegu city middle schools.
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KDI SCHOOL
WORKING PAPER SERIES
KDI SCHOOL WORKING PAPER SERIES
The Impact of Project-Based Learning on
Teacher Self-Efficacy
Junghee Choi
KDI School of Public Policy and Management
Booyuel Kim
KDI School of Public Policy and Management
Ju-Ho Lee
KDI School of Public Policy and Management
Yoonsoo Park
Korea Development Institute
May, 2016
Working Paper 16-05
This paper can be downloaded without charge at:
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* We are grateful to the KDI School of Public Policy and Management for providing financial support.
The Impact of Project-Based Learning on
Teacher Self-Efficacy
May, 2016
Junghee Choia, Booyuel Kima, Ju-Ho Leea*, Yoonsoo Parkb
a KDI School of Public Policy and Management, 263 Namsejong-ro, Sejong-si, 30149, Republic of Korea.
b Korea Development Institute, 263 Namsejong-ro, Sejong-si, 30149, Republic of Korea.
* Corresponding author.
Email addresses: jhc@kdis.ac.kr (J. Choi), bkim@kdischool.ac.kr (B. Kim), jhl@kdischool.ac.kr (J.H. Lee),
yoonpark@kdi.re.kr (Y. Park)
The Effect of Project-Based Learning on Teacher Self-Efficacy
Junghee Choi, Booyuel Kim, Ju-Ho Lee, Yoonsoo Park
Abstract
The expansion of project-based learning has been advocated for as a solution and reform
measure to the problem of rote learning-based teaching practices in Korean schools, deemed
unfit for the development of diverse skills needed in the 21st century. While the ultimate goal
of initiating project-based learning is to affect students in positive ways, it is important to
analyze how conducting project-based learning affects teachers, as they are the direct
implementers of teaching practices and are bound to have immense influence on the overall
learning experience of students. By using the OECD TALIS database, we show that
conducting project-based learning is strongly and positively associated with teacher self-
efficacy. Such results are in line with an analysis using data obtained from a field experiment
on teacher training of project-based learning conducted on Daegu city middle schools.
.
1
I. Introduction
The core skills required in the 21st century, referred to as the “6C’s,” include communication,
collaboration, critical thinking, creativity, character and citizenship (Fullan & Langworthy,
2014). While education is the fundamental route through which skills are developed, Korea’s
education, which primarily focuses on rote learning, has been criticized for its inability to
adapt to the changing times, and deemed insufficient for developing the required skills of the
21st century (Lee, Jeong, & Hong, 2014; Lee, Ryoo, & Lee, 2014). Against this backdrop, the
expansion of the implementation of project-based learning has been advocated for as a
solution and reform measure to the problem of teaching practices in Korea’s education (Lee,
2016).
Project-based learning is defined as learning that is focused on projects through student-
centered collaboration and teamwork to solve real problems and tasks (Bender, 2012;
Cameron, 2014; Krauss & Boss, 2013; Maltese, 2012; Stanley, 2012). By leading students to
collaborate amongst one another, inquire and deal with complexity, deal with actual issues
pertaining to society, and develop contextual and systems thinking (Kraus & Boss, 2013),
project-based learning is highly relevant to developing the aforementioned skills required in
the 21st century.
While the ultimate goal of initiating project-based learning is to affect students in positive
ways, it is important to analyze how conducting project-based learning affects teachers, as
they are the direct implementers of teaching practices and are bound to have immense
influence on the overall learning experience of students. In this regard, this research aims to
empirically analyze how conducting project-based learning is associated with teacher self-
efficacy.
According to social cognitive theory, an individual’s self-efficacy is the degree to which
one believes in one’s ability to complete a certain task (Bandura, 1986). In the context of
education, teacher self-efficacy can be defined as the teachers’ beliefs about their capability
to teach their subject matter effectively to students and bring about desired outcomes of
student engagement and learning (Tschannen-Moran & Woolfolk Hoy, 2001; Holzberger,
Phillip, & Kunter, 2013). The self-efficacy of teachers has been shown to be strongly related
to various aspects of education, such as teachers’ job satisfaction and student achievement
outcomes (Caprara et al., 2006). While teacher self-efficacy has generally been assumed to be
an important cause of various educational outcomes, the precise direction of causality is not
clear (Holzberger et al., 2013). For example, teacher self-efficacy has been shown to be a
consequence of educational processes, namely instructional quality (Holzberger et al., 2013).
Also, Stein and Wang (1988) show that previous success in the implementation of innovative
teaching practices enhanced teacher self-efficacy, but not vice versa.
By utilizing various databases, this research aims to analyze how project-based learning is
related to teacher self-efficacy. A better understanding of this relationship will contribute to
gaining a more complete understanding of the mechanism of how students are affected by
project-based learning. Furthermore, we aim to contribute to the literature on teacher self-
efficacy and teaching practices by exploring the empirical relation between them.
2
To begin with, we use data from the Program for International Student Assessment
(PISA), an international student achievement assessment for 15-year old students, and the
Teaching and Learning International Study (TALIS), an international survey conducted on
middle school teachers, and show that the rate of project-based learning conducted in Korean
schools is much lower than that of schools in other countries. We show that there is a strong
and positive cross-country correlation between the rate of project-based learning and the level
of teacher self-efficacy. Within-country and within-school micro-estimates using the TALIS
database show that the correlation between project-based learning and teacher self-efficacy is
positive and statistically significant across different countries and among the highest for
Korean teachers.
To empirically analyze the relationship between project-based learning in a more causal
way, we use data from a field experiment on teacher training for project-based learning
conducted on middle schools in Daegu city. We show that teacher training and consultation
for conducting project-based learning has a positive effect on teacher self-efficacy. The
results of the analyses using the TALIS database and the data from the Daegu middle school
experiment provide empirical support for the positive educational effect of project-based
learning, and that expanding its implementation can play a vital role in Korea’s education
reform.
This paper is organized as follows. In Section 2 we use the PISA and TALIS databases to
compare the rate of project-based learning conducted in Korean schools to that of schools in
other countries. In Section 3 we show that there is a strong and positive cross-country
correlation between project-based learning and teacher self-efficacy. In Section 4 we use the
TALIS database and find a strong correlation between project-based learning and teacher
self-efficacy at the teacher level, both within countries and within schools. In Section 5 we
use the data from the Daegu middle school field experiment to empirically analyze the
relationship between project-based learning and teacher self-efficacy in a more causal way.
Section 6 concludes.
II. Korea’s Low Rate of Project-Based Learning
We use databases from the PISA and TALIS to compare the rate of project-based learning
conducted in schools in Korea with that of schools in other countries.
PISA, developed by the Organization for Economic Cooperation and Development
(OECD), is an international student achievement assessment centered on math, reading, and
science for 15-year old students, conducted every three years since 2000. In addition to
assessments of academic achievement, PISA provides a wide range of information obtained
through student surveys, including various student characteristics and values, characteristics
of teachers and schools, and teaching practices. As measures of project-based learning, we
use variables that represent the frequency of small group work in math lessons and group
3
work using computers at school, answered on a four-point and five-point scale, respectively.1
Taking part in group work may not be the complete equivalent of project-based learning, but
since the definitions of the PISA group work measures include coming up with “joint
solutions to a problem or task” (for group work in math lessons) and “communication with
other students” (for group work using computers at school), they contain the key components
of our definition of project-based learning, and thus we use them to measure the rates of
project-based learning in our analysis.
We use the PISA 2012 database, the most recent data available for public use, to compare
the rates of project-based learning conducted in math lessons and project-based learning
using computers at school among OECD countries.2 What we specifically observe are the
shares of students in each country who take part in group work in math lessons either in
“most lessons” or “every lesson,” and in group work using computers at school at least “once
or twice a week.” Results are shown in Figure 1.
1 Frequency of group work in math is obtained through the question, “In your mathematics lessons, how often
does the teacher have you work in small groups to come up with joint solutions to a problem or task?” answered
on the following four-point scale: 1) Every lesson; 2) Most lessons; 3) Some lessons; 4) Never or hardly ever.
For frequency of group work using computers at school, students are asked, “How often do you use school
computers for group work and communication with other students?” which is answered on the following five-
point scale: 1) Never or hardly ever; 2) Once or twice a month; 3) Once or twice a week; 4) Almost every day; 5)
Every day.
2 The comparison is restricted to OECD countries that participated in PISA 2012 and whose data is publically
available. For group work in math, such countries are Australia, Austria, Belgium, Canada, Chile, Czech
Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan,
Korea, Luxemburg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic,
Slovenia, Spain, Sweden, Switzerland, Turkey, the United Kingdom, and the United States. For group work
using computers at school, such countries are Australia, Austria, Belgium, Chile, Czech Republic, Denmark,
Estonia, Finland, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Mexico, the
Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland,
and Turkey.
4
Figure 1. The Rate of Project-Based Learning by Students in OECD Countries (PISA)
(a) Math Lessons
(b) Using Computers at School
Notes: For math lessons, the Rate of Project-Based Learning (%) represents the share of students who
take part in project-based learning in either “most lessons” or “every lesson.” For using computers at
school, the Rate of Project-Based Learning (%) represents the share of students who take part in
project-based learning at least “once or twice a week.”
Source: PISA 2012.
0
10
20
30
40
50
60
Estonia
Finland
Hungary
Ireland
Czech Republic
Japan
Korea
Slovenia
Belgium
Italy
France
Slovak Republic
Australia
Spain
Greece
Poland
Luxemburg
United Kingdom
Israel
Norway
Austria
Iceland
Netherlands
New Zealand
Turkey
Germany
Denmark
Int'l Pooled
Sweden
Portugal
Canada
Switzerland
Chile
United States
Mexico
Rate of Project-Based Learning (%)
0
10
20
30
40
50
60
Japan
Korea
Germany
Poland
Estonia
Ireland
Israel
Finland
Belgium
Turkey
Iceland
Int'l Pooled
Switzerland
Italy
New Zealand
Slovenia
Austria
Hungary
Slovak Republic
Mexico
Netherlands
Sweden
Portugal
Spain
Chile
Czech Republic
Greece
Australia
Norway
Denmark
Rate of Project-Based Learning (%)
5
As evident in Figure 1, Korea’s shares of students that experience project-based learning are
well below the OECD average levels. For math, Korea’s rate of project-based learning is
drastically lower than that of other countries, ranking 28th out of 34 OECD countries. For
project-based learning using computers, Korea ranks second to last among the 29 OECD
countries compared, and Korea’s rate is less than one-fourth of that of the international average.
Next, we use the TALIS database to internationally compare the share of teachers that
conduct project-based learning in schools. TALIS is an international survey for teachers and
principals of middle schools,3 developed by the OECD in 2008. The survey takes place every
five years, and we use the 2013 (second phase) teacher survey data, which focuses on diverse
aspects of teachers, such as teaching practices, professional development, work environment,
and self-efficacy and job satisfaction. In TALIS 2013 a total of 34 countries,4 including 24
OECD countries, participated, and the final international sample includes more than 170,000
teachers from more than 10,000 schools. The survey was conducted between 2012 and 2013
through either paper-based or online-based methods, and the final sample for Korea includes
2,933 teachers from 177 schools.
As a measure of the frequency of project-based learning, we use the TALIS variable which
asks teachers how often “students work in small groups to come up with a joint solution to a
problem or task” (answered on a four-point scale: 1) Never; 2) Occasionally; 3) Frequently; 4)
In all or nearly all lessons). As was the case for the PISA variable for group work in math
lessons, the TALIS variable includes coming up with “a joint solution to a problem or task,”
which significantly resembles our definition of project-based learning.
Figure 2 displays the rate of project-based learning that occurs in middle schools within
each country. We refer to the “rate of project-based learning” as the share of teachers who
conduct project-based learning either “frequently” or “in all or almost all lessons.” As is evident
in Figure 2, Korean teachers’ rate of project-based learning is the lowest among countries in
comparison. It is not only lower than that of developed countries like Canada (Alberta), Finland,
France and Singapore, but also much lower than that of developing countries like Chile,
Mexico, Brazil and Bulgaria.
3 Although the main target group for TALIS is teachers and principals of middle schools (International Standard
Classification of Education (ISCED) level 2), countries had the option of conducting additional surveys for the
ISCED levels 1 (primary school) and 3 (upper-secondary school) (OECD, 2014a).
4 The countries that participated in the 2013 TALIS survey are Australia, Belgium (Flanders), Brazil, Bulgaria,
Canada (Alberta), Chile, Croatia, Cyprus, the Czech Republic, Denmark, England, Estonia, Finland, France,
Iceland, Israel, Italy, Japan, Korea, Latvia, Malaysia, Mexico, the Netherlands, Norway, Poland, Portugal,
Romania, Serbia, Singapore, the Slovak Republic, Spain, Sweden, the United Arab Emirate (Abu Dhabi), and
the United States. The data for Cyprus and Iceland were not publically available, and the data for the US did not
meet the sampling standards (OECD, 2014a), and thus these three countries were excluded from this research.
6
Figure 2. The Rate of Project-Based Learning Conducted by Teachers (TALIS)
Note: The Rate of Project-Based Learning (%) is the share of teachers who conduct project-based
learning either “frequently” or “in all or almost all lessons.”
Source: TALIS 2013.
III. Cross-Country Correlation between Project-Based Learning and Teacher
Self-Efficacy
Next, we analyze the cross-country correlation between project-based learning and teacher
self-efficacy to show how the drastically low level of project-based learning in Korea is
associated with teacher self-efficacy.
For teacher self-efficacy, TALIS initially measures three different sub-categories: 1)
efficacy in instruction; 2) efficacy in student engagement; and 3) efficacy in class
management. Four questions are asked for the assessment of each of the sub-categories of
teacher self-efficacy, and are answered on a four-point scale. Based on the answers to these
four questions the measure of each sub-category is obtained through the CFA (Confirmatory
Factor Analysis) method.5 The integrated measure of teacher self-efficacy is the average of
the values of the three sub-categories. Thus, in total, four variables pertaining to self-efficacy
are available. The survey questionnaire used in TALIS to measure each sub-category of
5 For details on the statistical procedure of obtaining the self-efficacy measurements, please refer to OECD
(2014b).
0
10
20
30
40
50
60
70
80
90
Korea
Italy
Israel
Japan
Singapore
Croatia
Spain
Belgium(Flanders)
Latvia
Czech Republic
Finland
France
Estona
Serbia
Slovak Republic
Poland
Australia
Bulgaria
Sweden
Netherlands
Portugal
Int'l Pooled
Romania
Malaysia
Canada(Alberta)
England
Brazil
Norway
Mexico
Chile
UAE(Abu Dhabi)
Denmark
Rate of Project-Based Learning (%)
7
teacher self-efficacy are shown in Figures 1A~3A of the Appendix.
Based on the TALIS database, Figure 3 displays the cross-country relationship between
project-based learning and teacher self-efficacy. A positive relationship is evident and the
coefficient of correlation is 0.497. On the other hand, through Figure 4 it is evident that
teacher self-efficacy has no significant relationship with annual teacher income,6 which goes
against the general expectation that one’s self-efficacy is greatly influenced by monetary
rewards. In particular, the fact that countries with low project-based learning rates also
display low levels of teacher self-efficacy is interesting. It provides a clue to why teachers in
Korea, despite having relatively higher earnings and higher skills compared to their
international counterparts have low levels of self-efficacy.
Figure 3. The Rate of Project-Based Learning and Teacher Self-Efficacy (TALIS)
Note: The Rate of Project-Based Learning (%) is the share of teachers who conduct project-based
learning either “frequently” or “in all or almost all lessons.”
Source: TALIS 2013.
6 The information for annual teacher income was obtained from OECD (2013). Annual teacher income refers to
the average annual income of teachers with 15 years of teaching experience as of 2011, which is the most recent
data available.
8
Figure 4. Annual Teacher Income and Teacher Self-Efficacy
Notes: Annual teacher income is the average yearly income of teachers with 15 years of teaching
experience as of 2011. The scale for teacher annual income is US Dollars (PPP adjusted).
Source: TALIS 2013, OECD (2013)
While we showed that there is a positive cross-country correlation between project-based
learning and teacher self-efficacy, there are limitations to such aggregate correlations. First,
our analysis does not control for country fixed effects, which means that entire differences
among countries are included in analyzing the relationship between teacher self-efficacy and
project-based learning. This means that omitted factors which can influence both teacher self-
efficacy and project-based learning may have affected the observed cross-country correlation.
More importantly, the causal relationship is unclear; higher rates of project-based learning
can be either a cause or consequence of higher teacher self-efficacy. To obtain a clearer
understanding of the empirical relationship between project-based learning and teacher self-
efficacy, we analyze the TALIS data at the teacher level.
IV. Empirical Analysis Based on TALIS
In order to overcome the limitations of cross-country correlation, we use the TALIS
database to conduct micro data analysis at the teacher level on the relationship between
project-based learning and teacher self-efficacy. We exclude those whose variables for the
self-efficacy measure and the rate at which project-based learning is conducted are missing.
9
As explained in Section 2, the variable for the rate of project-based learning is scaled from
one to four, but for our analysis we transform it to a dummy variable whose value is 1 if
project-based learning is conducted “frequently” or “in all or nearly all lessons,” and 0 if
conducted “occasionally” or “never or almost never.” The descriptive statistics of all
variables used in the analysis are shown separately for the entire international sample and the
Korean sample in Table 1. Through Table 1 it is evident that the mean levels of the three sub-
categories of self-efficacy, as well as the integrated level of self-efficacy for Korean teachers,
are lower than those of the international sample. Also, as observed in the previous section, the
average rate of project-based learning conducted in Korean middle schools is lower than the
international average rate.7
7 T-tests on comparison of the mean values of the international and Korean sample indicate that the differences
are statistically significant at the 1% level.
10
Table 1. Descriptive Statistics
(a) International Sample
Variable Obs. Mean Std. Dev. Min. Max
Teacher self-efficacy 78155 12.340 1.972 3.777 15.529
Efficacy in instruction 78155 12.423 2.097 2.949 15.775
Efficacy in student engagement 78155 11.921 2.135 3.803 15.375
Efficacy in class management 78155 12.675 2.066 3.967 15.655
Project-based learning 78155 0.490 0.500 0 1
Female 78155 0.356 0.479 0 1
Age 78155 42.087 10.368 18 99
Total teaching experience (years) 78155 15.975 10.140 0 58
Doctorate degree 78155 0.016 0.124 0 1
Permanent employment status 78155 0.833 0.373 0 1
N
egative view on prof. development 78155 0.425 0.494 0 1
(b) Korean Sample
Variable Obs. Mean Std. Dev. Min. Max
Teacher self-efficacy 2254 11.133 2.009 3.777 15.406
Efficacy in instruction 2254 10.957 2.141 3.260 15.538
Efficacy in student engagement 2254 11.024 1.937 4.105 15.120
Efficacy in class management 2254 11.418 2.123 3.967 15.561
Project-based learning 2254 0.318 0.466 0 1
Female 2254 0.303 0.460 0 1
Age 2254 42.296 9.182 22 62
Total teaching experience (years) 2254 16.306 9.934 0 40
Doctorate degree 2254 0.015 0.122 0 1
Permanent employment status 2254 0.840 0.366 0 1
N
egative view on prof. development 2254 0.427 0.495 0 1
otes: Sub-categories of teacher self-efficacy were measured through the CFA (Confirmatory Facto
r
Analysis) method using the answers to four questions pertaining to the assessment of each sub-
category. Teacher self-efficacy: the average of the three variables for the sub-categories of teache
r
self-efficacy. Project-based learning: dummy variable indicating the relative frequency with which
project-based learning is conducted in class (=1 if conducted “frequently” or “in all or almost all
lessons”; =0 if conducted “occasionally” or “never or almost never”). Doctorate degree: dummy
variable indicating the completion of a doctorate degree. Permanent employment status: dummy
variable indicating whether individual is a permanent employ (=1) or on a temporary contract (=0).
N
egative view on prof. development: a dummy variable indicating agreement with the idea that “no
relevant professional development offered” is a barrier to participation in professional developmen
t
(=1 if “Strongly agree” or “agree”; =0 if “Strongly disagree” or “disagree”).
Source: TALIS 2013
11
As previously mentioned, cross-country analysis on the relationship between project-based
learning and teacher self-efficacy may be affected by omitted variables. In order to estimate the
across schools, within-country correlation between project-based learning and teacher self-
efficacy, the following model is estimated for each country sample:
 

 
 

 (1)
where  is the self-efficacy level of teacher in school in country , standardized to
have a mean of 0 and standard deviation of 1 within each country sample ( is standardized
in the same way but across the entire international sample for the regression run on the
international pooled sample);  is the dummy variable for conducting project-
based learning of teacher in school in country ;  is a vector of characteristics
(gender, age, total years of teaching experience, completion of doctorate degree, employment
status, and a dummy variable indicating the teacher’s opinion on the relevance of professional
development activities) of teacher in school in country ;
is the country fixed effect;
and  is the error term.
It is possible that differences among schools within a country, such as the school culture
and principal leadership, may contribute to differences in teaching practice and teacher self-
efficacy. In relation to such differences, teachers may self-sort into specific schools. In these
cases equation (1) may estimate a school effect, rather than an isolated effect of project-based
learning. To estimate the within-school correlation between project-based learning and
teacher self-efficacy, we control for differences that may exist between schools within each
country and estimate the following model for each country’s sample:
 

 
 
 
 (2)
where  is the self-efficacy level of teacher in school in country , standardized to
have a mean of 0 and standard deviation of 1 within each country sample ( is standardized
in the same way but across the entire international sample for the regression run on the
international pooled sample);  is the dummy variable for conducting project-
based learning of teacher in school in country ;  is a vector of characteristics
(gender, age, total years of teaching experience, completion of doctorate degree, employment
status, and a dummy variable indicating the teacher’s opinion on the relevance of professional
development activities) of teacher in school in country ;
is the school fixed effect;
and  is the error term.
Table 2 reports the OLS estimates of the statistical association between project-based
learning and teacher self-efficacy using equation (1). The estimates for Korea, countries in
the Asian region (Japan, Singapore), countries in Europe (England, Finland), and the
estimates for the pooled international sample with country fixed effects is reported in Table 2.
As reported in Table 2, it is evident that there is a strong positive correlation between
project-based learning and teacher self-efficacy in Korea. The point estimate on project-based
learning is 0.441 and statistically significant at the 1% level. This means that within Korea,
12
the self-efficacy level of teachers that conduct project-based learning more frequently is, on
average, 0.441 standard deviations higher than teachers that occasionally or never conduct
project-based learning. Korea’s point estimate on project-based learning is not only greater
than the point estimate of the international pooled sample (with country fixed effects), but the
fourth highest among the 31 countries included in the analysis (Figure 5).
In addition, it is reported that longer years of teaching experience is associated with
greater teacher self-efficacy, but the rate of increase is generally negative across countries. In
Korea, the self-efficacy of female teachers is greater than that of male teachers, and the
completion of a doctorate degree and permanent employment status do not seem to be
associated with teacher self-efficacy. Also, for the Korean sample, teachers who believe that
the absence of relevance in professional development activities is a barrier to participation in
such activities have a lower level of self-efficacy than those who do not.
13
Table 2. Project-Based Learning and Teacher Self-Efficacy: OLS Micro Estimates –
Within Countries
D
ependent Variable:
Teacher Self-Efficacy Korea Japan Singapore England Finland
International
Pooled
Project-based learning 0.441***
(0.046) 0.415***
(0.047) 0.411***
(0.040) 0.403***
(0.057) 0.179***
(0.055) 0.298***
(0.011)
Female 0.151***
(0.057) 0.290***
(0.043) -0.087**
(0.042) -0.044
(0.047) -0.073*
(0.041) -0.046***
(0.011)
Age -0.056
(0.039) 0.022
(0.024) 0.032
(0.021) -0.007
(0.018) 0.029
(0.026) 0.000
(0.005)
Age2 0.000
(0.000) -0.000
(0.000) -0.000
(0.000) 0.000
(0.000) -0.000
(0.000) -0.000
(0.000)
Experience 0.059***
(0.017) 0.010
(0.012) 0.030***
(0.009) 0.028*
(0.014) 0.022*
(0.013) 0.019***
(0.002)
Experience2 -0.001**
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000***
(0.000)
Doctorate degree 0.252
(0.171) 0.276
(0.274) 0.788***
(0.182) -0.247
(0.448) 0.297
(0.198) 0.008
(0.054)
Permanent -0.101
(0.062) -0.003
(0.056) 0.023
(0.065) 0.204**
(0.103) 0.064
(0.055) 0.002
(0.014)
N
egative view on
prof. development -0.218***
(0.043) 0.004
(0.040) -0.011
(0.047) -0.097*
(0.055) -0.094**
(0.046) -0.082***
(0.010)
Observations
R-squared 2,254
0.077 2,915
0.083 2,828
0.098 1,908
0.058 2,232
0.02 78,155
0.387
Notes: Teacher self-efficacy variable standardized to have a mean of 0 and standard deviation of 1
within each country. Experience: total years of teaching experience. Doctorate degree: dummy
variable indicating completion of doctorate degree. Permanent: dummy variable indicating permanent
employment status. Negative view on prof. development: dummy variable indicating teacher’s
negative feelings on the relevance of professional development activities offered. Standard errors
obtained through balanced repeated replication weights in parentheses. Results for the international
pooled sample includes country fixed effects.
*p<0.1
**p<0.05
***p<0.01
Source: TALIS 2013
14
Figure 5. Project-Based Learning and Teacher Self-Efficacy:
OLS Micro Estimates – Within Countries
Notes: ‘beta_1’ refers to the beta 1 coefficients of equation (1). Vertical lines indicate the 95%
confidence interval.
Source: TALIS 2013
Table 3 reports the results of the OLS regressions run using equation (2). It is evident that
including school fixed effects do not drastically change the OLS estimates compared to those
obtained through equation (1). For the Korean sample, after controlling for differences that
may exist between schools, teachers who conduct project-based learning more frequently are
associated with higher self-efficacy levels by 0.448 standard deviations than teachers that
occasionally or never conduct project-based learning. As displayed in Figure 6, the point
estimate on project-based learning for Korea is the third highest among all countries included
in the analysis, lower only than that of the UAE (Abu Dhabi) and Romania.
When considering the fact that difference in school environment may significantly affect
teaching practices and teacher self-efficacy, the fact that the OLS estimates of equation (2),
which includes school fixed effects, does not significantly differ from those of equation (1) is
quite meaningful. In other words, the positive correlation between project-based learning and
teacher self-efficacy is shown to be quite stable, maintaining its consistency even after
controlling for differences between schools like school culture and principal leadership.
15
Table 3. Project-Based Learning and Teacher Self-Efficacy: OLS Micro Estimates –
Within Schools
D
ependent Variable:
Teacher Self-Efficacy Korea Japan Singapore England Finland
International
Pooled
Project-based learning 0.448***
(0.042) 0.401***
(0.047) 0.425***
(0.039) 0.356***
(0.061) 0.155***
(0.057) 0.287***
(0.011)
Female 0.177***
(0.055) 0.277***
(0.041) -0.096**
(0.043) -0.024
(0.049) -0.064
(0.045) -0.045***
(0.010)
Age -0.017
(0.036) 0.034
(0.027) 0.043**
(0.020) -0.004
(0.019) 0.036
(0.025) 0.003
(0.005)
Age2 0.000
(0.000) -0.000
(0.000) -0.000
(0.000) 0.000
(0.000) -0.000*
(0.000) -0.000
(0.000)
Experience 0.043***
(0.015) 0.011
(0.014) 0.028***
(0.009) 0.029*
(0.016) 0.023*
(0.012) 0.019***
(0.002)
Experience2 -0.001
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000***
(0.000)
Doctorate degree 0.163
(0.160) 0.129
(0.244) 0.663***
(0.171) -0.172
(0.452) 0.333
(0.225) 0.019
(0.055)
Permanent -0.099
(0.071) -0.026
(0.056) 0.009
(0.071) 0.258**
(0.120) 0.034
(0.057) 0.014
(0.016)
N
egative view on
prof. development -0.206***
(0.046) -0.006
(0.040) -0.024
(0.047) -0.096*
(0.053) -0.069
(0.045) -0.077***
(0.010)
School Fixed Effect YES YES YES YES YES YES
Observations
R-squared 2,254
0.186 2,915
0.175 2,828
0.159 1,908
0.164 2,232
0.108 78,155
0.464
Notes: Teacher self-efficacy variable standardized to have a mean of 0 and standard deviation of 1
within each country. Experience: total years of teaching experience. Doctorate degree: dummy
variable indicating completion of doctorate degree. Permanent: dummy variable indicating permanent
employment status. Negative view on prof. development: dummy variable indicating teacher’s
negative feelings on the relevance of professional development activities offered. Standard errors
obtained through balanced repeated replication weights in parentheses.
*p<0.1
**p<0.05
***p<0.01
Source: TALIS 2013
16
Figure 6. Project-Based Learning and Teacher Self-Efficacy:
OLS Micro Estimates – Within Schools
Notes: ‘beta_1’ refers to the beta 1 coefficients of equation (1). Vertical lines indicate the 95%
confidence interval.
Source: TALIS 2013
As previously mentioned, TALIS measures three sub-categories of teacher self-efficacy
(efficacy in instruction, efficacy in student engagement, and efficacy in class management). Table 4-
6 report the results of regressions using equation (2), which controls for school fixed effects, with
each sub-category of teacher self-efficacy as the dependent variable. As was the case with the
integrated teacher self-efficacy measure, project-based learning has a positive and statistically
significant association with each sub-category of teacher self-efficacy. In the case of Korea, teachers
who conduct project-based learning on a relatively more frequent basis are associated with higher
efficacy in instruction by 0.470 standard deviations; higher efficacy in student engagement by 0.466
standard deviations; and higher efficacy in class management by 0.372 standard deviations; and
each of the point estimates are greater than those obtained from the international pooled sample.
Since project-based learning is directly associated with instructional methods, the fact that it has
a strong association with efficacy in instruction is expected, but the fact that project-based learning
is also strongly associated with efficacy in student engagement and class management is quite
interesting. Rather than a form of “vertical teaching practice,” where learning is centered on
teachers lecturing and students copying notes, since project-based learning is a form of “horizontal
teaching practice,” where students cooperate amongst one another and ask teachers questions
(Algan, Cahuc, & Schleifer, 2013), it can be understood that project-based learning also has positive
associations with efficacy in student engagement and class management.
17
Table 4. Project-Based Learning and Efficacy in Instruction: OLS Micro Estimates –
Within Schools
Dependent Variable:
Efficacy in Instruction Korea Japan Singapore England Finland
International
Pooled
Project-based learning 0.470***
(0.041) 0.381***
(0.046) 0.462***
(0.038) 0.382***
(0.064) 0.213***
(0.055) 0.300***
(0.011)
Female 0.154***
(0.056) 0.205***
(0.045) -0.098**
(0.046) -0.050
(0.045) -0.072
(0.045) -0.063***
(0.010)
Age -0.007
(0.034) 0.026
(0.027) 0.033
(0.021) 0.005
(0.020) 0.034
(0.026) 0.005
(0.005)
Age2 -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.001*
(0.000) -0.000
(0.000)
Experience 0.038**
(0.015) 0.004
(0.014) 0.029***
(0.009) 0.025
(0.016) 0.021*
(0.013) 0.014***
(0.003)
Experience2 -0.001
(0.000) 0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000***
(0.000)
Doctorate degree 0.255
(0.171) 0.136
(0.230) 0.685***
(0.181) -0.120
(0.436) 0.366
(0.225) 0.072
(0.052)
Permanent -0.072
(0.072) -0.035
(0.059) 0.013
(0.070) 0.157
(0.122) 0.016
(0.055) -0.008
(0.015)
Negative view on
prof. development -0.214***
(0.048) -0.019
(0.040) -0.007
(0.046) -0.086
(0.054) -0.080*
(0.041) -0.072***
(0.010)
School Fixed Effect YES YES YES YES YES YES
Observations
R-squared 2,254
0.185 2,915
0.159 2,828
0.160 1,908
0.148 2,232
0.11 78,155
0.458
Notes: Efficacy in instruction variable standardized to have a mean of 0 and standard deviation of 1
within each country. Experience: total years of teaching experience. Doctorate degree: dummy
variable indicating completion of doctorate degree. Permanent: dummy variable indicating permanent
employment status. Negative view on prof. development: dummy variable indicating teacher’s
negative feelings on the relevance of professional development activities offered. Standard errors
obtained through balanced repeated replication weights in parentheses.
*p<0.1
**p<0.05
***p<0.01
Source: TALIS 2013
18
Table 5. Project-Based Learning and Efficacy in Student Engagement: OLS Micro
Estimates – Within Schools
Dependent Variable:
Efficacy in Student
Engagement Korea Japan Singapore England Finland
International
Pooled
Project-based learning 0.466***
(0.043) 0.378***
(0.047) 0.384***
(0.038) 0.360***
(0.057) 0.169***
(0.056) 0.270***
(0.010)
Female 0.151***
(0.054) 0.212***
(0.042) -0.069
(0.044) 0.015
(0.055) -0.064
(0.050) -0.039***
(0.010)
Age -0.036
(0.036) 0.036
(0.029) 0.034*
(0.020) -0.005
(0.019) 0.051**
(0.025) 0.006
(0.005)
Age2 0.000
(0.000) -0.000
(0.000) -0.000
(0.000) 0.000
(0.000) -0.001**
(0.000) -0.000
(0.000)
Experience 0.045***
(0.015) 0.004
(0.015) 0.030***
(0.009) 0.021
(0.014) 0.015
(0.013) 0.014***
(0.002)
Experience2 -0.001*
(0.000) 0.000
(0.000) -0.000*
(0.000) -0.000
(0.000) -0.000
(0.000) -0.000***
(0.000)
Doctorate degree 0.192
(0.175) 0.248
(0.241) 0.589***
(0.170) -0.007
(0.343) 0.405*
(0.224) 0.057
(0.049)
Permanent -0.087
(0.072) -0.082
(0.064) -0.035
(0.069) 0.138
(0.109) -0.008
(0.050) -0.024*
(0.014)
Negative view on
prof. development -0.204***
(0.045) -0.022
(0.042) -0.052
(0.045) -0.115**
(0.058) -0.078*
(0.042) -0.086***
(0.009)
School Fixed Effect YES YES YES YES YES YES
Observations
R-squared 2,254
0.184 2,915
0.172 2,828
0.157 1,908
0.170 2,232
0.11 78,155
0.527
Notes: Efficacy in student engagement variable standardized to have a mean of 0 and standard
deviation of 1 within each country. Experience: total years of teaching experience. Doctorate degree:
dummy variable indicating completion of doctorate degree. Permanent: dummy variable indicating
permanent employment status. Negative view on prof. development: dummy variable indicating
teacher’s negative feelings on the relevance of professional development activities offered. Standard
errors obtained through balanced repeated replication weights in parentheses.
**p<0.05
***p<0.01
Source: TALIS 2013
19
Table 6. Project-Based Learning and Efficacy in Class Management: OLS Micro
Estimates – Within Schools
D
ependent Variable:
E
fficacy in Class
Management Korea Japan Singapore England Finland
International
Pooled
Project-based learning 0.372***
(0.042) 0.365***
(0.047) 0.357***
(0.043) 0.245***
(0.065) 0.052
(0.056) 0.232***
(0.012)
Female 0.210***
(0.055) 0.335***
(0.039) -0.104***
(0.040) -0.033
(0.050) -0.043
(0.043) -0.024**
(0.011)
Age -0.009
(0.037) 0.034
(0.027) 0.055***
(0.020) -0.009
(0.018) 0.014
(0.027) -0.001
(0.006)
Age2 -0.000
(0.000) -0.000
(0.000) -0.001**
(0.000) 0.000
(0.000) -0.000
(0.000) -0.000
(0.000)
Experience 0.043***
(0.015) 0.021
(0.014) 0.018**
(0.009) 0.033**
(0.016) 0.027**
(0.012) 0.026***
(0.002)
Experience2 -0.001
(0.000) -0.000
(0.000) -0.000
(0.000) -0.001
(0.000) -0.001*
(0.000) -0.000***
(0.000)
Doctorate degree 0.030
(0.136) 0.031
(0.234) 0.601***
(0.177) -0.342
(0.502) 0.157
(0.206) -0.077
(0.059)
Permanent -0.127*
(0.070) 0.020
(0.052) 0.047
(0.075) 0.407***
(0.122) 0.087
(0.066) 0.072***
(0.017)
N
egative view on
p
rof. development -0.184***
(0.045) 0.016
(0.038) -0.011
(0.051) -0.065
(0.055) -0.034
(0.054) -0.058***
(0.011)
School Fixed Effect YES YES YES YES YES YES
Observations
R-squared 2,254
0.175 2,915
0.170 2,828
0.132 1,908
0.154 2,232
0.100 78,155
0.351
Notes: Efficacy in class management variable standardized to have a mean of 0 and standard deviation
of 1 within each country. Experience: total years of teaching experience. Doctorate degree: dummy
variable indicating completion of doctorate degree. Permanent: dummy variable indicating permanent
employment status. Negative view on prof. development: dummy variable indicating teacher’s
negative feelings on the relevance of professional development activities offered. Standard errors
obtained through balanced repeated replication weights in parentheses.
*p<0.1
**p<0.05
***p<0.01
Source: TALIS 2013
20
Thus far, our results indicate that greater frequency of conducting project-based learning
is positively correlated with teacher self-efficacy. Such a relation holds true not only at the
cross-country level, but also within countries. In particular, the strong positive correlation
between project-based learning and teacher self-efficacy is existent even after controlling for
differences between schools within each country, and the same holds for the relationship
between project-based learning and each of the three sub-categories of teacher self-efficacy.
Comparisons of the point estimates for project-based learning revealed that the correlation
between project-based learning and teacher self-efficacy is particularly strong for Korean
teachers. In the case of the between-school analysis using equation (1), conducting project-
based learning on a more frequent basis is associated with higher teacher self-efficacy level
of 0.441 standard deviations for the Korean sample, which is approximately 48% greater than
the higher teacher self-efficacy level (0.298 standard deviations) associated with more
frequent project-based learning for the international pooled sample. When controlling for
school fixed effects, the point estimate of project-based learning for Korea (0.448) is greater
than the point estimate of the international pooled sample (0.287) by approximately 56%.
However, the analyses conducted thus far only reveal relationships of correlation and thus
it is difficult to make causal interpretations. In other words, while it is possible that
conducting project-based learning leads to higher levels of teacher self-efficacy, it could also
be the case that teachers who have greater self-efficacy tend to conduct project-based learning
on a more frequent basis.
In order to deal with the issue of causality, we analyze data from a field experiment on
project-based learning conducted on middle school teachers of Daegu city.
V. Empirical Analysis of a Field Experiment on Project-Based Learning
In order to empirically analyze the effect of project-based learning on teacher self-efficacy in
a more causal way, from August to December of 2015 we conducted a teacher training
program on project-based learning for teachers from two Daegu city middle schools. After
providing training and consultation on project-based learning for a single semester (the fall
semester of the 2015 school year), we surveyed teachers of two middle schools that received
training (treatment group) and three schools that did not (control group).8 As shown in Table
7, 51 teachers from the treatment group and 58 teachers from the control group participated in
the survey.
8 The two schools of the treatment group voluntarily applied for the project-based learning teacher training
program, and the three schools of the control group were selected from the same school district as that of the
treatment group. Therefore, the field experiment is weak in meeting the condition of random selection and
issues of endogeneity are likely to exist.
21
Table 7. Project-Based Learning Field Experiment Survey
Type No. of
Participants Proportion
Treatment Group School A 12 11.01% 46.79%
School B 39 35.78%
Control Group
School C 31 28.44%
53.21%
School D 16 14.68%
School E 11 10.09%
Total 109 100%
N
otes: After conducting the project-based learning teacher training program on middle
school teachers from August 2015 until December 2015, the survey was conducted on the
teachers of the treatment group (two schools) and control group (three schools).
Source: Daegu field experiment data.
The difference in pre-determined characteristics between teachers of the treatment and
control groups, including gender, education, total teaching experience and experience in
current school, are shown in Table 8. It is evident that there is no statistical difference in
gender proportion between the treatment and control groups. Also, there is no statistical
between-group difference in the proportion of teachers whose highest education level is
master’s degree or higher. In the case of total teaching experience, teachers of the treatment
group, on average, had 11 months of more teaching experience than teachers of the control
group, but the difference was not statistically significant. However, teachers in the control
group had, on average, more than seven years (87 months) of more experience in teaching at
the current school than that of teachers from the treatment group, and this difference was
significant at the 1% level.
22
Table 8. Comparison of Teacher Characteristics between the Treatment and Control
Groups
Dependent Variable: Gender Education Total
Teaching
Experience
Teaching
Experience at
Current School
Panel A: Entire Treatment
Group
Treatment Group
(School A, School B) -0.140
(0.096) 0.150
(0.096) -10.871
(19.634) -87.080***
(17.746)
Observations 109 108 105 104
R-squared 0.020 0.022 0.003 0.186
Panel B: School A Only
Treatment Group
(School A) -0.052
(0.161) 0.061
(0.161) -56.185*
(29.967) -57.462**
(27.576)
Observations 70 69 66 65
R-squared 0.002 0.002 0.037 0.037
Panel C: School B Only
Treatment Group
(School B) -0.167
(0.103) 0.177*
(0.103) 3.071
(19.966) -96.193***
(16.960)
Observations 97 96 93 92
R-squared 0.027 0.030 0.000 0.211
N
otes: Gender: Male=1, Female=0. Education: Dummy indicator for completing master’s degree o
r
above (includes master’s degree, completion or graduation from doctorate level program). The
teaching experience variables are expressed in months. Robust standard errors in parentheses.
*p<0.1
**p<0.05
***p<0.01
Source: Daegu field experiment data.
To assess the level of teacher self-efficacy for our experiment, we used the same 12
questions used by the TALIS 2013 survey to measure the sub-categories of teacher self-
efficacy (efficacy in instruction, efficacy in student engagement, efficacy in class
management), and then used the average of the three sub-categories to measure teacher self-
efficacy. For a more precise empirical analysis, the pre-determined characteristics of the
treatment and control groups need to be statistically identical. However, as previously
mentioned, there was a statistically significant difference in the ‘teaching experience in the
current school’ between the treatment and control groups. Also, when comparing only School
23
A of the treatment group with the control group, there was a statistically significant difference
in ‘total teaching experience’ and ‘teaching experience in the current school’. For this reason,
when estimating the effect of project-based learning on teacher self-efficacy, we include
controls for pre-determined characteristics, including gender, a dummy indicator for
completion of master’s degree or higher, total teaching experience and teaching experience at
the current school. The equation used for analysis is as follows:





(3)
where is a variable on self-efficacy of teacher , standardized to have a mean of 0 and
standard deviation of 1 of the control group, and 
is the dummy variable
indicating whether teacher was treated with the project-based learning training program.
is a vector of teacher s pre-determined characteristics, and is the error term.
The OLS estimates obtained through equation (3) are reported in Table 9. After
conducting a teacher training program on project-based learning for a single semester during
the fall semester of the 2015 school year, the teachers of the treatment group show higher
levels of efficacy in instruction and efficacy in student engagement than those of the teachers
in the control group, and the difference is statistically significant. For efficacy in class
management, however, there is no statistical difference between the two groups. In the case
of the integrated measure of teacher self-efficacy, the level for teachers of the treatment group
are 0.4~0.5 standard deviations higher than that of the control group, which is very similar to
the previously reported point estimates of OLS regressions using the TALIS 2013 Korean
sample.
In particular, such results seem quite large when considering the relatively short period of
time of the experiment. Also, it may be natural that initially there is a positive effect on
efficacy in instruction and efficacy in student engagement, and that more time is required for
changes in efficacy in class management to occur.
24
Table 9. The Effects of Project-Based Learning on Teacher Self-Efficacy
Dependent Variable: Efficacy in
Instruction Efficacy in Student
Engagement Efficacy in Class
Management Teacher
Self-Efficacy
(1) (2) (3) (4) (5) (6) (7) (8)
Treatment 0.485**
(0.195) 0.509**
(0.247) 0.485**
(0.202) 0.631**
(0.245) 0.184
(0.183) 0.217
(0.202) 0.435**
(0.194) 0.513**
(0.227)
Control Variables NO YES NO YES NO YES NO YES
Observations
R-squared 109
0.055 100
0.123 109
0.052 100
0.077 109
0.009 100
0.021 109
0.045 100
0.079
N
otes: Controls: Gender (male=1, female=0), education level (master’s degree or above=1, below
master’s degree=0), total teaching experience, and teaching experience at current school. Dependen
t
variables standardized to have a mean of 0 and standard deviation of 1 of the control group. The
survey questions to assess the sub-categories of teacher self-efficacy were obtained from the survey
questionnaire of TALIS 2013. Each question is answered on a four-point scale (1: “Never” ~ 4: “In
all or nearly all lessons”), and there are four questions asked for each sub-category. The actual
survey questionnaire is shown in Figures 1A~3A of the Appendix. Robust standard errors in
p
arentheses.
*p<0.1
**p<0.05
***p<0.01
Source: Daegu field experiment data.
The results of the empirical analysis using data from the Daegu experiment, despite the
relatively short period of implementation and the limitation of a small sample, are fairly
consistent with the results of the analysis using the TALIS database. The results of the
analyses on the two different datasets show that conducting project-based learning is
associated with higher teacher self-efficacy levels of approximately 0.4~0.5 standard
deviations. The association between project-based learning and efficacy in instruction and
efficacy in class management are quite high and statistically significant for analyses using
both datasets. In the case of efficacy in class management, training in project-based learning
has no significant impact for the Daegu experiment data, but analysis using the TALIS
database showed a positive and statistically significant relationship between project-based
learning and efficacy in class management. However, for analysis on the TALIS database, it
should be noted that the OLS estimate of the project-based learning variable with efficacy in
class management as the dependent variable is lower than the OLS estimates of the project-
based learning variable for regressions on other sub-categories of teacher self-efficacy, and
thus it can be said that the regression results using the two datasets show some degree of
consistency.
Despite such consistency between the results of analyses using the TALIS database and
the Daegu experiment data, there are limitations that should be noted. In the case of the
25
TALIS database, although the sample size is quite large and the survey was designed to be
compatible for international comparison, endogeneity may exist in the relationship between
project-based learning and teacher self-efficacy which cannot be fully controlled. For the
Daegu field experiment, the data consists of a relatively small sample size, as a total of 109
teachers from five schools (two in the treatment group, three in the control group) took part in
the experiment. Also, schools of the treatment group voluntarily applied for the project-based
learning teacher training program, which means participation in the program was not
determined exogenously, and schools of the control group were selected among those in the
same school district as that of the treatment group. Such a limitation may induce bias
pertaining to sample selection and omitted variables.
The second phase of the Daegu experiment, expected to take place in 2016, will provide
us with more extensive data, including a larger treatment group (six schools) and information
from all remaining schools in Daegu city (126 schools). This will allow us to conduct more
rigorous quasi-experimental empirical analysis on the causal relationship between project-
based learning and teacher self-efficacy.
VI. Conclusion
In recent years, research in education has recognized the limitations of quantitative measures,
such as years of schooling, and has increasingly focused on empirical analysis of qualitative
measures like students’ academic achievement (Hanushek & Woessmann, 2010). In the case
of Korea, focusing on student test scores has the effect of overshadowing serious qualitative
problems of Korea’s education, namely excessive use of rote learning (Lee, Jeong, & Hong,
2014). Therefore, there needs to be more emphasis on the empirical analysis of variables
directly pertaining to teaching practices like project-based learning in order to gain a more
clear understanding of the fundamental problems of Korea’s education.
This research analyzed the relationship between project-based learning and teacher self-
efficacy using various databases, and obtained the following results.
First, through the internationally comparable PISA and TALIS databases it is evident that
Korea’s rate of conducting project-based learning is much lower than that of other countries.
In particular, the TALIS database shows that Korean teachers conduct project-based learning
at the lowest rate among the 31 countries compared.
Second, a cross-country analysis shows that low rate of project-based learning is strongly
correlated with low teacher self-efficacy. In other words, countries with greater rates of
conducting project-based learning tend to have higher levels of teacher self-efficacy, and this
implies that Korea’s low rate of project-based learning can have important implications for
Korea’s education.
Third, micro data analysis using the TALIS database reveals that in the case of Korea,
conducting project-based learning on a more frequent basis is associated with a higher
teacher self-efficacy level of 0.441 standard deviations. After controlling for differences
among schools, Korean teachers’ relatively more frequent use of project-based learning is
associated with a higher teacher self-efficacy level of 0.448 standard deviations, which is the
26
third highest degree of association among the 31 countries compared. Project-based learning
is also strongly and positively associated with efficacy in instruction, efficacy in student
engagement, and efficacy in class management.
Fourth, analysis of the Daegu field experiment data reveals that teacher training in
project-based learning is associated with higher teacher self-efficacy levels of 0.4 to 0.5
standard deviations, which are similar to the point estimates of the analysis using the TALIS
database. The fact that analyses on two different datasets lead to consistent results is quite
meaningful, but limitations do exist, as both analyses are not free from endogeneity issues. In
particular, for the Daegu field experiment data, the sample size is quite small and the bias
pertaining to sample selection and omitted variables could not be fully eliminated.
The second phase of the Daegu field experiment will lead to the gathering of more
extensive data which will allow for more precise analysis on the empirical relationship
between project-based learning and teacher self-efficacy.
27
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28
Appendix
Figure 1A. TALIS Survey Questions on Assessing Efficacy in Instruction
In your teaching, to what extent can you do the following?
Question Not at all To some
extent Quite a bit A lot
Craft good questions for my students
Use a variety of assessment strategies
Provide an alternative explanation for
example when students are confused.
Implement alternative instructional strategies
in my classroom
Figure 2A. TALIS Survey Questions on Assessing Efficacy in Student Engagement
In your teaching, to what extent can you do the following?
Question Not at all To some
extent Quite a bit A lot
Get students to believe they can do well in
school work
Help my st udents valu e l ear ning
Motivate students who show low interest in
school work.
Help students think critically
Figure 3A. TALIS Survey Questions on Assessing Efficacy in Class Management
In your teaching, to what extent can you do the following?
Question Not at all To some
extent Quite a bit A lot
Control disruptive behavior in the classroom
Make my expectations about student
behavior clear
Get students to follow classroom rules
Calm a student who is disruptive or noisy
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Paper 09-22 Younguck KANG Demand Analysis of Public Education: A Quest for New Public Education System for
Next Generation
Working
Paper 09-23 Seong-Ho CHO
Jinsoo LEE Valuation and Underpricing of IPOs in Korea
Working
Paper 09-24 Seong-Ho CHO Kumho Asiana’s LBO Takeover on Korea Express
Working
Paper 10-01 Yun-Yeong KIM
Jinsoo LEE Identification of Momentum and Disposition Effects Through Asset Return Volatility
Working
Paper 10-02 Kwon JUNG Four Faces of Silver Consumers:
A Typology, Their Aspirations, and Life Satisfaction of Older Korean Consumers
Working
Paper 10-03 Jinsoo LEE
Seongwuk MOON Corporate Governance and
International Portfolio Investment in Equities
Working
Paper 10-04 Jinsoo LEE Global Convergence in Tobin’s Q Ratios
Working
Paper 10-05 Seongwuk MOON Competition, Capability Buildup and Innovation: The Role of Exogenous Intra-firm
Revenue Sharing
Working
Paper 10-06 Kwon JUNG Credit Card Usage Behaviors among Elderly Korean Consumers
Working
Paper 10-07 Yu-Sang CHANG
Jinsoo LEE Forecasting Road Fatalities by the Use of Kinked Experience Curve
Working
Paper 10-08 Man CHO Securitization and Asset Price Cycle: Causality and Post-Crisis Policy Reform
Working
Paper 10-09 Man CHO
Insik MIN Asset Market Correlation and Stress Testing: Cases for Housing and Stock Markets
Working
Paper 10-10 Yu-Sang CHANG
Jinsoo LEE Is Forecasting Future Suicide Rates Possible?
- Application of the Experience Curve -
Working
Paper 10-11 Seongwuk MOON What Determines the Openness of Korean Manufacturing Firms to External
Knowledge?
Working
Paper 10-12 Joong Ho HAN
Kwangwoo PARK
George PENNACCHI Corporate Taxes and Securitization
Working
Paper 10-13 Younguck KANG Housing Policy of Korea: Old Paradigm, New Approach
Working
Paper 10-14 Il Chong NAM A Proposal to Reform the Korean CBP Market
Working
Paper 10-15 Younguck KANG Balanced Regional Growth Strategy based on the Economies of Agglomeration:
the Other Side of Story
Working
Paper 10-16 Joong Ho HAN CEO Equity versus Inside Debt Holdings and Private Debt Contracting
* The above papers are available at KDI School Website <http://www.kdischool.ac.kr/new/eng/faculty/working.jsp>.
You may get additional copy of the documents by downloading it using the Acrobat Reader.
Working Paper Series
Category Serial # Author Title
Working
Paper 11-01 Yeon-Koo CHE
Rajiv SETHI Economic Consequences of Speculative Side Bets:
The Case of Naked Credit Default Swaps
Working
Paper 11-02 Tae Hee CHOI
Martina SIPKOVA Business Ethics in the Czech Republic
Working
Paper 11-03 Sunwoo HWANG
Woochan KIM Anti-Takeover Charter Amendments and Managerial Entrenchment: Evidence from
Korea
Working
Paper 11-04 Yu Sang CHANG
Jinsoo LEE
Yun Seok JUNG
The Speed and Impact of a New Technology Diffusion in Organ Transplantation:
A Case Study Approach
Working
Paper 11-05 Jin PARK
Jiwon LEE The Direction of Inter-Korean Cooperation Fund
Based on ODA Standard
Working
Paper 11-06 Woochan KIM Korea Investment Corporation: Its Origin and Evolution
Working
Paper 11-07 Seung-Joo LEE Dynamic Capabilities at Samsung Electronics:
Analysis of its Growth Strategy in Semiconductors
Working
Paper 11-08 Joong Ho HAN Deposit Insurance and Industrial Volatility
Working
Paper 11-09 Dong-Young KIM Transformation from Conflict to Collaboration through Multistakeholder Process:
Shihwa Sustainable Development Committee in Korea
Working
Paper 11-10 Seongwuk MOON How will Openness to External Knowledge Impact Service Innovation? Evidence from
Korean Service Sector
Working
Paper 11-11 Jin PARK Korea’s Technical Assistance for Better Governance:
A Case Study in Indonesia
Working
Paper 12-01 Seongwuk MOON How Did Korea Catch Up with Developed Countries in DRAM Industry? The Role of
Public Sector in Demand Creation: PART 1
Working
Paper 12-02 Yong S. Lee
Young U. Kang
Hun J Park The Workplace Ethics of Public Servants in Developing Countries
Working
Paper 12-03 Ji-Hong KIM Deposit Insurance System in Korea and Reform
Working
Paper 12-04 Yu Sang Chang
Jinsoo Lee
Yun Seok Jung
Technology Improvement Rates of Knowledge Industries following Moore’s Law?
-An Empirical Study of Microprocessor, Mobile Cellular, and Genome Sequencing
Technologies-
Working
Paper 12-05 Man Cho Contagious Real Estate Cycles: Causes, Consequences, and Policy Implications
Working
Paper 12-06 Younguck KANG
Dhani Setvawan INTERGOVERNMENTAL TRANSFER AND THE FLYPAPER EFFECT
– Evidence from Municipalities/Regencies in Indonesia –
Working
Paper 12-07 Younguck KANG Civil Petitions and Appeals in Korea
: Investigating Rhetoric and Institutional settings
Working
Paper 12-08 Yu Sang Chang
Jinsoo Lee Alternative Projection of the World Energy Consumption
-in Comparison with the 2010 International Energy Outlook
Working
Paper 12-09 Hyeok Jeong The Price of Experience
Working
Paper 12-10 Hyeok Jeong Complementarity and Transition to Modern Economic Growth
Working
Paper 13-01 Yu Sang CHANG
Jinsoo LEE
Hyuk Ju KWON
When Will the Millennium Development Goal on Infant Mortality Rate Be Realized?
- Projections for 21 OECD Countries through 2050-
Working
Paper 13-02 Yoon-Ha Yoo Stronger Property Rights Enforcement Does Not Hurt Social Welfare
-A Comment on Gonzalez’ “Effective Property Rights, Conflict and Growth (JET,
2007)”-
Working
Paper 13-03 Yu Sang CHANG
Changyong CHOI Will the Stop TB Partnership Targets on TB Control be Realized on Schedule?
- Projection of Future Incidence, Prevalence and Death Rates -
Working
Paper 13-04 Yu Sang CHANG
Changyong CHOI Can We Predict Long-Term Future Crime Rates?
– Projection of Crime Rates through 2030 for Individual States in the U.S. –
* The above papers are available at KDI School Website <http://www.kdischool.ac.kr/new/eng/faculty/working.jsp>.
You may get additional copy of the documents by downloading it using the Acrobat Reader.
Working Paper Series
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Paper 13-05 Chrysostomos Tabakis Free-Trade Areas and Special Protection
Working
Paper 13-06 Hyeok Jeong Dynamics of Firms and Trade in General Equilibrium
Working
Paper 13-07 Hyeok Jeong Testing Solow's Implications on the Effective Development Policy
Working
Paper 13-08 Jaeun SHIN Long-Term Care Insurance and Health Care Financing in South Korea
Working
Paper 13-09 Ilchong Nam Investment Incentives for Nuclear Generators and Competition in the Electricity Market
of Korea
Working
Paper 13-10 Ilchong Nam Market Structure of the Nuclear Power Industry in Korea and Incentives of Major Firms
Working
Paper 13-11 Ji Hong KIM Global Imbalances
Working
Paper 14-01 Woochan KIM When Heirs Become Major Shareholders
Working
Paper 14-02 Chrysostomos Tabakis Antidumping Echoing
Working
Paper 14-03 Ju Ho Lee Is Korea Number One in Human Capital Accumulation?:
Education Bubble Formation and its Labor Market Evidence
Working
Paper 14-04 Chrysostomos Tabakis Regionalism and Con
ict: Peace Creation and Peace Diversion
Working
Paper 14-05 Ju Ho Lee Making Education Reform Happen:
Removal of Education Bubble through Education Diversification
Working
Paper 14-06 Sung Joon Paik Pre-employment VET Investment Strategy in Developing Countries
- Based on the Experiences of Korea -
Working
Paper 14-07 Ju Ho Lee
Josh Sung-Chang Ryoo
Sam-Ho Le
e
From Multiple Choices to Performance Assessment:
Theory, Practice, and Strategy
Working
Paper 14-08 Sung Joon Paik Changes in the effect of education on the earnings differentials between men and
women in Korea (1990-2010)
Working
Paper 14-09 Shun Wang Social Capital and Rotating Labor Associations:
Evidence from China
Working
Paper 14-10 Hun Joo Park Recasting the North Korean Problem:
Towards Critically Rethinking about the Perennial Crisis of the Amoral Family State
and How to Resolve I
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Paper 14-11 Yooncheong Cho Justice, Dissatisfaction, and Public Confidence in the E-Governance)
Working
Paper 14-12 Shun Wang The Long-Term Consequences of Family Class Origins in Urban China
Working
Paper 14-13 Jisun Baek Effect of High-speed Train Introduction on Consumer Welfare
Working
Paper 14-14 Jisun Baek Effect of High Speed Trains on Passenger Travel: Evidence from Korea
Working
Paper 15-01 Tae-Hee Choi Governance and Business Ethics - An International Analysis
Working
Paper 15-02 Jisun Baek The Impact of Improved Passenger Transport System on Manufacturing Plant
Productivity
Working
Paper 15-03 Shun Wang The Unintended Long-term Consequences of Mao’s Mass Send-Down Movement:
Marriage, Social Network, and Happiness
Working
Paper 15-04 Changyong Choi Information and Communication Technology and the Authoritarian Regime:
A Case Study of North Korea
Working
Paper 15-05 Wonhyuk Lim
William P. Mako AIIB Business Strategy Decisions:
What Can It Do Differently to Make a Difference?
* The above papers are available at KDI School Website <http://www.kdischool.ac.kr/new/eng/faculty/working.jsp>.
You may get additional copy of the documents by downloading it using the Acrobat Reader.
Working Paper Series
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Paper 15-06
Ju-Ho Lee
Kiwan Kim
Song-Chang Hong
JeeHee Yoon
Can Bureaucrats Stimulate High-Risk High-Payoff Research?
Working
Paper 15-07 Seulki Choi Geographical Proximity with Elderly Parents of Korean Married Women in 30-40s
Working
Paper 15-08 Taejun Lee An Analysis of Retirement Financial Service Providers' Approach to Using Websites to
Augment Consumer Financial Acumen
Working
Paper 15-09 Sung Joon Paik Education and Inclusive Growth – Korean Experience
Working
Paper 15-10 Sung Joon Paik Policies to Attract High Quality Foreign Students into Korea
Working
Paper 15-11 Changyong Choi
June Mi Kang · ODA 전략 비교 분석: 지식공유사업(KSP) 사례연구
Working
Paper 15-12 WooRam Park
Jisun Baek Firm’s Employment Adjustment in Response to Labor Regulation
Working
Paper 15-13 Jisun Baek
WooRam Park Higher Education, Productivity Revelation and Performance Pay Jobs
Working
Paper 15-14 Sung Joon Paik 고급 두뇌인력 네트워크 구축ㆍ활용 정책 - 국제 사례 분석
Working
Paper 15-15 Sunme Lee
Yooncheong Cho Exploring Utility, Attitude, Intention to Use, Satisfaction, and Loyalty in B2C/P2P Car-
Sharing Economy
Working
Paper 15-16 Chrysostomos Tabakis Endogenous Sequencing of Tariff Decisions
Working
Paper 15-17 Tae Hee Choi Business Ethics - Evidence from Korea
Working
Paper 16-01 Hyeok Jeong
Ju-Ho Lee Korea’s Age-Skill Profile from PIAAC: Features and Puzzles
Working
Paper 16-02
M. Jae Moon
Ju-Ho Lee
Jin Park
Jieun Chung
Jung Hee Choi
Skills and Wages of Public Employees
Investigating Korean Bureaucracy through PIAAC
Working
Paper 16-03 Taejun Lee The Role of Psychological Processing and Government-Public Relationship in
Managing the Public’s Communicative Actions of Problem-Solving
Working
Paper 16-04 Shun Wang
Wenia Zhou Do Siblings Make Us Happy?
Working
Paper 16-05
Junghee Choi
Booyuel Kim
Ju-Ho Lee
Yoonsoo Park
The Impact of Project-Based Learning on Teacher Self-efficacy
* The above papers are available at KDI School Website <http://www.kdischool.ac.kr/new/eng/faculty/working.jsp>.
You may get additional copy of the documents by downloading it using the Acrobat Reader.
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