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The Effects of Problem-Based, Project-Based, and Case-Based Learning on Students’
Motivation: A Meta-Analysis
[Eindrapport NRO-project 405-15-720]
Lisette Wijnia a, b *([email protected])
Sofie M. M. Loyens a, b
Gera Noordzij c
Lidia R. Arends b, d
Remy M. J. P. Rikers a, b
aRoosevelt Center for Excellence in Education, University College Roosevelt, Utrecht
University, Lange Noordstraat 1, 4330 AB Middelburg, the Netherlands
bDepartment of Psychology, Education and Child Studies, Erasmus University Rotterdam, PO
Box 1738, 3000 DR, Rotterdam, the Netherlands
cErasmus Unversity College, Erasmus University Rotterdam, the Netherlands
dDepartment of Biostatistics, Erasmus MC, Rotterdam, the Netherlands
2
Samenvatting
Student-gecentreerde leeromgevingen, zoals probleemgestuurd onderwijs (PGO), project-
gestuurd onderwijs (PjGO) en casusgericht leren (CGL) worden vaak geïntroduceerd om de
motivatie van leerlingen en studenten te verhogen. Het hoofddoel van deze overzichtsstudie is
om te onderzoeken of deze instructiemethoden inderdaad een positief effect hebben op de
leermotivatie. Daarnaast onderzoeken wij of de drie methoden van elkaar verschillen in hun
effecten op motivatieconstructen. Bovendien werd gekeken naar systematische verschillen
tussen de gevonden effecten en of deze verschillen werden bepaald door kenmerken van de
studie, leeromgeving, of het motivatieconstruct dat gemeten werd.
Op basis van literatuuronderzoek werden 131 artikelen/ onderzoeksrapporten
gevonden, waarin het effect van PGO, PjGO of CGL op motivatie werd onderzocht. Over
deze artikelen is een meta-analyse uitgevoerd. Er werd een klein-tot-gemiddeld, positief effect
gevonden van de drie instructiemethodes op motivatie. Dit positieve effect bevestigt de
veronderstelling dat student-gecentreerde instructiemethodes de leermotivatie kunnen
verhogen.
Echter, bepaalde variabelen hadden invloed op hoe effectief de instructiemethodes
waren voor motivatie. Zo werden er voor PGO kleinere effecten gevonden dan voor PjGO en
CGL. Bovendien bleek het effect kleiner voor studies die in het basis- en middelbaar
onderwijs waren uitgevoerd vergeleken met de studies uitgevoerd in het hoger onderwijs.
Niet-gepubliceerde onderzoeksrapporten (bijv. dissertaties) rapporteerden daarnaast kleinere
effecten dan gepubliceerde artikelen. Ook werd het effect van instructiemethode op motivatie
kleiner naarmate de kwaliteit van het gemeten motivatieconstruct toenam. De kwaliteit van
het motivatieconstruct gaf een indicatie van hoe duidelijk het construct stond beschreven in
het onderzoeksrapport/ artikel.
3
Motivatie is opgebouwd uit verschillende facetten, zoals 1) de waargenomen controle
over het leren (bijv. vertrouwen in eigen kunnen), 2) attitude ten opzichte van leren, 2)
percepties van de waarde van de taak en 3) de redenen om te studeren (bijv. intrinsieke
redenen). Daarom is ook onderzocht of er verschillende effecten gevonden werden per type
motivatie. Voor de eerste drie constructen werden positieve effecten gevonden van alle drie
de instructiemethoden. Echter, het effect van PjGO op waargenomen controle en attitude was
groter dan het effect van PGO. Voor “redenen om te studeren” werd alleen een klein, positief
effect gevonden van PjGO.
De resultaten van onze meta-analyse hebben implicaties voor de onderwijspraktijk. Uit
het onderzoek komt naar voren dat PGO, PJGO en CGL een positief effect op motivatie
kunnen hebben, maar de grootte van dit effect hangt af van verschillende factoren. Dat het
effect kleiner was in het basis- en voortgezet onderwijs, komt mogelijk omdat deze
leermethodes veelal in het hoger onderwijs zijn ontwikkeld. Dit betekent dat er goed moet
worden gekeken hoe de methodes aangepast kunnen worden naar een andere setting. Ook
moeten leerlingen en docenten goed voorbereid worden als de onderwijsmethode wordt
geïmplementeerd. Bovendien lijken de effecten voor PjGO groter te zijn dan voor PGO. Dit
hoeft niet te betekenen dat PjGO effectiever is voor de motivatie. Mogelijk wordt het effect
verklaard doordat PjGO vaak als tijdelijke aanvulling op het reguliere programma wordt
gebruikt. Omdat de methode dan mogelijk als “nieuw” wordt gezien, zou de motivatie extra
geprikkeld kunnen worden. Toekomstig onderzoek dient hier uitsluitsel over te geven.
Keywords: Motivation, attitude, problem-based learning, project-based learning, case-based
learning.
4
Content
Samenvatting ........................................................................................................................................ 2
Content ................................................................................................................................................. 4
Chapter 1: Introduction .............................................................................................................. 5
1.1 Lifelong Learning .................................................................................................................. 5
1.2 Theoretical Framework: Motivation to Learn ....................................................................... 6
1.3 Problem-based, Project-Based, and Case-Based Learning .................................................. 11
1.4 Prior Reviews and Meta-Analyses ...................................................................................... 14
1.5 Objectives and Research Questions ..................................................................................... 16
Chapter 2: Method ..................................................................................................................... 19
2.1 Literature Search ................................................................................................................. 19
2.2 Inclusion of Studies ............................................................................................................. 20
2.3 Coding Procedure ................................................................................................................ 23
2.4 Data Analyses ...................................................................................................................... 25
Chapter 3: Results of the Meta-Analysis ................................................................................. 27
3.1 Description of Studies ......................................................................................................... 27
3.2 Overall Effects on Motivation ............................................................................................. 27
3.3 Effects on Control Beliefs, Attitude, Task Value, and Goals and Reasons ......................... 33
Chapter 4: Studies with Longitudinal Designs ........................................................................ 35
Chapter 5: Discussion ................................................................................................................ 36
5.1 Aims of Meta-Analysis ........................................................................................................ 36
5.2 Main Results of the Meta-Analysis ..................................................................................... 37
5.3 Effects of Moderators .......................................................................................................... 37
5.4 Effects on Different Motivational Constructs ...................................................................... 39
5.5 Limitations ........................................................................................................................... 41
5.6 Implications for Research and Practice ............................................................................... 42
Acknowledgements. ........................................................................................................................... 44
References .......................................................................................................................................... 45
Appendix A: Search terms ............................................................................................................ 72
Appendix B: Coding Scheme – Problem-Based Learning .......................................................... 73
Appendix C: Overview of the PBL Papers .................................................................................. 77
Appendix D: Overview of the PjBL Papers ................................................................................. 81
Appendix E: Overview of the CBL Papers .................................................................................. 83
5
Chapter 1: Introduction
1.1 Lifelong Learning
Since the beginning of this century, lifelong learning has been a central issue in European
education policy (Commission of the European Communities, 2000; European Commission,
2001). In our current society, knowledge and skills change rapidly, therefore employees need
to have the motivation and skills to continuously learn and develop themselves throughout
their careers (Gijbels, Raemdonck, & Vervecken, 2010; Kyndt & Baert, 2013). Research has
indicated that employees’ motivational beliefs and willingness to learn are predictive of their
actual participation in learning activities (Kyndt & Baert, 2013).
Although all people are believed to have a natural inclination toward learning,
negative learning experiences or uncertainty can suppress this tendency (McCombs, 1991).
To foster students’ willingness to learn, student-centered learning methods are becoming
increasingly popular in education (Baeten, Kyndt, Struyven, & Dochy, 2010; Loyens &
Rikers, 2017; Könings, Brand-Gruwel, & Van Merriënboer, 2005; Schmidt, Van der Molen,
Te Winkel, & Wijnen, 2009). These methods were developed as a reaction to teacher-
centered learning, which focuses on the transmission of knowledge and meaning from the
teacher to students. In contrast, in student-centered learning, students have an active role and
make use of classroom practices such as observations, generating questions, discussion, and
self-study.
These active, student-centered learning methods aim to promote students’ motivation
and attitudes toward learning (e.g., Blumenfeld et al., 1991; Hmelo-Silver, 2004; Schmidt et
al., 2009). However, there is considerable debate about the effectiveness of these learning
environments. On the one hand, there are several factors present in student-centered
environments that have been shown to foster motivation. For example, students receive
6
ample opportunities to exercise control over their own learning process, which is assumed to
be motivating (Black & Deci, 2000). Furthermore, learning is often conducted in the context
of challenging, meaningful, realistic tasks, which can lead to higher motivation as well
(Blumenfeld, 1992; Norman & Schmidt, 1992). On the other hand, in these student-centered
learning environments, there is a potential danger that too little guidance is offered during
learning, which can lead to frustrations and uncertainties (Dahlgren & Dahlgren, 2002;
Miflin, Campbell, & Price, 1999, 2000), and might negatively affect motivation. The
objective of the current paper is to present the findings of a systematic review and meta-
analysis into the effects of three commonly implemented student-centered learning
environments on students’ motivational beliefs. Specifically, problem-based learning (PBL),
project-based learning (PJBL), and case-based learning (CBL) are examined.
1.2 Theoretical Framework: Motivation to Learn
Motivation is a complex and extensively researched subject (Murphy & Alexander, 2000;
Pintrich, 2003; Pintrich & Schunk, 2002). Although many different conceptualizations of and
theories on motivation exist, motivation to learn is often driven by two questions: “Can I do
this task?” and “Why am I doing this task?” (see Pintrich, 2003). Figure 1 presents an
overview of the motivational constructs incorporated in this review.
Can I do this task? Students’ answers to the question “Can I do this task?” are
determined by their control beliefs. Perceived control constructs can be classified in three
groups based on the relationship between the student who exerts control, the pathway through
which it is exerted, and the desired (or undesired) learning outcomes (Skinner, 1996). The
first group of perceived control constructs concerns students’ beliefs about their personal
capabilities or skills, such as self-efficacy beliefs (Skinner, 1996). Self-efficacy measures ask
students to rate their confidence in their ability to perform certain tasks (e.g., school tasks) or
7
Figure 1. Motivational framework and concepts.
8
skills (Bandura, 1997). The second group of constructs refers to students’ beliefs
about the factors that influence success in school, such as ability, effort, others, or chance
(Skinner, 1996). Within these constructs an internal locus of control or student-related causes
are contrasted against an external locus of control or non-student-related causes. Examples of
internal causes can refer to specific behaviors (e.g., effort) or attributes (e.g., ability) of the
student. In contrast, external causes are beyond the students’ control and can be divided in
those that emanate from others (e.g., task difficulty) or factors outside of human control (e.g.,
chance). It is believed that perceptions of internal control are more beneficial for learning
than perceptions of external control (Pintrich, 2003). The final group of perceived control
constructs refers to beliefs about one’s own influence on success. It concerns the extent to
which an individual can intentionally attain desired outcomes or prevent undesirable
outcomes (Skinner, 1996). Examples of these beliefs are outcome expectations or
competence expectancy beliefs in which students perceive a linkage between their doing and
the outcome (Bandura, 1997; Pintrich, 2003).
Research demonstrated that if students feel self-efficacious in their ability to perform a
study-related task, feel in control of their own learning, and perceive a link between their own
actions and the outcome, they are more likely to exert effort and to obtain better performances
(Bandura, 1997; Pintrich, 2003). Furthermore, control beliefs might play an important role in
promoting lifelong learning. For example, Kyndt and Baert (2013) concluded in their review
that an employee’s self-efficacy is one the best predictors of actual engagement in work-
related learning activities. Therefore, if educational environments can positively foster
effective control beliefs, students might be more inclined to learn now and in the future.
Why should I do this task? The question “Why should I do this task?” refers to three
elements: 1) students’ attitudes toward learning, 2) their perception of task value, and 3)
students’ reasons or goals for engaging in learning activities (Pintrich, 2003). An attitude
9
toward an activity reflects the individual’s global positive or negative evaluations of
performing a particular activity (Ajzen, 1991; Armitage & Conner, 2001). It is often
considered to be an affective evaluation of something (Germann, 1988). If students have a
positive attitude toward learning they are more likely to engage in it. Attitudes toward
learning are often measured in the context of Science, Technology, Engineering, and
Mathematics (STEM) courses, to measure how students feel toward STEM-subject in school
(Germann, 1988).
A related construct to attitude toward learning is task value. Task value is determined
by weighing the positive and negative aspects or consequences of engaging in an activity. If
students perceive the activity as important or useful for (future) plans or goals (e.g., finding a
job), they are more likely to engage in it (Eccles, 1983; Eccles & Wigfield, 2002; Wigfield &
Eccles, 2000). In addition, students’ interest in performing the activity (now or in the future)
is an important aspect of task value. In problem-based environments, interest is considered to
be the driving force for learning (Schmidt, Rotgans, & Yew, 2011).
Students’ goals or reasons to perform an activity determine if and why study-related
tasks are performed as well (Pintrich, 2003). Most people are familiar with the classical
distinction between intrinsic and extrinsic motivation. Intrinsically motivated students, study
because they find the task interesting or enjoyable, whereas extrinsically motivated students,
learn to obtain an external reward (e.g., recognition, praise, Ryan & Deci, 2000a). However,
current theories that focus on goals or reasons for studying, present a more differentiated view
on motivation to learn. Both achievement goal theory and self-determination theory are
focused on students’ reasons or goals for engaging in activities (Deci & Ryan, 2000; Elliot &
McGregor, 2001; Ryan & Deci, 2000a). They are the most commonly cited motivational
theories nowadays.
10
In achievement goal theory, goal orientation refers to how a person interprets and
reacts to tasks (e.g., Dweck & Leggett, 1988; Elliot & McGregor, 2001). An important
distinction is made between developing ability (i.e., learning/mastery goal orientation) versus
demonstrating ability (i.e., performance goal orientation) during goal pursuit. This distinction
was later refined by incorporating an approach/avoidance dimension, resulting in four types of
goal orientation: mastery-approach, mastery-avoidance, performance-approach, and
performance-avoidance goals (Elliot & McGregor, 2001). Individuals with a mastery-
approach goal want to develop their competence, whereas people with a mastery-avoidance
goal want to avoid the deterioration of their competence. In contrast, people with a
performance-approach goal want to demonstrate their competence or outperform others,
whereas individuals with a performance-avoidance goal want to avoid looking incompetent.
Self-determination theory presents a self-determination continuum that ranges from
intrinsic motivation to amotivation (Deci & Ryan, 1985, 2000; Ryan & Deci, 2000a, 2000b).
The most important distinction is made between autonomous and controlled motivation (Deci
& Ryan, 2008). Autonomously motivated students experience psychological freedom. They
either perform activities out of interest (i.e., intrinsic motivation) or because they want to
develop themselves or believe the task is important for obtaining personal life goals (i.e.,
identified motivation). In contrast, students with high scores on controlled motivation
experience pressure from within, such as feelings of shame or guilt (i.e., introjected
motivation) or from an external source, such as demands of others (i.e., external motivation).
Because the different types of motivation are expected to lie on a continuum, sometimes one
composite score is calculated, the relative autonomy index (RAI; Grolnick & Ryan, 1987).
The RAI gives insight into the degree of autonomy or self-determination a student
experiences. In addition to autonomous or controlled motivation, students can experience
amotivation as well (Deci & Ryan, 2000; Ryan & Deci, 2000a, 2000b). If students are
11
amotivated, they lack motivation to engage in the activity, for example, due to learned
helplessness.
Research has indicated that autonomous motivation has close links with mastery goal
orientation, whereas controlled motivation has close links with performance goal orientation
(Assor, Vansteenkiste, & Kaplan, 2009; Wijnia, Loyens, & Derous, 2011). Autonomous and
mastery goal types of motivation are often assumed more beneficial outcomes than controlled
and performance goal types of motivation (e.g., Deci & Ryan, 2000; Elliot & McGregor,
2001). In this review, scores on mastery goal orientation and autonomous motivation are
grouped in the same category, as are performance goal orientation and controlled motivation
(see Figure 1).
1.3 Problem-based, Project-Based, and Case-Based Learning
According to McCombs (1991), student-centered learning environments might foster
students’ motivational beliefs. In this review, we examine the effects of PBL, PjBL, and CBL
environments on students’ motivation to learn. These learning environments share similar
characteristics (Dochy, Segers, Gijbels, & Van den Bossche, 2002: Loyens & Rikers, 2017).
Firstly, teachers have a coaching instead of a directive role, whereas students have an active
role instead of a passive one. Furthermore, emphasis is put on knowledge construction
instead of reproduction and learning often takes place in small, collaborative groups. Finally,
PBL, PjBL and CBL are all methods of instruction based on inquiry. While the exact
operationalization might differ. All methods rely on the process of inquiry: generating
questions and working towards answers to these questions (Loyens & Rikers, 2017). Due to
the similarities between the learning environments, the terms problem-based, project-based,
and case-based are sometimes used interchangeably. However, in this review, we argue that
12
important differences exist between these three methods and that each environment has
unique characteristics that might affect student outcomes differently.
Problem-based learning. PBL is a student-centered, collaborative learning method,
in which small groups of students work together on meaningful, real-life problems under the
guidance of a teacher (Barrows, 1996). Although various types of PBL curricula can be
distinguished, researchers generally agree that PBL has five defining characteristics (Barrows,
1996; Hmelo-Silver, 2004; Schmidt et al., 2009). These characteristics include: 1) the use of
problems as the start of the learning process, 2) collaborative learning in small groups, 3)
student-centered, active learning, 4) the guiding role of teachers, and 5) ample time for self-
study.
In PBL, the learning process always starts with a problem. The problem describes an
event or phenomenon in daily life in need of explaining. An example of a problem was
described by Schmidt (1983a, p. 387): “A red blood cell is put into pure water under a
microscope. The red blood cell swells rapidly and eventually bursts. Another red blood cell is
added to a solution of salt in water and it is observed to shrink.” In groups of 5 to 12, students
try to explain or solve the problem by use of their prior knowledge and common sense
(Barrows, 1996; Schmidt, 1983b). Because students’ prior knowledge is insufficient to
understand the problem completely, students formulate learning issues (i.e., questions) for
further self-study. During the self-study phase, students use these learning issues to collect
and study new information (e.g., books, articles, websites). Students either conduct this self-
study process alone or together with fellow students. After a period of self-study, students
return to their groups to discuss their findings and apply the new knowledge to the problem.
In many PBL-environments, a large portion of time is allocated to the self-study process
(Schmidt et al., 2009).
13
Project-based learning. PjBL has its origins in the project method described by
Kilpatrick in 1918 and was later elaborated upon by other researchers, such as Blumenfeld et
al. (1991; Pecore, 2015; Savery, 2006). In PjBL, the learning process is organized around
projects (Loyens & Rikers, 2017; Thomas, 2000). Projects are complex tasks that are based
on challenging questions or problems and drive students’ learning activities. According to
Thomas (2000), PjBL has the following defining characteristics: 1) projects are central to the
curriculum, that is they are the main vehicles through which students learn new concepts, 2)
projects are focused on questions that drive students to learn the central concepts and
principles, 3) projects let students engage in knowledge construction, 4) projects are in a large
part student-driven (i.e., no predetermined path exists), and 5) projects are realistic.
Similar to PBL, collaboration is important and teachers have a facilitating or coaching
role (Loyens & Rikers, 2017). However, an important difference between PBL and PjBL is
the role of the problem. In PBL the problem is used as a means to foster the learning process,
whereas PjBL culminates in the creation of an end product that addresses the problem or
question (Blumenfeld et al., 1991). The end product reflects students’ new knowledge or
attitudes concerning the issue under investigation and can be presented in different ways (e.g.,
a computer animation, website, or thesis).
Case-based learning. CBL or case-based instruction is often assumed to have its
origins in the case studies and case method used at Harvard Law School and Harvard
Business School (Merseth, 1991). However, PBL has been described as an important
influence on the development of CBL as well (Williams, 2005). CBL is a student-centered,
collaborative learning method, where students are presented with a case (Loyens & Rikers,
2017). Cases are often written as realistic problems or scenarios that need to be solved or
explained. They can vary in length (paragraph vs. several pages). Small groups of students
14
work together to solve the case. Teachers have a guiding role and facilitating role while
students work on the case.
CBL is often described as a special case of problem-based learning (Loyens & Rikers,
2017), however, there are some important differences. In contrast to PBL, in CBL, students
are expected to have some prior knowledge on the case, therefore they need to prepare in
advance for the case or are asked to apply the knowledge they have learned (Srinivasan,
Wilkes, Stevenson, Nguyen, & Slaving, 2007; Williams, 2005). Moreover, teachers are more
directive in bringing students back to the learning objectives (Srinivasan et al., 2007). Also,
in contrast to PBL where students have to seek out additional data after being presented with
the case, there is often little work/self-study after a CBL session (Srinivasan et al., 2007). In
summary, important defining features of CBL are that students prepare the case in advance
and that the main work is done during the CBL session.
1.4 Prior Reviews and Meta-Analyses
Problem-based, project-based, and case-based learning are often assumed to promote
students’ motivation, interest, and attitudes. In PBL, promoting students’ intrinsic motivation
for studying is even included as an important educational objective (Barrows, 1986; Hmelo-
Silver, 2004; Norman & Schmidt, 1992). As mentioned, these student-centered environments
have several elements that could potentially enhance motivation. For example, students have
a certain amount control over and choice in their own learning process. Feelings of being in
control and having a choice have been shown to enhance motivation (Black & Deci, 2000;
Patall, Cooper, & Robinson, 2008). Furthermore, students learn in the context of meaningful,
real-life, complex tasks, which could promote motivational beliefs as well (e.g., Ames, 1992:
Blumenfeld, 1992; Blumenfeld et al., 1991; Katz & Assor, 2007).
15
To date, several reviews and meta-analyses have been conducted about the effects of
student-centered learning environments. However, most of these reviews have focused on the
effectiveness of these learning environments on learning outcomes, approaches to learning, or
self-directed learning skills (e.g., Baeten et al., 2010; Dochy, Segers, Van den Bossche, &
Gijbels, 2003; Loyens, Magda, & Rikers, 2008). With respect to students’ motivation only
one prior meta-analysis was performed.
Yukhymenko (2011) conducted a meta-analysis regarding the effects of a web-based
PBL program, GlobalEd Project, on students’ interest in social studies and negotiation self-
efficacy. The GlobalEd Project is a 4-week intervention for middle and high school students
in which they learn to conduct international negotiations in the context of their social studies
classroom. Several classes and schools participate in the intervention simultaneously. Each
class is assigned to a specific country. During the intervention students learn about the
culture, economy, history, and political structure of the participating countries.
Communications between the countries (i.e., different classes) takes place though email and
online chats. The meta-analysis covered 13 applications of the GlobalEd Project that were
conducted between 2002 and 2008. Results revealed a small statistically significant increase
in middle school (d = 0.05, 95% CI [0.00, 0.10]) and high school (d = 0.18, 95% CI [0.12,
0.25]) students’ interest in social studies. With respect to negotiation self-efficacy, only a
small significant increase between pre- and posttest was found for the high school students (d
= 0.08, 95% [0.02, 0.14]), whereas there was no significant increase for the middle school
students (d = -0.01, 95% [-0.06, 0.04]). This meta-analysis provides some support for the
assumption that environments, such as PBL, can be motivating. However, because the meta-
analysis was only performed on one program, more research is needed to examine whether the
results of this meta-analysis hold for other programs.
16
Furthermore, two meta-analyses have been conducted about the effects of PBL on
students’ attitudes (Batdı, 2014; Demirel & Dağyar, 2016). Batdı (2014) included 25 samples
in which pre- and post-attitude measures were filled out in a PBL and a control group. A
medium-sized positive effect was found in favor of PBL. Demirel and Dağyar (2016)
included 47 studies that compared PBL versus “traditional” learning. They found a small,
positive effect in favor of PBL as well (Hedges’s g = 0.44, 95% CI [0.28, 0.60]). However,
“attitude” is a broad construct (Germann, 1988). Both meta-analyses above did not
exclusively focus on positive attitudes toward learning, but also included studies in which
attitudes reflected a students’ feelings toward the methods of teaching that were applied in a
course or attitudes about issues other than learning (Batdı, 2014; Demirel & Dağyar, 2016).
However, in the current systematic review and meta-analysis, we are only interested in
attitude toward learning (i.e., in general or toward a specific subject).
In conclusion, the results of previous meta-analyses suggest that PBL environments
can positively affect students’ interest, self-efficacy beliefs, and attitudes. However, less is
known about the effectiveness of PjBL and CBL. Furthermore, the prior meta-analyses were
only focused on a certain program or a specific type of design (e.g., independent groups
designs).
1.5 Objectives and Research Questions
With the present systematic review and meta-analysis we aim to contribute to the knowledge
base in several ways. Firstly, in addition to examining the effects of PBL, we examine the
effects of project-based and case-based learning as well. Some researchers use these terms
interchangeably, whereas others argue these learning environments are qualitatively different
(Loyens & Rikers, 2017). By examining all three learning environments in the same meta-
analysis, we can gain more insight into their possible differential effectiveness. Secondly, we
17
examine the effects on multiple motivational outcomes. As discussed above, motivation is a
multifaceted construct (e.g., Pintrich, 2003). It is possible that student-centered learning
environments are more effective in fostering some motivational beliefs, while others are
unaffected.
In the meta-analysis, we include studies that measure motivation on a continuous
scale/Likert scale with different types of designs, such as single-group pre-post designs,
independent groups posttest-only, and independent groups pre-posttest designs in which the
student-centered group was compared to traditional or conventional teacher-centered
instruction. By doing so, we can examine the effect of design as well. Studies that examine
the effects of PBL, PjBL, and CBL on motivation longitudinally will be discussed separately.
Our research objectives were investigated by performing a systematic review and
meta-analysis of the literature between 1970 and January 2017. In the review, we included
gray literature, such as conference papers and dissertations as well as peer-reviewed articles.
Although, PjBL and CBL have roots before 1970, their development was partly influenced by
the popularity of PBL as well (e.g., Williams, 2005). Therefore, we decided to only include
studies after PBL came into existence (Neufeld & Barrows, 1974; Spaulding, 1969).
Specifically, the following main research questions are addressed in the meta-analysis:
1) What is the effect of problem-based, project-based, and case-based learning on
students’ motivation?
2) Do PBL, PjBL, and CBL environments have a different effect on students’
motivation?
Furthermore, we examine whether systematic variance in effect sizes exists and
whether this variance can be explained by several moderators, such as characteristics of the
learning environment (e.g., quality of the environment, duration of the intervention, school
18
level), study characteristics (e.g., design and publication status), and the quality of the
motivational measure (for more details see “Coding Procedure”).
3) Which characteristics of study, learning environment, study, or motivational measure
moderate the effects of PBL, PjBL, and CBL on motivation?
Because we view motivation as a multifaceted construct, we additionally investigated
the effect of PBL, PjBL, and CBL on control beliefs, attitudes toward learning, perceptions of
task value, and students’ goals and reasons for studying. Specifically, we are interested in
answering the following research question:
4) Do PBL, PjBL, and CBL environments have different effects on students’ control
beliefs, attitudes toward learning, task value, and goals and reasons for studying?
19
Chapter 2: Method
2.1 Literature Search
A variety of literature search strategies was used to uncover the studies that were conducted
between 1970 and January 2017. The ProQuest interface was used to search ERIC, ProQuest
Dissertations and Theses A&I, and ProQuest Social Science Journals. Using the Web of
Science interface the databases Medline and Web of Science Core Collection1 was searched.
Finally, using the Ovid interface, PsycINFO, PsycARTICLES, and PsycBOOKS were
searched. After several trial runs, final searches were conducted in April and May 2016, and
updated on January 4, 2017 (date last searched). The search strategies combined two sets of
terms: keywords for the learning environments and keywords for motivation. For the learning
environment terms, we used different variations of problem-based, project-based, case-based,
and inquiry-based learning. Terms related to inquiry-based learning were included, because
PBL, PjBL, and CBL are sometimes described as inquiry-based learning methods and we
wanted to make sure that we did not miss any important studies (see Loyens & Rikers, 2017).
For motivation, several variations of the terms included in Figure 1 were used. The searches
conducted in the ProQuest and Web of Science interfaces with the learning environment
keywords for inquiry-based, problem-based, and project-based learning were restricted with
NOT “case study”, because we were only interested in quantitative research design instead of
qualitative case studies. A full overview of the combination of search terms can be found in
Appendix A. The search resulted in 3,554 titles of which 2,722 remained after removal of
duplicates. The first and third author scanned all titles, abstracts, and, when necessary, the
full texts for inclusion (95.90% interrater agreement). Disagreements (about 112
1 The Web of Science Core Collection could only be searched from 1975 – January 2017.
20
manuscripts) were resolved through discussion, and when needed, discussed with the second
author. Eventually 164 of the 2,722 titles were selected for further inspection.
A key-journal in the field, Interdisciplinary Journal of Problem-Based Learning, was
hand-searched and members of the Special Interest Group of the American Educational
Research Association were contacted for additional papers. However, no new papers were
identified through these searches. Additionally, the reference lists of selected and other
relevant papers were checked for publications we had not identified in the database search,
which resulted in 17 new papers. An additional, 8 papers were found by contacting authors or
by checking relevant websites of authors who were included in the meta-analysis2. One paper
was included based on the first author’s personal archive.
2.2 Inclusion of Studies
The studies had to meet several criteria to be eligible for inclusion:
1) The study had to examine the effect of PBL, PjBL, or CBL on students’ self-reported
motivation.
2) The study contained a pretest, control group (i.e., “traditional,” lecture-based/teacher-
centered group) or both.
3) The description of the learning environment had to meet the defining characteristics of
PBL, PJBL, or CBL (as previously described).
4) The study was conducted in a school or classroom setting; studies conducted in laboratory
settings or at summer camps were excluded (e.g., Schmidt, 1983a).
2 Often these papers were other duplicates of the dissertation/conference paper we identified through our
database search.
21
5) The study had to investigate a student sample; studies conducted in professional
development courses or with service teachers, residents, or patient samples were excluded.
6) The study had to be reported in English, Dutch, or German.
7) The study provided sufficient statistical data to compute effect sizes.
Additionally, we decided to exclude studies on the web-based PBL program, the GlobalEd
project (see Yukhymenko, 2011) and only include studies on its successor, the GlobalEd 2
project (see Brown, Lawless, & Boyer, 2013). The GobalEd/Ed 2 program is an often-
occurring program. We believed it was better to only focus on the effects of the “new”
program instead of the older version of the program.
Figure 2 offers an overview of the search and selection process. Of the 190 papers that
were selected for further inspection. One study had to be excluded, because a full-text could
not be retrieved. An additional, 28 studies were excluded because they did not meet the
inclusion criteria. Most of these studies were excluded because they did not meet the defining
characteristics of PBL, PjBL, or CBL (10 studies), used an inadequate motivation measure (6
studies), or both (1 study). Three studies on the GlobalEd Project were excluded. Some
studies did not have a suitable research design (6 studies) or were not conducted in a
classroom setting (2 studies). Furthermore, 14 studies were excluded because they contained
duplicate data (e.g., a dissertation or conference paper that was later published).
A total of 147 articles met our inclusion criteria. When these studies did not provide
sufficient statistical data to compute effect sizes, the main author was contacted with a request
to provide the missing data. For 13 studies, we were unable to retrieve sufficient data to
compute effect sizes; these studies were discarded. Eventually, 134 papers were selected for
inclusion in the systematic review. Of these papers, 83 investigated a PBL environment, 43 a
PjBL environment, and 9 a CBL environment. Because 3 of the PBL studies had a
22
longitudinal design, these studies were discussed separately. Therefore, 131 studies were
eventually included in the meta-analysis.
Figure 2. Flow chart of the search and study process.
2.3 Coding Procedure
All included studies were coded according to a data extraction form. A separate form was
developed for each of the three learning environments (see Appendix B). The data extraction
form allowed for the coding of bibliographical information of the research report, the research
objective, study and sample characteristics of the treatment and control group, treatment (i.e.,
PBL, PjBL, CBL) characteristics, and the outcome measures.
For the bibliographical information of the research report, we coded the author
name(s), publication year, type of report (i.e., journal article, dissertation, conference paper,
other), the journal in which the article was published, the conference at which the paper was
presented, or the university at which the dissertation was defended. We additionally wrote
down the exact research objectives or questions that were mentioned in the paper. Study
characteristics that were coded included the country in which the study was conducted, the
domain under investigation (e.g., STEM, health/medical education), research design, and the
level of randomization between treatment and control group (if a control group was present).
Samples were coded according to school level (i.e., K-12 or higher education).
For each learning environment, we wrote down the definition and/or implementation
of the PBL, PjBL, or CBL environment under study. This definition was checked against our
own definition and used to give an indication of the quality of the learning environment. The
quality of the learning environment refers to the level of detail in which the PBL, PjBL, or
CBL environment/implementation was described and to what extent the defining features of
the learning method were present (categories: low, moderate, high). We also coded the
duration of students’ exposure to the learning method. Based on Slavin (2008), a distinction
was made between studies that were less than 12 weeks in duration or at least 12 weeks.
Furthermore, we determined whether only part of the study program was problem-, project-,
or case-based or whether the entire curriculum was designed that way.
24
In line with Figure 1, the motivational outcome measures were grouped in five main
categories: 1) control beliefs, 2) task value, 3) attitude, 4) goal and reasons, and 5) a general
motivation constructs (i.e., a composite motivation score that includes two or more of the
aforementioned categories). The category “control beliefs” consisted of three subcategories:
1.1) perceptions of ability (e.g., self-efficacy), 1.2) locus of control/attribution, and 1.3)
outcome expectancy. Based on the literature, we decided to further subcategorize the
“perceptions of ability” category in general perceptions of ability, perceptions about academic
ability, perceptions about professional skills (e.g., teaching self-efficacy for pre-service
teachers), perceptions of inquiry skills (e.g., problem-solving skills, self-study skills), and
perceptions of technology/computer skills.
The “task value” category was further divided in three subcategories: 2.1) interest, 2.2)
interest in future learning tasks, and 2.3) other task-value beliefs. Finally, the “goal and
reasons” category was further subdivided in 4.1) autonomous or mastery, 4.2) controlled and
performance, 4.3) intrinsic vs. extrinsic (i.e., high scores indicate intrinsic motivation, low
scores indicate extrinsic motivation) and 4.4) amotivation.
For most motivation constructs an increase in scores or a higher mean/increase for the
treatment when compared to the control group indicated a positive effect (unless otherwise
stated). However, for constructs in the categories “controlled and performance” and
“amotivation”, a decrease/lower score was viewed as a positive. For each outcome measure
we further coded information about the specificity of the construct (i.e., situation-specific or
general measure), reliability, and the quality of the motivation measure. The quality of the
motivation construct indicates to what extent the definition and items used were clearly
described and whether these items were an accurate reflection of the motivation construct
under study (categories: low, moderate, high).
25
Interrater agreement. All studies were coded by the first author. The quality of the
learning environment was additionally coded for all studies by either the second (PBL and
PjBL) and third author (CBL) so that interrater reliability could be calculated. Intraclass
correlation coefficients (ICC) were used as an indication of interrater reliability (see Landers,
2015). Overall high agreement was found when comparing the quality ratings of the learning
environment, this resulted in a ICC(3) of .896 for PBL, .929 for PjBL, and 1.00 for CBL.
Disagreements were resolved through discussion. The quality of all motivation constructs
was coded by the first and third author. The interrater reliability analysis for the quality of the
motivation constructs resulted in an ICC(3) = .867. Disagreements were again resolved
through discussion.
Furthermore, parts of the coding scheme relating to the country in which the study was
conducted, domain under investigation, school level, level of implementation (curriculum
implementation or other), and duration of the intervention were additionally coded for 70
independent study samples by three research assistants. Interrater agreement in coding ranged
from 74.29% to 98.57%. When differences were found between the first author and one of
the research interns, these were discussed with the research intern and/or the third author.
Afterward, the original coding of the first author was checked and changes were made when
necessary.
2.4 Data Analyses
All analyses were performed in Comprehensive Meta-Analysis statistical software (version 2;
Biostat, Englewood, NJ, Borenstein, Hedges, Higgins, & Rothstein, 2009) by the fourth
author. The 131 selected reports reported outcomes for 151 independent subsamples. These
subsamples were used as the unit of analysis. To analyze the overall effect of the three
inquiry instructional methods on student motivation, we first computed one weighted effect
26
size for motivation using the standardized mean difference (Cohen’s d). If a study included
several motivational measures, these data were combined into a single effect size as an
indication of overall motivation. To be able to analyze the effects for the different
motivational subcategories (see Figure 1 and coding procedure), additionally one effect size
was computed per category and sample. Effect sizes of .20 will be interpreted as a small
effect, .50 as a medium effect, and .80 as a large effect.
If reported, we used sample size and the pretest and posttest means and standard
deviations (SDs) to compute effect sizes. If the correlation between pre- and posttest data was
not reported, we assumed a correlation of .50 to be able to compute the variance. For
independent groups pre-posttest designs we used the posttest SD to standardize the effect size.
If no sample means or SDs were reported, we used statistical data such as t-values, F-values,
or p-values, combined with sample size to compute effect sizes.
The mean effect sizes were estimated using random effects models for all outcomes, in
which heterogeneity across studies was taken into account. In random effect models the mean
effect size is weighted by the variance of the sample as well as the variance between studies to
account for differences in sampling error related to sample size. Moderator analyses for the
categorical variables were conducted based on analysis of variance (ANOVA). Between
group differences in the categorical random effects analyses were tested with the Q-statistic
for between group means.
27
Chapter 3: Results of the Meta-Analysis
3.1 Description of Studies
Appendices C to D present an overview of the 131 papers that were selected in the meta-
analysis. In the papers 151 subsamples were examined. In most subsamples the effectiveness
of PBL was investigated (k = 90, 59.60%). The effects of PjBL were investigated in 50
subsamples, whereas CBL was only investigated in 11 subsamples.
Most studies were conducted in the United States (k = 75, 49.67%). The second
largest country was Turkey (k = 25, 16.56%). More than half of the studies were conducted in
a higher education setting (k = 84, 55.63%). The subsamples from K-12 education (k = 67)
ranged from grade 2 to grade 12. Although, PBL and CBL are commonly applied (k =29,
19.21%) in the health/medical domain, most subsamples investigated the outcomes of PBL,
PjBL, and CBL in the STEM-domain (k = 70, 46.36%).
3.2 Overall Effects on Motivation
The 151 subsamples included in the meta-analysis reported outcomes for 441 different
motivational outcomes/items. Ignoring the data structure (using outcome as the unit of
analysis), analysis over the 441 outcomes resulted in a significant, positive effect, d = 0.345
(SE = .03, 95% CI [0.293, 0.403]), z = 12.42, p < .001. To answer Research Question 1, we
first conducted an analysis with subsample as the unit of analysis (k =151) on overall
motivation (i.e., different motivational measures were combined in one effect size). A
positive, small to medium, effect was found, d = 0.449 (SE = .04). However, the effect was
heterogenous, Q(150) = 5155.52, p < .001, I² = 97.09, T² = 0.25 (SE = .07). This implies that
28
the variability in effect sizes has sources other than sampling error. Therefore, we further
examined the role of several moderators.
To answer Research Question 2, we first checked whether significant differences were
found for type of inquiry-instructional method on motivation, Q(2) = 9.05, p = .011. For all
inquiry-instructional methods, a positive effect was found. However, a smaller effect size
was found for the PBL group (k = 90, d = 0.343, SE = .06), than for PjBL (k = 50, d = 0.599,
SE = .06) and CBL groups (k = 11, d = 0.589, SE = .18).
To examine Research Question 3, we further checked the effect of moderators, such as
design, quality of the learning environment, duration of the intervention (i.e., at least 12
weeks), school level (i.e., K-12 or higher education), quality of the motivational measure, and
publications status (journal article or other). The results of the moderator analyses are
reported in Table 1. Design, quality of the learning environment, and duration of the
intervention did not moderate the combined effect of PBL, PjBL, and CBL on motivation.
However, school level did moderate the effects of the three inquiry-instructional methods on
motivation. A higher effect size was found for the subsamples that were examined in a higher
education setting than for the subsamples/studies conducted in K-12 education. Also, the
quality of the motivational measure moderated the effect. A lower effect size was found for
motivation constructs that were rated high in quality relative to moderate/low quality ratings.
Furthermore, publication status moderated the effects of the inquiry-instructional methods on
motivation. Higher effect sizes were found for the results published in journal articles, when
compared to other reports (e.g., dissertations, conference papers). Because most of the studies
were conducted in a PBL (k = 90) or PjBL environment (k = 50) the moderator analyses of
Research Question 3 were conducted separately for the effects of PBL and PjBL on students’
overall motivation as well.
29
Table 1
Moderator Analyses for Overall Motivation
k d SE Q df p
Overall 151 0.449 .04
Inquiry type 9.05 2 .011
PBL 90 0.343 .06
PjBL 50 0.599 .06
CBL 11 0.589 .18
Design 0.60 2 .741
Independent groups 36 0.366 .11
Independent groups pre-post 46 0.513 .17
Single group pre-post 69 0.434 .05
Quality of the learning environment 2.20 2 .333
Low 46 0.491 .06
Moderate 55 0.359 .08
High 50 0.507 .08
Duration (at least 12 weeks) 1.20 1 .274
Unknown 6 1.022 .49
Yes 68 0.361 .04
No 77 0.452 .07
School level 11.75 1 .001
K-12 67 0.286 .06
Higher education 84 0.586 .07
Quality of the motivation measure 22.04 3 < .001
Low 31 0.751 .13
Moderate 56 0.513 .08
High 48 0.291 .08
Combination 16 0.175 .06
Publication status 17.22 2 < .001
Journal article 105 0.519 .06
Other 45 0.281 .05
Combination 1 0.139 .08
30
Moderator analyses problem-based learning. Effects of the moderators, such as
design, quality of the learning environment, duration of exposure to PBL, school level, quality
of the motivation construct, and publication status are reported in Table 2. Only one
moderator, school level, had a significant effect. Again, a higher effect size was found for
studies conducted in higher education than for the studies conducted in K-12 education. In
addition, a trend was found for the quality of the motivation construct, studies using
motivational constructs that were rated to be low in quality resulted in a larger effect size,
than the studies using motivation constructs that were rated to be high in quality.
Moderator analyses project based learning. Results of the moderator analyses for
the effect of PjBL on students’ motivation are reported in Table 3. For school level, quality
of the motivation construct, and publication status similar effects were found when PjBL was
investigated separately as when all learning environments were combined. Again, a smaller
effect size was found for K-12 studies in comparison to studies conducted in higher
education. Also, a lower effect size was found for studies that used motivational constructs
that were rated to be high in quality, when compared to constructs that were rated to be
moderate or low in quality. A larger weighted average effect size was found for journal
articles, when compared to dissertations/conference papers.
Moreover, an effect was found for the duration of students’ exposure to PjBL. A
larger effect size was found for studies in which students’ experience with PjBL was shorter
than 12 weeks, than for studies in which students had more experience with PjBL. Although
not statistically significant, in the 4 subsamples for which the PjBL-implementation was rated
to be high in quality a larger effect on motivation was found when compared to the
subsamples with a low or moderate-quality PjBL-implementation. Again, no effect was
found for the design of the study (i.e., independent groups, independent groups pre-post, and
single group pre-post).
31
Table 2
Moderator Analyses for the Effect of PBL on Motivation
k d SE Q df p
Overall 90 0.343 .06
Design 0.14 2 .933
Independent groups 31 0.343 .12
Independent groups pre-post 25 0.267 .30
Single group pre-post 34 0.370 .07
Quality of the learning environment 1.77 2 .412
Low 15 0.407 .11
Moderate 36 0.236 .11
High 39 0.413 .10
Duration (at least 12 weeks) 0.90 1 .344
Unknown 2 1.132 .93
Yes 44 0.365 .06
No 44 0.256 .10
School level 5.97 1 .015
K-12 35 0.153 .10
Higher education 55 0.470 .09
Quality of the motivation measure 7.25 3 .064
Low 16 0.729 .25
Moderate 35 0.361 .09
High 29 0.185 .11
Combination 10 0.126 .10
Publication status 4.54 2 .103
Journal article 64 0.371 .08
Other 25 0.273 .08
Combination 1 0.139 .08
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Table 3
Moderator Analyses for the Effect of PjBL on Motivation
k d SE Q df p
Overall 50 0.599 .06
Design 4.52 2 .105
Independent groups 4 0.639 .25
Independent groups pre-post 13 1.025 .29
Single group pre-post 33 0.441 .06
Quality of the learning environment 5.01 2 .082
Low 27 0.503 .07
Moderate 18 0.570 .09
High 5 1.438 .42
Duration (at least 12 weeks) 6.93 1 .008
Unknown 2 0.830 .95
Yes 20 0.392 .07
No 28 0.717 .12
School level 12.85 1 < .001
K-12 31 0.414 .06
Higher education 19 0.912 .13
Quality of the motivation measure 12.52 3 .006
Low 14 0.717 .14
Moderate 15 0.925 .20
High 15 0.387 .07
Combination 6 0.274 .11
Publication status 25.61 2 < .001
Journal article 34 0.793 .10
Other 16 0.223 .05
33
3.3 Effects on Control Beliefs, Attitude, Task Value, and Goals and Reasons
Next, we examined the effects of PBL, PjBL, and CBL on students’ perceptions of control
beliefs, attitude, and task value, and their goals and reasons for studying to answer Research
Question 4. For this analysis, we only included the subsamples for which one or more of the
motivational measures could be classified in these four categories. We, therefore, excluded
“general motivation” measures. We also excluded “amotivation” from the analysis as it was
only measured in one subsample.
Control beliefs were measured in 39 subsamples (d = 0.639, SE = .11). In 23
subsamples students’ attitude toward learning (d = 0.538, SE = .09) were measured. Task
value was measured in 15 subsamples (d = 0.876, SE = 0.283), whereas students’ goal and
beliefs were measured in 11 subsamples (d = 0.066, SE = .35). However, 45 subsamples
measured constructs of multiple categories (d = 0.226, SE = .03).
Differential effects of the three learning methods under study on control beliefs,
attitude, task value, and goal and reasons were also investigated. For control beliefs (k = 81),
a marginally significant effect was found, Q(2) = 5.51, p = .064. Although not significantly
different, the effect of PjBL environments (k = 26, d = 0.690, SE = .09) on control beliefs
seemed to be larger than the effect of PBL (k = 51, d = 0.410, SE = .09) or CBL environments
(k = 4, d = 0.408, SE = .24). Because “perceptions of the ability” was the most common
measure within the category “control beliefs” a separate analysis was conducted for that
construct. Again a trend was found, Q(2) = 5.82, p = .055, indicating that PjBL environments
had a larger effect on perceptions of ability (k = 26, d = 0.697, SE = .09), than PBL (k = 49, d
= 0.395, SE = .09) or CBL environments (k = 4, d = 0.425, SE = .24).
We further examined differences among the three learning methods on attitudes
toward learning, task value, and goals and reasons for studying. However, we have to be
cautious about the effects that are found, because these categories were examined in less
34
subsamples than control beliefs. A significant difference among the three learning
environments was found for attitude toward learning, Q(2) = 36.68, p < .001. Although for all
learning environments a positive effect was found, the effect of PBL (k = 18, d = 0.232, SE =
.05) on attitude seemed to be smaller than the effects of PjBL (k = 9, d = 0.713, SE = .18) and
CBL (k = 3, d = 1.278, SE = .18). For task value, no significant differences were found
among the three learning methods, Q(2)= 0.10, p = .950. All learning environments had a
positive effect on students’ task value beliefs (PBL: k = 25, d = 0.504, SE = .17; PjBL: k = 17,
d = 0.566, SE = .13; CBL: k = 2, d = 0.493, SE = .33).
Finally, students’ goals and reasons for studying were scrutinized. As mentioned,
increases or high scores on “autonomous & mastery” constructs were indicated as positive
effects, whereas increases or high scores on “controlled & performance” constructs, were
coded as negative effects. A significant difference was found, Q(2) = 7.08, p = .029. Only a
positive effect was found for PjBL (k = 13, d = 0.238, SE = .10). For PBL (k = 18, d = -0.003,
SE = .16) and CBL (k = 2, d = -0.051, SE = .06) near-zero, negative effects were found.
35
Chapter 4: Studies with Longitudinal Designs
Three studies examined the effects of PBL on motivational variables longitudinally (Duman
& Şen, 2012; Kocaman, Dicle, & Ugur, 2009; Mert, Kızılcı, Uğur, Küçükgüçlü, & Sezgin,
2012). All three studies were conducted with nursing students at Dokuz Eylül University,
Turkey. Kocaman et al. (2009) investigated students’ motivation to learn (n = 50, “learning
desire”) using five measurement points (from first year to completion of the fourth year).
Results revealed an increase in motivation. Specifically, motivation increased from the first
to the second year, remained stable during the second and third year, and increased again in
the fourth year.
Duman and Şen (2012; n = 47) and Mert et al. (2012; n = 58) both examined the
development of locus of control in PBL across the four-year nursing program. In both studies
students’ internal locus of control increased from the first to the second year, however internal
locus of control decreased at the beginning of the fourth year. During the fourth year,
students spent most of their time in a clinical work environment (Duman & Şen, 2012). The
change from the school setting to the work setting might explain these results, as the transition
from study to work is often described as stressful (Duchscher, 2009).
Overall, the results from the longitudinal studies seem to suggest that motivation to
learn and feelings of internal control can increase during the first year of a PBL program.
However, because there was no comparison group, it is unclear whether similar effects would
occur for students in more teacher-centered programs. Furthermore, all longitudinal studies
have been conducted at the same study program and university. Therefore, more research is
needed.
36
Chapter 5: Discussion
5.1 Aims of Meta-Analysis
Student-centered, active learning methods are becoming increasingly popular (e.g., Baeten et
al., 2010). Often these learning methods are implemented, because it is assumed that they
have beneficial effects on students’ motivation and learning (e.g., Hmelo-Silver, 2004).
Because these learning methods often center learning around a real-life, challenging problem
or project, it is believed that learning will become more meaningful and interesting (e.g.,
Blumenfeld, 1992). Furthermore, due to the student-centered nature of the learning
environment, students can (learn to) take control of their learning process and often have a
certain degree of choice in the direction the problem or project will take. The possibility of
students to take autonomous control of their learning is assumed to increase students’
motivation (Black & Deci, 2000). Nevertheless, not all studies have found positive effects,
and some researchers have reported about motivational problems that might occur in these
environments (Dolmans & Schmidt, 2006).
The main aim of this systematic review and meta-analysis was, therefore, to
investigate the effect of PBL, PjBL, and CBL environments on students’ motivation
(Research Question 1). We additionally examined whether systematic differences existed
among the three learning methods on students’ motivation (Research Question 2).
Furthermore, we determined whether several moderators affected the effectiveness of these
learning methods in promoting students’ motivational beliefs (Research Question 3). Finally,
we examined the effects of PBL, PjBL, and CBL on different subcategories of motivation
(Research Question 4).
37
5.2 Main Results of the Meta-Analysis
To answer Research Question 1, we first combined all learning methods and all motivational
outcomes in one analysis. We found a small-to-medium effect of student-centered learning
methods on students’ motivation. However, the effect was heterogenous, indicating that
several variables might moderate the effectiveness of these learning methods on motivation.
To answer Research Question 2, the first moderator we examined was type of learning
method. Results indicated a significant difference among PBL, PjBL, and CBL in their
effects on students’ motivation. Although, for all learning environments positive effects were
found, for PBL the effect was small, whereas PjBL and CBL had moderate effects on
motivation. The fact that our analyses demonstrated that these learning environments have
different effects on motivation indicates that researchers should not use the terms problem-
based, project-based, and case-based learning interchangeably and that they should always
specify the intervention/learning method they have implemented.
5.3 Effects of Moderators
To examine Research Question 3, we further analyzed whether several characteristics of the
learning environment, study, and outcome measures moderated the effectiveness of the three
learning methods. An important moderator was school level. Although for both school types
positive effects were found of the learning methods on motivation, the effects appeared to be
smaller for K-12 education than for higher education. As mentioned, PBL and CBL have
their origins in higher education (Barrows; 1996; Merseth, 1991; Williams, 2005). Therefore,
many of the process models that were developed for learning methods, such as PBL, to
facilitate learning, are specifically focused on higher education students. Furthermore,
teachers have to face many challenges if they want to implement instructional methods based
38
on inquiry in their classroom (Ertmer & Simons, 2006) as they have to take on a new
facilitating or coaching role. Moreover, it has been suggested by several researchers that
younger learners need more preparation before the new instructional method can be applied
(Ertmer & Simons, 2006; Simons & Klein, 2007; Torp & Sage, 1998, 2002). Many of the K-
12 interventions or implementations were relatively short in duration, which leaves the
possibility that students might not have always been properly prepared for engaging in the
new learning method. As a consequence, the effects of these “new” learning methods on
motivation might have turned out lower.
Also, the quality of the motivational measure seemed to affect the magnitude of the
effect size. Motivational constructs that were rated to be lower in quality (e.g., unclear
description in the paper, no clear theoretical framework) resulted in higher effect sizes than
constructs that were rated to be high in quality. Constructs were rated as lower in quality
when the construct was only measured with one items, when the construct was not well
defined, and/or when it was impossible to retrieve example items of the scale. It is possible
that some of the “lower-quality” constructs were in actuality good measures, however,
sometimes too little information in the reports or articles was provided to get an accurate
impression of the measure. A recommendation for future research is therefore to accurately
describe their measures and give a clear definition of the construct researchers are measuring,
for instance by providing example items.
Publication status of the research report moderated the overall effect of the three
learning methods on motivation. Publication status also moderated the effect of PjBL on
motivation. Although positive effects were found regardless of publication status, a small
effect size was found for conference papers/dissertations and a moderate (i.e., learning
methods combined) or moderate to high (i.e., PjBL) effect size for journal articles. For PBL,
publication status did not affect the outcomes; there was a small positive effect for both
39
published and gray literature. The fact that publication status significantly moderated the
effects of some of the learning methods on motivation illustrates the importance of including
gray literature in the meta-analysis. Only including journal articles in a meta-analysis, might
inflate the magnitude of the effect size.
Slavin (2008) indicated that when synthesizing the effects of educational programs, it
is important to look at the duration of the study or implementation. A 12-week criterion was
suggested, so that it can be examined whether the learning method can be used over an
extended time period. For the PBL and the overall analyses, duration of the program (i.e.,
coded as at least 12 weeks or less), did not moderate the effect on motivation. However, for
PjBL larger effect sizes were found for shorter implementations. A higher effect for shorter
implementations of PjBL might indicate that there is a novelty effect in play. Possibly, part of
the beneficial effect of PjBL on motivation can be explained by the fact students were excited
about experiencing something different than their “normal” classroom experience.
Finally, design of the study (i.e., independent groups, independent groups pre-post, or
single group pre-post) and quality of the implementation or description of the learning method
under study did not moderate the effects of PBL, PjBL, and CBL on motivation.
5.4 Effects on Different Motivational Constructs
We further examined potential differential effects of PBL, PjBL, and CBL on students’
control beliefs, attitude toward learning, task value, and goals and reason for studying
(Research Question 4). For control beliefs, such as perceptions of ability, a moderate,
positive effect was found for all learning environment combined. A trend suggested that the
effect of PjBL on students’ control beliefs was somewhat larger (moderate effect) than the
effect of PBL and CBL on students’ control beliefs (small-to-medium effects). Results were
40
similar when we only investigated the effects of the learning methods on students’
perceptions of ability.
For attitudes toward learning, positive effects were found for all learning methods.
However, moderator analysis revealed a significant difference among the learning methods.
Moderate-to-high and large effect sizes were found for the PjBL and CBL studies
respectively. However, the effect size in the PBL studies was small but positive. The effect
of PBL on attitude in our meta-analysis concur with the effects found in previous meta-
analyses (Batdı, 2014; Demirel & Dağyar, 2016).
With respect to students’ perceptions of task value, a positive, moderate effect size
was found for PBL, PjBL, as well as for CBL. No significant differences occurred. As
mentioned, learning in the context of real-life problems and projects is often assumed to
increase students’ interest and their perceptions of meaningfulness (e.g., Ames, 1992:
Blumenfeld, 1992; Blumenfeld et al., 1991; Katz & Assor, 2007). Our results seem to
indicate that PBL, PjBL, and CBL can indeed increase students’ perceptions of interest,
importance, and utility of the learning task.
Finally, we examined students’ goals and reasons for studying. Increases or high
scores on “autonomous & mastery” constructs were indicated as positive effects, whereas
increases or high scores on “controlled & performance” constructs, were coded as negative
effects. Moderator analysis revealed a significant difference among the learning methods.
Only a small, positive effect was found for PjBL environments, whereas near-zero, negative
effects were found for PBL and CBL environments. PBL methods have the instructional goal
of increasing students’ intrinsic motivation for studying (Barrows, 1986; Hmelo-Silver, 2004;
Norman & Schmidt, 1992). Intrinsic motivation is an important aspect of autonomous
motivation (Deci & Ryan, 2000). Based on the results of this meta-analysis the claim that
PBL can promote students’ intrinsic motivation for studying cannot be supported. However,
41
considering the limited number of studies examining the effects of students’ goal and reasons
for studying, more research is needed.
In summary, in many of the analyses conducted for Research Question 4. Larger
effects were found for PjBL environments than for PBL environments. A key difference
between these learning environments is the role of the problem. In PBL, the problem is used
as a means to foster the learning process, whereas PjBL culminates in the creation of an end
product that addresses the problem or question (Blumenfeld et al., 1991). In PBL, instructors
often have a certain direction in mind when they present students with a problem, whereas in
PjBL the problem and project should be largely student-driven. It is possible that students in
PjBL might experience more freedom in their learning process than PBL students. More
research is needed to examine this assumption. Alternatively, it is also possible that the effect
size of PjBL is somewhat inflated due to novelty effects. We did not identify studies that
used a curriculum-wide implementation of PjBL. That is, in all studies, projects were often
included as a temporary addition to the study program, which might have affected the
outcomes.
5.5 Limitations
When interpreting the results of this meta-analysis, some limitations need to be considered.
First of all, some of the analyses were conducted with a relatively small number of studies.
For example, for CBL we only identified 11 subsamples. Therefore, it was impossible to
conduct moderator analyses for CBL. Although, for PBL and PjBL more subsamples were
identified, sample size in some of the moderator analyses was quite low. It is therefore
important to interpret the results with some caution. Nevertheless, the results of our meta-
analysis are a valuable addition to the field.
42
For all subsamples, it was determined by two authors whether or not the
implementations of PBL, PjBL, and CBL were in line with the defining characteristics of
these instructional methods. However, several differences can still exist among the different
implementations of the instructional methods (e.g., Maudsley, 1999), which might have
affected the outcomes. Although we analyzed the effects of several moderators, variability in
effect sizes might also be explained by other variables that we could not include in our meta-
analysis. Another variable of interest might have been the level of preparation students
received before the instructional method was implemented and the level of guidance teachers
provided during the implementation. However, this information was often not reported in the
research reports.
Furthermore, motivation is a complex construct (Murphy & Alexander, 2000).
Although the categories we used in our meta-analysis were based on prior research (e.g.,
Pintrich, 2003), differences in the operationalization of measures, even for constructs derived
from the same theory, can affect the outcomes in a meta-analysis (Hulleman, Schrager,
Bodmann, & Harackiewicz, 2010). However, all motivation measures were coded and
labeled in categories by the first and third author, to assure that the constructs were
sufficiently similar to include in the same category.
5.6 Implications for Research and Practice
It is often assumed that student-centered learning environments can increase students’
motivation. Overall, the results of our meta-analysis suggest a positive, small-to-medium
effect of PjBL, PBL, and CBL on motivation. Especially, positive effects were found for
students’ perceptions of control beliefs, attitudes toward learning, and perceptions of task
value. With respect to students’ goals and reasons for studying, only a small, positive effect
43
was found for PjBL. The latter effect is in contrast to the popular belief that PBL can increase
students’ intrinsic motivation for studying (e.g., Hmelo-Silver, 2004).
Analyses further revealed that positive effects were found for studies conducted in K-
12 settings as well as in higher education settings. However, larger effect sizes were found
for higher education implementation. This finding is important for policymakers and
teachers, who are interested in the implementation of problem-based, project-based, or case-
based learning in their classrooms. These results imply that students and teachers in K-12
education first need some time to adapt to the learning method and that good preparation and
sufficient training is needed (Ertmer & Simons, 2006).
Results further indicate that PBL, PjBL, and CBL had differential effects on
motivation. For all learning methods, generally, positive effects were found. However, the
effects for PjBL were often somewhat larger than the effects of PBL. Although some
researchers use the terms PBL, PjBL, and CBL interchangeably, the results of our meta-
analysis suggest that is all-important that researchers clearly describe the type of instructional
method they are investigating, because differences in these learning methods can affect their
effectiveness.
44
Acknowledgements.
This systematic review is funded by the Netherlands Organisation for Scientific Research
(405-15-720). We would like to thank Greta Petkauskaité, Simon Zöphel, and Siham El
Hammouti for their help in coding the studies.
45
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Appendix A: Search terms
Type Search terms
Learning Environment “inquiry based learning” OR “enquiry based learning” OR “inquiry
based teaching” OR “enquiry based teaching”, “inquiry based
instruction” OR “enquiry based instruction” OR “model based
inquiry”, “problem based learning” OR “problem based approach”
OR “PBL”a “project based learning” OR “project based instruction”
OR “project centered learning” OR “PjBL” OR “case based
learning” OR “case based instruction”
Motivation “motivation” OR “control belief*” OR “self efficacy” OR
“perceived competence” OR “locus of control” OR “attribution*”
OR “competence expectancy” OR “outcome expectancy” OR
“expectancy value” OR “self confidence” OR “perceived
confidence” OR “task value” OR “interest” OR “attitude toward*”
OR “learning attitude” OR “attitude to learn*” OR “attitude to
study*” OR “goal orientation*”, “achievement goal*” OR “learning
goal*”, “mastery goal*” OR “performance goal*” OR “self
determination” OR “perceived autonomy” OR “intrinsic*” OR
“willingness to learn” OR “learning intention”
Restrictions Timeframe: From 1970-current
Restrictive keyword: NOT “case study”; used in combination with
learning environment keywords for inquiry-based, problem-based,
and project-based learning in ProQuest and Web of Science
interface
Note. a “PBL” was only used in PsycINFO, PsycARTICLES, and PsycBooks databases, because in the other
searches it led to too many unrelated-medical papers.
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Appendix B: Coding Scheme – Problem-Based Learning Coder:
A Research Report A1 # A2 Name A3 Year A4 Manuscript ☐ Journal article
☐ Book chapter
☐ Conference paper ☐ Dissertation/ master thesis
☐ Unpublished study A5 Journal/Book/Conference/
University
A6 Advisor/ promotor A7 Peer-reviewed
☐ Yes
☐ Partly
☐ No
☐ Unclear B Research Goal B1 Research Question/ Objective C Study Setting and Treatment C1 Domain
☐ STEM (including biology) = 1
☐ Medical/ Health Sciences = 2
☐ Sports = 3
☐ Social & Behavioral sciences = 4
☐ Law = 5
☐ Economics & Business = 6
☐ Humanities (history, language) = 7
☐ Teacher Education = 8
☐ C2 Country (where the study was
conducted)
C3 School/institute PBL intervention
C4 Definition/ description of PBL C5a Elements of PBL that are
present ☐ Problem = starting point
☐ Teachers have a guiding/ facilitating role
☐ Collaborative learning
☐ Ample time for self-study
☐ Resource are (in part) student-selected C5b Group size C6a Are there lectures available?
☐ No (= pure PBL) ☐ Yes
☐ Unclear
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C6b Explanation about lectures C7a Is PBL combined with an end
project or presentation? ☐ No ☐ Yes
C7b Explanation about the project or presentation
C8 PBL process ☐ Alien Rescue
☐ GlobalEd/ GlobalEd 2
☐ Seven-Jump (activation prior knowledge)
☐ Closed-loop PBL (simulation professional practice
☐ Other:
☐ Unclear C9a Quality of PBL description (to
what extent is the environment representative of PBL?)
☐ PBL description is unclear
☐ Some elements are unclear ☐ Clear
C9b Explanation Quality Score C10 Additional comments PBL
environment
C11 Multiple samples (samples that need to be coded separately)
☐ No
☐ Yes Fill out part D and E separately for each sample
D Participants and Treatment per Sample: Sample #1 D1 PBL mean age (estimate if
necessary)
D2 PBL gender ratio (% female) D3a School level: ☐ Kindergarten
☐ Elementary School (Grades 1-4) ☐ Middle School (Grades 5-8)
☐ High School (Grades 9-12)
☐ Higher Education D3b Grade or year D4 Intervention or Curriculum ☐ Intervention: only part of a course is problem-based
☐ Course-wide implementation: entire course is problem-based in a larger curriculum
☐ Curriculum-wide implementation
☐ Unclear D5a Is the duration of the
intervention at least 12 weeks? ☐ No
☐ Yes
☐ Unclear D5b Describe intervention or
exposure
D6 Is PBL computer-supported (hypermedia or asynchronous communication)?
☐ No
☐ In part
☐ Yes
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D7 Additional comments – participants (e.g., at risk students; ability level)
E Control group: Sample #1 E1 Is there a control group? ☐ No Skip the remainder of the E-questions
☐ Yes E2 Description of control or
comparison group
E3 Control mean age E4 Control gender ratio (%
female)
E5 Random assignment ☐ Random assignment of participants
☐ Random assignment of groups ☐ No random assignment
☐ Unclear E6 Same teacher(s) for
treatment/control group? ☐ Yes ☐ No
☐ Unclear E7 Notable differences between
treatment or control group or additional comments
Outcome Measures: Fill out for each construct separately
F Motivational Construct F1 Type of construct Kies een item. F2 Definition of construct F3 Specificity ☐ Situation or task-specific
☐ General measure
☐ Unclear F4 Is the construct measured with
an existing scale? ☐ Yes
☐ No
☐ Unclear F5 Scale name F6 Example item
F7 Number of items F8 Scale range F9a Psychometric properties of
scale ☐ Not mentioned
☐ Poor: Below .60
☐ Questionable: .60-.69
☐ Acceptable: .70-.79
☐ Good or excellent: .80 or above F9b Additional comments
reliability
F10a Quality of Construct ☐ Definition and items seem adequate
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☐ Doubts about definition or items
☐ Definition and items are unclear F11b Explanation Quality Score F12 Study Design ☐ Independent groups pre-post
☐ Independent groups post-test only
☐ Single group pre-post
☐ Longitudinal
☐ Other: F13 Are the posttest measures
adjusted for a covariate ☐ No
☐ Yes:
F14 Additional comments
Effect-size calculation* G Effect Size G1 Confidence effect size ☐ All relevant information is provided
☐ Not all data is provided G2 Explanation G3 Additional comments G4 Relevant page numbers G5 Correlation between multiple
outcomes
*Information regarding the computations of effect sizes was coded in a separate excel-file.
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Appendix C: Overview of the PBL Papers
Author(s) Publication Country School Domain Design ≥ 12 weeks Curriculum Outcomes
Achuonye (2010) Article Nigeria K-12 STEM IG no no Interest
Akınoğlu & Tandoğan (2007) Article Turkey K-12 STEM IG pre-post no no Attitude
Ali & El Sebai (2010) Article Saudi Arabia HE Health SG pre-post yes no Motivation
Banes (2013) Dissertation USA HE STEM IG pre-post yes no Motivation, PA (academic), value, interest
Baragona (2009) Dissertation USA HE STEM IG pre-post no no Motivation
Boren (2012) Dissertation USA K-12 STEM IG no no PA (academic), interest
Brand (2010) Dissertation USA K-12 Health IG pre-post no no PA (academic), LOC, value, attitude, autonomous & mastery, controlled & performance
Brown et al. (2013) Article USA K-12 Other SG pre-post yes no PA (academic), PA (computer), future interest
Carll-Williamson (2003) Dissertation USA K-12 STEM IG pre-post no no Attitude
De Witte & Rogge (2016) Article Belgium K-12 Other IG pre-post no no Autonomous & mastery, controlled & performance
Dilek Eren & Akinoglu (2013) Article Turkey HE STEM IG pre-post yes no PA (PBL)
Doody (2009) Dissertation Ireland HE STEM IG pre-post yes no PA (academic), intrinsic vs. extrinsic
Dunlap (2005) Article USA HE STEM SG pre-post yes no PA (academic)
Eccott et al. (2012) Article Canada HE Health SG pre-post no no PA (professional)
Ferreira & Trudel (2012) Article USA K-12 STEM SG pre-post - no Attitude
Galand et al. (2010) Article Belgium HE STEM IG yes yes PA (academic), autonomous & mastery, controlled & performance
Grant (2005) Dissertation/ Article UK HE Health IG yes yes PA (PBL), autonomous & mastery
Günüşen et al. (2014) Article Turkey HE Health IG yes yes LOC
Hesterberg (2005) Dissertation USA HE Social IG pre-post yes no PA (professional)
Horak (2013) Dissertation USA K-12 STEM IG no no PA (academic), interest
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Hsieh et al. (2008) Article USA K-12 STEM SG pre-post no no PA (academic), autonomous & mastery, controlled & performance
Hwang & Kim (2006) Article South Korea HE Health IG yes no Motivation
Kaufman & Mann (1996) Article Canada HE Health IG yes yes Interest
Kazemi & Goraishi (2012) Article Iran HE STEM IG yes no Attitude
Könings et al. (2005) Article Netherlands K-12 Other IG pre-post no no Motivation, PA (general)
Krivel-Zacks (2001) Dissertation Canada HE Teacher Ed. SG pre-post yes yes PA (professional)
Kuhnigk & Schauenburg (1997) Article Germany HE Health IG yes yes LOC
Langelotz et al. (2005) Article Germany HE Health IG no no Motivation, future interest
Lawless & Brown (2015) Article USA K-12 Other SG pre-post yes no PA (academic), future interest
Layne et al. (2014) Article USA HE Social SG pre-post - no PA (professional)
LeJeune (2002) Dissertation USA HE STEM IG pre-post no no Motivation
Liu (2004) Article USA K-12 STEM SG pre-post no no Attitude
Liu (2005) Article USA K-12 STEM SG pre-post no no Attitude, autonomous & mastery, controlled & performance
Liu et al. (2006) Article USA K-12 STEM SG pre-post no no PA (academic), attitude
Lohse Bayard (1994) Dissertation USA HE Health IG no no Motivation, PA (PBL)
Loyens et al. (2009) Article Netherlands HE Social IG yes yes Motivation
Lucas (2009) Dissertation UK HE STEM SG pre-post no no PA (academic)
Lucieer et al. (2016) Article Brazil HE Health IG yes yes PA (academic)
Masek (2015) Article Malaysia HE STEM IG pre-post no no Autonomous & mastery
Masek et al. (2016) Conference paper Malaysia HE STEM IG pre-post no no Motivation
Massa et al. (2012) Conference paper USA HE STEM SG pre-post yes no PA (academic), autonomous & mastery
Massa et al. (2013) Conference paper USA HE STEM SG pre-post yes no PA (academic), autonomous & mastery
Michel et al. (2002) Article Germany HE Health IG no no Interest
Mykyten et al. (2008) Article USA HE Economics IG yes no Motivation, PA (academic)
Nelson (2002) Dissertation USA HE Health SG pre-post no no PA (general)
Nelson Ross (2003) Dissertation USA K-12 Other IG no no Value, interest
79
Özbıçakçı et al. (2015) Article Turkey HE Health IG yes no PA (PBL)
Ozturk et al. (2008) Article Turkey HE Health IG yes yes PA (PBL)
Papinczak et al. (2008) Article Australia HE Health SG pre-post yes yes PA (academic), PA (PBL)
Pedersen (2003) Article USA K-12 STEM SG pre-post no no Intrinsic vs. extrinsic
Rajab (2007) Dissertation USA HE STEM IG pre-post no no PA (academic), attitude
Rehmat (2015) Dissertation USA K-12 STEM IG pre-post yes no Motivation
Reich et al. (2007) Article Germany HE Health IG no no Motivation, interest
Rideout et al. (2002) Article Canada HE Health IG yes yes PA (PBL), PA (professional)
Roh & Kim (2015) Article South Korea HE Health SG pre-post no no PA (academic) LOC, value, autonomous & mastery, controlled & performance
Ryan (1993) Article Australia HE Health SG pre-post yes no PA (PBL)
Schauber et al. (2015) Article Germany HE Health IG yes yes PA (academic)
Senocak et al. (2007) Article Turkey HE STEM IG pre-post no no Attitude
Serin (2009) Dissertation Turkey K-12 STEM IG pre-post no no Attitude
Sezgin Selçuk (2010) Article Turkey HE STEM IG pre-post no no Value, interest
Short et al. (1997) Article USA HE Health IG pre-post yes yes PA (professional)
Sungur & Tekkaya (2006) Article Turkey K-12 STEM IG pre-post no no PA (academic), LOC, value, autonomous & mastery, controlled & performance
Tarmizi & Bayat (2010) Article Malaysia HE STEM SG pre-post no no Motivation
Tiwari et al. (2006) Article China HE Health IG pre-post yes yes PA (PBL)
Toprac (2008) Dissertation USA K-12 STEM SG pre-post no no PA (academic), value, interest
Tosun & Senocak (2013) Article Turkey HE STEM SG pre-post no no Attitude
Turan et al. (2009) Article Turkey HE Health IG yes yes Motivation
Uygun & Işık Tertemiz (2014) Article Turkey K-12 STEM IG pre-post no no Attitude
Vazquez (2008) Dissertation USA K-12 Other SG pre-post no no PA (academic), value, autonomous & mastery
Vish (2013) Dissertation USA K-12 Humanities IG no no Motivation
Westhues et al. (2014) Article Canada HE Social IG pre-post yes no PA (professional)
80
Wijnen et al. (2016) Unpublished Netherlands HE Law IG yes yes Autonomous & mastery, controlled & performance
Wijnia et al. (2011) Article Netherlands HE Social IG yes yes PA (academic), outcome expectancy, autonomous & mastery, controlled & performance
Williams et al. (1998) Article USA K-12 STEM IG pre-post no no Attitude
Yardimci et al. (2017) Article Turkey HE Health IG yes yes Amotivation, autonomous & mastery, controlled & performance
Yukhymenko et al. (2010) Conference paper USA K-12 Other SG pre-post no no PA (academic), PA (computer), interest, future interest
Zhang et al. (2012) Article China HE Health IG yes no PA (professional), interest
Zheng (2002) Conference paper USA K-12 STEM SG pre-post yes no PA (academic), attitude
Zumbach et al. (2004) Article Germany K-12 STEM IG pre-post no no Motivation
Note. HE = Higher Education, Teacher Ed. = Teacher Education, IG = Independent Groups, SG = Single Group, PA = Perceptions of Ability, LOC = Locus of Control.
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Appendix D: Overview of the PjBL Papers
Author(s) Publication Country School Domain Design ≥ 12 weeks Curriculum Outcomes
Alexander et al. (2014) Article USA HE STEM SG pre-post yes no Interest, future interest
Apedoe et al. (2008) Article USA K-12 STEM IG no no Future Interest
Aslan Efe et al. (2012) Article Turkey HE Teacher Ed. IG pre-post yes no PA (professional)
Atadero et al. (2015) Article USA HE STEM IG pre-post yes no PA (academic), outcome expectancy
Baş & Beyhan (2010) Article Turkey K-12 Humanities IG pre-post no no Attitude
Bilgin et al. (2015) Article Turkey HE Humanities IG pre-post no no PA (professional)
Bright (2015) Dissertation USA K-12 Humanities SG pre-post yes no Motivation, PA (general)
Çakıroğlu (2014) Article Turkey K-12 STEM SG pre-post no no Attitude
Chen (2012) Dissertation USA HE STEM SG pre-post no no PA (professional)
Chen & Chan (2011) Article Taiwan HE Teacher Ed. SG pre-post yes no PA (computer)
Chen et al. (2015) Article USA HE STEM SG pre-post no no PA (academic)
Cooper & Koyts-Schwartz (2013) Conference paper USA HE STEM SG pre-post yes no PA (academic), value, interest
Dahl (2002) Dissertation USA HE STEM SG pre-post no no Interest
DeWaters & Powers (2011) Conference paper USA K-12 STEM SG pre-post no no PA (academic)
Ferretti et al. (2001) Article USA K-12 Humanities SG pre-post no no PA (academic), autonomous & mastery
Filippatou & Kaldi (2010) Article Greece K-12 Other SG pre-post no no PA (academic), value
Fini & Mellat-Parast (2012) Article USA HE STEM SG pre-post yes no PA (academic)
Gerlach (2008) Dissertation USA K-12 Humanities SG pre-post no no PA (PBL)
Harding et al. (2007) Conference paper USA HE STEM IG no no Autonomous & Mastery
Haugen (2013) Dissertation USA K-12 STEM SG pre-post no no Future Interest, attitude
Helle et al. (2007) Article Finland HE STEM IG pre-post yes no Autonomous & Mastery
Işik & Gücüm (2013) Article Turkey K-12 STEM IG pre-post - no PA (academic), value
Kaldi et al. (2011) Article Greece K-12 Other SG pre-post no no PA (academic), value
Knezek et al. (2013) Article USA K-12 STEM SG pre-post yes no Interest, future interest
Koparan & Güven (2014) Article Turkey K-12 STEM IG pre-post no no Attitude
82
Liu (1998) Article USA K-12 Other SG pre-post yes no PA (academic), LOC, Value, autonomous & mastery, controlled & performance
Liu & Hsiao (2002) Article USA K-12 Other SG pre-post yes no PA (academic), LOC, value, autonomous & mastery, controlled & performance
Liu & Pedersen (1998) Article USA K-12 Other IG pre-post yes no Intrinsic vs. Extrinsic
Liu & Rutlegde (1997) Article USA K-12 Other IG pre-post yes no PA (academic), LOC, value, autonomous & mastery, controlled & performance
MacArthur et al. (2002) Article USA K-12 Humanities SG pre-post no no PA (academic), autonomous & mastery
Mergele (2013) Dissertation USA K-12 Humanities IG - no Value
Mills (2009) Article USA HE Humanities SG pre-post yes no PA (academic)
Mioduser & Betzer (2007) Article Israel K-12 STEM IG pre-post yes no Attitude
Okolo & Ferretti (1996) Article USA K-12 Humanities SG pre-post no no Motivation
Özdemir (2006) Dissertation Turkey K-12 STEM SG pre-post no no Attitude
Papastergiou (2005) Article Greece HE Other SG pre-post yes no Interest
Reinertsen (2008) Dissertation USA K-12 Social SG pre-post no no Attitude
Rodríguez et al. (2015) Article Spain HE STEM IG pre-post no no Value, interest
Schaffer et al. (2012) Article USA HE STEM SG pre-post no no PA (professional)
Toci (2000) Dissertation USA K-12 Other SG pre-post yes yes Intrinsic vs. Extrinsic
Worry (2011) Dissertation USA K-12 STEM IG no no Motivation
Yalçin et al. (2009) Article Turkey HE STEM IG pre-post no no Attitude
Yancy (2012) Dissertation USA K-12 STEM IG pre-post yes no PA (academic), value, autonomous & mastery
Note. HE = Higher Education, Teacher Ed. = Teacher Education, IG = Independent Groups, SG = Single Group, PA = Perceptions of Ability, LOC = Locus of Control.
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Appendix E: Overview of the CBL Papers
Author(s) Publication Country School Domain Design ≥ 12 weeks Curriculum Outcomes
Ali (2001) Dissertation Egypt HE Teacher Ed. SG pre-post no no Attitude
Ayyıldız & Tarhan (2012) Article Turkey HE STEM SG pre-post - no Attitude
Ayyıldız & Tarhan (2013) Article Turkey HE STEM IG pre-post - no Attitude
Baeten et al. (2013) Article Belgium HE Social IG pre-post yes no Autonomous & mastery, controlled & performance
Barise (1998) Dissertation Canada HE Social IG pre-post no no Motivation
Bozic (2014) Dissertation USA HE STEM IG no no PA (academic), value
Bruning et al. (2008) Article USA HE Teacher Ed. IG pre-post yes no PA (professional)
Yalҫinkaya et al. (2012) Article Turkey K-12 STEM IG pre-post yes no PA (academic), LOC, value, autonomous & mastery, controlled & performance
Yoo & Park (2015) Article South Korea HE Health IG pre-post no no Motivation
Note. HE = Higher Education, Teacher Ed. = Teacher Education, IG = Independent Groups, SG = Single Group, PA = Perceptions of Ability, LOC = Locus of Control.