the effects of problem-based, project-based, and …...mathematics (stem) courses, to measure how...

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

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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.

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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.

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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

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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

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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

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Figure 1. Motivational framework and concepts.

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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

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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.

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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

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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

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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).

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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

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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).

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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.

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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

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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?

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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


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).

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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





Low 15 0.407 .11

Moderate 36 0.236 .11

High 39 0.413 .10


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


Quality of the motivation measure 7.25 3 .064

Low 16 0.729 .25

Moderate 35 0.361 .09

High 29 0.185 .11


Publication status 4.54 2 .103


Other 25 0.273 .08


32

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





Low 27 0.503 .07

Moderate 18 0.570 .09

High 5 1.438 .42


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


Quality of the motivation measure 12.52 3 .006

Low 14 0.717 .14

Moderate 15 0.925 .20

High 15 0.387 .07


Publication status 25.61 2 < .001


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.

73

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

74

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

75

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

76

☐ 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.

77

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

78

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.

81

Appendix D: Overview of the PjBL Papers


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


83

Appendix E: Overview of the CBL Papers


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


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