ArticlePDF Available

The Effect of Digital Game-Based Learning Interventions on Cognitive, Metacognitive, and Affective-Motivational Learning Outcomes in School: A Meta-Analysis

May 2023
Review of Educational Research 94(2)

DOI:10.3102/00346543231167795

Authors:

Nathalie Barz

Saarland University

Laura Dörrenbächer-Ulrich

Saarland University

Manuela Benick

Saarland University

Franziska Perels

Saarland University

Digital game-based learning (DGBL) interventions can be superior to traditional instruction methods for learning, but previous meta-analyses covered a huge period and included a variety of different target groups, limiting the results’ transfer on specific target groups. Therefore, the aim of this meta-analysis is a theory-based examination of DGBL interventions' effects on different learning outcomes (cognitive, metacognitive, affective-motivational) in the school context, using studies published between 2015 and 2020 and meta-analytic techniques (including moderator analyses) to examine the effectiveness of DGBL interventions compared to traditional instruction methods. Results from random-effects models revealed a significant medium effect for overall learning (g = .54) and cognitive learning outcomes (g = .67). Also found were a small effect for affective-motivational learning outcomes (g = .32) and no significant effect for metacognitive learning outcomes. Additionally, there was no evidence of publication bias. Further meta -regression models did not reveal evidence of moderating personal, environmental, or confounding factors. The findings partially support the positive impact of DGBL interventions in school, and the study addresses its practical implications.

Content uploaded by Nathalie Barz

Content may be subject to copyright.

The full arcle can be retrieved with the following citaon:

Barz, N., Benick, M., Dörrenbächer-Ulrich, L., & Perels, F. (2023). The Eect of Digital Game-Based

Learning Intervenons on Cognive, Metacognive, and Aecve-Movaonal Learning Outcomes in

hps://doi.org/10.3102/00346543231167795

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 1

The Effect of Digital Game-Based Learning Interventions on Cognitive, Metacognitive, and

Affective-Motivational Learning Outcomes in School: A Meta-Analysis.

Page 1 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 2

Abstract

Digital game-based learning (DGBL) interventions can be superior to traditional instruction

methods for learning, but previous meta-analyses covered a huge period and included a variety of

different target groups, limiting the results’ transfer on specific target groups. Therefore, the aim of

this meta-analysis is a theory-based examination of DGBL interventions' effects on different

learning outcomes (cognitive, metacognitive, affective-motivational) in the school context, using

studies published between 2015 and 2020 and meta-analytic techniques (including moderator

analyses) to examine the effectiveness of DGBL interventions compared to traditional instruction

methods. Results from random-effects models revealed a significant medium effect for overall

learning (g = .54) and cognitive learning outcomes (g = .67). Also found were a small effect for

affective-motivational learning outcomes (g = .32) and no significant effect for metacognitive

learning outcomes. Additionally, there was no evidence of publication bias. Further meta-regression

models did not reveal evidence of moderating personal, environmental, or confounding factors. The

findings partially support the positive impact of DGBL interventions in school, and the study

addresses its practical implications.

Keywords: game-based learning, learning outcomes, meta-analysis, school context, systematic

review

Page 2 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 3

The Effect of Digital Game-Based Learning Interventions on Cognitive, Metacognitive,

and Affective-Motivational Learning Outcomes in School: A Meta-Analysis

Due to the COVID-19 pandemic, learning with digital media is more relevant than ever. But

learners may experience mere e-learning environments as boring because those environments often

lack engaging elements (Connolly & Stansfield, 2009). One solution could be the application of

digital game-based learning (DGBL), because games can be highly motivating (Chang et al., 2017).

Prensky (2007) strongly influenced the term ‘digital game-based learning’, defining it as

‘any marriage of educational content and computer games’ (p. 145). Over time, DGBL definitions

focused more on the aim to promote teaching and learning processes. Al-Azawi et al. (2016) argue

that we can speak of DGBL when digital games are specifically ‘designed and used for teaching and

learning’ (p. 132). According to Malliarakis et al. (2018), the goal of DGBL is to learn during

gameplay and promote desired learning outcomes, which also summon up the terms ‘serious game’

or ‘game with a purpose’. Another characteristic of DGBL that Cojocariu and Boghian (2014)

highlighted is the connection of educational content with new learning technologies, such as mobile

devices (e.g., tablets, smartphones). Moreover, the use of new learning technologies could foster

cognitive change and enrich the learning process with entertainment, leading to improved learning

(Khan et al., 2017). The extensive definition by Erhel and Jamet (2013) summarized the previous

views of DGBL, defining it as:

a competitive activity in which students are set educational goals intended to promote

knowledge acquisition. The games may either be designed to promote learning or the

development of cognitive skills, or else take the form of simulations allowing learners to

practice their skills in a virtual environment. (p. 156)

Page 3 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 4

This definition combines the digital environments and the objective of promoting learning

processes or specific skills, but also encompasses simulations as DGBL interventions, providing the

basis for the present meta-analysis.

A growing body of research indicates DGBL interventions’ positive effects in comparison

with traditional instruction methods. Increased learning gains (e.g., higher test scores) have

appeared after DGBL interventions, in such different domains as language learning (Franciosi,

2017) or STEM education (McLaren et al., 2017) in comparison with traditional instruction

methods.

The comparison with traditional instruction methods is of relevance to determine the

advantages of DGBL interventions and deduce recommendations for scientific and educational

practice. Digital games offer an innovative approach to educate pupils in the classroom because

well-designed games can adapt to the learners’ needs (Plass & Pawar, 2020) and therefore, can

contribute to the successful handling of heterogeneity in the classroom. Furthermore, they provide a

secure learning environment where pupils are allowed to make mistakes and try again. This

‘graceful failure’ (Plass et al., 2015, p. 261) leads to mastery experiences, which increase pupils’

self-efficacy and motivation. Digital games support a learner-centered pedagogy and enable pupils

to actively make their own learning experiences within the game.

According to the self-determination theory (Ryan & Deci, 2000), implementing game

mechanics to satisfy the basic psychological needs for competence, autonomy, and relatedness

(Ryan & Rigby, 2020) can make digital games highly motivating. Chang et al. (2017) conducted a

study with 103 university students in an education course, comparing game-based learning and

traditional learning methods regarding flow experiences. The experimental group played a digital

game about the carbon footprint; the control condition was learning with webpages. The results

Page 4 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 5

show that participants who played the game had a significantly stronger experience of flow during

the experiment, represented through higher enjoyment, engagement, and control.

As a group, that Admiraal et al. (2011) described as ‘bored and disengaged’ (p. 1185), pupils

could especially benefit from motivation through DGBL interventions, and evidence exists for

DGBL interventions’ positive effect on them (López-Fernández et al., 2021). In an Iranian

elementary school, Partovi & Razavi (2019) examined the influence of DGBL on pupils’ academic

achievement motivation. After three months of learning with a digital game, the experimental group

had significantly higher academic achievement motivation than the control group.

These findings support the assumption that DGBL interventions could benefit pupils, but

they just capture a snapshot of learning with digital games. Previous meta-analyses show that digital

games outmatch traditional instruction methods regarding learning gains for young children and

young adults (Clark et al., 2016). In the context of elementary school to university, there is also

evidence for DGBL interventions’ positive impact on cognitive, affective, and behavioral outcomes

(Lamb et al., 2018). Prior meta-analyses agree that DGBL can have positive effects on learning, but

they only included studies until 2015. In the last five years, which the current meta-analysis

includes, rapid technological development occurred, offering new technological opportunities for

DGBL interventions. Games can be developed at lower costs and are more accessible for research

and teachers. Due to the ongoing digital transformation, the number of digital devices in school has

increased. Those digital devices provide more memory space, better graphic boards, and main

storage, which facilitated the implementation of DGBL interventions in school in the recent years.

In game development, more and more complex game mechanics and detailed textures can be

applied. This makes it hard to compare modern DGBL interventions with DGBL interventions from

ten years ago. Therefore, there is renewed demand to analyze the impact of DGBL interventions in

Page 5 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 6

the last years. To make DGBL interventions comparable and to merge with the latest meta-analyses,

only studies between the years 2015 and 2020 are analyzed in the current meta-analysis. Moreover,

the prior meta-analyses examined a wide range of target groups, making transferring the findings to

special subgroups difficult. As mentioned, pupils could greatly benefit from DGBL interventions,

which is why they are the focus of this meta-analysis. Accordingly, the objective of this meta-

analysis is to analyze the effect of DGBL interventions in comparison with that of traditional

instruction methods within the years 2015–2020 purely in the school context. To specify the impact

of DGBL interventions, a theoretical model, namely the Integrated Design Framework for Playful

Learning (Plass et al., 2015), supported deducing different categories of learning outcomes.

Integrated Design Framework for Playful Learning

As shown in Figure 1, the Integrated Design Framework for Playful Learning (Plass et al.,

2015) combines different theoretical foundations of gameplay that lead to specific game-design

elements. The model describes four areas of theoretical foundations: affective, motivational,

cognitive, and sociocultural foundations.

Affective foundations of DGBL include the evocation of emotions to promote learning. The

so-called emotional design deals with the question of how to induce emotion with different game-

design elements, such as narrative or music (Plass et al., 2015). Games can evoke various emotions

with, for example, empathic characters that increase cognitive processing and thus, facilitate

learning processes (Plass et al., 2020). One emotional foundation of DGBL represents the

integrative model by Loderer et al. (2020), which is based on Pekrun’s (2006) content-value theory

of achievement emotions. It assumes that emotions depend on the evaluation of internal (e.g., value)

and external (e.g., musical score) stimuli and the emotional transmission from other people or game

elements (e.g., peers, visual aesthetic; Loderer et al., 2020).

Page 6 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 7

Motivational foundations of DGBL emphasize the characteristics of games to motivate or

engage players to play for enjoyment. Ryan and Rigby (2020) refer to motivation as the ‘core

element in game-based learning’ (p. 153). One motivation theory they include is the expectancy-

value theory (Wigfield & Eccles, 2000), which assumes that the expectation of a benefit from their

actions motivates players. In addition, self-determination theory (Ryan & Deci, 2000) focuses on

intrinsic motivation, which means that a person pursues something because of interest or fulfillment

resulting from the action itself. According to this theory, intrinsic motivation depends on three

different psychological needs, namely competence, autonomy, and relatedness. Competence

describes the feeling of effectiveness and mastery of a task (Ryan & Deci, 2000). In DGBL,

feedback or level-ups satisfy the need for competence because players experience growth and self-

efficacy, ‘people’s beliefs about their capabilities to exercise control over events that affect their

lives’ (Bandura, 1989, p. 1175). Digital games offer the possibility for a retry after a failure, and

they enable ‘graceful failure’ (Plass et al., 2015, p. 261), which positively affects self-efficacy.

Moreover, games can be adapted to the players’ skills or abilities, and therefore, lead to mastery

experiences that can also increase self-efficacy (Bandura, 1997). The need for autonomy refers to

the desire for self-determined and volitional activities. Digital games provide virtual worlds with

many possibilities and the freedom to personalize and choose activities that increase satisfaction of

autonomy needs (Rigby & Ryan, 2011). The last factor, relatedness, includes the need to help

others, collaborating to reach common goals. Multiplayer games or adoption of special team roles to

contribute to joint goal attainment could meet the demand for relatedness.

Cognitive foundations of DGBL refer to cognitive characteristics for learning—for example,

information processing and explaining how players could learn from digital games. The cognitive

theory of game-based learning combines the cognitive load theory (Sweller, 2011) as well as the

Page 7 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 8

cognitive theory of multimedia learning (Mayer, 2014) and makes three assumptions: 1) Players use

two separate channels to process visual and verbal information which interact with each other. 2)

Players have a limited capacity to process information in the respective channels. 3) Players must

actively process information by paying attention, structuring information, and integrating new

knowledge to be able to learn (Mayer, 2014). Games may contain pictures or verbal narrations that

players receive through eyes or ears. The working memory further processes the filtered visual or

verbal information into verbal and pictorial models. Prior knowledge enriches created verbal and

visual representations, and long-term memory stores them (Mayer, 2020). Information processing

can occur in three different ways. Extraneous processing includes cognitive processing unrelated to

the learning goal, which is caused by distraction from extraneous stimuli (e.g., unnecessary

background animations). Essential processing refers to the cognitive processing that assimilating

information in the working memory requires, and generative processing manages the organization

and integration of information in long-term memory (Mayer, 2020).

Sociocultural foundations of DGBL take account of ‘interactions among players, the

construction of collective knowledge, and the application of this knowledge in the context of

cultural norms’ (Plass et al., 2020, p. 17). Games enable interactions and relationships with other

players and provide a connection to the game’s community, which could exceed the game itself

(Steinkuehler & Tsaasan, 2020). Social context can promote learning, for example, by increasing

motivation due to the feeling of belonging to the community (Plass et al., 2015). Social interactions,

like collaborative or competitive play, could influence how much effort a player invests in a game

and, therefore, represents an important factor of DGBL (Plass et al., 2020).

To summarize, different perspectives on digital games are represented in their different

theoretical foundations and the selected game-design elements depend on the chosen theoretical

Page 8 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 9

foundation and the intended learning goals. To assess the broad variety of learning goals, the

present meta-analysis examines different learning outcomes based on this model and extends them

to the category of metacognitive outcomes.

Different game-design elements for digital game-based learning are suitable to promoting

specific learning goals and aspiring to ‘achieve the intended interactions with the learning content in

a playful, motivating way’ (Plass et al., 2020, p. 11). Game-design elements in the model are

incentive systems, aesthetic design, game mechanics, narrative, and sound design, which depend on

the content and skills that the game should convey. The incentive system offers rewards to provide

feedback and influence player behavior (Kinzer et al., 2012). Incentives could trigger extrinsic

motivation with extrinsic rewards that are not necessary for the core gameplay (e.g., experience

points) or increase intrinsic motivation with extrinsic rewards that could result in intrinsic

motivation (e.g., a new tool for exploration; Tam & Pawar, 2020). Aesthetic design includes the

visual design of the game, the avatars, and characters, as well as the visual signaling to provide cues

and feedback.

Game mechanics describe repeated activities the player performs to enable gameplay. They

comprise two categories: assessment and learning mechanics. Assessment mechanics, based on test

theory approaches, contain diagnostical goals (e.g., apply rules to solve a problem; Plass et al.,

2011), whereas learning mechanics are based on learning theories and contain learning goals (e.g.,

acquire knowledge through interaction with other characters; Plass et al., 2020). A narrative

contains the storyline or dialogue with characters. It could provide a context for learning processes

and often connects different game elements with each other (Dickey, 2020). The game’s sound

design represents all auditory stimuli (e.g., character sounds, action sounds) and could support

cueing (Pawar et al., 2020). The implemented game-design elements could induce different types of

Page 9 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 10

engagement, including cognitive, behavioral, affective, and social engagement (Domagk et al.,

2010). For example, using a narrative that captivates the player could achieve an affective

engagement that causes the player to finish the game.

Based on the presented model, we deduced different learning outcomes to represent the

engagement types that DGBL interventions could evoke. The next chapter describes the analyzed

learning outcomes in detail.

Definition of Learning Outcomes

To enable a more precise insight into the effectiveness of digital game-based learning

interventions, the present meta-analysis examines learning outcomes in specific categories. The

previous theoretical model classifies learning outcomes as cognitive and affective-motivational,

reflecting the types of engagement that different game elements could induce. DGBL interventions

often neglect behavioral and social engagement because their main goal is to acquire knowledge or

motivate people to learn. Therefore, this meta-analysis does not include behavioral and social

outcomes. However, the model disregards another important category of learning outcomes,

namely, metacognitive learning outcomes, which the present meta-analysis considers as an

extension of the theoretical model. Cognitive learning outcomes contain conceptual or domain-

specific knowledge and the ability to remember, understand and recall this knowledge (Post et al.,

2019). Affective-motivational learning outcomes include attitudes, beliefs, emotions, values, and

interests (Allen & Friedman, 2010). Metacognitive learning outcomes comprise two components:

metacognitive knowledge and metacognitive skills. Metacognitive knowledge includes declarative

(e.g., what learning strategy would be appropriate) and procedural (e.g., how to use a learning

strategy) knowledge of one’s own knowledge and describes higher order knowledge, whereas

Page 10 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 11

metacognitive skills involve planning, monitoring, and reflection strategies to regulate learning

processes (Veenman et al., 2006).

Evidence From Current Meta-Analyses

Investigating the influence of digital game-based learning is a relevant topic with which

meta-analyses have dealt before. Vogel et al. (2006) compared the effects of DGBL interventions,

—namely, serious games and simulations—regarding cognitive gains with traditional teaching

methods, between 1986 and 2003. Their analyses included 32 studies with different target groups

and revealed that serious games and simulations lead to higher cognitive gains than traditional

methods. Sitzmann (2011) analyzed the effect of simulation games on trainees in studies from 1976

to 2009. As dependent variables, self-efficacy, declarative and procedural knowledge were analyzed

in a sample of 65 studies. The results showed that the participants who used simulation games for

learning had higher procedural and declarative knowledge as well as better knowledge recall than

participants utilizing traditional learning. Furthermore, in eight studies, self-efficacy was 20%

higher when learning with a simulation game in comparison to the control group.

In 2013, Wouters et al. examined the effectiveness of DGBL interventions, assessed by

using serious games for knowledge acquisition and learning retention, between the years 1990 and

2012. They did not set an age restriction for the studies and consequently examined a sample of 39

studies with a broad target population. Their findings indicate greater learning gains for serious

game conditions compared to traditional instruction methods (d = .29), but they also reveal no

difference in motivation between the two conditions. Serious games seem no more motivating than

traditional methods.

Page 11 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 12

Clark et al. (2016) investigated the effect of DGBL interventions on learning, assessed

through the use of digital games in the age group from 6 to 25 years, by synthesizing studies

between the years 2000 and 2012. They included 69 studies in their analysis and, in accordance

with the results of previous meta-analyses, they found evidence that digital games outmatch control

groups regarding learning.

Another meta-analysis that Lamb et al. (2018) conducted focused on the effect of

simulations and serious games on students’ cognition, affect and learning from elementary school to

university. They analyzed 46 studies from the period 2002–2015. The results of their meta-analysis

indicate a medium effect for cognitive and affective outcomes regarding learning and a small effect

for behavioral outcomes for participants using simulation games and serious games.

All these meta-analyses share the conclusion that DGBL has positive effects on learning, but

they examined studies covering a huge period and, therefore, do not do justice to the rapid

technological development and new technological opportunities. Furthermore, they focused on very

heterogeneous target groups, making it hard to transfer the findings to specific target groups.

Therefore, the present meta-analysis examines studies that cover a shorter and more up-to-date

period and focuses on a more specific target group, namely pupils, because they are predestined to

benefit from DGBL interventions due to their motivational needs. Additionally, to extend the

previous meta-analyses, all learning outcomes derive from a theoretical model, considering

metacognitive learning outcomes in the analysis that have not been examined before. Based on the

previous findings, we assume positive effects on learning in general (Hypothesis 1.1) as well as on

cognitive (Hypothesis 1.2), metacognitive (Hypothesis 1.3) and affective-motivational learning

outcomes (Hypothesis 1.4).

Page 12 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 13

Impact of the Moderating Role of Personal, Environmental, and Confounding Factors

In addition to the examination of the main effects of DGBL on different learning outcomes,

this meta-analysis also scrutinized the impact of personal factors, learning environment factors, and

confounding factors to pursue the aim to deduce recommendations for scientific and educational

practice how to design and implement digital games. The variables, which were considered in the

different categories, were deduced from previous meta-analyses on the one hand and based on

explorative considerations on the other hand. The following sections describe the moderator

variables.

Personal Factors

Age. For age as a moderator in DGBL interventions, findings show no differences between

the age groups from preschool to college students (Vogel et al., 2006). The comparison of different

age groups (children, preparatory education, students, adults) revealed also no differences regarding

DGBL interventions in the meta-analysis by Wouters and colleagues (2013). DGBL interventions

led to better learning gains in all age groups (except adults) when compared to the control group.

We also assume that DGBL interventions are effective for all participants, and no differences

between the age groups would appear in the present meta-analysis (Hypothesis 2.1).

Gender. Vogel et al. (2006) found evidence for gender differences regarding cognitive gains

for DGBL interventions. Female participants ‘showed significant cognitive gains favoring the

interactive simulation and game method’ (p. 234). We also assume, due to playing behaviors that

differ from males’ (Veltri et al., 2014) that DGBL interventions are more effective for female

players (Hypothesis 2.2).

Learning Environment Factors

Page 13 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 14

Additional Non-Game Instruction. Many studies use additional non-game instruction

(e.g., discussion, preparative lessons) but the findings are mixed regarding additional non-game

instruction as a moderator for DGBL. Whereas Sitzmann (2011) and Wouters et al. (2013) found

evidence that DGBL interventions combined with additional non-game instruction led to greater

learning gains, Clark et al. (2016) did not find differences between DGBL interventions with and

without additional non-game instruction. Therefore, additional non-game instruction is further

analyzed exploratively in the current meta-analysis (Research question 1).

Type of DGBL Intervention. Regarding the type of DGBL intervention, using a serious

game or an interactive simulation made no difference; both were likewise superior to traditional

methods (Vogel et al., 2006). The results from Lamb et al. (2018) indicated differences between

serious games and simulations, in that the former had a greater effect on learning than simulations.

With the unclear impact of the DGBL intervention type, this variable is exploratively examined as a

moderator (Research question 2).

Number of Sessions. The assumption that one game session may not be sufficient to

increase learning was based on the well-investigated advantage of distributed learning over massed

learning (Cepeda et al., 2006). Wouters et al. (2013) substantiated this hypothesis for serious

games, reporting in their meta-analysis that serious games with multiple sessions led to higher

learning gains than traditional learning methods. They explained this result by stating that

participants need time to understand the games’ control. Clark et al. (2016) found further evidence

of the superiority of multiple game sessions over single sessions. The effects of digital games on

learning were smaller when games were only played once rather than in distributed sessions.

Therefore, we include the number of sessions in the meta-analysis and assume the superiority of

multiple game sessions over single game sessions in DGBL (Hypothesis 2.3).

Page 14 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 15

Playing Mode. The impact of the playing mode in DGBL interventions is still unclear.

Vogel et al. (2006) revealed that both, single players and players in groups, outperformed the

control group in terms of learning, but they did not further analyze the difference between the two

playing modes. Wouters et al. (2013) found evidence for greater learning gains favoring gaming in

groups. Participants in single-player and multiplayer games learned more than the control group,

but the effect was larger for multiplayer games. Clark et al. (2016) also analyzed player modes and

first reported the largest learning outcomes for single players. However, this effect disappeared

when other game characteristics (e.g., story relevance, visual realism) were controlled. Single-

player games then showed no significant difference from multiplayer games. As a result of these

inconsistent findings, this study exploratively analyzed the influence of player mode in DGBL

interventions (Research question 3).

Competition. Closely associated with the playing mode are competitive game designs. In

their examination of player modes, Clark et al. (2016) also considered competitive and

noncompetitive single and multiplayer configurations. According to their findings, single-player

games without competition did not lead to larger effects than team competition games, but both

noncompetitive single-player and competitive multiplayer games led to greater learning outcomes

than competitive single-player games. Based on this evidence, the effect of the mere presence of

competition in games remains unclear because it was confounded with playing mode. But Clark et

al. (2016) provided the first insights onto possible differences between noncompetitive and

competitive game designs. Evidence exists that competitive game designs could lead to higher

intrinsic motivation and therefore result in greater learning outcomes (Cagiltay et al., 2015). Chen

and Chiu (2016) argue that teamwork leads to an effective exchange of information and the creation

of new ideas. Competitive teams could increase interest as well as engagement and decrease

Page 15 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 16

pressure to perform (Chen, 2019), making them superior to noncompetitive learning. In their meta-

analysis concerning competition in DGBL environments, Chen et al. (2020) found a positive effect

of competitive DGBL environments, dependent on subject and game type. Thus, we assume that

competitive DGBL interventions lead to greater learning gains than noncompetitive DGBL

interventions (Hypothesis 2.4).

Dimensionality. 2D and 3D games are effective for learning (Ak & Kutlu, 2017), but the

dimensionality of game environments could also influence the learning effect. Three-dimensional

games lead to the greatest effect on learning, according to the findings from Lamb et al. (2018),

outmatching two-dimensional and mixed environments regarding cognition and affect. Three-

dimensional learning environments seem to lead to greater cognitive and affective activation and

facilitate the transfer of the learning content to the real world, which is also three-dimensional

(Lamb et al., 2018). We assume that three-dimensional DGBL interventions lead to greater learning

gains than two-dimensional or mixed DGBL interventions (Hypothesis 2.5).

Visual Realism. Not only the dimensionality but also the level of visual realism could

influence learning with DGBL interventions. The impact of visual realism is still unclear, given the

inconsistent findings for this variable. Vogel et al. (2006) concluded in their meta-analysis that the

level of realism has no influence on learning, whereas Wouters et al. (2013) found evidence that

schematic serious games are more effective than traditional instruction methods. Realistic or

cartoonlike serious games did not lead to better learning than traditional instruction methods. The

results from Clark et al. (2016), who also described schematic games as superior to realistic games,

support these findings. Controlled for visual and narrative game characteristics, the difference

between schematic and realistic games was diminished to marginal significance. Based on the

previous studies and taking into account that highly realistic learning environments could lead to a

Page 16 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 17

higher cognitive load and, therefore, more complex information processing (Mayer, 2014; Nelson &

Kim, 2020), we assume that schematic DGBL interventions lead to greater learning gains than

realistic or cartoonlike DGBL interventions (Hypothesis 2.6).

Learning Domain. Another interesting factor to consider regarding DGBL interventions is

the learning domain. Wouters et al. (2013) described DGBL interventions as exceptionally more

effective in verbal domains than in scientific or mathematical domains. On the contrary, Karakoç et

al. (2020) found no differences regarding learning domains, but their findings are restricted to

Turkish publications and difficult to generalize. Due to the unclear impact of different learning

domains, this moderator was analyzed exploratively (Research question 4).

Narration. Whether to include a narrative in a game is a controversial topic. One party

supports the integration of a strong narration into game environments because it causes immersion

and greater intrinsic motivation. Narrations can evoke emotions and promote the relatedness with

the game by solving a common problem (Dickey, 2020; Rowe et al., 2011). The other side argues

that a strong narrative distracts learners from the actual learning content, because of higher

extraneous cognitive load that decreases learning (Novak, 2015). In their meta-analysis, Wouters et

al. (2013) could not find evidence for a learning difference between games with or without a

narrative, but both were superior to traditional instruction methods. Clark et al. (2016) compared

relevant to irrelevant narratives and found significantly larger effects for games that used irrelevant

narratives, but when controlled for visual characteristics and story depth, this difference vanished.

They also found a negative relationship between narratives and learning, but their results must be

handled with caution because they only included a small number of studies with relevant narratives

(n = 5). There is strong evidence that narratives support problem-solving in games (Lester et al.,

2014) and are effective for learning (Jackson et al., 2018). Furthermore, they can foster emotional

Page 17 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 18

engagement (Bowers et al., 2013) that could also support deeper information processing. Based on

these explanations, we assume that DGBL interventions with a narrative lead to greater learning

gains than DGBL interventions without a narrative (Hypothesis 2.7).

Avatar. Avatars, which represent the players, could also influence the learning process.

Players identify with their avatar, which causes an emotional bond and increases motivation (van

Reijmersdal et al., 2013). The identification means that the player ‘imagines being that character

and replaces his/her personal identity […] with the role of the character’ (Cohen, 2001, p. 251).

Thus, the player merges with the avatar during gameplay. This can occur because the avatar is

perceived as similar to oneself or because the avatar possesses characteristics the player wishes for

(Klimmt et al., 2010). Hence, the identification with the avatar could cause the intrinsic desire to

continue with the game, which could lead to greater learning gains in the context of educational

games (Tam & Pawar, 2020). Wrzesien et al. (2015) also found that avatars that resemble the player

result in better achievement in emotional strategy learning. Therefore, the mere presence of an

avatar could make a difference in the effect on learning in DGBL interventions (Hypothesis 2.8).

Digital Agent. Whereas avatars represent characters the player controls, digital agents are

so-called nonplayer characters (NPCs) that the player does not control. They can ‘create rich face-

to-face interactions’ (Johnson & Lester, 2016, p. 26) and offer scaffolding and support (e.g., hints,

feedback). Digital agents also play a socio-emotional role, for example, as a peer, which could

improve learning motivation (Lester et al., 2020). A digital agent significantly improved girls’

motivation and self-efficacy for STEM (van der Meij et al., 2015), and Liew and Tan (2016)

revealed digital agents mirroring the player’s personality are advantageous. Furthermore, digital

agents that show emotions (Theng & Aung, 2012) and empathic abilities can also increase player

motivation (Chen et al., 2012). The impact of digital agents in games focuses especially on

Page 18 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 19

motivational and emotional levels and can increase learning motivation and outcomes (Martha &

Santoso, 2019). Therefore, the use of digital agents could make a difference in the effect on learning

in DGBL interventions (Hypothesis 2.9).

Confounding Factors

Year of Publication. Sitzmann (2011) did not find a shift in learning for simulation games

between 1976 and 2009. But because of the rapid development of digital technology and the

difficulty of generalizing to DGBL interventions other than simulations, whether learning has

changed in recent years should be controlled. We therefore examine exploratively whether the year

of publication influences the effects on DGBL (Research question 5).

Country of Data Collection. The country of data collection should also be considered when

analyzing confounding factors. In some countries (e.g., Taiwan), digital learning environments are

already well-established, in others (e.g., Germany) digital learning environments are relatively new

in the classroom. This may lead to different effects, depending on the location of data collection,

which we include exploratively in the analysis (Research question 6).

Objectives

Based on the previous explanations, the objective of this meta-analysis is to analyze the

effect of DGBL interventions, assessed through different learning outcomes, in the school context

in comparison with traditional instruction methods. Because the synthesis is based on published

studies, we examined whether and to what extent publication bias confounded the results.

Furthermore, we examined the impact of different personal factors, learning environment factors,

and confounding factors to replicate previous findings and enhance the insight into DGBL

intervention effectiveness to provide recommendations for the design of future digital learning

environments.

Page 19 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 20

Hypotheses

Based on the previous theoretical descriptions, we assume that digital game-based learning

has positive effects regarding learning outcomes in the school context, which leads to the following

hypotheses:

H 1.1

DGBL interventions in school lead to higher level overall learning, assessed through

learning outcomes, than traditional instruction methods.

H 1.2

DGBL interventions in school are associated with higher level cognitive learning

outcomes than traditional instruction methods.

H 1.3

DGBL interventions in school are associated with higher level metacognitive learning

outcomes than traditional instruction methods.

H 1.4

DGBL interventions in school are associated with higher level affective-motivational

learning outcomes than traditional instruction methods.

Moderator Hypotheses

In addition to the hypotheses regarding learning outcomes, we examined the influence of

personal, environmental, and confounding factors by using moderator analyses. In a case of

sufficient robust evidence from the literature, we deduced hypotheses for the corresponding

moderators. If the evidence from the literature was unclear or insufficient, exploratory research

questions (RQ) were deduced.

The deduced hypotheses for the corresponding moderators are:

H 2.1

DGBL interventions do not have a different impact in different age groups.

H 2.2

The effect of DGBL interventions is larger for female than for male participants.

H 2.3

DGBL interventions with multiple sessions lead to higher level learning gains than

DGBL interventions with only one session.

Page 20 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 21

H 2.4

Competitive DGBL interventions lead to higher level learning outcomes than

noncompetitive DGBL interventions.

H 2.5

Three-dimensional DGBL interventions lead to greater effects on learning outcomes

than two-dimensional or mixed DGBL interventions.

H 2.6

Schematic DGBL interventions lead to higher level learning gains than realistic or

cartoonlike DGBL interventions.

H 2.7

DGBL interventions with a narrative lead to higher level learning gains than DGBL

interventions without a narrative.

H 2.8

DGBL interventions that use avatars lead to higher level learning gains than DGBL

interventions without avatars.

H 2.9

DGBL interventions that include digital agents are more effective for learning than

DGBL interventions without digital agents.

The deduced exploratory research questions for the corresponding moderators are:

RQ 1

What is the difference regarding learning between DGBL interventions with and

without additional non-game instruction?

RQ 2

What are the differences regarding learning between different DGBL intervention

types?

RQ 3

How does the playing mode influence the effect of DGBL interventions regarding

learning?

RQ 4

What influence does the learning domain have on the effect of DGBL interventions

regarding learning?

RQ 5

What influence does the year of publication have?

Page 21 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 22

RQ 6

What influence does the country of data collection have?

Method

Eligibility and Exclusion Criteria

To determine whether a study was eligible for synthesis, eligibility and inclusion criteria

were defined before the search process started. The following passages describe the criteria in

detail.

Digital Game-Based Learning

Eligible studies had to focus on DGBL interventions. To satisfy this criterion, according to

the definition of Erhel and Jamet (2013), a complete digital game or simulation had to be

implemented as an experimental condition on a computer or mobile device. Studies with games that

were not digital (e.g., board games, role play in classroom, card games) or just used one single

game element (gamification) were excluded from the sample (e.g., Sala & Gobet, 2017).

Furthermore, games that used embodiment (e.g., Microsoft Kinect), augmented or virtual reality

were also excluded from the sample (e.g., Lai et al., 2019) because of the different quality of

immersion, which would be difficult to compare with other digital games.

Period

Due to the fast development of technology and a wider range of possibilities for designing

digital games, only studies from 2015 to 2020 were suitable. Studies that were published before this

period were excluded from the analyses because previous meta-analyses had already considered

them.

Sample Size

Page 22 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 23

To ensure that the effect size Cohen’s d, needed to calculate Hedges’ g, is distributed

normally within the studies, only studies with more than 10 participants in total were selected. All

studies with an insufficient number of participants were excluded from the analyses.

Target Population

Eligible studies had to provide sufficient information about the participants. For the

synthesis, only studies with pupils from grades 1 to 13 (depending on the country where the study

was conducted) and between ages 6 and 18 were eligible. Studies with university students, third-

level education or employees were excluded (e.g., Cohen, 2016) due to assuming that adults show

different learning patterns than adolescents and children (Kuhn & Pease, 2006). Studies focusing on

special subpopulations (e.g., low- or high achievers, at-risk students) or participants with diseases

were also not eligible (e.g., Fien et al., 2016).

Study Design

To avoid the ‘garbage in – garbage out problem’ (Döring & Bortz, 2016), only studies of

good quality should contribute to the meta-analysis. Therefore, only studies with at least a quasi-

experimental pre-post-control-design were eligible, studies that deviated from this requirement

(e.g., no control group) were excluded (e.g., Tangsripairoj et al., 2019). The control group had to

participate in a traditional learning setting or receive no intervention to satisfy the inclusion criteria.

Studies that included control groups with digital pseudo-treatments (e.g., reading a website) were

not eligible (e.g., Nussbaum et al., 2015), nor were studies whose experimental conditions

developed a game on their own instead of participating in a DGBL intervention (e.g., Pellas &

Vosinakis, 2018). Because the target population consisted of pupils, only studies conducted in a

school setting were included, studies in a clinical setting or at the workplace were excluded (e.g.,

All et al., 2017).

Page 23 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 24

Learning Outcomes

Selected studies had to measure at least one appropriate dependent variable representing

students’ cognitive, metacognitive, or affective-motivational learning outcomes. Studies were not

eligible if they measured outcomes that did not address the analysis’s objectives, e.g., studies that

measured teachers’ attitude towards digitalization or studies that reported children’s frequency of

media usage (e.g., Coombes et al., 2016).

Publication Type

Eligible studies had to be articles published in peer-reviewed journals or conference

proceedings. Reviews, meta-analyses, reports, as well as all theses were excluded.

Language

Only studies written in German or English were selected. Studies written in other languages

could not be considered for the synthesis (e.g., Ada et al., 2016).

Measures

Eligible studies had to use quantitative methods and provide sufficient statistical information

to calculate effect sizes (e.g., sample size, t-value or F-value). Qualitative research, e.g.,

observational studies, and studies that did not report required statistical parameters were excluded.

Literature Search

The literature search period lasted from February 2020 until December 2020. The goal was a

broad literature sample to avoid missing important findings. Thus, several psychological, medical,

and computer science databases were consulted, namely PubMed, ProQuest, IEEE, ACM, Web of

Science, EBSCOhost, and Google Scholar. Six research assistants, as well as the first author,

conducted the literature search following a literature search manual.

Page 24 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 25

To identify as many relevant studies between 2015 and 2020 as possible, the following

search terms were used: ‘Game-based learning’, ‘Simulation game’, ‘Serious game’, ‘Educational

game’ and each search term was also combined with ‘training’, ‘learning’ and ‘education’,

respectively. Every database had special search settings to consider during the literature search. If

possible (e.g., in ProQuest), a filter for peer-reviewed journals as well as Boolean search with

“AND” (e.g., EBSCOhost) was used. If there were many hits for one search term, additional filters,

e.g., ‘undergraduate’, ‘patient’, ‘employees’ and ‘disorder’ were applied to make the search more

efficient.

Selection Process

Following Clark et al. (2016), eligible studies were selected following a three-step procedure

based on a manual that contained the eligibility and exclusion criteria. In the first step, studies were

selected by screening the titles in different databases. Thereby, a liberal approach was used and only

studies were rejected that hit an exclusion criterion or were clearly irrelevant to answering the

objectives of the analysis. In total 7,013 studies were selected in the first step. Altogether, 859

studies were selected from IEE, 632 from PubMed, 866 from Google Scholar, 59 from ACM, 2,625

from Web of Science, 675 from ProQuest and 1,298 from EBSCOhost. All duplicates were removed

afterwards, and the abstracts of all remaining studies (n = 3,120) were screened to identify further

eligible and ineligible articles. The full texts were considered in a last step to determine the final

study sample for the analyses. After the selection process, N = 36 studies were extracted for the

analyses. All selected studies are marked with an asterisk in the reference section. During the whole

selection process, the first author was consulted in case of uncertainty regarding a study’s

eligibility. Figure 2 shows the flow chart for the selection process and the reasons why certain

studies were not selected for the analysis. The category ‘Other reasons’, for example, includes

Page 25 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 26

studies in which the control group watched the experimental group playing or studies in which the

teacher used the simulation, and the pupils were not allowed to interact with it. Furthermore,

approaches that used just one game element rather than a complete game also joined the ‘Other

reasons’ category.

Coding Procedure

The coding occurred after the selection process, by two raters independently following a

coding guideline manual. For each study, the year of publication and study’s location was recorded.

Furthermore, processing included extracting the number of conditions and descriptive sample

information (e.g., number of participants, mean age) and assessing participants’ grade level. The

number of training sessions, any additional non-game instruction (1 = yes, 0 = no) and the duration

of the intervention were coded. For each study, the raters determined whether the intervention

consisted of a serious game (coded with 1), a simulation (coded with 2) or a mix (coded with 3), the

mode in which the participants played (1 = single player, 2 = multiplayer, 3 = mixed) and whether

the game was competitive (1) or not (0). Coding also included further learning-environment

characteristics, like dimensionality (1 = mixed, 2 = 2D, 3 = 3D), visual realism (1 = schematic, 2 =

cartoon, 3 = realistic, 4 = mixed), narration (1 = yes, 0 = no) and the corresponding content domain.

Moreover, coding included whether the players had an avatar with which to play (1 = yes, 0 = no)

and non-player-characters (digital agents) with which to interact (1 = yes, 0 = no). All reported

statistical parameters (e.g., F-value, p-value, degrees of freedom) were extracted to enable the

calculation of the corresponding effect sizes, if necessary. With two raters and all coded variables

nominally scaled, calculating the inter-rater reliability (Cohen’s Kappa) assessed rater agreement

while considering random agreements (Cohen, 1960). Based on conventional standards, values for

Cohen’s Kappa larger than .75 represent very good agreement, values between .60 and .75 are good,

Page 26 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 27

values between .40 and 60 are acceptable and values lower than .40 are not acceptable (Landis &

Koch, 1977). For all coded variables, Cohens Kappa was between κ = .35 and κ = .76, depicting a

variation of the rater agreement from ‘low’ to ‘very good’. Due to the low congruence for playing

mode (κ = .43) and visual realism (κ = .37), a third rater was consulted to rate the variables in

question again. Hence, they achieved at least moderate agreement in all variables with a mean

agreement of κ = .57.

Table 1 represents the particular inter-rater reliabilities in detail. Discussion with the first

author until consensus was reached solved all remaining disagreements.

To categorize the different learning outcomes (cognitive, metacognitive, affective-

motivational) for each study result, seven experts from an educational science department with

expertise in self-regulated learning and its cognitive, metacognitive, and motivational components,

were requested to estimate the learning outcomes for each study result. In total n = 57 cognitive

learning outcomes, n = 5 metacognitive learning outcomes and n = 27 affective-motivational

learning outcomes were observed.

Effect Size Measures

If reported, the pretest-adjusted posttest effect sizes for the outcomes of interest were

extracted directly from the studies. In a first step, all reported effect sizes were converted into

Cohen’s d by using the pooled standard deviation in the denominator to enable the calculation of

Hedges’ g with small sample size correction. If an effect size was missing, the parameter was

calculated from the provided statistical information in the study. After transferring all effect sizes

coherent to Cohen’s d with pooled standard deviation, all outcomes were converted to Hedges’ g,

corrected for small-sample bias. According to Cohen (1988), values smaller than .50 are interpreted

as small, values between .50 and .80 as medium and values greater than .80 as large effect sizes.

Page 27 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 28

However, knowing that this is just a rule of thumb, effect sizes will also be interpreted in relation to

previous meta-analytic results. Some studies provided numerous results that rely on the same

sample, causing dependent effect sizes. To cope with this circumstance, the average effect size was

calculated from the different partial results.

Synthesis Method

In the present meta-analysis, one study was excluded as an outlier due to an unrealistically

high effect size. Thus, the synthesis was conducted with a final sample of n = 35 studies. The

random-effects meta-analysis and meta-regression models to analyze the impact of the moderator

variables were carried out using R (version 4.1.2; R Core Team, 2020) and the metafor package

(version 3.1.43; Viechtbauer, 2010). Due to the fact that game interventions in the selected studies

varied, a random-effects model was fitted to the data and the amount of heterogeneity was estimated

using the restricted maximum likelihood estimator (REML). To assess heterogeneity, the Q-statistic

(Cochran, 1954) and the parameter τ2, with its corresponding prediction intervals, were used to

indicate the amount of heterogeneity in the random-effects model. Additionally, the inconsistency

was also specified by using I2 (Higgins & Thompson, 2002) and the confidence intervals were

calculated with Wald-type CI. If heterogeneity was detected (i.e., τ2 > 0), a prediction interval for

the true outcomes was also provided, which considers the intervention effect on the individual study

level. Therefore, it depicts a more accurate way to interpret the results (Riley et al., 2011).

Studentized residuals and Cook’s distances were used to analyze whether studies may be outliers

and examine their influence on the results (Viechtbauer & Cheung, 2010). Studies with a

studentized residual larger than the th percentile of a standard normal distribution

100

∗

―

0.05

∗

𝑘

)

were considered potential outliers. Studies with a Cook’s distance larger than the median plus six

Page 28 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 29

times the interquartile range of the Cook’s distances were assumed to have a huge influence in the

context of the model.

Given that the analyses are based on published articles, it is important to also consider the

influence of publication bias. To analyze whether the sample reflected publication bias, Fail safe N,

which determines the number of nonsignificant studies that must be included in the synthesis to

annihilate a significant effect (Rosenthal, 1979), was calculated, and funnel plots were generated for

a visual examination. Their symmetry was tested with Egger’s regression test (Egger et al., 1997),

using the standard error of the observed outcomes as predictor. An asymmetric funnel plot could be

first evidence for the influence of publication bias. But neither the funnel plot nor Egger’s

regression test is appropriate for detecting and correcting publication bias (Hedges & Vevea, 1996).

In fact, they deal with the influence of small study bias. To cope with this problem, selection

models were calculated, because they take the publication probability into account by weighing the

studies according to their p-value.

Results

Study characteristics

The n = 35 studies represent N = 7,139 participants in total. Participants’ average age was

10.89 years (SD = 2.41), and the data was collected on average in grade six (SD = 2.81). Most of the

studies were published in 2019 (n = 10). Ten studies were carried out in Europe, 6 in America, 16 in

Asia, 2 in Australia and only one study in Africa. Most of the studies came from Taiwan (n = 6).

Table S2 (online only) shows further study characteristics, and Table S3(online only)

illustrates an overview of the coded learning-environment factors.

Table S2 (online only) shows further study characteristics, and Table S3(online only)

illustrates an overview of the coded learning-environment factors.

Page 29 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 30

Results of syntheses

For the synthesis of the overall learning outcomes, the analysis included a total of κ = 35

studies. The observed outcomes ranged from -0.56 to 2.03, with 91% of the estimates being

positive. Based on the random-effects model, the estimated average outcome was g = 0.54 (95% CI:

[0.37, 0.72]) and differed significantly from zero (z = 6.04, p < .001). A forest plot showing the

observed outcomes and the estimate appears in Figure S3 (online only).

The true outcomes appear to be heterogeneous (Q (34) = 3626.72, p < .001, τ2 = 0.27, I2 =

98.04 %). For the true outcomes, a 95% prediction interval is given at -0.49 to 1.58. Hence,

although the average outcome is estimated to be positive, in some studies, the true outcome may be

negative.

To analyze cognitive learning outcomes, the analysis included a total of κ = 29 studies. The

observed outcomes ranged from 0.06 to 2.29, and all estimates were positive. Based on the random-

effects model, the estimated average outcome was g = 0.67 (95% CI: 0.48 to 0.86). Therefore, the

average outcome differed significantly from zero (z = 6.83, p < .001). Figure S4 (online only)

shows a forest plot of the results.

According to the Q-test, the true outcomes seem to be heterogeneous (Q (28) = 3247.18, p <

.001, τ2 = 0.27, I2 = 98.16 %) and a 95% prediction interval is given at -0.36 to 1.70. Although the

average outcome is estimated to be positive, in some studies the true outcome may be negative.

Metacognitive outcomes were analyzed with a total of κ = 5 studies. The observed outcomes

ranged from -0.56 to 1.14, with most estimates being positive (60%). Based on the random-effects

model, the estimated average outcome was g = 0.32 (95% CI: -0.26 to 0.89) and did not differ

significantly from zero (z = 1.09, p = .276). A forest plot showing the results appears in Figure S5

(online only).

Page 30 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 31

According to the Q-test, the true outcomes seem to be heterogeneous (Q (4) = 157.12, p <

.001, τ2 = 0.42, I2 = 97.62 %). A 95% prediction interval for the true outcomes is given at -1.07 to

1.71. Although the average outcome is estimated to be positive, in some studies the true outcome

may be negative.

Affective-motivational learning outcomes were analyzed with a total of κ = 12 studies. The

observed outcomes ranged from -0.24 to 1.78, with most estimates being positive (75%). Based on

the random-effects model, the estimated average outcome was g = 0.32 (95% CI: 0.03 to 0.61) and

differed significantly from zero (z = 2.14, p = .032). A forest plot showing the observed outcomes

and the estimate is shown in Figure S6 (online only).

According to the Q-test, the true outcomes seem to be heterogeneous (Q (11) = 240.30, p <

.001, τ2 = 0.25, I2 = 97.47 %) and for the true outcomes, a 95% prediction interval is given at -0.70

to 1.34. Although the average outcome is estimated to be positive, in some studies the true outcome

may be negative.

Results of Moderator Analyses

To analyze the potential effects of different moderator variables, meta-regression models

were conducted with the R package metafor (Viechtbauer, 2010). The results follow.

Results for Hypothesized Moderators

Age. The participants’ mean age from each study was considered a continuous variable in

the meta-regression model. No evidence could be found that participants’ mean age influenced the

impact of DGBL interventions (QM (1) = 0.25, p = .617). H2.1 was confirmed.

Gender. We considered the studies’ gender distribution by calculating the percentage of

female participants in each study. Information about the participants’ gender was given in n = 23

studies, and n = 12 studies did not provide that information. The percentage of female participants

Page 31 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 32

ranged from 37% to 62%, with a mean percentage of M = 49.50% (SD = 5.60). The almost even

distribution of males and females did not allow further examination because the differences

between the studies were too small. As a result, H2.2 could not be tested.

Number of Sessions. The number of sessions ranged from 1 session to 50 sessions and,

therefore, was split into quartiles. The first quartile contained studies with up to 2 sessions; the

second quartile included studies with 3 to 7 sessions and the third quartile included studies with 8 to

19 sessions. Based on the quartiles, the categories became 0-2, 3-7, 8-19 and more than 19 sessions.

As Table S4 (online only) shows, the estimated effect size was highest for games with more than 19

sessions, but there was no significant difference between the four categories (QM (3) = 1.82, p =

.610). This did not conform with our hypothesis, and H2.3 was rejected.

Competition. As Table S4 (online only) shows, the findings in the current meta-analysis

indicated that DGBL interventions without competitive elements are associated with higher learning

gains than DGBL interventions with competition, but the meta-regression revealed no significant

differences between DGBL interventions with and without competition (QM (1) = 0.21, p = .648).

This did not conform with our hypothesis, and H2.4 was rejected.

Dimensionality. As Table S4 (online only) shows, DGBL interventions with mixed

dimensions tended towards the strongest effect, followed by three-dimensional learning

environments and two-dimensional DGBL interventions with the lowest effect. However, the meta-

regression model showed no significant differences regarding dimensionality (QM (2) = 0.86, p =

.651). This did not conform with our hypothesis, and H2.5 was rejected.

Visual Realism. The visual realism was coded using four different categories: schematic,

cartoonlike, realistic, and mixed. The model results (see Table S4 (online only)) revealed a

tendency towards the strongest effect for realistic games followed by cartoonlike and schematic

Page 32 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 33

games; DGBL interventions with mixed realism had the lowest effect on learning. But the meta-

regression model found no significant differences across the mean effect sizes among the four

categories (QM (3) = 3.23, p = .358). This did not conform with our hypothesis, and H2.6 was

rejected.

Narration. As Table S4 (online only) shows, DGBL interventions with narration were

associated with a greater increase in learning than DGBL interventions without narration, but the

two categories do not differ significantly (QM (1) = 0.41, p = .523). This did not conform with our

hypothesis, and H2.7 was rejected.

Avatar. Although the results in Table S4 (online only) suggested that DGBL interventions

with avatars led to stronger effects on learning than DGBL interventions without avatars, the

variable did not moderate the effect of DGBL interventions (QM (1) = 0.26, p = .609). This did not

conform with our hypothesis, and H2.8 was rejected.

Digital Agent. Results suggested that DGBL interventions that use digital agents led to

greater learning effects than DGBL interventions without digital agents (see Table S4 (online

only)), but the meta-regression model indicated no significant differences between the two

categories (QM (1) = 1.99, p = .159). This did not conform with our hypothesis, and H2.9 was

rejected.

Results for Explorative Moderators

Additional Non-Game Instruction. The results indicated, as Table S4 (online only) shows,

that DGBL interventions with additional non-game instruction seemed to be more effective than

DGBL interventions without additional non-game instruction, but the two groups did not

significantly differ (QM (1) = 0.44, p = .509).

Page 33 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 34

Game Type. There was no evidence for a different impact regarding learning gains of

serious games and simulations or mixed designs (QM (2) = 4.41, p = .110), but there was a trend,

showing serious games as more effective than mixed DGBL interventions and simulations (see

Table S4 (online only)).

Playing Mode. The tendency towards learning effects for mixed-mode DGBL interventions

was the strongest, and games for single players closely followed (see Table S4 (online only)). The

results indicated that DGBL interventions with multiple players have the least effect. Although the

results hint at the superiority of mixed-mode games, the meta-regression model with a dummy

indicator for playing mode revealed no significant differences across the variable (QM (2) = 0.78, p

= .677) regarding DGBL intervention effectiveness.

Domain. The investigated studies covered a broad field of domains. The coded domains

included mathematics, science, prevention, history, cybersecurity, literature, and cognitive skills.

The results, that Table S4 (online only) presents, revealed a tendency towards the strongest effect

for DGBL interventions with literature content and the weakest effect for DGBL interventions that

promote cognitive skills. But the findings of the meta-regression model also promote no significant

differences between the domains (QM (6) = 10.55, p = .103).

Publication Year. The publication year was considered as a continuous moderator variable

and showed no significant influence (QM (1) = 0.61, p = .434).

Country of Data Collection. The countries of data collection were assigned to their

continents, among which no significant differences appeared (QM (4) = 0.20, p = .996).

Reporting Biases

For the overall learning outcomes, an examination of the studentized residuals showed that

no study had a value larger than 3.19, hence, there was no indication of outliers in the context of

Page 34 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 35

this model. According to Cook’s distances, two studies (2; 28) could be strongly influential. Fail

safe N was Nfs = 20,745. Because this number is higher than the rule of thumb (Nfs ˃ 5 * κ + 10;

Fragkos et al., 2014), the effect can be considered robust. A funnel plot of the estimates appears in

Figure S7. The regression test did not indicate any funnel plot asymmetry (z = 0.07, p = .947).

The selection model showed no significant change in the estimate due to a nonsignificant

likelihood ratio test (χ2 (1) = 0.40, p = .528), indicating no advantage of the adjusted model.

For cognitive learning outcomes, one study (23) may be a potential outlier. According to

Cook’s distances, two studies could have a very strong influence (2; 23). Fail safe N was Nfs =

22,796, which also indicates a robust effect. Figure S8 (online only) shows a funnel plot with the

estimates. The regression test revealed no funnel plot asymmetry (z = -0.28, p = .778). The selection

model indicated no advantage of an adjusted model because of a nonsignificant likelihood ratio test

(χ2 (1) = 3.70, p = .054).

For metacognitive learning outcomes, no study had a residual larger than 2.58, so no

study was regarded as an outlier. Furthermore, Cook’s distances showed no highly influential

studies. Fail safe N (Nfs = 49) suggested a robust effect. A funnel plot of the estimates appears in

Figure S9 (online only), and there was no evidence of funnel plot asymmetry (z = 1.44, p = .151).

The selection model showed no significant change in the estimate due to a nonsignificant likelihood

ratio test (χ2 (1) = 0.04, p = .845), which indicates no advantage of the adjusted model.

For affective-motivational learning outcomes, Study 9 had residuals larger than 2.87 and

might be an outlier. Cook’s distances also showed that Study 9 could be overly influential. A robust

effect could be assumed based on Fail safe N (Nfs = 409). A funnel plot of the estimates is shown in

Figure S10 (online only). The regression test revealed a funnel plot asymmetry (z = 2.15, p = .032),

Page 35 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 36

that could be an indication of publication bias, but the selection model showed no significant

change in the estimate due to a nonsignificant likelihood ratio test (χ2 (1) = 0.07, p = .794).

In summary, no evidence of publication bias was revealed in the sample for all learning

outcomes.

Discussion

Summary and interpretation of findings

The aim of the current meta-analysis was to examine the impacts DGBL interventions have

in the school context, compared to traditional instruction methods. Furthermore, we analyzed

whether different personal, environmental, or confounding factors influence the effectiveness of

DGBL interventions. Based on the Integrated Design Framework of Playful Learning (Plass et al.,

2015), cognitive and affective-motivational learning outcomes were included in the analyses and

extended by considering metacognitive learning outcomes. With this approach, the current meta-

analysis contributes to the replication of prior meta-analyses on the one hand and, on the other hand,

extends the knowledge about DGBL interventions in the school context. The examination of

metacognitive learning outcomes as well as avatars and digital agents as moderators were, to the

knowledge of the authors, not considered in meta-analyses before. Unlike prior meta-analyses, the

current meta-analysis focuses on pupils as a more specific target group which makes the results

easier to generalize for the school context. The examination of DGBL interventions only in the last

five years considers the rapid technologic development and enables a better comparability of the

interventions used. Furthermore, the current meta-analysis contributes to theory-based research by

deducing the examined learning outcomes on basis of the underlying theoretical model which

increases the external validity of the current findings. Moreover, the aggregation of different study

results leads to a higher validity which makes a meta-analytic approach superior to a single study.

Page 36 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 37

For overall learning, a medium effect for DGBL interventions was revealed, confirming the

assumption that DGBL interventions lead to improved learning compared to traditional instruction

methods (H 1.1). This result is in accordance with previous meta-analytic evidence (e.g., Clark et

al., 2016; Wouters et al., 2013), which suggests an advantage of DGBL interventions over

traditional instruction methods. Hypothesis 1.2, the assumption that DGBL interventions improve

cognitive learning outcomes more than traditional instruction methods, was also confirmed. A

medium effect on learning was found for cognitive learning outcomes, accounting for the majority

of studies. This result is in line with Lamb and colleagues (2018), who also found a medium effect

of DGBL interventions on cognitive outcomes (d = .67). The assumption that DGBL interventions

lead to higher metacognitive learning outcomes (H 1.3) could not be confirmed. It remains unclear

whether DGBL interventions have an impact on metacognitive learning outcomes, because there

was insufficient test power, due to a lack of studies (n = 5) that assessed this type of outcome. For

affective-motivational learning outcomes (H 1.4), a small effect of DGBL interventions was

detected, surprising because games are often described as motivating (Ryan & Rigby, 2020) and

could lead to flow experiences (Chang et al., 2017). A reason for this small effect on affective-

motivational learning outcomes could be the broad variability of DGBL interventions with different

game designs. To be motivating, games must be designed thoughtfully (Lee & Hammer, 2011), and

the game designers must ensure that the learning content is well integrated and does not

overshadow the engaging game mechanics (De Freitas et al., 2018). In our sample, it could be

possible that the balance between gameplay and learning was not achieved in every DGBL

intervention, which could have impacted the effect on affective-motivational learning.

The results concerning these hypotheses regarding learning outcomes reinforce the

effectiveness of DGBL interventions, based on the Integrated Design Framework for Playful

Page 37 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 38

Learning (Plass et al., 2015), and highlight the cognitive and affective-motivational engagement the

model assumes.

In addition to examining of the hypotheses regarding learning outcomes, the influence of

personal, environmental, and confounding moderators was analyzed by using meta-regression

models. Hypothesis 2.1 assumed no age differences for the impact of DGBL interventions and was

confirmed. In the current meta-analysis, participants’ age was not influential regarding the

effectiveness of DGBL interventions. Hypothesis 2.2., the influence of gender in DGBL

interventions, could not be tested because of the balanced distribution of male and female

participants in the included studies.

The number of sessions showed an advantage of multiple sessions on a descriptive level in

the current study, but unlike the studies of Wouters et al. (2013) and Clark et al. (2016), no

significant difference between the different numbers of sessions was found. The current findings

suggest that the number of sessions for DGBL interventions does not have an influence on their

effectiveness. Thus, Hypothesis 2.3, the assumption that DGBL interventions with multiple sessions

lead to greater learning gains, could not be confirmed. Moreover, using competitive or

noncompetitive environments made no difference regarding the effectiveness of DGBL

interventions. Therefore, the assumption that competitive DGBL interventions lead to greater

learning gains (H 2.4) was rejected. Competitive games did not lead to greater learning gains than

noncompetitive games in the current meta-analysis which is surprising, because Abdul Jabbar and

Felicia (2015) identified competition in games in their systematic review ‘as a gameplay element

that could emotionally and cognitively engage players and could have a significant impact on

learning’ (p. 762). Lamb et al. (2018) found a significantly stronger effect for three-dimensional

over two-dimensional DGBL interventions, which the current data could not replicate because no

Page 38 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 39

significant differences between the dimensions were found (H2.5). Based on the current findings,

the dimensionality of a game which is used as DGBL intervention seems to make no difference in

the effectiveness of DGBL interventions. The same applies to visual realism, narrative, avatars, and

digital agents, for which no moderating effect could be detected (H2.6–H 2.9). A trend exists on the

descriptive level that DGBL interventions with a narrative, avatars and digital agents outperform

DGBL interventions without these features, but with no significant evidence.

For the exploratory research questions, no significant influence of additional non-game

instruction, game type, playing mode, and learning domain appeared. Furthermore, the year of

publication and the country of data collection had no confounding impact on the results.

The unexpected results for the hypotheses and research questions could have been caused by

the sample’s very high heterogeneity. The DGBL interventions may differ too much from each

other, exacerbating the analyses and not leading to meaningful results. Furthermore, some analyzed

subgroups were very small, which could have also prevented detecting significant differences.

Because the basis for the current analyses was published literature, we examined their

robustness and the influence of publication bias. Fail Safe N strengthened the assumption that the

results were robust, and we checked publication bias visually with funnel plots, testing their

symmetry with Egger’s regression test and finding no evidence for asymmetry, except for affective-

motivational learning outcomes. Since these methods do not very accurately detect and correct for

publication bias (Hedges & Vevea, 1996), selection models were used additionally. Hence, the

selection models did not significantly better fit to the data, leading to the conclusion that the current

data showed no publication bias.

Limitations

Page 39 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 40

Although the present meta-analysis could partially extend the findings of prior meta-

analyses, several limitations must be considered when interpreting the results. Regarding the

literature research, Google Scholar only shows the first 1,000 hits for each search term, which did

not allow an in-depth literature search. Furthermore, the different databases had varying options to

refine the search process, which could have caused a failure to find all relevant studies, always a

possibility when working with data based on a literature search. To minimize the probability of

missing important studies, a broad literature search in different data bases should occur.

Furthermore, since the authors can only read papers in English and German, a language bias in the

data is possible. Inability to include studies in other languages in the synthesis could confound the

results.

Concerning the coding procedure, determining visual realism was based on the graphics in

the papers provided. Depending on the number of photos, deciding to which category of visual

realism the game belongs was not easy for the raters. One cannot rule out the possibility that games

were miscategorized due to a lack of pictures, which would also affect the meta-regression results.

The decision to use the mean of dependent effect sizes for each study could have led to loss

of information in the dataset. However, a multivariate meta-analysis, sometimes suggested as an

alternative procedure, has high costs (e.g., complicated procedure, high dataset requirements) and

its use is controversial. In our opinion, its benefits (e.g., less loss of information) did not balance the

costs, the reason we chose to use the dependent effect sizes’ mean.

Another limitation is the small number of studies assessing metacognitive learning

outcomes—only five studies in the current meta-analysis to analyze the effect of DGBL

interventions on those outcomes. Therefore, the results should be interpreted with caution, and the

Page 40 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 41

impact of DGBL interventions on metacognitive learning outcomes remains a desideratum on

which prospective studies should focus.

Regarding the moderator analyses, one limiting factor is the unequal distribution of studies

in the analyzed categories. For example, only one study with a mixed playing mode was compared

to 29 single-player games and only 4 multiplayer games. Furthermore, the primary studies did not

provide some information on the moderators, leading to a smaller sample that made the analyses

and the detection of moderator effects more unlikely. Moreover, the considered moderator ‘number

of sessions’ has limited informative value because the number of sessions does not reveal the

duration of the intervention (e.g., five sessions could have occurred in one week or in three weeks).

Future studies should consider the exact duration as a more accurate variable than the number of

sessions. Also, the year of publication is not a very precise variable. If the paper does not mention

it, we do not know when the data was collected. A study published in 2015 could potentially use

data from 2010, which could also influence the results.

Implications and future directions

Despite these limitations, the current study strengthens the assumption that DGBL

interventions are also effective for pupils’ learning, especially for cognitive and affective-

motivational outcomes.

As a practical implication, the findings confirm that DGBL in school provides another tool

for teachers to use in class, to offer variation in learning methods for their pupils. Based on the

current findings, well-designed DGBL interventions could motivate pupils to engage with learning

materials and, therefore, promote their learning process. This could be especially beneficial for

pupils who are bored in traditional learning settings or pupils who have the need either to work

more autonomous or to collaborate with other pupils. Due to the high heterogeneity in the

Page 41 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 42

classroom, teachers cannot always satisfy all their pupils’ needs. DGBL interventions in the

classroom can be designed to adapt to their users’ needs by, for example, offering exercises with an

adequate difficulty for the user. This could contribute to a learner-centered pedagogy, which

focusses on learners’ needs and enables them to learn at their own pace and to avoid excessive

demands and resignation. In fact, DGBL interventions offer a safe learning environment, which

allows ‘graceful failure' (Plass et al., 2015, p. 261) that promotes experiences of success (mastery

experiences) and could lead to an increased self-efficacy. Cognitive outcomes seem especially

suitable for DGBL interventions, making them an adequate tool for teachers to convey knowledge

to their pupils. Furthermore, DGBL could also occur during distance learning and, therefore, be a

learning solution for pupils who cannot attend school in person, e.g., because of quarantine. Indeed,

pupils need access to digital devices or computers, requiring well-equipped school and home

environments. However, there are still schools which lack the equipment for DGBL interventions.

To improve the possibilities to offer DGBL interventions in the classroom or at home, it should be

the governance’s responsibility to invest in education and, therefore, provide financial support for

schools and families.

Another important factor for the successful implementation of DGBL interventions in school

is teachers’ technology literacy (Marklund & Alklind Taylor, 2016). Studies reveal that teachers are

interested in using DGBL interventions but are often worried whether they have enough knowledge

and gaming literacy to implement DBGL interventions in the classroom (Jong, 2016). This shows

the need to foster the knowledge and self-efficacy to use digital games by integrating the use of

different digital media, including digital games, into the teacher education curriculum.

An implication for research is the revealed lack of studies that analyze metacognitive

learning outcomes, calling for more studies that target those outcomes. Another topic for

Page 42 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 43

prospective research is that to be motivating, future DGBL interventions need well-integrated

learning content balanced with intrinsic or extrinsic game elements. Game designers must consider

individually which game elements suit the intervention’s learning goals. A general recommendation

for fitting a DGBL intervention to all pupils is not possible because pupils have individual needs

and preferences during learning. Therefore, adaptive games that align with pupils’ needs during the

learning process could be a solution. But the development of DGBL interventions in general, and

especially adaptive games, is time-consuming and costly. If it fits the learning goal, researchers

could make use of publicly available games whenever possible. The question of which game-design

elements cause the positive effects of DGBL is still unclear, and future studies should examine it.

Future DGBL intervention studies should focus on specific game-design elements separately and

compare different game versions.

The impact of DGBL interventions on teacher education would also be interesting to study

in future DGBL intervention research because teachers would gain experience with digital games

and could act as models for their prospective students (Peeters et al., 2014). Also involving the

teachers in acting as a multiplicator could promote the learning with digital games on two different

levels. This means that pupils could acquire knowledge by playing digital games and learn by

observing and adopting teachers’ behavior.

Furthermore, the results of the current meta-analysis cannot be transferred to all DGBL

interventions in general. They include only games without embodiment, augmented or virtual

reality. Due to the different quality of immersion (Skarbez et al., 2021), they are not comparable to

games that do not use these methods. Therefore, future studies considering DGBL interventions

with embodiment, augmented or virtual reality would be interesting. Given that the current meta-

analysis did not find any moderating effects, a deeper examination of mentioned and additional

Page 43 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 44

moderators (e.g., intervention duration, device type) could also provide new insights into DGBL

interventions’ effectiveness.

Page 44 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 45

References

Studies which were used in the analysis are marked with *

Abdul Jabbar, A. I., & Felicia, P. (2015). Gameplay Engagement and Learning in Game-Based

Learning: A Systematic Review. Review of Educational Research, 85(4), 740–779.

https://doi.org/10.3102/00346543155772

Ada, M., Akdeniz, M. F., Gümgüm, Ö., Keskin, M., Yazıcı, A., & Yayan, U. (2016, May).

Interactive Serious Games With Visual Programming for Mobile Robot Learning. In 2016 24th

Signal Processing and Communication Application Conference (SIU) (pp. 485–488). IEEE.

https://doi.org/10.1109/SIU.2016.7495783

Admiraal, W., Huizenga, J., Akkerman, S., & Ten Dam, G. (2011). The Concept of Flow in

Collaborative Game-Based Learning. Computers in Human Behavior, 27(3), 1185–1194.

https://doi.org/10.1016/j.chb.2010.12.013

Ak, O., & Kutlu, B. (2017). Effect of Game Environments on Students’ Learning. British Journal

of Educational Technology, 48, 129–144. https://doi.org/10.1111/bjet.12346

Al-Azawi, R., Al-Faliti, F., & Al-Blushi, M. (2016). Educational Gamification vs. Game Based

Learning: Comparative Study. International Journal of Innovation, Management and

Technology, 7(4), 131–136. https://doi.org/10.18178/ijimt.2016.7.4.659

All, A., Plovie, B., Castellar, E. P. N., & Van Looy, J. (2017). Pre-Test Influences on the

Effectiveness of Digital-Game Based Learning: A Case Study of a Fire Safety

Game. Computers & Education, 114, 24–37. https://doi.org/10.1016/j.compedu.2017.05.018

Page 45 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 46

Allen, K. N., & Friedman, B. D. (2010). Affective Learning: A Taxonomy for Teaching Social

Work Values. Journal of Social Work Values and Ethics, 7(2), 1–12.

Bandura, A. (1989). Human Agency in Social Cognitive Theory. American Psychologist, 44(9),

1175–1184. https://doi.org/10.1037/0003-066X.44.9.1175

Bandura, A. (1997). Self-Efficacy: The Exercise of control. Freeman.

* Barros, C., Carvalho, A. A., & Salgueiro, A. (2020). The Effect of the Serious Game Tempoly on

Learning Arithmetic Polynomial Operations. Education and Information Technologies, 25(3),

1497–1509. https://doi.org/10.1007/s10639-019-09990-4

Bowers, C. A., Serge, S., Blair, L., Cannon-Bowers, J., Joyce, R., & Boshnack, J. (2013). The

Effectiveness of Narrative Pre-Experiences for Creating Context in Military Training.

Simulation & Gaming, 44(4), 514–522. https://doi.org/10.1177/1046878113475341

* Brezovszky, B., McMullen, J., Veermans, K., Hannula-Sormunen, M. M., Rodríguez-Aflecht, G.,

Pongsakdi, N., Laakkonen, E., & Lehtinen, E. (2019). Effects of a Mathematics Game-Based

Learning Environment on Primary School Students’ Adaptive Number Knowledge. Computers

& Education, 128, 63–74. https://doi.org/10.1016/j.compedu.2018.09.011

Cagiltay, N. E., Ozcelik, E., & Ozcelik, N. S. (2015). The Effect of Competition on Learning in

Games. Computers & Education, 87, 35–41. https://doi.org/10.1016/j.compedu.2015.04.001

* Cayvaz, A., Akcay, H., & Kapici, H. O. (2020). Comparison of Simulation-Based and Textbook-

Based Instructions on Middle School Students’ Achievement, Inquiry Skills and Attitudes.

International Journal of Education in Mathematics, Science and Technology, 8(1), 34–43.

https://doi.org/10.46328/ijemst.v8i1.758

Page 46 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 47

* Cejudo, J., López-Delgado, M. L., & Losada, L. (2019). Effectiveness of the Videogame “Spock”

for the Improvement of the Emotional Intelligence on Psychosocial Adjustment in Adolescents.

Computers in Human Behavior, 101, 380–386. https://doi.org/10.1016/j.chb.2018.09.028

Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed Practice in

Verbal Recall Tasks: A Review and Quantitative Synthesis. Psychological Bulletin, 132(3), 354–

380. https://doi.org/10.1037/0033-2909.132.3.354

Chang, C.-C., Liang, C., Chou, P.-N., & Lin, G.-Y. (2017). Is Game-Based Learning Better in Flow

Experience and Various Types of Cognitive Load Than Non-Game-Based Learning? Perspective

From Multimedia and Media Richness. Computers in Human Behavior, 71, 218–227.

https://doi.org/10.1016/j.chb.2017.01.031

* Chen, C.-C., & Huang, P.-H. (2020). The Effects of STEAM-Based Mobile Learning on Learning

Achievement and Cognitive Load. Interactive Learning Environments, 1–17.

https://doi.org/10.1080/10494820.2020.1761838

Chen, C.-H. (2019). The Impacts of Peer Competition-Based Science Gameplay on Conceptual

Knowledge, Intrinsic Motivation, and Learning Behavioral Patterns. Educational Technology

Research and Development, 67(1), 179–198. https://doi.org/10.1007/s11423-018-9635-5

Chen, C.-H., & Chiu, C.-H. (2016). Employing Intergroup Competition in Multitouch Design-

Based Learning to Foster Student Engagement, Learning Achievement, and Creativity.

Computers & Education, 103, 99–113. https://doi.org/10.1016/j.compedu.2016.09.007

Page 47 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 48

Chen, C.-H., Shih, C.-C., & Law, V. (2020). The Effects of Competition in Digital Game-Based

Learning (DGBL): A Meta-Analysis. Educational Technology Research and Development,

68(4), 1855–1873. https://doi.org/10.1007/s11423-020-09794-1

* Chen, C.-Y., Huang, H.-J., Lien, C.-J., & Lu, Y.-L. (2020). Effects of Multi-Genre Digital Game-

Based Instruction on Students’ Conceptual Understanding, Argumentation Skills, and Learning

Experiences. IEEE Access, 8, 110643–110655. https://doi.org/10.1109/ACCESS.2020.3000659

Chen, G.-D., Lee, J.-H., Wang, C.-Y., Chao, P.-Y., Li, L.-Y., & Lee, Y. (2012). An Empathic

Avatar in a Computer-Aided Learning Program to Encourage and Persuade Learners. Journal of

Educational Technology & Society, 15(2), 62–72.

* Chen, H.-R., Liao, K.-C., & Chang, J.-J. (2015). Design of Digital Game-Based Learning System

for Elementary Mathematics Problem Solving. 2015 8th International Conference on Ubi-Media

Computing (UMEDIA), 303–307. https://doi.org/10.1109/UMEDIA.2015.7297475

Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016). Digital Games, Design, and

Learning: A Systematic Review and Meta-Analysis. Review of Educational Research, 86(1), 79–

122. https://doi.org/10.3102/0034654315582065

Cochran, W. G. (1954). The Combination of Estimates From Different Experiments. Biometrics,

10(1), 101–129. https://doi.org/10.2307/3001666

Cohen, E. L. (2016). Enjoyment of a Counter-Hedonic Serious Digital Game: Determinants and

Effects on Learning and Self-Efficacy. Psychology of Popular Media Culture, 5(2), 157–170.

http://dx.doi.org/10.1037/ppm0000052

Page 48 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 49

Cohen, J. (1960). A Coefficient of Agreement for Nominal Scales. Educational and Psychological

Measurement, 20(1), 37–46. https://doi.org/10.1177/001316446002000104

Cohen, J. (1988). Statistical Power Analysis for the Behavioural Sciences (2. Ed.). Erlbaum

Associates.

Cohen, J. (2001). Defining Identification: A Theoretical Look at the Identification of Audiences

With Media Characters. Mass Communication & Society, 4(3), 245–264.

https://doi.org/10.1207/S15327825MCS0403_01

Cojocariu, V.-M., & Boghian, I. (2014). Teaching the Relevance of Game-Based Learning to

Preschool and Primary Teachers. Procedia - Social and Behavioral Sciences, 142, 640–646.

https://doi.org/10.1016/j.sbspro.2014.07.679

Connolly, T. M., & Stansfield, M. (2009). From e-learning to games-based e-learning. In

Encyclopedia of Information Communication Technology (pp. 268–275). IGI Global.

https://doi.org/10.4018/978-1-59904-845-1.ch035

Coombes, L., Chan, G., Allen, D., & Foxcroft, D. R. (2016). Mixed‐Methods Evaluation of the

Good Behaviour Game in English Primary Schools. Journal of community & applied social

psychology, 26(5), 369-387. https://doi.org/10.1002/casp.2268

De Freitas, V., Mohan, P., & Kinshuk, (2018). A Game Designers’ Guide for Creating Learning

Games for Mathematics. 2018 IEEE 18th International Conference on Advanced Learning

Technologies (ICALT), 146–148. https://doi.org/10.1109/ICALT.2018.00144

Dickey, M. D. (2020). Narrative in Game-Based Learning. Plass, J. L., Mayer, R. E. & Homer, B.

D. (Eds..), Handbook of Game-Based Learning, (pp. 283–306). MIT Press.

Page 49 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 50

Domagk, S., Schwartz, R. N., & Plass, J. L. (2010). Interactivity in Multimedia Learning: An

Integrated Model. Computers in Human Behavior, 26(5), 1024–1033.

https://doi.org/10.1016/j.chb.2010.03.003

Döring, N., & Bortz, J. (2016). Forschungsmethoden und Evaluation in den Sozial- und

Humanwissenschaften. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41089-5

* Dorji, U., Panjaburee, P., & Srisawasdi, N. (2015). A Learning Cycle Approach to Developing

Educational Computer Game for Improving Students’ Learning and Awareness in Electric

Energy Consumption and Conservation. Educational Technology & Society, 18(1), 91–105.

Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in Meta-Analysis Detected by a

Simple, Graphical Test. BMJ, 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629

Erhel, S., & Jamet, E. (2013). Digital Game-Based Learning: Impact of Instructions and Feedback

on Motivation and Learning Effectiveness. Computers & Education, 67, 156–167.

https://doi.org/10.1016/j.compedu.2013.02.019

* Fendt, M. W., & Ames, E. (2019). Using Learning Games to Teach Texas Civil War History to

Public Middle School Students. IEEE Conference on Games (CoG), 1–4.

https://doi.org/10.1109/CIG.2019.8847968

Fien, H., Doabler, C. T., Nelson, N. J., Kosty, D. B., Clarke, B., & Baker, S. K. (2016). An

Examination of the Promise of the NumberShire Level 1 Gaming Intervention for Improving

Student Mathematics Outcomes. Journal of Research on Educational Effectiveness, 9(4), 635-

661. https://doi.org/10.1080/19345747.2015.1119229

Page 50 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 51

* Fiorella, L., Kuhlmann, S., & Vogel-Walcutt, J. J. (2019). Effects of Playing an Educational Math

Game That Incorporates Learning by Teaching. Journal of Educational Computing Research,

57(6), 1495–1512. https://doi.org/10.1177/0735633118797133

Fragkos, K. C., Tsagris, M., & Frangos, C. C. (2014). Publication Bias in Meta-Analysis:

Confidence Intervals for Rosenthal’s Fail-Safe Number. International Scholarly Research

Notices, 1–17. https://doi.org/10.1155/2014/825383

Franciosi, S. J. (2017). The Effect of Computer Game-Based Learning on FL Vocabulary

Transferability. Educational Technology & Society, 20 (1), 123–133.

* Freina, L., Bottino, R., & Ferlino, L. (2018). Visuospatial Abilities Training With Digital Games

in a Primary School. International Journal of Serious Games, 5(3), 23–35.

https://doi.org/10.17083/ijsg.v5i3.240

* Giannakas, F., Papasalouros, A., Kambourakis, G., & Gritzalis, S. (2019). A Comprehensive

Cybersecurity Learning Platform for Elementary Education. Information Security Journal: A

Global Perspective, 28(3), 81–106. https://doi.org/10.1080/19393555.2019.1657527

* Hannel, S. L., & Cuevas, J. (2018). A Study on Science Achievement and Motivation Using

Computer-Based Simulations Compared to Traditional Hands-on Manipulation. Georgia

Educational Researcher, 15(1), 38–55. https://doi.org/10.20429/ger.2018.15103

* Hawkins, R. D., Ferreira, G. A. M., & Williams, J. M., (2019). The Development and Evaluation

of ‘Farm Animal Welfare’: An Educational Computer Game for Children. Animals, 9(3), 1–17.

https://doi.org/10.3390/ani9030091

Page 51 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 52

Hedges, L. V., & Vevea, J. L. (1996). Estimating Effect Size Under Publication Bias: Small Sample

Properties and Robustness of a Random Effects Selection Model. Journal of Educational and

Behavioral Statistics, 21(4), 299–332. https://doi.org/10.3102/10769986021004299

Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying Heterogeneity in a Meta-Analysis.

Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186

* Hussein, M. H., Ow, S. H., Cheong, L. S., & Thong, M.-K. (2019). A Digital Game-Based

Learning Method to Improve Students’ Critical Thinking Skills in Elementary Science. IEEE

Access, 7, 96309–96318. https://doi.org/10.1109/ACCESS.2019.2929089

* Hwang, G.-J., Hsu, T.-C., Lai, C.-L., & Hsueh, C.-J. (2017). Interaction of Problem-Based

Gaming and Learning Anxiety in Language Students’ English Listening Performance and

Progressive Behavioral Patterns. Computers & Education, 106, 26–42.

https://doi.org/10.1016/j.compedu.2016.11.010

Jackson, L. C., O’Mara, J., Moss, J., & Jackson, A. C. (2018). A Critical Review of the

Effectiveness of Narrative-Driven Digital Educational Games. International Journal of Game-

Based Learning, 8(4), 32–49. https://doi.org/10.4018/IJGBL.2018100103

Johnson, W. L., & Lester, J. C. (2016). Face-to-Face Interaction with Pedagogical Agents, Twenty

Years Later. International Journal of Artificial Intelligence in Education, 26(1), 25–36.

https://doi.org/10.1007/s40593-015-0065-9

Jong, M. S. Y. (2016). Teachers’ concerns about adopting constructivist GBL. British Journal of

Educational Technology, 47: 601–617. https://doi.org/10.1111/bjet.12247

Page 52 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 53

* Kapici, H. O., Akcay, H., & de Jong, T. (2020). How do Different Laboratory Environments

Influence Students’ Attitudes Toward Science Courses and Laboratories? Journal of Research

on Technology in Education, 52(4), 534–549. https://doi.org/10.1080/15391523.2020.1750075

Karakoç, B., Eryılmaz, K., Turan Özpolat, E., & Yıldırım, İ. (2020). The Effect of Game-Based

Learning on Student Achievement: A Meta-Analysis Study. Technology, Knowledge and

Learning, 27(1), 207–222. https://doi.org/10.1007/s10758-020-09471-5

* Ke, F. (2019). Mathematical Problem Solving and Learning in an Architecture-Themed Epistemic

Game. Educational Technology Research and Development, 67(5), 1085–1104.

https://doi.org/10.1007/s11423-018-09643-2

* Khan, A., Ahmad, F. H., & Malik, M. M. (2017). Use of Digital Game Based Learning and

Gamification in Secondary School Science: The Effect on Student Engagement, Learning and

Gender Difference. Education and Information Technologies, 22(6), 2767–2804.

https://doi.org/10.1007/s10639-017-9622-1

* Kiili, K., Moeller, K., & Ninaus, M. (2018). Evaluating the Effectiveness of a Game-Based

Rational Number Training - In-Game Metrics as Learning Indicators. Computers & Education,

120, 13–28. https://doi.org/10.1016/j.compedu.2018.01.012

Kinzer, C. K., Hoffman, D. L., Turkay, S., Gunbas, N., Chantes, P., Dvorkin, T., & Chaiwinij, A.

(2012). The Impact of Choice and Feedback on Learning, Motivation, and Performance in an

Educational Video Game. Proceedings of the Games, Learning, and Society Conference, 2, 175–

181.

Page 53 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 54

Klimmt, C., Hefner, D., Vorderer, P., Roth, C., & Blake, C. (2010). Identification With Video

Game Characters as Automatic Shift of Self-Perceptions. Media Psychology, 13(4), 323–338.

https://doi.org/10.1080/15213269.2010.524911

Kuhn, D., & Pease, M. (2006). Do Children and Adults Learn Differently? Journal of Cognition

and Development, 7(3), 279–293. https://doi.org/10.1207/s15327647jcd0703_1

Lai, A. F., Chen, C. H., & Lee, G. Y. (2019). An Augmented Reality‐Based Learning Approach to

Enhancing Students’ Science Reading Performances From The Perspective of the Cognitive

Load Theory. British Journal of Educational Technology, 50(1), 232–247.

https://doi.org/10.1111/bjet.12716

* Lamb, R. L. (2016). Examination of the Effects of Dimensionality on Cognitive Processing in

Science: A Computational Modeling Experiment Comparing Online Laboratory Simulations and

Serious Educational Games. Journal of Science Education and Technology, 25(1), 1–15.

https://doi.org/10.1007/s10956-015-9587-z

Lamb, R. L., Annetta, L., Firestone, J., & Etopio, E. (2018). A Meta-Analysis With Examination of

Moderators of Student Cognition, Affect, and Learning Outcomes While Using Serious

Educational Games, Serious Games, and Simulations. Computers in Human Behavior, 80, 158–

167. https://doi.org/10.1016/j.chb.2017.10.040

Landis, J. R., & Koch, G. G. (1977). The Measurement of Observer Agreement for Categorical

Data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310

Page 54 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 55

* Lee, H. K., & Choi, A. (2020). Enhancing Early Numeracy Skills With a Tablet-Based Math

Game Intervention: A Study in Tanzania. Educational Technology Research and Development,

68(6), 3567–3585. https://doi.org/10.1007/s11423-020-09808-y

Lee, J. J., & Hammer, J. (2011). Gamification in Education: What, How, Why Bother? Academic

Exchange Quarterly, 15(2), 146.

Lester, J. C., Spain, R. D., Rowe, J. P., & Mott, B. W. (2020). Instructional Support, Feedback, and

Coaching in Game-based Learning. In J. L. Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook

of Game-based Learning (pp. 209–238). MIT Press.

Lester, J. C., Spires, H. A., Nietfeld, J. L., Minogue, J., Mott, B. W., & Lobene, E. V. (2014).

Designing Game-Based Learning Environments for Elementary Science Education: A Narrative-

Centered Learning Perspective. Information Sciences, 264, 4–18.

https://doi.org/10.1016/j.ins.2013.09.005

Liew, T. W., & Tan, S.-M. (2016). Virtual Agents With Personality: Adaptation of Learner-Agent

Personality in a Virtual Learning Environment. Eleventh International Conference on Digital

Information Management (ICDIM), 157–162. https://doi.org/10.1109/ICDIM.2016.7829758

Loderer, K., Pekrun, R., & Plass, J. L. (2020). Emotional Foundations of Game-Based Learning. In

J. L. Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook of Game-based learning (pp. 111–

152). MIT Press.

López-Fernández, D., Gordillo, A., Alarcón, P. P., & Tovar, E. (2021). Comparing Traditional

Teaching and Game-Based Learning Using Teacher-Authored Games on Computer Science

Page 55 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 56

Education. IEEE Transactions on Education, 64(4), 367–373.

https://doi.org/10.1109/TE.2021.3057849

Malliarakis, C., Tomos, F., Shabalina, O., & Mozelius, P. (2018). Andragogy and E.M.O.T.I.O.N: 7

Key Factors of Successful Serious Games. In M. Ciussi (Ed.), Proceedings of the 12th European

Conference on Games Based Learning (pp. 371–378). ACI.

Marklund, B. B., & Alklind Taylor, A. S. (2016). Educational Games in Practice: The Challenges

Involved in Conducting a Game-Based Curriculum. The Electronic Journal of E-Learning, 14(2),

122–135.

Martha, A. S. D., & Santoso, H. B. (2019). The Design and Impact of the Pedagogical Agent: A

Systematic Literature Review. Journal of Educators Online, 16(1).

https://doi.org/10.9743/jeo.2019.16.1.8

Mayer, R. E. (2014). Computer Games for Learning: An Evidence-Based Approach. Teachers

College Record (pp. 1–3). MIT Press.

Mayer, R. E. (2020). Cognitive Foundations of Game-Based Learning. In J. L. Plass, R. E. Mayer

& B. D. Homer (Eds.), Handbook of Game-Based Learning (pp. 83–110). MIT Press.

McLaren, B. M., Adams, D. M., Mayer, R. E., & Forlizzi, J. (2017). A Computer-Based Game That

Promotes Mathematics Learning More Than a Conventional Approach. International Journal of

Game-Based Learning, 7(1), 36–56. https://doi.org/10.4018/IJGBL.2017010103

Nelson, B., & Kim, Y. (2020). Multimedia Design Principles in Game-Based Learning. In J. L.

Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook of Game-Based Learning (pp. 307–328).

MIT Press.

Page 56 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 57

Novak, E. (2015). A Critical Review of Digital Storyline-Enhanced Learning. Educational

Technology Research and Development, 63(3), 431–453. https://doi.org/10.1007/s11423-015-

9372-y

Nussbaum, E. M., Owens, M. C., Sinatra, G. M., Rehmat, A. P., Cordova, J. R., Ahmad, S., Harris

Jr., F. C., & Dascalu, S. M. (2015). Losing the Lake: Simulations to Promote Gains in Student

Knowledge and Interest About Climate Change. International Journal of Environmental and

Science Education, 10(6), 789–811.

* O’Rourke, J., Main, S., & Hill, S. M., (2017). Commercially Available Digital Game Technology

in the Classroom: Improving Automaticity in Mental-Maths in Primary-Aged Students.

Australian Journal of Teacher Education, 42(10), 50–70.

https://doi.org/10.14221/ajte.2017v42n10.4

Partovi, T., & Razavi, M. R. (2019). The Effect of Game-Based Learning on Academic

Achievement Motivation of Elementary School Students. Learning and Motivation, 68: 101592.

https://doi.org/10.1016/j.lmot.2019.101592

Pawar, S., Tam, F., & Plass, J. L. (2020). Emerging Design Factors of Game-Based Learning:

Emotional Design, Musical Score, and Game Mechanics Design. In J. L. Plass, R. E. Mayer &

B. D. Homer (Eds.), Handbook of Game-Based Learning (pp. 347–367). MIT Press.

Peeters, J., De Backer, F., Reina, V. R., Kindekens, A., Buffel, T., & Lombaerts, K. (2014). The

Role of Teachers’ Self-Regulatory Capacities in the Implementation of Self-Regulated Learning

Practices. Procedia - Social and Behavioral Sciences, 116, 1963–1970.

https://doi.org/10.1016/j.sbspro.2014.01.504

Page 57 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 58

Pekrun, R. (2006). The Control-Value Theory of Achievement Emotions: Assumptions,

Corollaries, and Implications for Educational Research and Practice. Educational Psychology

Review, 18(4), 315–341. https://doi.org/10.1007/s10648-006-9029-9

Pellas, N., & Vosinakis, S. (2018). The Effect of Simulation Games on Learning Computer

Programming: A Comparative Study on High School Students’ Learning Performance by

Assessing Computational Problem-Solving Strategies. Education and Information

Technologies, 23(6), 2423–2452. https://doi.org/10.1007/s10639-018-9724-4

Plass, J. L., Homer, B. D., Kinzer, C., Frye, J., & Perlin, K. (2011). Learning Mechanics and

Assessment Mechanics for Games for Learning. White Paper, 1, 1–19.

https://doi.org/10.13140/2.1.3127.1201

Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of Game-Based Learning.

Educational Psychologist, 50(4), 258–283. https://doi.org/10.1080/00461520.2015.1122533

Plass, J. L., Home r, B. D., Mayer, R. E., & Kinzer, C. K. (2020). Theoretical Foundations of

Game-Based and Playful Learning. In J. L. Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook

of Game-Based Learning (pp. 3–24). MIT Press.

Plass, J. L., & Pawar, S. (2020). Adaptivity and Personalization in Game-Based Learning. In J. L.

Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook of Game-Based Learning (pp. 263–282).

MIT Press.

Post, L. S., Guo, P., Saab, N., & Admiraal, W. (2019). Effects of Remote Labs on Cognitive,

Behavioral, and Affective Learning Outcomes in Higher Education. Computers & Education,

140, 1–9. https://doi.org/10.1016/j.compedu.2019.103596

Page 58 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 59

Prensky, M., & Prensky, M. (2007). Digital Game-Based Learning. Paragon House, 1.

R Core Team. (2020). A Language and Environment for Statistical Computing. R Foundation for

Statistical Computing. https://www.R-project.org/

* Ramos, D. K., & Melo, H. M. (2019). Can Digital Games in School Improve Attention? A Study

of Brazilian Elementary School Students. Journal of Computers in Education, 6(1), 5–19.

https://doi.org/10.1007/s40692-018-0111-3

* Ratamun, M. M., & Osman, K. (2018). The Effectiveness of Virtual lab Compared to Physical lab

in the Mastery of Science Process Skills for Chemistry Experiment. Problems of Education in

the 21st Century, 76(4), 544–560. https://doi.org/10.33225/pec/18.76.544

Rigby, S., & Ryan, R. M. (2011). Glued to Games: How Video Games Draw us in and Hold us

Spellbound. Praeger, 510-511.

Riley, R. D., Higgins, J. P. T., & Deeks, J. J. (2011). Interpretation of Random Effects Meta-

Analyses. BMJ, 342, 964–967. https://doi.org/10.1136/bmj.d549

Rosenthal, R. (1979). The „File Drawer Problem“ and Tolerance for Null Results. Psychological

Bulletin, 86(3), 638–641. https://doi.org/10.1037/0033-2909.86.3.638

Rowe, J. P., Shores, L. R., Mott, B. W., & Lester, J. C. (2011). Integrating Learning, Problem

Solving, and Engagement in Narrative-Centered Learning Environments. International Journal

of Artificial Intelligence in Education, 21(1-2), 115–133.

Ryan, R. M., & Deci, E. L. (2000). Self-Determination Theory and the Facilitation of Intrinsic

Motivation, Social Development, and Well-Being. American Psychologist, 55(1), 68–78.

https://doi.org/10.1037/0003-066X.55.1.68

Page 59 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 60

Ryan, R. M., & Rigby, C. S. (2020). Motivational Foundations of Game-Based Learning. In J. L.

Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook of Game-Based Learning (pp. 153–176).

MIT Press.

* Sadler, T. D., Romine, W. L., Menon, D., Ferdig, R. E., & Annetta, L. (2015). Learning Biology

Through Innovative Curricula: A Comparison of Game- and Nongame-Based Approaches.

Science Education, 99(4), 696–720. https://doi.org/10.1002/sce.21171

Sala, G., & Gobet, F. (2017). Does Chess Instruction Improve Mathematical Problem-Solving

Ability? Two Experimental Studies With an Active Control Group. Learning & behavior, 45(4),

414–421. https://doi.org/10.3758/s13420-017-0280-3

* Shum, A. K., Lai, E. S., Leung, W. G., Cheng, M. N., Wong, H. K., So, S. W., Law, Y. W., &

Yip, P. S. (2019). A Digital Game and School-Based Intervention for Students in Hong Kong:

Quasi-Experimental Design. Journal of Medical Internet Research, 21(4), 1–13.

* Siew, N. M., Geofrey, J., & Lee, B. N. (2016). Students’ Algebraic Thinking and Attitudes

Towards Algebra: The Effects of Game-Based Learning Using Dragonbox 12+ App. The

Research Journal of Mathematics and Technology, 5(1), 66–79.

Sitzmann, T. (2011). A Meta-Analytic Examination of the Instructional Effectiveness of Computer-

Based Simulation Games. Personnel Psychology, 64(2), 489–528.

https://doi.org/10.1111/j.1744-6570.2011.01190.x

Skarbez, R., Smith, M., & Whitton, M. C. (2021). Revisiting Milgram and Kishino’s Reality-

Virtuality Continuum. Frontiers in Virtual Reality, 2, 1–8.

https://doi.org/10.3389/frvir.2021.647997

Page 60 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 61

* Srisawasdi, N., & Panjaburee, P. (2019). Implementation of Game-Transformed Inquiry-Based

Learning to Promote the Understanding of and Motivation to Learn Chemistry. Journal of

Science Education and Technology, 28(2), 152–164. https://doi.org/10.1007/s10956-018-9754-0

* Stapinski, L. A., Reda, B., Newton, N. C., Lawler, S., Rodriguez, D., Chapman, C., & Teesson,

M. (2018). Development and Evaluation of ‘Pure Rush’: An Online Serious Game for Drug

Education. Drug and Alcohol Review, 37(1), 420–428. https://doi.org/10.1111/dar.12611

Steinkuehler, C., & Tsaasan, A. M. (2020). Sociocultural Foundations of Game-Based Learning. In

J. L. Plass, R. E. Mayer, & B. D. Homer (Hrsg.), Handbook of Game-Based Learning (pp. 177–

208). MIT Press.

Sweller, J. (2011). Cognitive Load Theory. In J. P. Mestre & B. H. Ross (Eds.), Psychology of

Learning and Motivation (Vol. 55, pp. 37–76). Academic Press. https://doi.org/10.1016/B978-0-

12-387691-1.00002-8

Tam, F., & Pawar, S. (2020). Emerging Design Factors in Game-Based Learning: Incentives, Social

Presence, and Identity Design. In J. L. Plass, R. E. Mayer & B. D. Homer (Eds.), Handbook of

Game-Based Learning (pp. 367–386). MIT Press.

* Tan, J. L., Goh, D. H.-L., Ang, R. P., & Huan, V. S. (2016). Learning Efficacy and User

Acceptance of a Game-Based Social Skills Learning Environment. International Journal of

Child-Computer Interaction, 9, 1–19. https://doi.org/10.1016/j.ijcci.2016.09.001

Tangsripairoj, S., Sukkhet, M., Sumanotham, J., & Yusuk, B. (2019, July). Kiddy Manner: A

Game-Based Mobile Application for Children Learning Thai Social Etiquette. In 2019 16th

Page 61 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 62

International Joint Conference on Computer Science and Software Engineering (JCSSE) (pp.

109–114). IEEE. https://doi.org/10.1109/JCSSE.2019.8864177

* Tao, S.-Y., Huang, Y.-H., & Tsai, M.-J. (2016). Applying the Flipped Classroom With Game-

Based Learning in Elementary School Students’ English Learning. International Conference on

Educational Innovation through Technology (EITT), 59–63.

https://doi.org/10.1109/EITT.2016.19

Theng, Y.-L., & Aung, P. (2012). Investigating Effects of Avatars on Primary School Children’s

Affective Responses to Learning. Journal on Multimodal User Interfaces, 5(1), 45–52.

https://doi.org/10.1007/s12193-011-0078-0

* Tsai, C.-Y., Lin, H.-S., & Liu, S.-C. (2020). The Effect of Pedagogical GAME Model on

Students’ PISA Scientific Competencies. Journal of Computer Assisted Learning, 36(3), 359–

369. https://doi.org/10.1111/jcal.12406

van der Meij, H., van der Meij, J., & Harmsen, R. (2015). Animated Pedagogical Agents Effects on

Enhancing Student Motivation and Learning in a Science Inquiry Learning Environment.

Educational Technology Research and Development, 63(3), 381–403.

https://doi.org/10.1007/s11423-015-9378-5

* van der Ven, F., Segers, E., Takashima, A., & Verhoeven, L. (2017). Effects of a Tablet Game

Intervention on Simple Addition and Subtraction Fluency in First Graders. Computers in Human

Behavior, 72, 200–207. https://doi.org/10.1016/j.chb.2017.02.031

Page 62 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 63

van Reijmersdal, E. A., Jansz, J., Peters, O., & van Noort, G. (2013). Why Girls go Pink: Game

Character Identification and Game-Players’ Motivations. Computers in Human Behavior, 29(6),

2640–2649. https://doi.org/10.1016/j.chb.2013.06.046

* Vanbecelaere, S., van den Berghe, K., Cornillie, F., Sasanguie, D., Reynvoet, B., & Depaepe, F.

(2020). The Effects of two Digital Educational Games on Cognitive and Non-Cognitive Math

and Reading Outcomes. Computers & Education, 143, 1–47.

https://doi.org/10.1016/j.compedu.2019.103680

Veenman, M. V. J., Van Hout-Wolters, B. H. A. M., & Afflerbach, P. (2006). Metacognition and

Learning: Conceptual and Methodological Considerations. Metacognition and Learning, 1(1), 3–

14. https://doi.org/10.1007/s11409-006-6893-0

Veltri, N. F., Krasnova, H., Baumann, A., & Kalayamthanam, N. (2014). Gender Differences in

Online Gaming: A Literature Review. Social-Technical Issues and Social Inclusion.

Viechtbauer, W. (2010). Conducting Meta-Analyses in R With the Metafor Package. Journal of

Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03

Viechtbauer, W., & Cheung, M. W.-L. (2010). Outlier and Influence Diagnostics for Meta-

Analysis. Research Synthesis Methods, 1(2), 112–125. https://doi.org/10.1002/jrsm.11

Vogel, J. J., Vogel, D. S., Cannon-Bowers, J., Bowers, C. A., Muse, K., & Wright, M. (2006).

Computer Gaming and Interactive Simulations for Learning: A Meta-Analysis. Journal of

Educational Computing Research, 34(3), 229–243. https://doi.org/10.2190/FLHV-K4WA-

WPVQ-H0YM

Page 63 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 64

Wigfield, A., & Eccles, J. S. (2000). Expectancy–Value Theory of Achievement Motivation.

Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015

Wouters, P., van Nimwegen, C., van Oostendorp, H., & van der Spek, E. D. (2013). A Meta-

Analysis of the Cognitive and Motivational Effects of Serious Games. Journal of Educational

Psychology, 105(2), 249–265. https://doi.org/10.1037/a0031311

Wrzesien, M., Rodríguez, A., Rey, B., Alcañiz, M., Baños, R. M., & Vara, M. D. (2015). How the

Physical Similarity of Avatars can Influence the Learning of Emotion Regulation Strategies in

Teenagers. Computers in Human Behavior, 43, 101–111.

https://doi.org/10.1016/j.chb.2014.09.024

Table 1

Inter-Rater Reliabilities for Coded Moderator Variables

Variable

Game type

0.46

Mode

0.43 (0.62)

Additional non-game instruction

0.48

Dimensionality

0.47

Visual realism

0.37 (0.53)

Competition

0.79

Narration

0.71

Avatar

0.58

Page 64 of 65

http://mc.manuscriptcentral.com/rer

RER

For Peer Review

EFFECT OF GAME-BASED LEARNING IN SCHOOL 65

Digital agent

0.52

Mean

0.53 (0.57)

Note. κ = Cohen’s Kappa. Inter-rater reliability after consulting a third rater in brackets.

Figure 1

The Integrated Design Framework of Playful Learning (adapted from Plass et al., 2015)

Figure 2

Flow Chart of the Selection Process

Page 65 of 65

http://mc.manuscriptcentral.com/rer

RER

Impact of achievement goals on academic achievement: mediating role of procrastination and moderating role of loneliness

Article

May 2025

Purpose Academic procrastination is prevalent among university students and adversely affects academic performance. This research intends to explore the direct relationship between various achievement goals and academic procrastination and also determine the role of academic procrastination as the mediator between achievement goals and academic achievement. Also, it examines the moderating role of loneliness in the relationship between academic procrastination and academic achievement. Design/methodology/approach The methodology of this paper applied a cross-sectional and causal research design. To gather responses from Northern Indian Region university students, the study created an English language survey. The analysis for this study was done using structural equation modelling (SEM), which necessitated a sample size of at least 300. After data cleaning, 513 complete responses—out of the 555 total responses received—were used in the study. Findings The study reveals that performance approach and mastery approach goals reduce academic procrastination, whereas performance-avoidance and mastery-avoidance enhance academic procrastination. The analysis revealed that academic procrastination mediated the association between achievement goals and academic performance. In addition, the study also shows that loneliness moderates the association between academic procrastination and academic achievement. Originality/value The paper examined a unique conceptual framework, including learning goals, loneliness, academic procrastination and academic achievement. The study not only improves past theoretical models concerning antecedents of academic achievements in university students but also makes a necessary contribution to educational psychology from a learning and behavioural perspective.

Методологии за унапредување на наставата по информатика во основно образование со учење базирано на игра - Докторски труд

Thesis

Full-text available

Jun 2025

Maja Videnovik

In recent years, the landscape of education has undergone a remarkable transformation, driven by advancements in technology and a shift toward innovative pedagogical approaches that effectively engage learners and enhance their interest and motivation in the educational process. This doctoral thesis explores the implementation of game-based learning approaches in computer science education in primary schools, aiming to establish interactive, engaging, and student-centered learning environments. To explore current trends and practices, a comprehensive review and analysis of 113 articles published between 2017 and 2021 was conducted, focusing on educational level, types of games, computer science topics, pedagogical strategies, and the aim for implementing a game-based approach. An in-depth analysis of 32 articles on the implementation of a game-based learning approach in computer science education in primary schools was done. The findings indicate a growing academic interest in the integration of game-based learning in computer science education. However, a significant part of these studies focus on higher education and programming-related topics, while research exploring game-based learning in primary education and its use in other computer science topics remains limited. Furthermore, while game playing is identified as the predominant instructional strategy, game creation as a form of learning remains underexplored, particularly for content beyond programming. Based on these findings, the thesis proposes a structured methodology for developing students’ programming skills in primary education, built around four spiral learning cycles that alternate between collaborative and individual learning strategies, and integrates game-based learning, flipped classroom strategies, gamification, and project-based learning. Game-based learning methodologies were implemented in computer science education, including topics not related to programming, focusing on: the use of design thinking methodology for game creation; the development and implementation of a methodological approach that combines game-based learning and peer instruction in cybersecurity education; as well as the implementation of approaches that utilize the potential of mobile devices. The findings indicate increased engagement, interest, and motivation among students, as well as significant improvement in acquiring long-lasting knowledge and developing core 21st-century skills, such as collaboration, critical thinking, and problem-solving.

Analyzing Role of Abstract Thinking: Teaching Solvable and Nilpotent Groups in Algebra

Article

Jun 2025

This study explored the role of abstract thinking in teaching solvable and nilpotent groups in abstract algebra. We used an ethnographic approach, preparing a set of questionnaires and working with three university-level abstract algebra teachers to gather detailed insights. The main research objective was to explore the role of abstract thinking in understanding and teaching the concepts of solvable and nilpotent groups in algebra, and research question was how abstract reasoning influences students’ conceptual clarity, problem-solving ability, and mathematical maturity in group theory. We used open-ended questionnaires to facilitate in-depth discussions about their pedagogical approaches and we observed the classroom teaching of abstract algebra for finding, challenges, and successes in conveying concepts in solvable and Nilpotent group. The study maintained rigorous ethical considerations throughout data collection and analysis, ensuring participant confidentiality and informed consent. Findings highlighted the critical role of abstract thinking in enhancing comprehension and promoting a supportive learning environment, ultimately empowering students to navigate advanced algebraic structures confidently and creatively.

Digital and Analogue Gaming in the Daily Lives of People with Intellectual Disability: A Case Study in the Portuguese Context

Chapter

Full-text available

May 2025

The role of games in promoting cognitive and social development for People with Intellectual Disability (PwID) is increasingly recognised, yet the specific impacts of digital versus analogue games remain underexplored. This study explores the cognitive, social, and emotional influence of digital and analogue games on PwID in Portuguese institutions. Using a participatory design approach, four games-two digital and two analogue-were developed collaboratively between academia and self-advocacy institutions. Semi-structured interviews were conducted with support workers from two institutions in the North of Portugal, who provided feedback based on their experiences of using these games with PwID. Thematic analysis of these interviews identified key themes such as cognitive skills development, social interaction, accessibility challenges, and game design preferences. Results indicate that both digital and analogue games can promote cognitive stimulation and social engagement, though analogue games tend to foster richer peer interaction, while digital games are associated with maturity and autonomy by the participants. The study highlights the importance of customisation and accessibility in game design and suggests future research should focus on longer-term effects.

Impact of Interactive Multimedia on Digital Literacy Among Chinese Grade-3 Students

Article

Full-text available

May 2025

This study investigates the impact of interactive multimedia on Chinese character recognition skills among third-grade students in Beijing, China. The research aims to study the impact of incorporating mnemonics into multimedia on the acquisition of Chinese character recognition skills in Grade 3 students and to compare the skill level between students who learn using CLT and DCT and students who learn using non-CLT and DCT. Employing an experimental research design, the study compares the effectiveness of interactive multimedia teaching methods with traditional classroom approaches. A Target group from two elementary schools participated in the survey, with 30 students learning through Cognitive Load Theory (CLT) and Dual Coding Theory (DCT) based multimedia methods and 30 through non-CLT and non-DCT methods. Data was collected through pre-post test and survey by questionnaire. The study used descriptive and inferential statistics, including t-tests, to analyze the data. Results indicate the interactive games made learning Chinese characters more fun, and they had the lowest level of very high engagement. Students who learn using Cognitive Load Theory (CLT) and Dual Coding Theory (DCT) based multimedia methods demonstrate significantly higher Chinese character recognition skill than students who learn using non-CLT and non-DCT methods. This research contributes to the growing body of literature on the efficacy of multimedia in language education. It provides practical insights for educators and policymakers in leveraging technology to enhance literacy among young learners.

«Agentes del tiempo»: evaluación de la experiencia de usuario para la enseñanza interdisciplinar de temáticas ambientales

Article

Full-text available

May 2025

El videojuego educativo Agentes del tiempo ha sido diseñado para abordar una problemática ambiental relacionada con las especies exóticas invasoras desde un enfoque interdisciplinario. Este estudio evalúa la experiencia de usuario de Agentes del tiempo en docentes en formación de nivel primario y secundario, para valorar su potencial como herramienta didáctica en educación ambiental. A través de un enfoque mixto, se analizó la experiencia en términos de navegación, efectividad, arquitectura de la información, motivación e inmersión en la interfaz. Los resultados indican una recepción positiva, destacando la capacidad del juego para involucrar a los usuarios y facilitar la adquisición de conocimientos en geografía y biología. Los hallazgos sugieren que el juego promueve una comprensión interdisciplinaria y permite introducir el tema de especies invasoras, en particular el mejillón dorado. Además, se recomiendan mejoras en la usabilidad para optimizar la fluidez del juego y su función en el aprendizaje escolar. Finalmente, Agentes del tiempo muestra un potencial prometedor como recurso para la educación ambiental, fomentando el compromiso estudiantil (hombres y mujeres) en temáticas ambientales complejas mediante el aprendizaje basado en juegos.

Evolution and Frontiers of Digital Game-Based Learning in Education: A Bibliometric Analysis

Conference Paper

Dec 2024

How the timing of using digital games in courses influences students' learning: a study on digital citizenship education

Article

Jun 2025
INTERACT LEARN ENVIR

Using Matific digital games to enhance second-grade students’ conceptual understandings of multiplication

Article

May 2025
J EDUC RES

Influence of a Two-Tier Test and Self-Efficacy on Students’ Problem-Solving Tendencies, Knowledge Gains, Cognitive Load, and Behaviors in a Game-Based Learning Context

Article

May 2025
J Educ Comput Res

Prior research has emphasized that two-tier tests are an effective approach to guiding students through game tasks; furthermore, self-efficacy, which is potentially related to students’ surroundings and academic performance, has a positive impact on students’ cognitive outcomes in games. This implies the significance of conducting a study to probe the influence of a two-tier test and self-efficacy on students’ knowledge gains, perceptions, and skills in a game-based learning context. In this study, a two-tier test-assisted game-based learning approach and an interactive guidance-assisted game-based learning approach were designed to support students’ science learning. Furthermore, an experiment was conducted on a natural science course to investigate the influences of the two-tier test and students’ self-efficacy on their science learning. The experimental results displayed that both the two-tier test-assisted learning approach and high self-efficacy can effectively enhance the problem-solving tendencies of the students with lower initial tendencies in the game-based learning activities. The students with high self-efficacy perceived a higher germane cognitive load than those with low self-efficacy. However, neither learning approaches nor self-efficacy had a significant effect on students’ knowledge gains. Moreover, the differences between the learning patterns of students with different learning approaches and self-efficacy were revealed.

Revisiting Milgram and Kishino's Reality-Virtuality Continuum

Article

Full-text available

Mar 2021

Since its introduction in 1994, Milgram and Kishino's reality-virtuality (RV) continuum has been used to frame virtual and augmented reality research and development. While originally, the RV continuum and the three dimensions of the supporting taxonomy (extent of world knowledge, reproduction fidelity, and extent of presence metaphor) were intended to characterize the capabilities of visual display technology, researchers have embraced the RV continuum while largely ignoring the taxonomy. Considering the leaps in technology made over the last 25 years, revisiting the RV continuum and taxonomy is timely. In reexamining Milgram and Kishino's ideas, we realized, first, that the RV continuum is actually discontinuous; perfect virtual reality cannot be reached. Secondly, mixed reality is broader than previously believed, and, in fact, encompasses conventional virtual reality experiences. Finally, our revised taxonomy adds coherence, accounting for the role of users, which is critical to assessing modern mixed reality experiences. The 3D space created by our taxonomy incorporates familiar constructs such as presence and immersion, and also proposes new constructs that may be important as mixed reality technology matures.

The Effect of Game-Based Learning on Student Achievement: A Meta-Analysis Study

Article

Full-text available

Mar 2022

The purpose of this study was to combine the results of the experimental studies conducted between the years of 2000–2018 examining the effect of game-based learning method on the academic achievement of students through a meta-analysis. In this study addressing the effect of game-based learning method on the academic achievement of students, meta-analysis included 38 studies which had been issued in the databases of Google Academic and National Thesis Center of Turkish Council of Higher Education between 2010 and 2018 and selected according to certain criteria. The study also involved subgroup analyses in addition to revealing the overall effect of game-based learning on academic achievement. According to the research findings, it is possible to allege that Hedges g value which was estimated to be 1.695 for the overall effect size of game-based learning on student achievement indicates a wide-ranging effect. Furthermore, as a result of the analyses, it was revealed that the effect of game-based learning on the academic achievement of students does not differ according to the sub-dimensions of the levels of schooling, the different types of reporting and various disciplines.

The effect of pedagogical GAME model on students' PISA scientific competencies

Article

Full-text available

Dec 2019
J COMPUT ASSIST LEAR

The purpose of this study is to explore the effect of a pedagogical model of digital games on students' scientific competencies that are advocated by the Programme for International Student Assessment (PISA). As a single game‐based learning strategy may not be enough to enhance such competencies, the online game in the current study incorporated the design of the proposed pedagogical gamification, assessment, modeling, and enquiry (GAME) model. The participants were 69 sixth grade students at one primary school in Taiwan. A quasi‐experimental design was adopted. The experimental group students learned with the GAME model, whereas the comparison group students only learned with traditional learning way. The results showed that the learning gain in scientific competencies of the experimental group was better than those of the comparison group. This study revealed that the GAME model has potential to promote students' PISA scientific competencies. It is suggested that the integral GAME model may serve as one kind of strategies to enhance students' scientific competencies.

Glued to Games: How Video Games Draw Us In and Hold Us Spellbound

Book

Jan 2011

This book offers a practical yet powerful way to understand the psychological appeal and strong motivation to play video games. With video game sales in the billions and anxious concerns about their long-term effects growing louder, Glued to Games: How Video Games Draw Us In and Hold Us Spellbound brings something new to the discussion. It is the first truly balanced research-based analysis on the games and gamers, addressing both the positive and negative aspects of habitual playing by drawing on significant recent studies and established motivational theory. Filled with examples from popular games and the real experiences of gamers themselves, Glued to Games gets to the heart of gaming's powerful psychological and emotional allure—the benefits as well as the dangers. It gives everyone from researchers to parents to gamers themselves a clearer understanding the psychology of gaming, while offering prescriptions for healthier, more enjoyable games and gaming experiences.

Comparing Traditional Teaching and Game-Based Learning Using Teacher-Authored Games on Computer Science Education

Article

Mar 2021

Contribution: This article provides evidence on the effectiveness of game-based learning (GBL) for computer science education when using educational video games created by teachers using authoring tools. Background: Although teacher-oriented authoring tools for creating educational video games can help overcome the main barriers hampering the use and uptake of GBL, there is a lack of studies examining the effectiveness of educational video games authored by teachers using these authoring tools by means of rigorous scientific methods. Research Questions: Is GBL using teacher-authored games more effective than traditional teaching in terms of motivation for computer science students? Is GBL using teacher-authored games more effective than traditional teaching in terms of knowledge acquisition for computer science students? Methodology: Two randomized control trials with pretest, post-test, and one questionnaire were conducted to compare the effectiveness of traditional teaching and GBL in two computer science courses. The sample of the two experiments was composed by 75 and 49 students, respectively. Half of the students attended a traditional lecture, while the other half learned solely by playing teacher-authored educational video games. Findings: The results show that GBL using teacher-authored games was practically as effective as traditional teaching in terms of knowledge acquisition, but that it was emphatically successful in increasing student motivation. Students who learned by playing educational video games found the experience more motivating and fun than their counterparts, and a vast majority of them preferred the GBL approach over traditional teaching.

Enhancing early numeracy skills with a tablet-based math game intervention: a study in Tanzania

Article

Aug 2020

The study presents results of a tablet-based math game intervention to enhance early numeracy skills of children in Tanzania. Standard level 1 children (n = 122), attending a rural primary school, were randomly allocated to either intervention or control group. The intervention group participated in a daily intervention session for 46 days. Children’s performances in number identification, quantity discrimination, addition, subtraction, and missing number tasks were measured before and after the intervention with randomly selected children from both groups (treatment = 30, control = 31). Score gains in the intervention group were substantially greater than those in the control group. In particular, statistically significant effects of the intervention were identified in quantity discrimination, addition, and subtraction tasks. Item-level analyses using Item Response Theory showed that addition and subtraction items involving regrouping and most missing number items were too difficult even after the intervention. The study also identified which games were played the most or least during the sessions from play-log data and analyzed associations between children’s test performances and gameplays.

The effects of competition in digital game-based learning (DGBL): a meta-analysis

Article

Jun 2020

Digital game-based learning (DGBL) is known to be widely used for improving learning in various fields. Among the elements of DGBL, competition has been very controversial. This meta-analysis, which included 25 articles written between 2008 and 2019, revealed that DGBL has produced improvements for learning outcomes with an overall effect size of .386. In addition, we explored multiple moderators to understand how competition in DGBL influenced student learning for different learners, contexts, game types, and learning outcomes. We found that competition in DGBL was effective for math, science and language, but not for social science and other subjects. It was effective for K12 students and college students. It was effective for puzzle, strategy, role-playing, and simulation, but not for action games. Finally, competition in DGBL was equally effective for cognitive and non-cognitive outcomes. Through the results of this study, we fill a critical gap in the research left by recent reviews, which do not examine the role of competition; a key gaming element. In addition, we offer a number of suggestions for future studies.

The effect of game-based learning on academic achievement motivation of elementary school students

Article

Nov 2019

Game-Based Learning is widespread among elementary school students. Consequences in academic achievement motivation have been studied frequently. The aim of this study was to test the effectiveness of the Game-Based Learnings on the academic achievement motivation of the elementary school students. We used from a field method to collect the required data and complete the standard questionnaire. The study is a semi-experimental design with pretest-posttest design with the control group. The statistical population was 256,836 students of the first grade of elementary school students in the 2016-17 academic year. Sixty students (32 males and 28 females) were selected through a purposive method. Then, the subjects of the study were randomly allocated to the control and experimental groups, and a pre-test was performed from both groups. The experimental group was exposed to Misha and Kosha Game-Based Learnings, while we implemented the conventional teaching method to the control group. The measuring tool was the Inventory of School Motivation (ISM) questionnaire. The test has sufficient validity and reliability (α = 0.84). The covariance analysis test (MANCOVA) revealed that the experimental group had significantly higher scores for academic achievement motivation than the control group. Also, the results showed that the computer educational game impacted academic achievement motivation of elementary students. According to the results, the necessity of using computer-based games in elementary school students is felt. Therefore, it is necessary to find a more suitable place in the teachers' daily lesson plan. The results can be good for educators, instructional and game designers and researchers from implementation, design and research perspectives, respectively.

Kiddy Manner: A Game-Based Mobile Application for Children Learning Thai Social Etiquette

Conference Paper

Jul 2019

Using Learning Games to Teach Texas Civil War History to Public Middle School Students

Conference Paper

Aug 2019

The Effect of Digital Game-Based Learning Interventions on Cognitive, Metacognitive, and Affective-Motivational Learning Outcomes in School: A Meta-Analysis

Abstract

Recommended publications

Fostering self-regulated learning using synchronous or asynchronous digital learning environments: a...

Fostering Self-Regulated Learning in Primary School Students: Can Additional Teacher Training Enhanc...

Pre-service Teachers' Player Types and Their Relation to Self- efficacy With Digital Media

The evaluation of an educational game to promote pre-service teachers' self-regulated learning