Content area
Purpose
Since youngsters are being extensively engaged with digital devices these days, integrating digital technologies into food and nutrition education programs, stands out as a viable method. The current systematic review aimed to assess the available literature on the effectiveness of digital edutainment games on nutrition behavior of school-going children.
Design/methodology/approach
From the earliest date available until September 30, 2023, a comprehensive search was conducted in databases such as PubMed, Cochrane, Scopus, Lilacs, Science Direct, Web of Science and Google Scholar to identify relevant articles. Only randomized controlled studies were included in the review. Seven full-text publications that fulfilled the eligibility criteria were subjected to additional data extraction processing.
Findings
Children’s dietary behavior was found to be improved by playing digital games because they are entertaining and pleasurable. The majority of the studies' favored game type was game-based simulations. In terms of pedagogical role, all the studies were independent and not complementary to traditional conventional classroom lectures.
Research limitations/implications
Based on the results, digital educational games show promising results in terms of acceptability and early impacts on reducing sugar intake and enhancing dietary habits in school-age children. However, it is necessary to conduct more research to determine the essential elements of these games, their duration of usefulness and their generalizability.
Originality/value
This review contributes to the researchers and academicians by providing relevant information regarding effectiveness of digital edutainment games on nutrition behavior of school-going children. This is the first systematic review conducted to assess the effectiveness of digital edutainment games on nutrition behavior of school-going children.
Introduction
The prevalence of being overweight has increased exponentially, especially among children and adolescents, despite improvements in global health indicators (Bloch et al., 2016). The World Health Organization (WHO) estimates that 39 million children under the age of five are overweight or obese (WHO Obesity). Overweight and obesity in children are linked to more fatalities worldwide than underweight conditions in children. Overweight and obesity are currently regarded as the fifth most important risk factor for mortality globally. More than four million people die each year as a result of being overweight or obese, according to Global Burden of Disease 2017; (Afshin et al., 2017).
Obesity and various diet-related chronic diseases have been linked to specific dietary behaviors, such as low intake of nutritious foods like fruits, vegetables, whole grains and frequent consumption of ultraprocessed foods (such sweets, cookies and soft drinks). IBGE survey (2015), Souza et al. (2016)). Other harmful behaviors include embracing sedentary lifestyles and skipping meals during the day (Cureau et al., 2016). People who eat more fruits, 100% juice and vegetables (FJV) live longer and may be somewhat protected from a number of malignancies (Glade et al., 1999), heart disease (Joshipura et al., 2001), diabetes mellitus (Tuomilehto, 2001) and possibly even skin aging (Purba, 2001).
At this stage of life, picking one’s own food is seen as a sign of autonomy and a way to alter the social environment (Hare et al., 2015). Because of these traits, school-age children could be the subject of instructional initiatives that encourage lifelong good eating habits (WHO, 2005).
Schools are a key venue for delivering nutrition education to a significant population of children. After two years of program implementation, only one school nutrition education program, which was carried out by professionally qualified teachers, resulted in a significant FJV change (1.6 servings) (Reynolds et al., 2000). Others have had little (Luepkar et al., 1996; Baranowski et al., 2000) or no FJV change (Resnicow et al., 1998). One of these studies showed that the typical classroom instructor only used 50% of the activities that were prescribed by the curriculum, with just 22% of those likely to cause behavior change (Davis et al., 2000). Additionally, data have shown that there are challenges to successfully implementing programs, such as a high rate of staff turnover and incompetent educators (Kelder et al., 2005). In order to give nutrition education programs to children more directly, several routes must be discovered.
The amount of time youngsters spend online has increased in conjunction with the expansion of access to digital technology and computers. A UNICEF survey estimates that one in three Internet users worldwide are children and adolescents under the age of 18 (Livingstone et al., 2016). Since youngsters are being extensively engaged with digital devices these days, integrating digital technologies into food and nutrition education programs, stands out as a viable method (Barnett et al., 2016). In numerous educational and health-related sectors, game formats have been utilized to successfully improve knowledge, self-confidence, attitudes and behaviors (Lieberman, 2012). In contrast to more traditional didactic exercises, digital education games offer the chance to give hands-on, interactive multimedia activities that may be quickly implemented during school hours and require little teacher oversight (DeShazo et al., 2010). These games combine entertainment with education (edutainment), which increases the acceptability of the messages and the enjoyment of the activities (Morris et al., 1996). By advancing children’ knowledge and abilities, these games have the ability to alter behavior as well (Thompson et al., 2012).
Although there is data suggesting that digital games can significantly improve dietary and physical activity behavior of school going children (Baranowski et al., 2003a, b, 2008, 2011) a systematic evaluation comparing the studies is lacking. Hence, this systematic review was conducted to assess and compare the available data on the effectiveness of digital edutainment games on nutrition behavior of school-going children.
Materials and methods
The systematic review was completed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) standards (Shamseer et al., 2015).
Study registration
Details regarding the study’s protocol have been registered in PROSPERO (Registration number: CRD42023472227).
Focused question
What is the effect of digital edutainment games on nutrition behavior outcome compared to standard therapy in children?
PICO analysis
Population: children
Intervention: digital edutainment games
Comparator: standard therapy
Outcome: nutrition behavior
Search strategy
A thorough search in databases like PubMed, Cochrane, Scopus, Lilacs, Science Direct, Web of Science and Google Scholar was done to find pertinent papers from the earliest date available to September 30, 2023. Additional publications were also discovered by a manual search of unpublished works, cross-references, important journals and conference proceedings. The authors of the articles were contacted if they were not published. The following keywords were used as part of the search strategy and an article type filter of randomized controlled trials was employed.
Keywords used:
((((digital game) OR (video game)) OR (gamification)) AND (((nutrition behavior) OR (food consumption)) OR (eating habit))) AND (child)
Inclusion criteria
- Study design: randomized controlled trials (RCTs).
- Studies conducted on participants below 18 years of age with no restriction on gender.
- Studies comparing the effectiveness of digital edutainment games with standard therapy in improving nutrition behavior outcomes among children.
- Articles available in English language.
Exclusion criteria
- Articles comparing two different types of digital edutainment games on nutrition.
- Case reports, cross-sectional studies, longitudinal studies, case-control studies, cohort studies, in vitro studies and reviews due to lower level of evidence as compared to RCTs.
Sources used
PubMed, Scopus, Cochrane, Google Scholar, Web of Science, Lilacs and ScienceDirect.
Screening and selection
The study titles were examined independently by two reviewers (SM and RM). If the same articles were found in multiple databases, they were excluded due to duplication. If the search terms were in the article title, the papers were considered for abstract reading. If the abstracts were based on the aim of the study, the publications were considered for full-text reading. The papers' eligibility was then assessed after retrieving the entire texts. If the papers were eligible, they underwent additional processing for data extraction (Figure 1). The reference lists of the full-text publications were manually searched to identify further studies. Any conflict between the reviewers was resolved through discussion.
Outcome parameter assessed
The outcome assessed was whether digital edutainment games are effective in improving nutrition behavior among children. The change in nutrition behavior was measured at baseline and after using digital games and standard therapy, respectively.
Data extraction
PRISMA reporting guidelines were used to extract data for the systematic review (Moher et al., 2009). The following details were independently collected by two reviewers and entered into an excel spreadsheet (MS Excel 2020): the name of the game-based learning (GBL) app used, the control, methodology, outcome and conclusion of the included studies. The author information, year of study, location of study, study design, participant demographic information and study name. Google Translate was used to translate texts written in different languages into English (Balk et al., 2013). The concerned authors were contacted to request the full-text publications or any other necessary information when the articles were not available in full-text. Any issues were resolved through discussions.
Risk of bias assessment
RoB 2 was used to assess the risk of bias both within and between the included studies. RoB 2 stands for risk-of-bias tool for randomized trial version 2 (Cumpston et al., 2019). The following variables were used to categorize the bias as “high risk,” “unclear risk” or “low risk”: creation of random sequences, concealment of allocation, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other factors.
A study was declared to be low risk if all criteria for “low risk” were satisfied. If any one of the criteria was satisfied, a study was labeled as “high risk.” The study was labeled as having “unclear risk” if one criterion was “unclear risk,” but no other criterion was “high risk.” To end conflicts, consensus was found.
Quality of evidence
The quality of evidence offered (Table 1) by the included studies was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) Assessment Tool (Gramholm et al., 2019). Four categories – very low, low, moderate and high – were used to classify the evidence’s quality. Risk of bias, imprecision, consistency, indirectness and publication bias were employed as the GRADE domains to assess the quality of the evidence.
Results
Search and selection of results
A total of 33,403 papers were found after screening six databases – Cochrane, PubMed, Scopus, Web of Science, Lilacs, Science Direct, Google Scholar and hand-searched publications – based on the key phrases. A total of 30,002 articles were found after duplicates were eliminated. A total of 198 articles were chosen for abstract screening after the titles were read. Twenty papers were chosen for full-text reading after the abstract was read, of which seven articles (Table 2) were then processed for qualitative analysis.
Characteristics of included studies
Six articles (Baranowski et al., 2003a, b, Pempek et al., 2009, Baranowski et al., 2011, Sharma et al., 2015, Kato-Lin et al., 2020, Chagas et al., 2020, Alblas et al., 2020) were randomized controlled trials (RCT) whereas one article was a quasi-RCT (Sharma et al., 2015). One study was double blinded (Kato-Lin et al., 2020), in one study (Baranowski et al., 2011) the researcher was blinded whereas in another study the researcher was not blinded (Chagas et al., 2020). In both these studies, no information was given regarding the blinding of participants. Remaining four studies (Baranowski et al., 2003a, b, Pempek et al., 2009, Sharma et al., 2015, Alblas et al., 2020) gave no information regarding blinding. The included studies' research participants were between the ages of 8 and 16. The included studies had a maximum sample size of 1,578 and a minimum sample size of 30.
Place of study
Three studies were conducted in Texas (Baranowski et al., 2003a, b, Baranowski et al., 2011; Sharma et al., 2015), one in the Netherlands (Alblas et al., 2020), one in the USA (Pempek et al., 2009), one in Brazil (Chagas et al., 2020) and one in India, respectively (Kato-Lin et al., 2020).
Industry funding
The funding was acknowledged in all the studies. The studies were funded by the National Institutes of Health (Baranowski et al., 2003a, b), Georgetown university (Pempek et al., 2009), National Institute of Diabetes and Diabetes and Kidney Diseases (Baranowski et al., 2011), Cooper institute (Sharma et al., 2015), Remala Foundation (Kato-Lin et al., 2020), Research Support Foundation of the Federal District of Brazil (Chagas et al., 2020) and Radboud University (Alblas et al., 2020).
Methodology
In three studies (Pempek et al., 2009; Kato-Lin et al., 2020; Chagas et al., 2020), the participants were asked to select a food item (healthy vs unhealthy) post intervention. In one study (Baranowski et al., 2011), 24h dietary recall was recorded at baseline, between games, immediate postgame and two-months postgame. In one study (Sharma et al., 2015), 24h dietary recall was recorded at baseline and after six weeks intervention period. In one study (Baranowski et al., 2003a, b), four days of dietary intake was recorded before and after the intervention using the Food Intake Recording Software System. In one study (Alblas et al., 2020), dietary behavior was assessed using the National School-Aged Adolescent Health Survey criteria pre and post intervention.
Duration of the gaming session
One study (Baranowski et al., 2003a, b) consisted of ten play sessions with 25 min of gaming each. Two studies consisted of two play sessions with 5 min (Pempek et al., 2009) and 20 min (Kato-Lin et al., 2020) of gaming each, respectively. One study (Baranowski et al., 2011) consisted of nine play sessions with 40 min of gaming each. One study (Sharma et al., 2015) consisted of 90 min of gaming per week for six weeks. One study was conducted over 7–17 days (Chagas et al., 2020) One study consisted of one play session with 10 min of gaming (Alblas et al., 2020).
Outcome
In three studies (Baranowski et al., 2003a, b, Baranowski et al., 2011; Alblas et al., 2020), children chose and consumed more of FJV as compared to control group. Similarly, in two studies (Pempek et al., 2009; Kato-Lin et al., 2020), children chose and consumed more of healthy snacks as compared to control group. In one study (Sharma et al., 2015), children in the treatment group reported decreased sugar consumption. However, there was no significant difference in the consumption of FJV in treatment and control group. In one study (Chagas et al., 2020), the habit of eating while watching TV or studying reduced from 53.8% to 41.9% in the treatment group. The habit consuming foods at fast food restaurants also reduced from 6.8% to 5.3% in the treatment group.
Pedagogical description of games
None of the authors of the included studies provided a clear explanation of the educational value of the games. However, the pedagogical preference was revealed from the games’ objectives. Five games (Baranowski et al., 2003a, b, Pempek et al., 2009, Baranowski et al., 2011; Sharma et al., 2015; Alblas et al., 2020) (71.43%) were game-based simulations, based on the game type, while two (Kato-Lin et al., 2020; Chagas et al., 2020) (28.57%) were gamified apps. Additionally, it was discovered that 28.57% of the games were mobile apps (Kato-Lin et al., 2020; Chagas et al., 2020), 14.28% were video games (Baranowski et al., 2011) and 57.15% of the games were computer-based (Baranowski et al., 2003a, b, Pempek et al., 2009, Sharma et al., 2015, Alblas et al., 2020). Based on the game genre, all of them (100%) were adventure-based (Baranowski et al., 2003a, b, Pempek et al., 2009, Baranowski et al., 2011, Sharma et al., 2015, Kato-Lin et al., 2020, Chagas et al., 2020, Alblas et al., 2020).
Based on the games’ pedagogical role, all of them were independent and were not complementary to any classroom lecture (Baranowski et al., 2003a, b, Pempek et al., 2009, Baranowski et al., 2011, Sharma et al., 2015, Kato-Lin et al., 2020, Chagas et al., 2020, Alblas et al., 2020). A total of 42.86% of the games were found to fall under the behaviorism field (Baranowski et al., 2003a, b, Pempek et al., 2009, Kato-Lin et al., 2020). A total of 28.57% to fall under the cognitivism and behaviorism field (Sharma et al., 2015; Alblas et al., 2020) and 28.57% to fall under the insufficient pedagogical approach data category (Baranowski et al., 2011, Chagas et al., 2020). The game designs were in line with the pedagogical strategy in 71.42% of the studies (Baranowski et al., 2011, Sharma et al., 2015, Kato-Lin et al., 2020, Alblas et al., 2020). The games' educational description is shown in Table 3.
Risk of bias
Two studies (Sharma et al., 2015; Chagas et al., 2020) were rated as high risk whereas four studies were rated as unclear (Baranowski et al., 2003a, b, Pempek et al., 2009, Baranowski et al., 2011, Alblas et al., 2020) and one study was rated as low risk of bias (Kato-Lin et al., 2020), respectively.
Random sequence generation and blinding of outcome assessment showed more than 75% but less than 100% low risk of bias. Blinding of participants and personnel showed more than 25% but less than 50% low risk of bias. Allocation concealment showed less than 25% low risk of bias. No bias was seen in incomplete outcome data, selective reporting and other bias. The risk of bias graph and summary have been illustrated in Figure 2(a) and (b) , respectively.
Quality of evidence
The conclusion about the quality of the evidence was “moderate,” meaning that the true effect is most likely not too dissimilar from the estimated effect. Two studies (Sharma et al., 2015; Chagas et al., 2020) had a “high risk of bias,” while five additional studies (Baranowski et al., 2003a, b, Baranowski et al., 2011, Pempek et al., 2009, Alblas et al., 2020) had an “unclear risk of bias.” For these reasons, the risk of bias was graded as “serious.” (Table 1).
Discussion
Due to elevated nutritional requirements and unhealthful eating habits, adolescence is a time of nutritional fragility (Totland et al., 2013). Sedentary lifestyles, poor eating habits and a vulnerability to social influence are the main risk factors for chronic diseases at this stage of life (Patterson et al., 2009). As access to computers and digital technologies has expanded, so too has the amount of time children spend online. These days, children spend a lot of time on digital gadgets, so incorporating digital technology into food and nutrition education courses seems like a good idea. According to the current review, children’s dietary behavior is improved by playing digital games because they are entertaining and pleasurable.
Digital games aim to promote self-reliance/autonomy, authenticity (i.e. contextualized learning), learning through “fun,” intrinsic motivation and experiential learning (Perrotta et al., 2013). Rules, precise yet difficult objectives, imagination, escalating difficulty levels, interaction, player control, unpredictability, feedback and a social component are some examples of mechanisms of digital games (Dondlinger et al., 2007).
One of the main conclusions drawn from the review was that shorter-term studies demonstrated a lower mean change in nutrition behavior, while the Sharma et al. study revealed a larger mean change in nutrition behavior (10.49). Additionally, there was a 12% change in nutrition behavior in the Chagas et al. trial. The reason could be that the study duration in the study conducted by Sharma et al. was six weeks and Chagas et al. was 7–17 days. This implies that in order to evaluate the major change in feeding behavior, a lengthy randomized controlled experiment is advised. According to a systematic review by Mary et al., nutrition education programs need be implemented for a minimum of five months in order to sufficiently alter nutrition-related behavior (Murimi et al., 2017).
The majority of the studies' favored game type was game-based simulations. Simulations foster the application of critical and evaluative thinking while giving participants real-world experience (Rosen et al., 2008). They urge children to consider the ramifications of a scenario because they are unclear or open-ended (Hammick et al., 2007). Because the scenario seems genuine, children participate in the activity more fully and enthusiastically (Oandasan et al., 2005). Additionally, a player-centered game design fosters a closer relationship between the user and the technology, guaranteeing more enjoyment and playability (Baranowski et al., 2013).
Majority of the researchers preferred computer-based games instead of mobile apps and video games. Considerations such as (1) which technology reaches the greatest number or percentage of targeted participants in a form they can easily and affordably access, (2) which platform or platforms permit the types of programming anticipated, (3) where the game or games will be played (e.g. on the bus to school, lunch break, in a classroom) and (4) when (e.g. during the commute to work, school time, leisure time) are major considerations when choosing a channel and technology (desktop computer, laptop, tablet, mobile game system, smartphone or console game system) (Baranowski et al., 2013).
Because so many children attend school, computer games are a desired approach to reach children in general. Therefore, computer-based games are a desirable substitute for didactic classroom lectures in a school setting. But the same game – a video or mobile game – offered as an elective at home might not be all that appealing, particularly if the youngster has access to more amusing games, TV shows or in-person social interactions (Baranowski et al., 2013). Also, playing games on a mobile device makes it harder for parents to keep an eye on their children at home and can lead to an online gaming addiction (Baranowski et al., 2013).
In terms of pedagogical role, all the studies were independent and not complementary to traditional conventional classroom lectures. Traditional lectures are only partially successful in achieving the major goals of health education (Schmidt et al., 2015). They do not encourage critical thinking; both cognitive engagement and student attendance are typically poor (Schmidt et al., 2015). Furthermore, there is a dearth of empirical research on what students really take away from lectures (Bigdeli et al., 2017). Here is where digital games really shine. Game-based education use game design ideas to enhance the enjoyment, impact and engagement of health education.
Limitations
This review has various limitations even though a rigorous approach was employed. Small sample sizes in the included studies may have affected the research conclusions. The quality of the study may have been impacted by the significant bias risk in two studies and the unclear risk in four others. All the included studies assessed the change in nutrition behavior for a short period of time. Long term behavioral change and maintenance of healthy eating practices have not been determined. Also, change in behavior was assessed based on self-reported data which heavily relied on children’s ability to recall their food intake. This could have led to under or over reporting of data resulting in a bias.
Future directions
Long-term multicentric studies with a larger and wider sample size should be encouraged in order to lessen the bias in the findings. Additionally, every nation should create a unique game that takes into account the local way of life, dietary habits and health concerns. It would be beneficial to investigate implicit attitude shifts and how they affect snack preferences in more detail. Does it, for instance, alter cravings and likes? It is possible that making energy-dense meals less appealing will make it easier to stick to a balanced diet. Also, government should put forth health policies addressing the issue of equity and access to digital edutainment games for improving nutrition behavior among disadvantaged children and children in rural areas. Additionally, government funding in the form of seed money for infrastructure and technical feasibility should be encouraged.
Conclusion
Digital educational games show promising results in terms of acceptability and early impacts on reducing sugar intake and enhancing dietary habits in school-age children. It is necessary to conduct more research to determine the essential elements of these games, their duration of usefulness and their generalizability.
Authors’ contribution: Subhashree Mohapatra: concept, design and definition of intellectual content, literature search, data acquisition, data analysis and manuscript preparation. Rahul Mohandas: data acquisition, manuscript editing and manuscript review
Declaration: The manuscript has been read and approved by all the authors, the requirements for authorship as stated earlier in this document have been met and each author believes that the manuscript represents honest work.
Figure 1
PRISMA Flowchart
[Figure omitted. See PDF]
Figure 2
(a) Risk of bias graph (b) risk of bias summary
[Figure omitted. See PDF]
Table 1
Quality of evidence
| Certainty assessment | Certainty | ||||||
|---|---|---|---|---|---|---|---|
| № of studies | Study design | Risk of bias | Inconsistency | Indirectness | Imprecision | Other considerations | |
| 7 | randomized trials | serious | not serious | not serious | not serious | none | Moderate |
Source(s): Authors’ own work
Table 2
Characteristics of included studies
| Name of author, year | Place of study | Type of study | Participant description (sample size, age, gender) | Name of the GBL app/technology used | Methodology | Outcome (nutrition Behavior) | Conclusion |
|---|---|---|---|---|---|---|---|
| Baranowski et al. (2003a, b) | Texas | RCT | Sample size: 1,578 | Squire’s test | A 25 min session | Children participating in Squire’s Quest! increased their FJV consumption by 1.0 servings more than the children not receiving the intervention | Psychoeducational multimedia games have the potential to substantially change dietary behavior |
| Pempek et al. (2009) | USA | RCT | Sample size: 30 | Pac-man arcade game | Group 1 = Healthier advergame | Compared to those in the less healthy game condition, children in the healthier game condition chose and consumed more healthy snacks | Advergames may be used to promote healthier food and beverages |
| Baranowski et al. (2013) | Texas | RCT | Sample size: 153 | Diab and Nano | 9 sessions; 40 min game-play session | Children playing these video games increased fruit and vegetable consumption by about 0.67 servings per day (p < 0.018) | Playing Diab and Nano resulted in an increase in fruit and vegetable intake |
| Sharma et al. (2015) | Texas | Quasi-RCT (pilot study) | Sample size: 107 | Quest to Lava Mountain (QTLM) | Game exposure duration: 90 min/week for 6 weeks | Compared with the comparison group, children in the treatment group reported decreased sugar consumption (p = 0.021) | QTLM has some promising acceptability and initial effects on diet |
| Kato-Lin et al. (2020) | India | Double-blinded RCT | Sample size: 104 | Fooya! | Students spent 20 min playing Fooya! in the treatment group. Following the game, the children were given the opportunity to select two items from three pairs of food items (healthy and unhealthy) that were presented to them. The categories included liquids (water and Nimbooz), savory snacks (cashews and Lays potato chips), and sweet snacks (raisins and a 5 Star chocolate bar) | Children from treatment group chose more good foods as compared to control group (p < 0.001) | A mobile video game shows a positive impact on children’s food choices |
| Chagas et al. (2020) | Brazil | Cluster RCT | Sample size: 570 adolescents | Rango cards | First performed in school, the participants were accompanied by a researcher who handled questions. Then, over a period of 7–17 days, they could play it whenever and wherever it fit best with their schedule, either independently or together | Eating while watching TV/studying | A digital game is potentially effective in bringing about changes in nutrition behavior |
| Alblas et al. (2020) | Netherlands | RCT | Sample size: 79 | Sky islands | Following the intervention, participants were shown a picture of an apple and a chocolate bar side by side on a computer screen with the order of the images counterbalanced amongst them. They were asked to select the snack they would like to eat immediately (choice immediate) and the snack they would like to take home after the experiment (choice delayed) | In the health game, participants' preference for apples was greater than that in the control group | Health games can be used to modify nutrition behavior |
Source(s): Authors’ own work
Table 3
Pedagogical assessment of games
| Author | Game name | Type | Platform | Game genre | Games’ pedagogical role | Pedagogical strategy | Game and pedagogy coherence |
|---|---|---|---|---|---|---|---|
| Baranowski et al. (2003a, b) | Squire’s test | Game based simulation | Computer based | Adventure-based | Independent | Behaviorism | Coherent |
| Pempek et al. (2009) | Pac man arcade game | Game based simulation | Computer based | Adventure-based | Independent | Behaviorism | Coherent |
| Baranowski et al. (2013) | Diab and Nano | Game based simulation | Video game | Adventure-based | Independent | Insufficient pedagogical description | Insufficient game description |
| Sharma et al. (2015) | Quest to Lava Mountain | Game based simulation | Computer based | Adventure-based | Independent | Behaviorism + cognitivism | Coherent |
| Kato-Lin et al. (2020) | Fooya! | Gamified app | Mobile app | Adventure-based | Independent | Behaviorism | Coherent |
| Chagas et al. (2020) | Rango cards | Gamified app | Mobile app | Adventure-based | Independent | Insufficient pedagogical description | Insufficient game description |
| Alblas et al. (2020) | Sky Islands | Game based simulation | Computer based | Adventure-based | Independent | Behaviorism + cognitivism | Coherent |
Source(s): Authors’ own work
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