Immersive Tools in Engineering Education—A Systematic Review

Abstract

Immersive tools are being adopted as an alternative to traditional education methods, especially in engineering curricula, where it is common to integrate various disciplines such as science, technology, engineering, and mathematics (STEM). This systematic review aimed to evaluate the effectiveness of immersive tools and serious games in improving student engagement and knowledge retention in engineering education. This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, analyzing 31 articles published between 2020 and 2025 across four databases (Scopus, Web of Science, Dimensions, and ScienceDirect). Articles were included if they complied with the following inclusion criteria: using (any) immersive tools, carrying out evaluation methods, and participation of students in STEM-related engineering courses. The data extracted encompassed sample characteristics, game attributes, evaluation methods, and results. The findings suggest that immersive tools positively impact students’ engagement and motivation. However, challenges such as potential motion sickness, complexity of serious games (SGs), and high implementation costs exist. SG design must balance engagement, immersion and pedagogical effectiveness to ensure viability. Future research should assess long-term impacts and promote methodological consistency across studies, particularly in subject areas and sample demographics, while determining a way to reduce motion sickness and alleviating SG complexity and difficulty.

1. Introduction

1.1. Context of Engineering Education

Engineering education is inherently interdisciplinary, encompassing a wide range of knowledge areas, such as mathematics, technology, and science, that prepare students to take on complex challenges. Throughout their academic journey, engineering students engage in diverse subjects varying from fundamental courses such as math and physics to more complex and specific ones, such as thermodynamics, machine learning, or control systems. Each is designed to enhance their proficiency across different knowledge domains and develop essential skill sets and problem-solving. Engineering curricula go beyond traditional subjects, integrating science, technology, engineering, and math (STEM) elements to develop analytical, problem-solving, and technical skills [1]. As STEM education aims to strengthen students’ competencies in those four core areas, the increasing enrollment in STEM-related courses is a testament to its growing importance. Between 2007 and 2017, university enrollment in STEM fields across Europe rose from 22% to 28%, with notable increases in countries such as Germany, Greece, Finland, Estonia, Romania, and Portugal, reflecting the expanding emphasis on interdisciplinary education [2].

Despite the increase in enrollment, student retention rates are declining. According to Sithole [3], low academic performance, lack of self-efficacy, and socioeconomic factors contribute to a greater abandonment of STEM education. Several factors contributing to student dropout in STEM courses are directly associated with low academic performance during the first semester and failure in core STEM subjects such as mathematics, physics and chemistry [4]. These factors can be explained, besides the other reasons, by the type of teaching method applied.

1.2. Traditional Teaching Methods vs. New Methods

In more recent years, there has been a shift in traditional teaching methods. However, they remain primarily teacher-centered. These typical approaches involve passive learning, where the students mainly acquire knowledge through slide presentations, textbook readings, and lectures without the opportunity for practical learning and skill development. Such methods can negatively impact students’ long-term knowledge retention and motivation, especially after the evaluation phase of the subject [5].

In recent years, there has been an increase in the usage of different teaching methods and tools to overcome the challenges of traditional teaching methods. An example is immersive tools, showing great potential for STEM education; another is using more straightforward tools such as Problem-Based Learning (PBL).

Immersive tools are directly connected to spatial and visual dimensions created by computer-generated simulations. Recent research has also emphasized the importance of trust in the adoption of immersive educational technologies due to their effectiveness. An example is Metaverse environments, showcasing technological reliability, interpersonal dynamics, content quality, and learning outcomes [6]. The most traditional tools are virtual reality (VR), augmented reality (AR), and mixed reality (MR) [7].

The virtual reality continuum concerns the full extent of immersive tools, from physical to digital reality. This continuum includes several levels of immersion, with “reality” indicating the physical world and “digital reality” referring to entirely computer-generated scenarios. The intersection of these two dimensions is known as mixed reality. The virtual continuum is shown in Figure 1, demonstrating the various levels of immersion and the interaction between the real and virtual worlds.

1.3. Serious Games as a Pedagogical Tool

Digital or physical serious games (SGs) take advantage of immersive tools. Digital serious games use interactive media to create educational content or to simulate real-world problems/exercises where the user can train or learn a specific subject using any element from the virtual continuum [9]. In contrast, physical SGs are tangible, real-world activities or objects relying on direct interaction with physical materials or people. This is the start of physical reality in the virtual continuum.

SGs are developed to entertain the user and educate, train, or raise awareness on different topics and subjects related to STEM fields [10]. Serious games use immersive tools, offering enhanced visualization of abstract concepts, interaction with 3D simulations, and applying theoretical methods. These tools create a risk-free environment where users can engage in real-world problem-solving scenarios. SGs allow learners to explore a subject at their own pace, aligning their knowledge while often receiving immediate feedback. This combination of features makes SGs particularly useful for STEM education [11].

Immersive tools can be used as part of different applications in various sectors, such as business, education, finance, healthcare, manufacturing, military, real estate, entertainment, sports, tourism, and transportation. Since the post-pandemic period, the borders between the virtual and the real seem thinner and thinner, making these types of tools interesting in day-to-day activities [12].

Serious games can also help develop scientific research, as is the case with Borderlands Sciences (BLS), one of the most famous serious games within the Sciences field, focusing on pattern identification to improve the alignment of microbial DNA sequences [13]. Some other famous serious games that evidence the versatility of these tools and strengthen their importance and potential in science education are the cases of Foldit and Eterna [14] and Eyewire [15].

1.4. Gaps in the Literature and Research Questions

Even though immersive tools and serious games seem to have potential in engineering education, the current literature still has some gaps in this topic. Many systematic reviews only focus on STEM in general, and not the STEM fields applied to the engineering curricula, except engineering itself [11,16]. There is a need to understand how SGs can be adapted to each STEM area, what key points are vital to enhance SG engagement in the different fields, and how to increase the impact of game design features for a more immersive experience.

Based on these gaps, this systematic review aimed to address the following research questions:

(1)

“What are the common immersive tools and serious games used in engineering education, and how are they implemented?”

(2)

“How do these tools impact student engagement, learning, and motivation, compared to traditional teaching methods?”

(3)

“What are the limitations of immersive tools and serious games at the moment?”

This systematic review evaluated the effectiveness of immersive tools and serious games in enhancing knowledge retention, student engagement, and learning outcomes in engineering education.

2. Methodology

This research followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [17].

2.1. Search Strategy

This research was conducted in January 2025 and updated in May 2025. Four databases were used to conduct this study: Scopus, Web of Science, Dimensions, and Science Direct. Then, the keywords related to the subject were identified and grouped considering two main topics: different terms for gamification and terms related to learning and engineering. Group one had terms such as “gamification”, “game-based”, and “serious game”, whereas group two used “engineer”, “pedagogic”, and “learning environment” as key terms. Each word in group one was combined with the Boolean connector AND with each word from group two, creating nine different search groups in the respective databases.

For the Scopus database, the search was conducted through the following query, inserted in Title/Abstract/Keywords:

TITLE-ABS-KEY (“gamification” AND “engineer”) OR (“serious game” AND “engineer) OR (“game-based” AND “engineer”) OR (“gamification” AND “pedagogic”) OR (“serious game” AND “pedagogic”) OR (“game-based” AND “pedagogic”) OR (“gamification” AND “learning environment”) OR (“serious game” AND “learning environment”) OR (“game-based” AND “learning environment”);

The Web of Science database was searched through the “Topic” field; in the Dimensions database, the search was conducted in “Title and abstract”, and in the Science Direct database, the search was performed using the field “Title, abstract or author-specified keywords”. The query structure in these databases followed the same approach to the one used for Scopus.

In the records identification phase, automatic tools were employed to filter the information, helping to identify ineligible records before proceeding to further screening stages as follows: (1) date—only articles published between 2020 and 2025 were considered in the first phase; (2) the type of document was constrained to research articles (no systematic reviews nor gray literature were considered); (3) only peer-review journals were considered; and (4) only studies written in English were included. This process was carried out independently by two reviewers; a third reviewer resolved conflicts.

2.2. Eligibility Criteria

To be considered eligible, each study had to meet the following criteria: using immersive tools, including evaluation/feedback for the serious game, and involvement of university students in STEM disciplines related to/applicable in engineering courses. Based on the eligibility criteria, a text screening was performed (evaluating Title and Abstract in the first phase), where articles that did not seem related to the research topic were excluded.

The most common reasons for exclusion were 2D without using VR/AR, not being applied to university students enrolled in engineering-related courses, and no evaluation of the game. None of the articles were excluded because they contained little information, as long as the games were 3D/VR/AR games and the participants were university students.

2.3. Data Extraction and Synthesis

All the identified records were exported from the databases and imported into Rayyan. This software allowed for the identification and exclusion of duplicate records. A full-text analysis was then conducted to extract information and to assess whether the article was eligible for inclusion. Two independent reviewers managed the analysis of the records; a third reviewer resolved any conflicts.

A Microsoft Excel sheet was used to create detailed tables with key information from all the articles divided by categories: (1) general information—author, publication year, country, field; (2) sample—sample number, control sample, degree/course of the sample; (3) game characteristics—technology used, game objective, software; (4) game evaluation—type of evaluation, type of feedback gathering; (5) experiment results. Data was extracted directly to the Excel sheet, under each variable classification. If some of the information was missing, it was registered as “not mentioned” and excluded from the systematic review.

To systematize all the information while using visual representation, the PRISMA flow, MapCharts tools, and Microsoft Excel were used for different types of graphics.

Afterwards, snowballing techniques, including citation searching and citation tracking, were applied to identify other records that might be considered eligible.

2.4. Bias Assessment

Two different but complementary tools were used to carry out the bias assessment. The ROBINS-I tool was used in non-randomized studies [18], which are commonly used in educational research, where randomized allocation is not always feasible. RoB 2 is a Cochrane tool for assessing the risk of bias in randomized clinical trials [19]. It is structured into five domains covering the main types of bias that can affect the results of a study: the randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results. It was adapted into selection bias, reporting bias, and performance bias to support the nature of the included studies. The combination of both tools allowed for a methodologically appropriate evaluation of the studies to assess the risk of bias in the included studies.

The bias domains were evaluated as “High Risk”—severe limitations that might significantly impact the results; “Medium Risk”—some bias but will not have a significant impact on the results; and “Low Risk”—any or minimal bias with no effect on the results. In order to be considered Low Risk (LR), the interference should be almost zero; Medium Risk (MR) should be average but not as impactful; and High Risk (HR) should have some level of risk that might change the outcomes of the study. Two independent reviewers conducted the bias assessment; a third reviewer resolved disagreements.

3. Results

3.1. Research Results

In the first phase of the PRISMA methodology, 12.118 articles were identified and filtered using the automation tools from the databases. The reasons for excluding were as follows: (1) 6.078 were outside the period of reference, (2) 2.653 were excluded due to document type, (3) two studies were excluded because of source type, and (4) 210 were excluded because of publishing language. After reading the title and abstract, another 2.819 articles were excluded for not complying with the research topic. After all these processes, the articles were uploaded to Rayyan, where 297 duplicates were identified and removed, and a total of 59 records were moved to the eligibility assessment stage. Five of the fifty-nine records could not be retrieved after contacting the authors. In addition, after a full-text analysis, thirty-three articles were excluded for the following reasons: not using 3D/VR/AR (seven), not applied to undergraduates (eight), no evaluation performed (five), outside of the STEM field or not related to Engineering courses (twelve), and not specifying what type of technology was used (one). This methodology led to 21 studies being included in the qualitative synthesis. Different snowballing techniques were used; adding ten more articles through website search (eight) and citation searching (eight) was possible. A total of 31 articles covering classes in different STEM fields taught in engineering courses across various university student classes were included in this systematic review. The whole process is summarized in Figure 2.

3.2. Studies’ Content Analysis

In Figure 3, the articles’ geographical distribution is presented, in addition to the STEM field under study. Some articles focused on one particular field (i.e., engineering, represented in orange), while others were a combination of two or more fields (i.e., science, technology, engineering, and math, represented in red). The country with the highest number of articles is the United States of America [20,21,22,23,24], followed by Mexico [25,26,27,28], the United Kingdom [29,30], and Nigeria [31,32]. This systematic review encompasses works from 20 countries, showing that these tools are widespread.

In Figure 4, it is possible to observe the distribution of published papers by year; 2023 and 2024 were the most recurrent years, with a total of six articles, followed by 2020, with five, and 2021, with four. Articles prior to 2020 were added through snowballing techniques.

This systematic review only included journal articles. Figure 5 reflects which journals the articles come from.

After the contextualization of the statistics, a thorough STEM analysis was conducted, classifying articles under each field, as seen in Figure 6. The analysis of the selected articles shows that most studies following the trend of immersive tools are concentrated in the areas of engineering [21,23,25,26,27,28,29,33,34,35,36,37,38,39,40,41], followed by science [22,42,43], tech [20,31,44], and math [24,30,45]. The findings also indicate that immersive tools were applied in interdisciplinary studies, particularly when combining two or more STEM areas. This is observed in combinations such as technology/science [46], technology/engineering [47,48], engineering/science [32], and integrated STEM [49,50]. Figure 6 also provides a detailed overview of the specific fields within each STEM area. The fields with the highest number of articles are electrical engineering [26,27,28,41] and civil engineering [12,14,27,29,30,32]. Overall, 21 STEM sub-fields were identified across different serious games, demonstrating these immersive tools’ wide diversity and potential.

Figure 7 shows that Unity was the most used game engine [21,26,30,31,34,35,38,40,41,42,43,46,47,49], especially for VR applications, with six out of thirteen VR-based games developed using this engine. Out of those thirteen, four did not specify the game engine [29,32,33,48]. A significant proportion of the serious games were developed using virtual reality [23,24,29,31,32,33,40,41,42,43,45,46,48], 3D [20,22,25,30,34,36,38,39,50], and augmented reality [26,27,28,35,44,47]. Some studies employed combinations of immersive technologies, such as VR/AR [21,49] and 3D/VR/AR [37]. On the other hand, for 3D environments, the engines were more diverse, which can be attributed to the use of existing games or game software to develop their own serious game. Only four of the six AR-based articles explicitly stated the Unity game engine [26,35,44,47].

Some immersive tools require specialized hardware beyond standard computers or mobile devices. For example, VR typically uses head-mounted displays (HMDs) to enhance user immersion in a digital scenario. Figure 8 depicts several combinations and possibilities of HMD use, reporting the standard-use models.

The most used models were HTC Vive (HTC VIVE PRO [42] and HTC VIVE [41]) and Oculus Rift [40,45]. Microsoft Hololens 2 [21] and Cave Automatic Virtual Environment (CAVE) TM [14] were the least frequently used devices. CAVE is a VR system that utilizes large projection screens in a closed room. The screens usually display a 3D, high-quality, immersive scenario. The CAVE TM system, in turn, relies on four back-projection display screens, stereoscopic and synchronized image rendering, and magnetically tracked 3D input devices. The physical dimensions of the CAVE system are 304 cm × 304 cm × 274 cm [23].

In the VR/AR category, one article used Microsoft HoloLens 2, and another did not specify what type of HMD was used. The article under the 3D/VR/AR category does not specify the head-mounted display (HMD) type used. Of all 16 articles with VR, 10 do not specify what kind of HMD was used [24,29,31,32,33,37,43,46,48,49].

Training effectiveness and student feedback were also analyzed; it was concluded that their assessment used subjective and objective methods for both parameters, though

Table 1. Training effectiveness assessment methods.

Tool	Method	Control Group	Study
Not specified	Not Specified	No	[36,50]
Performance	In-Game Tasks	Yes	[41]
		No	[22,31]
	Game Performance	No	[28] *
	Learning Management System	No	[24]
Questionnaire	Not Specified	No	[23,32,35,48]
	Post-Game Questionnaire	Yes	[21,25,34,35] *
		No	[17,19,20,25,31,32,35,36,39] *
	Pre-Game Questionnaire	Yes	[29,38] *
		No	[30]
	User Experience Questionnaire	No	[49]
Quizzes	Pre- and Post-Game Quizzes	Yes	[45]
Test	Pre-Game Post-Game	Yes	[26]
		No	[12,26]

Refs. [20,25,35]. * Article using combined methodologies.

reflects a higher use of objective tools such as questionnaires, quizzes, and tests. Subjective methods, including questionnaires, interviews, and structured feedback, were preferred to assess participants’ feedback, as seen in

Table 2. Participants’ perception assessment methods.

Tool	Content	Study
Not specified	Not specified	[25,32,39,48]
Interview	Not specified (post-game)	[21,22,24,27,28,31,41]
	Learning outcomes	[30]
	Engagement and motivation	[30]
	Game mechanics and design	[30]
	Comparison to traditional learning	[30]
Questionnaire	Not specified	[34,36,45]
	Game experience questionnaire	[47]
	Pre- and post-game questionnaire	[26]
	Feedback	[20,33,37]
	Intrinsic Motivation Inventory	[35]
	User Experience Questionnaire	[17,26]
	Presence and immersion in virtual reality	[49]
	System Usability Scale	[43]
	Technology Acceptance Model	[43]
	Presence Questionnaire	[43]
	Gamer Motivation Profile	[43]
Surveys	Not specified	[11,24]
	Feedback	[28,35]
	Participants’ experiences	[50]
	Prior to the game	[38]
Observation	Not specified	[20]

. Some points raised by the participants’ experience with the serious games were related to the immersion feeling, graphics quality, SG usefulness, user-friendly experience, engagement, motion sickness, dizziness, and learning outcomes.

It was interesting that some studies included additional tools to measure outcomes. For instance, one study utilized eye-tracking technology to analyze participants’ focus and engagement [21]. Another article recorded the in-game performance to evaluate participant performance and how participants interact with the game [24]. Pre-game introductions or tutorials have been utilized in some studies to enhance the overall effectiveness of the gaming experience [12,18,19,20]. This approach gave participants a clear understanding of the game’s objectives and aims, providing a more significant engagement and enhancing learning outcomes.

The bias assessment from the articles included in the systematic review is shown in

Table 3. Studies’ bias assessment.

Study	Biases Method	Selection Bias	Reporting Bias	Performance Bias
[33]	ROBINS I	MR	MR	LR
[43]	ROBINS I	MR	LR	LR
[49]	ROBINS I	HR	MR	MR
[25]	ROBINS I	HR	MR	HR
[20]	ROBINS I	HR	MR	LR
[46]	RoB 2	MR	LR	MR
[37]	ROBINS 1	MR	MR	MR
[41]	ROBINS I	MR	LR	MR
[42]	ROBINS I	HR	MR	MR
[38]	ROBINS 1	MR	LR	HR
[34]	ROBINS 1	MR	LR	MR
[31]	ROBINS 1	MR	LR	MR
[39]	ROBINS 1	HR	MR	LR
[50]	ROBINS 1	MR	LR	MR
[35]	ROBINS 1	MR	MR	MR
[47]	ROBINS 1	MR	LR	MR
[21]	ROBINS 1	MR	MR	LR
[29]	ROBINS 1	MR	LR	MR
[32]	ROBINS 1	MR	HR	MR
[26]	ROBINS 1	MR	LR	LR
[30]	ROBINS 1	MR	MR	LR
[36]	ROBINS 1	MR	LR	MR
[22]	RoB 2	LR	MR	MR
[48]	ROBINS 1	MR	LR	MR
[44]	ROBINS 1	MR	MR	HR
[40]	ROBINS 1	HR	MR	HR
[27]	ROBINS 1	MR	MR	LR
[28]	ROBINS 1	MR	MR	LR
[23]	ROBINS 1	MR	MR	MR
[24]	ROBINS 1	MR	MR	HR
[45]	ROBINS 1	HR	MR	HR

.

4. Discussion

Overall, the articles included in this systematic review indicate that immersive tools are generally well-received by university students. Compared to traditional pedagogic methods, immersive tools demonstrated superior performance, higher scores on tests and quizzes, and reduced time required to complete tasks [13,25,35].

Generally speaking, studies indicated an increased motivation and engagement during gameplay, facilitating a more effective and enjoyable learning process [12,21]. The preference may be related to the first-experience effect, where participants are engaged by trying a new tool or scenario in an immersive experience, presenting a great contrast with traditional teaching methods. In some studies, participants found the experience enjoyable and highly beneficial for knowledge acquisition/retention. They also expressed a desire to expand the serious games to more subjects in their study curricula [38].

The serious games that offered a greater sense of immersion were the ones that the participants preferred. For a serious game to be perceived as immersive, it is essential that it have good-quality graphics. According to participants’ feedback, that was a focal point of criticism or improvement [11,24,33,35,37]. It is necessary to consider that even though a more realistic game increases the sense of immersion, it also increases the need for a more robust computer/laptop not to lose frames per second (fps) so the game runs smoothly. If the fps are unstable, motion sickness and dizziness might increase, which is one of the side effects of using these tools. Motion sickness can be assessed through participants’ feedback or using specific questionnaires, such as the motion sickness assessment questionnaire. To minimize motion sickness and regulate participants’ stress, objects like chairs can be incorporated into the game setup to improve comfort and overall user experience in immersive environments. In the study of Maragkou [42], for instance, a rotating wheelchair proved helpful in reducing side effects due to motion sickness during a seismic simulation or the simulator sickness questionnaire. Still, other equipment can be added to support data collection in the game setup branch. For example, eye-tracking technology can assess whether the participant is focusing on the serious game or becoming distracted [21]. Other sensors, such as Arduino Mega’s [27], can be used for enhanced interactivity and performance monitoring. While the first provides valuable insights into user engagement and cognitive load, the latter enables real-time collection and data integration.

Immersive tools such as VR/3D/AR are also seen as a challenging but rewarding experience, creating a desire to learn more and try out different scenarios while creating valuable skill sets [32,35]. However, some participants stated that even though the serious games seemed interesting, they felt lost while playing them or did not understand the game concept at first, not allowing them to take full advantage of the immersive tool [11,20]. To overcome these difficulties, it is advisable to introduce a pre-game tutorial [20,31] or a voice assistant throughout the game [31]. When the SG comprised different difficulty levels, it was perceived as unbalanced, as seen in Gill et al. [35], where students disapproved of the difference in complexity between puzzle solving tasks during the serious game, but in the end, the advantages outweighed the disadvantages [37,44].

Concerning knowledge retention, it is advisable to include long-term knowledge retention and feedback assessments, as seen in the studies of Graham [20] and Sandoval Pérez [26]. Also, a long-term comparative analysis between traditional learning methods and serious games can be conducted, or at least extended testing using similar serious games can be performed over time.

The relatively high hardware and technology costs associated with immersive tools are the most significant barriers to implementation [15,19]. Additionally, a low stress level was reported in scenarios where real-life situations typically induce some degree of stress [42]. Stress inducement can be achieved by utilizing soundtracks and editing the camera to heighten tension. Additionally, if an incorrect answer is selected, a brief animation can be displayed to illustrate the consequences of the decision.

The following subsections discuss the benefits, limitations, and suggested solutions/points of focus across different STEM areas.

4.1. Science

Only three of the thirty-one articles in the systematic review relate to science [25,31,33]. The limited number of studies in this field can be attributed to the minimal emphasis on scientific disciplines within engineering curricula, since engineering courses are often associated with practical applications and problem-solving skills in technical fields. In contrast, pure science curricula, such as medical education, use these tools and games to help students develop and improve skills required for clinical (practical) practice [51].

Despite this, immersive tools that introduce the user to an immersive scenario are crucial for skill acquisition and decision-making, particularly in high-risk environments like a surgery simulation or an in-lab procedure. These technologies enable students to engage with various scenarios in a controlled, low-risk, and stress-free environment, creating an optimal setting for effective teaching and learning. Furthermore, 3D/VR/AR play a vital role in enhancing observational capabilities by enabling the examination of objects from multiple perspectives rather than relying solely on two-dimensional representations or video-based instructional methods commonly used in traditional pedagogy. This approach has even greater effects when joined with prior use tutorials [43].

Generally speaking, there was significant motivation and engagement while using the immersive tools compared to less sophisticated means such as video [43].

The science articles also include laboratories [43], where participants can visualize and actively engage in experimental simulations at their own pace. This approach enhances their adaptability to the laboratory environment, fostering a deeper understanding of experimental processes and improving their proficiency in scientific practice. The virtual tours are considered highly beneficial for the students [43].

When students play serious games related to science areas, they expect to be able to interact with the scenario and learn by trying; when that does not happen, it is seen as a limitation. It is also essential for the game to induce a certain level of stress in situations where it is expected for that feeling to exist in real life; if not, it can be seen as an in-game limitation, as seen in Maragkou et al. [42]. It is important to state that even though the students said these things in their feedback, the article had a certain selection bias.

Using serious games and immersive tools in science education is advantageous for a more engaging and interactive learning experience. However, SG developers must prioritize graphics quality, particularly for immersive tools that aim to represent or demonstrate concepts and objects that are challenging to visualize using traditional teaching methods [52].

4.2. Technology

Only three of the thirty-one articles are exclusively focused on technology. The represented sub-fields are cybersecurity [35,40] and computer science [31].

The included articles stated that using the immersive tools is a fun and interesting way to learn specific concepts, as seen in Graham [20], but there are still limitations related to the non-appealing graphics quality or, in a particular case, the game difficulty was way too complex [46].

Although these areas are inherently tied to technology, they present challenges in replicating pedagogical concepts in 3D/VR/AR, as they tend to be more theoretical and less visually demonstrative compared to other fields, as is the example of a serious game that exemplifies and enhances computational thinking [31] or of another where the participants needed to analyze a code [46]. It is challenging to develop a serious game that effectively addresses the text-intensive nature of coding while retaining engagement and motivation for the student.

To overcome these limitations, one possibility is to simplify overcomplex subjects and apply them to real-world scenarios where the participants engage in a serious game to learn and apply cybersecurity concepts to a real-world scenario [44].

4.3. Engineering

Engineering-related topics can be found in 16 out of the 31 articles included in the systematic review. Of these sixteen, eight are from different fields, showing the adaptability of immersive tools in a problem-solving domain such as engineering, as seen previously in Figure 4. These tools facilitate the visualization of abstract concepts such as complex electrical systems (e.g., alternating current circuits) [27], computational fluid dynamics simulations (e.g., water flow in hydraulic turbines) [36], or structural modeling (e.g., material strength under varying conditions) [40]. These tools provide opportunities to engage with different types of problems and scenarios in a safe, risk-free environment, as in the construction sector, for example, which is directly related to dynamic scenarios with different kinds of hazards. The participants need to simulate a variety of actions related to on-site activities while simultaneously enhancing the development of industry-relevant skills.

This technology benefits the engineering curricula, helping students understand different concepts by visualizing them [24] and making them feel more confident about their skill set [36].

The major limitations pointed out in the engineering area come from the lack of different scenarios and limited infrastructures, where, in many cases, a simple solution is presented, leaving behind various types of possible approaches [26]. Other negative issues are the lack of clear guidance within games [34] and the inconsistency in difficulty levels within a serious game, where one stage is relatively simple and the next is disproportionately challenging [37], similar to previous feedback in Section 4.1. These aspects may lead to user frustration and negatively impact the learning experience.

To achieve the maximum potential of SGs in engineering, it is imperative to design diverse mechanics for different problem-solving methods while assisting participants in adapting to real-life situations [37]. Additionally, it is essential to structure the exercises with appropriate difficulty levels, organizing them into progressive levels of difficulty, such as those outlined in Bloom’s Taxonomy. Otherwise, there will be a risk of the participant getting frustrated and not taking full advantage of the serious game. This ensures learners gradually build their skills and knowledge [53].

4.4. Math

Mathematics is found in 3 of the 31 articles included in this systematic review, referring to three sub-fields: fractions [24], multivariable calculus [45] and general math [30]. As discussed for the technology field, the low number of studies can be attributed to the challenges in recreating abstract theoretical concepts in VR/AR. Mathematics is more theoretical and abstract due to subjects like algebra or calculus, making their adaptation to serious games more challenging.

Anagnostopoulou et al. [30] stated that the option of a Role Play Game (RPG) contributes to game engagement and motivation by creating a more interactive and immersive experience. These games also encourage collaborative learning, where participants must work together to solve math-related tasks. For that, they need to develop their critical thinking and problem-solving.

Even though immersive mathematics serious games can offer significant learning advantages, developing serious games related to math is challenging, especially compared to engineering and science, which are easier to adapt to real-world scenarios. Among others, the major limitations in this area are the challenge of adapting abstract concepts into a serious game format, the significant time required, and the challenges related to the visual adaptation of abstract concepts. Also, VR/AR technologies cannot always fully replace traditional theoretical instruction, expressing a need for a balanced integration of immersive tools with a traditional teaching method [45].

To overcome the previous limitations, serious games need to adapt the in-game difficulty to the participant’s knowledge, allowing them to progress through levels aligned with their knowledge [53]. Real-time corrective feedback is also beneficial, as it helps participants understand their mistakes and progress effectively without experiencing frustration. Additionally, animations can be employed to represent abstract concepts in a more engaging and accessible manner.

4.5. Cross-Disciplinary Studies in STEM

Six out of the thirty-one articles included in this review are on different serious games from various areas of STEM (two) [21,37], tech/science (one) [46], tech/engineering (two) [12,27], and engineering/science (one) [32]. These articles demonstrate the potential to integrate multiple areas of knowledge simultaneously. They report a significant increase in engagement and motivation across all domains while learning the respective topics, a positive and significant way to test knowledge and apply new concepts [46].

The advantage of combining different STEM areas into a serious game is the games’ ease and realism, which can be related to real-life scenarios that a future engineer will encounter in their working life. With these in mind, students can learn in a more engaging environment. An example of this is seen in the study of Smith et al. [32], where science and engineering are integrated into a serious game teaching participants to apply theoretical scientific principles related to combustion and gasification in hydrogen production to practical engineering challenges/situations. Participants design and optimize a hydrogen production facility and must consider key engineering concepts such as site selection, infrastructure requirements, and process efficiency. This approach directly connects fundamental concepts in thermodynamics, reaction kinetics, and environmental assessment to real-world engineering decisions.

The limitations are constrained to those seen in specific STEM areas.

Table 4. STEM field comparison.

STEM Field	Difficulty in Creating the SG	Real-World Applications	Limitations	Key Points to Enhance Serious Games	Best Immersive Tech
Science	Low to Medium	Virtual labs/ simulations	Lacks stress; high visual quality needed	Pre-game tutorials, immersive scenarios, stress simulation, multi-angle interaction	VR
Technology	High	Cybersecurity, programming logic	Abstract code is hard to visualize	Real-world tasks, simplified interaction, structured logic flow	AR
Engineering	Low to Medium	Construction, electrical systems testing, hydraulic and fluid dynamics, structural engineering, processes, and manufacturing	Inconsistent difficulty, unclear guidance, and a few scenario branches	Multi-solution paths, progressive levels, voice guidance, realistic risk-free simulations	VR/AR
Math	High	Visualizing abstract concepts	Difficult to visualize theory	Adaptive difficulty, animations, instant feedback, and collaborative RPG setup	3D

allows for direct comparison across STEM fields. While serious games under science and engineering are easier to create due to their real-world applicability, technological and mathematical games are harder due to their abstract and theoretical base. All the fields present limitations and key points that should be considered to obtain the best results possible during SG creation.

Regarding the best immersive technology to be used for each type of field, the more practical fields are better for the usage of VR/AR, while for the more theoretical ones, like mathematics, 3D should be the way to go. In the case of technology, AR can also be seen as a valid option for code studying or cybersecurity threats.

Based on the findings in Table 4, it is possible to set a set of design features that contribute to achieving the full potential of immersive tools used in serious games. A definition of objectives and tasks which gives clear instructions to the participant is critical to reduce possible participant frustration. Also, having a gradual difficulty increase across levels is important for the same reason. Whenever there is a high variability in participants’ backgrounds, it is advisable to start with shorter levels with slight difficulty and increase both difficulty and duration along the gameplay. It was also realized that it is important to give immediate feedback so the participants can understand what they are doing and how to correct it whenever they are doing something wrong. Finally, it is of the utmost interest to have the best graphics quality possible, to create an interactive environment with different options, and to mimic real-world situations.

When comparing the present systematic review with another study focusing on digital integration [49], it is possible to observe some key points. Both reviews find that digital/immersive technologies enhance student engagement through interactive and game-based learning experiences. These tools also improve critical thinking, problem-solving, and collaboration competencies. While the previous study on digital tools focuses on a broader STEM perspective, studying the impact on undergraduate and high school students, the present systematic review concentrates only on STEM related to engineering curricula. The digital integration review [49] also evaluates the 2D approach, where the engagement was high, especially for younger students, and the games were easier to implement and use, while the technical challenges were few. In the present review, the use of immersive tools relates to higher engagement, especially in the visual and interactivity aspects, higher retention of knowledge, and more real-life situations that could be trained, but, on the other hand, requires more expensive and advanced hardware/setup and, in some cases, it can lead to some issues or discomfort like motion sickness.

4.6. Bias and Systematic Review Limitations

A critical analysis of bias across all the studies included shows that of all the 31 articles, 11 were rated as high-risk (HR) in at least one domain (bias assessment, bias performance, or reporting bias), the majority of those in performance assessment [20,24,25,32,38,39,40,42,44,45,49]. These ratings raise concerns about the validity of the findings, since the HR classification was often due to small sample sizes, with nine articles using below 30 participants [21,23,24,26,29,31,40,43,48], absence of control groups, or lack of randomization in the sample used, which can undermine the strength and certainty of the conclusions, requiring a cautious interpretation of the outcomes. Small sample sizes increase the risk of bias, the absence of a control group limits the ability to compare obtained results effectively, and the lack of randomization makes it challenging to determine the actual impact of the immersive tools. These limitations are noticeable in several articles in the systematic review. However, these articles were not excluded from the systematic review, as their feedback and knowledge contributions were valuable for developing serious games related to the engineering curriculum.

The ROBINS-I tool mainly identified moderate risk (MR) of bias across most domains, although in some cases, specific bias domains were classified as high-risk (HR). Studies assessed using the RoB 2 tool mostly presented low risk (LR) for selection bias, with a few cases classified as MR or HR. The articles assessed with RoB 2 are more reliable and trustworthy due to RoB 2 being designed explicitly for randomized studies, including stricter criteria related to randomization, reducing the risk of bias and increasing credibility. In comparison, studies assessed with ROBINS-I should not be discarded. Still, the evaluation and data assessment should be (and was) performed more carefully due to a high level of bias. To do so, it is vital to critically examine the study designs, sample sizes, and methodologies.

As for performance bias, studies and assessments using RoB 2 are classified as LR or MR. On the other hand, studies and assessments using the ROBINS-I tool presented heterogeneity between LR, MR, and HR. Even though some performance bias could exist, the results were always positive, not being strictly affected by the difference in the backgrounds of the samples.

Concerning reporting bias, most of the studies were classified as LR and MR, with only a few articles classified as HR using ROBINS-I and RoB 2. This means that the outcomes of the game are trustworthy in both cases, with studies stating what worked and what did not work during the use of the serious game. With these results, even though more than a third of the articles included in this systematic review have at least one domain rated as HR, only one was rated HR in reporting bias.

Studies assessed with ROBINS-I were found to have a higher risk of selection and performance bias, which could have influenced the outcome of the results. For RoB 2, the results are more accurate. This can be attributed to the fact that this type of assessment employed distinct methodologies to ensure randomization, thereby amplifying the reliability of the results. Regarding reporting bias, MR remained across both studies, showing that the results presented can be trusted, but still with some caution, which is important to keep a critical perspective.

The limitations of this systematic review include the absence of longitudinal studies, the presence of small sample sizes in some of the articles, and the heterogeneity across subjects and samples in different studies. As discussed, the heterogeneity across subjects can impact the articles’ performance because of how differently STEM areas work with these immersive tools. There is a lack of consistency in evaluation methods, with studies using diverse criteria and metrics, which makes cross-comparison difficult. Also, although all the articles in this systematic review address the engineering curriculum, the diversity of sub-fields within the STEM area isolates many cases, making it hard to compare their interdisciplinary applicability. The immersive tools also vary, from VR and AR to MR or combinations, which can significantly affect the results and feedback. A wide disparity of hardware equipment is also associated with this heterogeneity, where the equipment ranges from PCs to specialized VR HMDs. Overall, there is a lack of standardized protocols for evaluating immersive learning tools, necessitating a more unified framework that can consistently compare more real-world applications (engineering) with more theoretical ones (mathematics), depending on the type of tools inside the virtual continuum being used.

In conclusion, a key challenge is the comparison of studies that vary widely in how they measure the outcomes, ranging from subject self-reported questionnaires or interviews to objective in-game performance metrics. Different immersive tools do not help in this context, and methodological standardization needs to be created. For example, VR has a higher level of immersion than 3D, but 3D will be less expensive than VR, yielding various results based on the goal we are trying to achieve with each type of serious game, making it a hard comparison.

So, it is possible to have confidence in the final statistics and feedback results, even more so with the overall trend indicating that immersive tools and serious games positively impact student learning, motivation, and engagement.

In further research, a more rigorous and robust methodology, standardized evaluation of protocols, and longitudinal designs should be considered.

It is also important to consider that individuals with prior experience using immersive tools may not experience the same excitement and motivation as someone interacting with this educational method for the first time. However, they are generally more adaptable to these technologies, which could potentially impact the sample results compared to less experienced participants.

5. Conclusions

Serious games are useful for engaging and motivating students and adding value to their studying while helping them acquire knowledge. Due to their interactivity, they are especially effective in fields that involve real-world problems/scenarios, allowing students to try different concepts in a risk-free environment.

This systematic review is intended to address three main questions, the first being “What are the common immersive tools and serious games used in engineering education, and how are they implemented?”, to which there is no straightforward answer. The results highlight that the design and implementation of serious games are adapted to the specific objectives of the subject they are being used for. In science and engineering, the games focus on storytelling, using real-time feedback and object interaction; the go-to immersive tools, in this case, are VR/AR. Concerning mathematics, animations are used to explain abstract concepts, where the immersive tool that works best is 3D. In technology, the development of valuable serious games prioritizes simplifying complex content, adapting it to real-world scenarios, and trying to deconstruct abstract concepts to minimize text-heavy explanations of code, for example. The go-to immersive tools for this latter field are usually AR/3D-based.

The included studies report that high-quality graphics and realism should be maximized whenever possible in the visualization of complex structures and emphasize that tasks in problem-solving scenarios should be well-defined and unambiguous. When the aim is to simulate stressful situations, the game design should incorporate elements that create tension in the participants. For that, one can use soundtracks and camera effects. As for real-life set skills, such as lab training, the serious game should allow the participant to interact with as many objects as possible, allowing them to practice procedures without the risks of actual accidents.

So, how do these tools impact student engagement, learning, and motivation compared to traditional teaching methods? The findings of this systematic review conclude that serious games have considerable potential to consolidate knowledge autonomously, motivating and engaging students and allowing them to explore real-world scenarios on their own without being exposed to actual risks. For that to be achieved, serious games must be well-designed, ensuring that the game mechanics align with the challenges/requirements of each field. General factors, such as graphic quality, defined objectives/tasks, good fps rate, and immersion, contribute to the success of serious games. Serious game design should be well-planned to maximize effectiveness in each educational field. Even though these games are regarded as useful, it is recommended that they should not be used as a standalone tool but as a complementary teaching method, allowing students to learn at their own pace and engage with content aligned with their knowledge development and skill set.

Finally, concerning the limitations of immersive tools, the high hardware cost, the difficulty in creating different virtual reality scenarios, and the possibility of motion sickness can be pointed out.

Based on the findings, the following recommendations are proposed for teachers/trainers: the use of serious games should be a complement to traditional teaching methods, especially to display abstract concepts; pre-game tutorials or voice assistants should be implemented to improve students’ performance; gradual difficulty levels should be ensured in order to improve knowledge retention and progression throughout the curricula.

In addition, this systematic review identified important gaps for future research, such as the need for longitudinal studies on knowledge retention, standardization of evaluating methods, and better comparability between different immersive tools. These are some of the priorities for advancing the effectiveness and scalability of immersive educational tools.