This study scrutinizes the existing literature regarding the use of augmented reality and gamification in education to establish its theoretical basis. A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was conducted. To provide complete and valid information, all types of related studies for all educational stages and subjects throughout the years were investigated. In total, 670 articles from 5 databases (Scopus, Web of Science, Google Scholar, IEEE, and ERIC) were examined. Based on the results, using augmented reality and gamification in education can yield several benefits for students, assist educators, improve the educational process, and facilitate the transition toward technology-enhanced learning when used in a student-centered manner, following proper educational approaches and strategies and taking students’ knowledge, interests, unique characteristics, and personality traits into consideration. Students demonstrated positive behavioral, attitudinal, and psychological changes and increased engagement, motivation, active participation, knowledge acquisition, focus, curiosity, interest, enjoyment, academic performance, and learning outcomes. Teachers also assessed them positively. Virtual rewards were crucial for improving learning motivation. The need to develop appropriate validation tools, design techniques, and theories was apparent. Finally, their potential to create collaborative and personalized learning experiences and to promote and enhance students’ cognitive and social–emotional development was evident.

This study aims to evaluate the impact of using augmented reality, gamification, and serious games in computer science education. The study presents the development process of an educational mobile application, describes an experiment that was conducted and involved 117 higher education students, and analyzes the results of a 49-item paper-based questionnaire. In total, 8 research questions were explored. The results of the study revealed that several educational benefits can be yielded when integrating such applications in teaching and learning activities and actively involving students in the design and development process. In particular, the application was assessed as an effective learning tool that could enrich and improve the educational process and create interactive, inclusive, and student-centered learning environments. Its use led mostly to positive effects and experiences while maintaining the negative ones to a minimum and most students expressed positive emotions. Students were able to learn in a more enjoyable and interesting manner, and their motivation, engagement, self-efficacy, and immersion were greatly increased. Students’ innate need for autonomy, competence, and relatedness was satisfactorily met and both their intrinsic and extrinsic learning motivations were triggered. They felt a sense of belonging and cultivated their social skills. The potential of the application to improve students’ knowledge acquisition and academic achievements was also observed. The application also enabled students to improve their computational thinking and critical thinking skills. Therefore, the potential of combining augmented reality, gamification, and serious games to enhance students’ cognitive and social–emotional development was highlighted.

This study aims to understand the public’s perspectives, sentiments, attitudes, and discourses regarding the adoption, integration, and use of augmented reality and virtual reality in education and in general by analyzing social media data. Due to its nature, Twitter was the selected platform. Over 17 million tweets were retrieved from January 2010 to December 2020 and four datasets were created. Two of them referred to the general use of these technologies and two to their educational use. The data was analyzed using text mining, sentiment analysis (e.g., polarity and emotion detection), and topic modeling methods. TextBlob, Word-Emotion Association Lexicon (EmoLex), Valence Aware Dictionary for Sentiment Reasoning (VADER), and Latent Dirichlet Allocation (LDA) were some of the tools used. Based on the results, the majority of the public were positively disposed toward the general and the educational use of both augmented reality and virtual reality and mostly expressed positive emotions (e.g., anticipation, trust, and joy) when referring to them. In total, 11 topics emerged that were related to education, new technologies, digital and social media use, marketing and advertising, the industrial domain, the health domain, gaming, fitness and exercising, devices, the travel and tourism domain, and software development kits. The educational benefits of augmented reality and virtual reality, their ability to enrich both teaching and learning activities, and their role as effective educational means were evident.

“Interaction” represents a critical term in the augmented and mixed reality ecosystem. Today, in mixed reality environments and applications, interaction occupies the joint space between any combination of humans, physical environment, and computers. Although interaction methods and techniques have been extensively examined in recent decades in the field of human-computer interaction, they still should be reidentified in the context of immersive realities. The latest technological advancements in sensors, processing power and technologies, including the internet of things and the 5G GSM network, led to innovative and advanced input methods and enforced computer environmental perception. For example, ubiquitous sensors under a high-speed GSM network may enhance mobile users’ interactions with physical or virtual objects. As technological advancements emerge, researchers create umbrella terms to define their work, such as multimodal, tangible, and collaborative interactions. However, although they serve their purpose, various naming trends overlap in terminology, diverge in definitions, and lack modality and conceptual framework classifications. This paper presents a modality-based interaction-oriented diagram for researchers to position their work and defines taxonomy ground rules to expand and adjust this diagram when novel interaction approaches emerge.

The dimensionality curse phenomenon states that in high dimensional spaces distances between nearest and farthest points from query points become almost equal. Therefore, nearest neighbor calculations cannot discriminate candidate points. Many indexing methods that try to cope with the dimensionality curse in high dimensional spaces have been proposed, but, usually these methods end up behaving like the sequential scan over the database in terms of accessed pages when queries like k-Nearest Neighbors are examined. In this paper, we experiment with state of the art multi-attribute indexing methods and try to investigate when these methods reach their limits, namely, at what dimensionality a kNN query requires visiting all the data pages. In our experiments we compare the Hybrid Tree, the R*-tree, and, the iDistance Method.

This study aims to examine the combination of educational data mining and learning analytics with virtual reality, augmented reality, mixed reality, and the metaverse, its role in education, and its impact on teaching and learning. Therefore, a systematic literature review, a bibliometric and scientific mapping analysis, and a content analysis are carried out based on 70 relevant documents identified from six databases, namely, ACM, ERIC, IEEE, ScienceDirect, Scopus, and Web of Science (WoS) following the PRISMA framework. The documents were separated into the following three categories, (i) Theoretical and Review studies, (ii) Proposal and Showcase studies, and (iii) Experimental and Case studies and were examined from different dimensions through an in-depth content analysis using both quantitative and qualitative approaches. The documents were further analyzed using scientometric tools, such as Bibliometrix and VOSviewer and topic modeling through Latent Dirichlet Allocation (LDA). The most prominent topics, areas, and themes were revealed and the outcomes regarding the influence of this combination on learning and teaching were summarized. Based on the results, this combination can effectively enrich education, positively affect learning and teaching, offer deep and meaningful learning, and support both students and teachers. Additionally, it can support different educational approaches and strategies, various learning styles, and special education and be utilized in both formal and informal learning environments. The real-time identification, tracking, monitoring, analysis, and visualization of multimodal learning data of students’ behavior, emotions, cognitive and affective states and the overall learning and teaching processes emerged as a significant benefit that contributes greatly to the realization of adaptive and personalized learning. Finally, it was revealed that the combination of extended reality technologies with learning analytics and educational data mining can support collaborative learning and social learning, improve students’ self-efficacy and self-regulated learning, and increase students’ learning gains, academic achievements, knowledge retention, motivation, and engagement.