Modern Digital and Technological Educational Methods

Abstract

The development and evolution of digital technologies can contribute to the transformation of the educational sector, allowing the integration of innovative teaching approaches. Typical examples of such approaches include artificial intelligence, augmented and virtual reality (AR/VR), adaptive learning, and online educational environments. This study explores modern digital educational methods, focusing on the advantages, challenges, and future prospects of modern technologies in education. The systematic literature review was based exclusively on the Scopus database. We explored 948 articles published from 1968 to 2025. Furthermore, using the VOSviewer program (version 1.6.20), the results were analyzed, identifying and highlighting various trends and key thematic areas. However, although digital educational methods are able to provide greater interactivity, personalization, and flexibility in learning, they also face significant challenges, some of which are the digital divide, privacy protection, and teacher training. In the future, research should shape best practices that will integrate digital technologies into education.

1. Introduction

The rapid development of digital technologies has brought about, among other sectors, significant changes in the education sector [1]. These changes contribute particularly to the development of new teaching approaches, utilizing modern digital tools. Modern digital educational methods are based on the integration of innovative technologies, such as augmented and virtual reality (AR/VR), artificial intelligence (AI), adaptive learning platforms, and online educational environments [2]. The ultimate goal of modern digital educational methods is to improve the learning experience and personalize educational interactivity.

The transition of the educational environment or teaching, from the traditional form to digital practices, allows the creation of personalized learning experiences, flexibility in access to educational material, and the strengthening of collaboration between learners. Collaboration can be implemented through both modern and asynchronous online tools [3]. At the same time, the use of big data and analytical learning allows, in addition to monitoring the progress of learners, the adaptation of educational content to their needs [4].

Despite the increasing use of digital teaching methods, their comparison with traditional approaches remains a matter of concern [5,6]. Digital methods, such as adaptive learning and gamification, offer dynamic learning environments and possibilities for personalization [7,8]. Understanding both the strengths and weaknesses of the above two approaches supports educators are choose the appropriate teaching method [9].

However, the application of digital methods in education is not without challenges. Issues such as the digital divide, educational equality, the protection of personal data, and training in the use of new technologies remain critical parameters that require systematic investigation [10].

The ultimate goal of this study is to examine modern digital educational methods. The results of the research focus on the analysis of education methods that are utilized in different countries. The bibliometric analysis that was implemented was based on the Scopus database, with a reference period from 1968 to 2025. In addition, the possibilities for future integration and upgrading of these technologies are evaluated.

2. Materials and Methods

An organized and methodical approach was adopted to conduct an in-depth bibliometric analysis of contemporary digital and technological approaches to education. The methodological process included the following stages.

2.1. Data Collection

Data were extracted from the Scopus database, which is renowned for its extensive coverage of the scientific literature and its rigorous indexing criteria through peer-reviewed processes. Scopus is one of the most complete and reliable sources of scientific publications worldwide. Scopus was chosen due to the breadth of coverage, the quality of the data, and the structure and analysis tools included. According to Mongeon et al. (2016), in contrast to other databases, such as the Web of Science (WoS), the Scopus database includes more open-access journals, which enhances scientific research [11]. Also, Falagas et al. (2008), on the topic of the quality of the data provided by the Scopus platform, claim that it is higher than others, since it includes rigorously evaluated publications, thus maintaining a balanced mix of theoretical and applied research [12]. The continuous updating of this specific database also ensures that the analysis is based on updated data [12]. Baas et al. (2020) share the same view and present Scopus as one of the largest curated abstract and citation databases, with a broad global and regional coverage of scientific journals, conference proceedings, and books [13]. Furthermore, Baas et al. (2020) report that Scopus implements extensive quality assurance processes that continuously monitor and improve all data elements. Scopus’s credibility has led to its use as a source of bibliometric data for large-scale analyses in research assessments, research landscape studies, political science assessments, and university rankings [13]. On the other hand, Burnham (2006) endorses the view that Scopus, created by the Elsevier publishing house, is a bibliography and citation database covering a wide range of scientific journals, books, and conference proceedings [14]. The evaluation highlights Scopus as a valuable tool for strengthening collections and supporting research activities, noting that, despite the incomplete coverage of both Scopus and Web of Science, the two databases are complementary [14]. In the same context, Chadegani et al. (2013) seek to offer a thorough comparison between the Scopus and Web of Science databases, analyzing both their qualitative and quantitative characteristics [15]. According to the study, Scopus provides broader journal coverage than Web of Science, which makes it particularly useful for bibliographic searches and citation analyses [15]. However, although the use of a single database is often sufficient for such literature searches, it is nevertheless recognized that it may limit a comprehensive coverage of the literature, omitting important studies that may exist in other databases, such as Web of Science or Google Scholar. In the future, the combined use of multiple databases may lead to a more comprehensive and accurate presentation of results.

The current literature review we conducted was limited to articles published between 1968 and February 2025. The search was carried out on 28 February 2025. The selection of this extended time period allowed the mapping of trends that developed over time, offering essential information on the dynamic evolution of digital technology in education, while emphasizing pedagogy and teaching practice. At the same time, the representativeness of the sample was enhanced through the selection of publications from different geographical regions and academic institutions.

2.2. Data Extraction and Selection Inclusion Criteria

Once relevant articles were identified, specific keywords were used to extract data from the titles, abstracts, and keyword sections of the publications. This targeted methodological approach allowed us to focus on studies that contribute substantially to the intersections of our main research interests. The search strategy adopted is presented in detail in

Table 1. Search strategy.

Database	Search Within	Keywords	No. of Sources
Scopus	Article title, Abstract, Keywords	modern AND digital AND (education or teaching) AND (method or methods)	2370

.

2.3. Inclusion Criteria

This study focused on journal articles related to digitization, education, and research methodologies, with the results filtered based on their relevance to the objectives pursued. In the first stage, a total of 2370 journals were evaluated; however, after applying inclusion criteria—such as publication of articles exclusively in English and in scholarly journals—the sample was limited to 948 journals, ensuring the quality and thematic accuracy of the selected sources. This process is presented in Figure 1.

In the systematic literature review, we followed the standards of Webster and Watson (2002) to reject an article [16]. We then evaluated the titles of 948 articles and, after reading their abstracts, we accepted 918. Further studies were rejected because their full text was not accessible. After the filtering process, 422 articles were included in the final phase of our search. The identification of this critical mass of relevant publications is illustrated in Figure 2.

2.4. Data Processing and Analysis

The collected data were processed using bibliometric tools such as VOSviewer, which allows advanced analyses of citation networks, co-authorship patterns, keyword co-occurrence, and research trends [17]. We chose this tool for its capabilities in visualizing complex networks and identifying important research topics and collaborations.

Network analysis is an increasingly popular tool for analyzing complex relationships between sectors and industries. Measuring all aspects of networks has made network analysis a central tool for analyzing bibliometric data [18].

Despite the advantages of the VOSviewer tool, it is necessary to recognize its limitations. Analysis based solely on Scopus data may miss important articles found in other databases.

2.5. Citation Analysis

This methodology allowed us to identify the most cited articles and journals, highlighting the important articles that have shaped the field [19].

2.6. Keyword Co-Occurrence Analysis

This method helped us identify frequently discussed topics and emerging trends, providing valuable insights into the most relevant issues in the field.

2.7. Co-Authorship and Collaboration Networks

By mapping co-author networks, we identified important authors and academic institutions, while simultaneously highlighting international trends in collaboration in research on teaching and education through digital technologies.

2.8. The Use of Artificial Intelligence Tools in Manuscript Preparation

During the preparation, writing, editing, and review stages of this manuscript, no artificial intelligence tools were utilized. The text and the captions of the images and tables were written by the authors.

In order to ensure the integrity, validity, and reliability of this manuscript, we also performed an independent AI content detection check. For this purpose, we used two freely available online platforms chosen purely randomly:

(a)

ZeroGPT, https://www.zerogpt.com/ (accessed on 25 April 2025);

(b)

PlagiarismDetector.net (AI Detector), https://plagiarismdetector.net/ai-content-detector (accessed on 25 April 2025).

We recognize that these tools, like most of those available online or offline, may not be completely reliable and may vary depending on the detection tool used. However, in this case, their results indicated that the text was assessed as human-generated.

3. Results

The findings from our search are presented below.

3.1. Quantitative Analysis

The results of our research date from 1968 to February 2025. No articles were published in the periods 1969–1971, 1973–1989, 1992–1993, and 1997–1998. On the contrary, from 2014 onwards, an increasing trend in digital teaching methods was observed. Figure 3 depicts the annual number of published articles in combination with the annual number of citations. Fluctuations can be observed in the reports from 1994 to February 2025.

Figure 4 shows the articles by thematic category to which they belong. The thematic area of “Social Sciences” holds 29%, followed by “Computer Sciences” with 14%. The high percentages in these two categories indicate the significant research activity of digital education methods and the growing interest of the scientific community in these areas. The combined dominance of these two thematic categories may also indicate the convergence of social research with technological developments, since artificial intelligence, data analysis, and the impact of digital media are critical issues for the modern era.

The third highest percentage is held by “Engineering” with 10%. This demonstrates not only the continuous evolution of this sector but also its contribution to the reshaping of the future, which can be achieved by incorporating innovation and technological progress. The “Engineering” sector plays a crucial role in the development and application of technologies related to the two previous categories, “Social Sciences” (29%) and “Computer Science” (14%). The interaction between these sectors is particularly intense, especially in issues such as smart technology, sustainable development, and the social impacts of engineering and technology.

Regarding the remaining thematic areas, they each represent percentages equal to or below 8%. Although these percentages can be considered low, they should in no case be underestimated, since they contribute valuable knowledge to the scientific community. Their current distribution and interconnections reflect research trends and highlight the dynamic nature of the sectors.

As shown in Figure 5, the spread of modern digital educational methods is recorded at a global level. This figure depicts the number of publications per country. Russia holds the lead, while China and Ukraine follow. These countries underline the global dimension of research in the field of digital teaching methods and pedagogy, with notable contributions from both developed and developing countries.

Russia leads with 184 publications, confirming its position as a central hub in this research. China follows with 140 publications, while Ukraine is in third place with 100 publications. In fourth place is the United States of America with 86 publications, while Germany ranks fifth with 46 publications. Then follows Kazakhstan, with 39 publications and other countries with fewer contributions. However, some countries have published only one article, which suggests new emerging trends or specialized contributions to the field.

The analysis of the geographical distribution of publications highlighted countries that are not traditionally considered pioneers in modern educational methods, while on the other hand, countries with a strong educational tradition, such as Finland (6 publications), were recorded with smaller numbers. This finding is due to the choice of the Scopus database, which, despite its reliability, does not include all relevant publications from various sources. For a more complete review of the use of modern educational methods, it would be advisable to use other scientific databases in future studies, such as Web of Science or ERIC, in order to achieve a more representative picture.

To complement the visual data in Figure 5,

Table 2. Top 10 countries by number of publications.

Country	Number of Publications	Percentage of Total (%)	Remarks
Russia	184	15.67	Significant increase in recent years; strong institutional research focus
China	140	11.94	Substantial investment in educational technologies and state-driven innovation
Ukraine	100	8.53	Emphasis on digital access and pedagogical modernization
United States	86	7.33	Consistent research presence; leader in EdTech startups
Germany	46	3.92	Focus on blended learning models and higher education innovation
Kazakhstan	39	3.32	Regional development programs promoting digital transformation in education
United Kingdom	39	3.24	Emphasis on hybrid education and data-driven methodologies
India	33	2.81	Emerging contributions in mobile and low-cost learning tools
Indonesia	29	2.47	Expansion of online learning platforms and teacher training initiatives
Poland	21	1.79	Growth in research on gamification and microlearning in schools and universities

provides a detailed breakdown of the top ten countries by number of publications. This table not only captures research output in absolute numbers but is also accompanied by brief observations that interpret the educational and technological context of each country. While countries such as Russia and China show steady growth, supported by targeted government investments in digital education, other countries such as Ukraine and Kazakhstan reflect regional efforts to modernize pedagogy and improve access to technologies. Developed countries such as the United States, the United Kingdom, and Germany contribute with a steady academic output and innovative practices in hybrid learning. At the same time, emerging countries such as India and Indonesia are emerging as important new “players”, with an emphasis on flexible and low-cost solutions. This distribution highlights the global and diverse nature of research in digital education, highlighting the need to consider not only the quantity but also the quality and context of research contributions.

The “Documents per Organization” (

Table 3. Documents per organization.

Documents per Organization
Country	Organization	No. of Publications
Russia	Vyatka State University	28
Russia	Kazan Federal University	23
Russia	Financial University under the Government of the Russian Federation	16
Russia	Sechenov First Moscow State Medical University	13
Ukraine	Interregional Academy of Personnel Management	11
Kazakhstan	Abai Kazakh National Pedagogical University	11
Ukraine	Kyiv National University of Culture and Arts	11
Russia	Plekhanov Russian University of Economics	10
Russia	HSE University	9
Russia	Moscow City Teacher Training University	8
Russia	RUDN University	8
Russia	Russian State Agrarian University—Moscow Timiryazev Agricultural Academy	8
Russia	Ural Federal University	8
Ukraine	Borys Grinchenko Kyiv Metropolitan University	8
Ukraine	Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University	8
Ukraine	Lviv Polytechnic National University	7
Kazakhstan	L.N. Gumilyov Eurasian National University	7
Russia	Russian State Social University	7
Ukraine	National Academy of Educational Sciences of Ukraine	7
Ukraine	National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”	6
Russia	Lomonosov Moscow State University	6
Russia	Bunin Yelets State University	6
Ukraine	Bogomolets National Medical University	5
Russia	Herzen State Pedagogical University of Russia	5
Russia	Russian Academy of Sciences	5
United Kingdom	University College London	5
Ukraine	Taras Shevchenko National University of Kyiv	5
Russia	Bauman Moscow State Technical University	5
Russia	Moscow Aviation Institute National Research University	5
Kazakhstan	Al Farabi Kazakh National University	5
Kazakhstan	Buketov Karagandy University	5
Russia	K.D. Ushinsky Yaroslavl State Pedagogical University	5
Russia	MIREA—Russian Technological University RTU MIREA	5
New Zealand	The University of Auckland	4
Mexico	Tecnológico de Monterrey	4
Ukraine	National Academy of Sciences of Ukraine	4
Russia	The State University of Management	4
Germany	Rheinisch-Westfälische Technische Hochschule Aachen	4
Canada	University of Toronto	4
Australia	Deakin University	4
Germany	Universitätsklinikum und Medizinische Fakultät Tübingen	4
Russia	Southern Federal University	4
Ukraine	V. N. Karazin Kharkiv National University	4
United States of America	Michigan State University	4
Russia	Saint Petersburg State University	4
Russia	Siberian Federal University	4
Ukraine	South Ukrainian National Pedagogical University named after K. D. Ushynsky	4
Ukraine	Luhansk Taras Shevchenko National University	4
Kazakhstan	M. Auezov South Kazakhstan University	4
Ukraine	Kamianets-Podilskyi Ivan Ohiienko National University	4
Russia	Moscow Polytechnic University	4
Crimea	V.I. Vernadsky Crimean Federal University	4
Saudi Arabia	Prince Sattam Bin Abdulaziz University	4
Germany	Klinikum der Universität München	3
Russia	Moscow Institute of Physics and Technology	3
China	Ministry of Education of the People’s Republic of China	3
Malaysia	Universiti Kebangsaan Malaysia	3
Slovakia	Univerzita Komenského v Bratislave	3
South Africa	University of South Africa	3
United Kingdom	The University of Manchester	3
Malaysia	Universiti Teknologi MARA	3
Singapore	Nanyang Technological University	3
United States of America	Mayo Clinic	3
China	Nanchang University	3
Croatia	University of Zagreb	3
Germany	Uniklinik Köln	3
Sweden	Linköpings Universitet	3
Switzerland	Universität Zürich	3
Germany	Julius-Maximilians-Universität Würzburg	3
United States of America	University of Maryland School of Medicine	3
United States of America	Northwestern University Feinberg School of Medicine	3
Taiwan	National Yunlin University of Science and Technology	3
Germany	Eberhard Karls Universität Tübingen	3
Russia	Altai State University, Barnaul	3
China	Guangxi Normal University	3
Ukraine	Oles Honchar Dnipro National University	3
Turkey	Ege Üniversitesi	3
China	Shanghai Jiao Tong University	3
Hungary	Eötvös Loránd Tudományegyetem	3
United Kingdom	University of Southampton	3
Germany	Charité—Universitätsmedizin Berlin	3
United Kingdom	University of Oxford	3
United States of America	Mayo Clinic Scottsdale-Phoenix, Arizona	3
China	University of Chinese Academy of Sciences	3
Germany	Ludwig-Maximilians-Universität München	3
Germany	Universitätsklinikum Erlangen	3
Ukraine	Odessa National Medical University	3
Russia	Moscow State Institute of International Relations MGIMO	3
Ukraine	Yuriy Fedkovych Chernivtsi National University	3
Russia	Moscow Pedagogical State University	3
Russia	Belgorod State University	3
Indonesia	Universitas Sebelas Maret	3
Russia	Platov South-Russian State Polytechnic University NPI	3
India	K L Deemed to be University	3
Jordan	Amman Arab University	3
China	Harbin University	3
Ukraine	West Ukrainian National University	3
Ukraine	Zhytomyr Ivan Franko State University	3
Ukraine	Dragomanov Ukrainian State University	3
Saudi Arabia	University of Ha’il	3
Russia	Russian State Vocational Pedagogical University	3
Roumania	Bucharest University of Economic Studies	3
Ukraine	Drohobych Ivan Franko State Pedagogical University	3
Ukraine	Donbas State Pedagogical University	3
Ukraine	Mykolayiv National Agrarian University	3
Turkey	Khoja Akhmet Yassawi International Kazakh-Turkish University	3
Russia	Taganrog Institute of Management and Economics	3
Ukraine	State Higher Educational Institution “University of Educational Management” of National Academy of Educational Sciences of Ukraine	3
Kazakhstan	Astana IT University	3
Ukraine	Khortytsia National Academy	3
Ukraine	Oleksandr Dovzhenko Hlukhiv National Pedagogical University	3
Ukraine	Institute of Pedagogy of the National Academy of Educational Sciences of Ukraine	3
Ukraine	Khmelnytskyi Humanitarian-Pedagogical Academy	3
Ukraine	Classic Private University	3
Hungary	Fazekas Mihály Primary and Secondary School	2
China	Hainan Vocational University of Science and Technology	2
Germany	Deutsche Schule Budapest	2
Germany	University of Münster	2
Iran	Urmia University	2
Germany	Humboldt-Universität zu Berlin	2
United kingdom	Loughborough University	2
Malaysia	Universiti Sains Malaysia	2
China	Guangdong Polytechnic Normal University	2
United kingdom	The University of Sheffield	2
Sweden	The Royal Institute of Technology KTH	2
United States of America	Harvard Medical School	2
Russia	Bashkir State Medical University	2
United States of America	The Ohio State University	2
Spain	Universidad de Málaga	2
Saudi Arabia	King Abdulaziz University	2
Hungary	Pécsi Tudományegyetem	2
Germany	Universitätsklinikum Hamburg-Eppendorf	2
Ireland	University College Dublin	2
Russia	Kuban State Agrarian University	2
United States of America	Johns Hopkins University	2
Germany	Ruhr-Universitat Bochum	2
United States of America	College of Sciences	2
Taiwan	National Taiwan University	2
South Africa	Tshwane University of Technology	2
United States of America	Johns Hopkins Medicine	2
China	The University of Hong Kong	2
Slovakia	Slovak University of Technology in Bratislava	2
Finland	Turun yliopisto	2
Russia	Pacific National University	2
Russia	Ural State Law University	2
Germany	Goethe-Universität Frankfurt am Main	2
United States of America	University of Kansas Medical Center	2
India	Amrita Institute of Medical Sciences India	2
Brazil	Universidade de São Paulo	2
United kingdom	University of Salford	2
Russia	Moscow State University of Psychology and Education	2
Russia	Irkutskij Gosudarstvennyj Tehniceskij Universitet	2
Canada	University of Montreal	2
Turkey	Ege University Medical School	2
Russia	University of Tyumen	2
Russia	National University of Oil and Gas «Gubkin University»	2
Nigeria	University of Ilorin	2
Germany	Universitätsklinikum Ulm	2
Ireland	Trinity College Dublin	2

) presents the number of publications, per country and organization or educational institution.

From the results of the previous Table 3, Figure 6 emerges, which depicts on a world map by country the number of total articles, for all organizations based in each country. That is, the sum of the publications of all organizations of a country creates the final result in this image. The first place with a number of 240 publications is held by Russia, while Ukraine follows with 133 publications. Germany is next with 43 publications, followed by Kazakhstan with 35. Other countries such as the United States of America, China, the United Kingdom, Saudi Arabia, etc., follow with a smaller number of publications. At the base, with just two publications per country in all organizations, are Brazil, Finland, Iran, Nigeria, and Spain. Meanwhile, there are also several countries with zero publications by their organizations regarding digital education methods.

3.2. Analysis of the Most Cited Articles

Table 4. Top 20 most highly cited publications.

No.	Articles	Citations
1	Kokotsaki, D., Menzies, V., Wiggins, A., Project-based learning: A review of the literature (2016), Journal Improving Schools, vol. 19, no. 3, pp. 267–277 [20]	717
2	Hatzinakos, D., Chrysostomos, L., Blind Equalization Using a Tricepstrum-Based Algorithm (1991), Journal IEEE Transactions on Communications, vol. 39, no. 5, pp. 669–682 [21]	161
3	Kessler, H., Mathers, S., Sobisch, H.-G., The capture and dissemination of integrated 3D geospatial knowledge at the British Geological Survey using GSI3D software and methodology (2009), Journal Computers and Geosciences, vol. 35, no. 6, pp. 1311–1321 [22]	142
4	Fierson, W. M., Capone, A., Gramet, D. B., Blocker, R. J., Bradford, G. E., Ellis, G. S., Lehman, S. S., Rubin, S. E., Siatkowski R. M., Ruben J. B., Telemedicine for evaluation of retinopathy of prematurity (2015) Journal Pediatris, vol. 135, no. 1 pp. e238–e254 [23]	137
5	Wen, K. Y., Kreps, G., Zhu, F., Miller, S., Consumers’ perceptions about and use of the Internet for personal health records and health information exchange: Analysis of the 2007 Health Information National Trends Survey (2010), Journal of Medical Internet Research, vol. 12, no. 4, pp. e73p.1–e73p.16 [24]	112
6	Chen, X., Chang-Richards, A. Y., Pelosi, A., Yaodong, J., Xueson, S., Siddiqui, M. K., Yang, N., Implementation of technologies in the construction industry: a systematic review (2022), Journal Engineering, Construction and Architectural Management, vol. 29, no. 8, pp. 3181–3209 [25]	106
7	Tavel, M., Cardiac auscultation: A glorious past—and it does have a future! (2006), Journal Circulation, vol. 113, no.9, pp. 1255–1259 [26]	101
8	Cukurova, M., Luckin, R., Millan, E., Mavrakis, M., The NISPI framework: Analysing collaborative problem-solving from students’ physical interactions (2018), Journal Computers and Education, vol. 116, pp. 93–109 [27]	94
9	O’Reilly, M. K., Reese, S., Herlihy, T., Geoghegan, T., Cantwell, C. P., Feeney, R. N. M., Jones, J. F. X., Fabrication and assessment of 3D printed anatomical models of the lower limb for anatomical teaching and femoral vessel access training in medicine (2016), Journal Anatomical Sciences Education, vol. 9, no. 1, pp. 71–79 [28]	94
10	Montello, D. R., Cognitive research in GI science: Recent achievements and future prospects (2009), Journal Geography Compass, vol. 3, no. 5, pp. 1824–1840 [29]	78
11	Mustafa, N., Ismail, Z., Tasir, Z., Mohamad Said, M. N. H., A meta-analysis on effective strategies for integrated STEM education (2016), Journal Advanced Science Letters, vol. 22, no. 12, pp. 4225–4288 [30]	74
12	Huang, C., Designing high-quality interactive multimedia learning modules (2005), Journal Computerized Medical Imaging and Graphics, vol. 29, no. 2–3, pp. 223–233 [31]	73
13	Liu, Z. Y., Shaikh, Z. A., Gazizova, F., Using the concept of game-based learning in education (2020), International Journal of Emerging Technologies in Learning, vol. 15, no. 14, pp. 53–64 [32]	72
14	Ren, Z., Wan, J., Deng, P., Machine-Learning-Driven Digital Twin for Lifecycle Management of Complex Equipment (2022), Journal IEEE Transactions on Emerging Topics in Computing, vol. 10, no. 1, pp.9–22 [33]	69
15	Liu, Z. J., Tretyakova, N., Federov, V., Kharakhording, M., Digital literacy and digital didactics as the basis for new learning models development (2020), International Journal of Emerging Technologies in Learning, vol. 15, no. 14, pp. 4–18 [34]	67
16	Fuchsova, M., Korenova, L., Visualisation in basic science and engineering education of future primary school teachers in human biology education using augmented reality (2019), European Journal of Contemporary Education, vol. 8, no. 1, pp. 92–102 [35]	66
17	Parham, G. P., Mwanahamuntu, M. H., Pfaendler, K. S., Sahasrabuddhe, V. V., Myung, D., Mkumba, G., Kapambwe, S., Mwanza, B., Chibwesha, C., Hicks, M. L., Stringer, J. S. A., EC3-A modern telecommunications matrix for cervical cancer prevention in Zambia (2010), Journal of Lower Genital Tract Disease, vol. 14, no. 3, pp. 167–173 [36]	64
18	Frolova, E. V., Rogach, O. V., Ryabova, T. M., Digitalization of education in modern scientific discourse: New trends and risks analysis (2020), European Journal of Contemporary Education, vol. 9, no. 2, pp. 331–336 [37]	61
19	Calazans, N. L. V., Moraes, F. G., Digitalization of education in modern scientific discourse: New trends and risks analysis (2001), Journal IEEE Transactions on Education, vol. 44, no. 2, pp. 109–119 [38]	57
20	Mesko, B., Gyrffy, Z., Kollár, J., Digital literacy in the medical curriculum: A course with social media tools and gamification (2015), JMIR Medical Education, vol. 1, no. 2 [39]	56

provides a list of the twenty most frequently cited publications in our research area. These are key contributions that have helped shape the debate, not only on digital educational methods in teaching but also on pedagogy, reflecting the studies that have had the most significant impact in the field.

The most cited publications include pioneering works that introduce key methodologies in education. Examples of such are personalized learning systems, artificial intelligence-based simulations, and the application of machine learning to data analysis. Their high number of citations indicates not only their importance and contribution but also their prominent position in advancing educational research. The information gathered from these twenty articles, on the main research topics, methodologies, and results, has influenced the development of various educational tools.

The aforementioned articles, which focus on the field of digital educational methods, highlight the ever-increasing importance of technology in education. The study by Kokotsaki, Menzies, and Wiggins (2016) presents an extensive overview of project-based learning, with 717 references [20]. This particular study approaches the enhancement of collaboration between students, critical thinking, and practical application of knowledge, making it particularly important in digital learning environments.

On the other hand, the article by Cukurova et al. (2018), with 94 citations, proposes the NISPI framework, which analyzes collaborative problem solving through natural interactions of students [27]. It is a technology that can support and enhance collaboration through interactive tools and platforms, such as adaptive learning systems and virtual reality (VR) tools.

Also important is the contribution of the study by Liu et al. (2020), with 72 citations, which focuses on the use of gamification in learning [34]. According to this study, the integration of game elements into the educational process increases student engagement and enhances memory and understanding, while applications such as “Kahoot!” provide dynamic solutions for the active participation of learners.

Finally, the study by Frolova et al. (2020) with 61 citations examines the trends and risks associated with the digital transformation of education [37]. The researchers highlight the challenge of maintaining the quality of the educational process, while at the same time addressing issues of inequality in access and privacy.

The studies in this table not only highlight how modern digital educational methods expand the possibilities of personalized learning but also introduce new challenges related to technological innovation and social equity in education.

3.3. Keyword Co-Occurrence Analysis

Figure 7 was created with the VOSviewer program and presents a thematic keyword map. It depicts the networking of scientific terms, based on their frequency of occurrence and their interrelationships. Both the nodes and the connections highlight the dominant research themes and their interrelationships. Regarding the analysis of the map, we observe four main thematic areas:

• The red area is related to education and digital technologies, including keywords such as “e-learning”, “students”, “digital technologies”, “virtual reality”, and “artificial intelligence”.
• The green area focuses on social sciences and health, with keywords such as “human”, “woman”, “man”, “health”, “social media”, and “digital health”.
• The blue area concerns both the educational process and teaching methods, including words such as “learning”, “education”, and “problem-based learning”.
• The purple area is associated with medical education, consisting of terms such as “medical”, “students”, and “dental education”.

The composition of all these areas indicates on the one hand the intense interaction of education with digital technologies, while on the other hand highlighting the importance of social sciences and health in the research process.

Figure 8, also created with the VOSviewer program, illustrates the correlations between research topics, according to their chronological development. The color scale at the bottom of the image indicates the temporal distribution of keywords, where older publications are rendered in darker blue, while the most recent ones are in light yellow. Four main thematic areas are distinguished:

• The yellow zone on the right is related to education and digital technologies (“e-learning”, “students”, “digital technologies”, “virtual reality”, “artificial intelligence”), with the most recent of these studies focusing on the digitalization of education and its adoption of new technologies.
• The green area in the center and left includes the social and health sciences (“human”, “health”, “digital health”, “social media”), with a particular emphasis on telemedicine and online communication issues.
• The blue area concerns the educational process (“education”, “learning”, “problem-based learning”).
• The dark blue area delimits keywords, such as “patient education” and “surveys and questionnaires”, focusing on a time period of past years.

Figure 8 depicts the majority of keywords in the period of 1968–2025. The VOSviewer program has, however, included in the image legend only the period of 2016–2025, although all the data for the entire period of 1968–2025 were utilized. However, this is a specific period where it displays a greater volume of studies and articles containing relevant keywords compared to previous years. A possible explanation could be the increasing use of digital methods in the last decade, especially after the emergence of the COVID-19 pandemic, in which the needs for investments and utilization of new technologies increased.

To summarize, Figure 8 captures the evolution of research on digital educational technologies, highlighting the significant increase in interest in digital learning and modern technological innovations.

In addition, Figure 9 presents the thematic keyword density map, illustrating the frequency of occurrence and importance of specific terms in various research publications. The brighter the areas (yellow–green), the higher the frequency of use, while on the other hand, the darker the areas (blue), the lower the frequency. This map confirms the increasing focus of the scientific community on digital technologies and educational innovation, reflecting the trends and developments of contemporary research.

3.4. Co-Citation and Bibliographic Coupling

Figure 10 depicts the relationships between authors who are most frequently cited together in scientific publications in the field of modern digital and technological educational methods.

Each color-coded group represents authors with common research areas. On the other hand, the connecting lines indicate the frequency and intensity of co-citations between them.

As for the red group, it includes authors such as Zhang Y., Wang Y., and Liu Y., who are at the center of the map. Their research concerns digital teaching methods and innovative educational practices. Their strong connections indicate close interactions and significant contributions to the scientific community.

Secondly, in the green group are Prensly M. and Mishra P. These authors focus on the integration of technology in education and the implementation of blended learning.

In the blue group, Popkova E.G. focuses on the economic and social impacts of digitalization in education, while the purple group consists of Meshalkin V.P. and Butusov O.B., who are active in more specialized areas of research.

Some authors, such as Papadakis S., are located in more peripheral positions on the map. This suggests that their studies are less frequently reported in collaboration with others.

Overall, the map captures the thematic diversity of the field of digital educational methods, highlighting the central research topics and the relationships between them. Strong connections in the main clusters reveal research collaboration and interaction, while peripheral nodes reflect independent or more specialized approaches.

In conclusion, Figure 11 presents bibliographically coupled authors. These are authors who either cite common sources in their scientific publications or have common research interests. Each colored group represents a group of authors with strong bibliographic links, while the distance between them also reflects their degree of connection.

In this figure, the authors are observed to have sparsely distributed nodes. This indicates a low degree of bibliographic coupling and limited common references between them. However, as it turns out, there are different groups, each of which represents an independent thematic unit or research direction. For example, Potchen E.J. and Handy Y. are represented in individual points, which indicates that their studies do not intersect significantly with those of the other authors.

Furthermore, it is observed that the authors Schnider D. and Hömöstrei M. share the same node. This implies a stronger bibliographic connection between them, possibly due to either common references or similar research interests. In contrast, authors such as Dobrovolska A. and Zhang J. are isolated, indicating that their publications have little or no common sources with the other authors. Overall, this map highlights the thematic differentiation among authors in the field of modern digital and technological educational methods. The absence of a strong connection between the nodes suggests that these researchers follow different approaches or focus on separate subfields of the scientific field.

4. Discussion

The evolution of technology, over the years, has brought about radical changes in the field of education. This is because it has incorporated new teaching methods, based not only on digital tools but also on innovative techniques. These approaches aim to provide, on the one hand, flexible and, on the other hand, interactive learning experiences that adapt to the needs of each student. In our research, we focused on four main digital educational methods: adaptive learning, gamification, microlearning, and learning through virtual/augmented reality (VR/AR).

4.1. Adaptive Learning

Adaptive learning is based on the use of artificial intelligence and data analysis to create personalized learning paths [40]. In contrast to traditional education, where all learners follow the same learning pace, this method allows the adaptation of educational material to both the needs and the performance of each learner. As for the operating mechanism of adaptive learning, it consists of artificial intelligence algorithms that monitor the progress of education through interactive tests and assessments [41]. In addition, these algorithms analyze the data and suggest exercises or clarifying videos if they identify weaknesses in learning. They also provide personalized learning paths, reducing the feeling of frustration and improving understanding. Some characteristic benefits of this method are the ability of each learner to learn at their own pace, the reduction in cognitive gaps, since it is able to automatically identify any difficulties during learning, and the provision of real-time feedback to both students and teachers. Examples of adaptive learning applications are Smart Sparrow [42] and Knewton [43]. Such applications that utilize the adaptive learning technique are able to personalize teaching in university learning environments, while allowing students to cultivate their educational abilities according to their capabilities.

There are a few studies that argue that adaptive learning contributes not only to performance but also to student engagement. For example, a study by Ma et al. (2014) claims that students who use adaptive learning tools perform better on final exams than those who do not [44]. Along the same lines, Walkington’s study (2013) demonstrates the contribution of personalized adaptive learning tools to the interconnection of new and old knowledge, while also contributing to understanding [45].

Although the adaptive learning technique offers several benefits, it is also faced with various challenges in its implementation. The lack of the necessary training, according to Luckin et al. (2016), in the use of these specific tools can reduce their effectiveness [46]. Almasri (2024), on the other hand, warns that overreliance on algorithms leads to reduced critical thinking. In this case, students rely on artificial intelligence, without developing their own critical thinking [47].

At the University of Arizona, the use of the Knewton platform improved math achievement rates, increasing student success rates over two years [48]. In contrast, other programs, such as the “ASSISTments” program in U.S. public schools, found that students needed additional guidance from teachers to fully utilize adaptive technology [49].

4.2. Gamification

An alternative digital teaching method is gamification [50]. This method integrates various game mechanisms into the educational process, aiming to enhance the interest and assimilation of learners [51]. Students interact with the content through games, challenges, and rewards, which increases their cognitive engagement. The operating mechanism of gamified learning is organized into tracks and levels, where learners earn points or badges, depending on their progress. However, there are also various challenges that enhance cooperation, as learners often participate in groups. Competition with friends, on the other hand, or with fellow educators increases motivation and enhances the mood for learning. The main benefits of this method are improving students’ motivation and promoting collaboration and social learning. In addition, gamification also facilitates the development of problem-solving skills. An example of a gamification application is Kahoot! This is an application that allows teachers to create interactive quizzes. In these quizzes, students are asked to answer questions with understanding and accuracy [52].

Gamification, although developing rapidly, nevertheless presents a number of challenges related to its actual application in the educational process. Although games, in general, and rewards can increase student interest and enhance interaction, their correct application depends largely on both the experience and skills of teachers. Anderson and Dill (2000) argue that the use of such applications in education should be combined with appropriate strategies and goals. This is because learners may become distracted from the content and focus exclusively on collecting points or rewards [53]. More specifically, there are cases where teachers are not adequately trained in the use of such tools. Gamification runs the risk of becoming trapped in a formal entertainment process, without any contribution to enhancing real learning [52].

At the same time, digital approaches can highlight the potential of gamification, offering teachers new possibilities for personalizing and differentiating teaching. Kahoot!’s ability to adapt quizzes based on student performance and provide immediate feedback allows teachers to monitor their students’ progress and needs in real time [52]. However, if not applied methodically, it may weaken the learning process, especially when used solely for competitive games rather than substantively supporting the course content.

In addition, the educational training of teachers on gamification issues is also considered critical. A typical example of such a successful implementation is the work of the University of Michigan. At this particular university institution, qualified educators in the field of gamification and digital tools succeeded in creating more attractive and effective learning environments [54]. However, there is also the other version, in which there is a lack of guidance and appropriate support from teachers. In this case, failure and disappointment prevail, according to Dichev & Dicheva (2017). These authors argued that there were many cases where students failed to benefit from the possibilities of gamification, especially when the content of these applications was not connected to the learning objectives [55].

Gamification, when used correctly, can significantly contribute to improving the learning experience. Its successful integration requires proper teacher training and alignment with learning objectives. However, if used superficially or without strategic planning, it can weaken the educational process and reduce its effectiveness.

4.3. Microlearning

Microlearning is a method based on breaking down existing knowledge into small units [9]. These units are implemented in relatively short periods of time. It is particularly effective in educational environments that require rapid absorption of information and is widely used in e-learning platforms. The material of this method is divided into short lessons lasting approximately 3–10 min. Each unit includes condensed content, such as videos, quizzes, interactive diagrams, and flashcards. It is most commonly used in mobile learning, allowing for learning “on the go” [56]. This is a teaching method that reduces cognitive overload and facilitates the retention of information through repetitive learning techniques. It is considered particularly ideal for professional training and continuing education [57]. The EdApp application is an example of this method and offers microlearning lessons, which combine images, animations, and interactive elements for learning new skills [58].

Microlearning has proven effective in various educational settings, especially in vocational training and continuing education. Hug (2005) argued that breaking down knowledge into small units helps reduce cognitive overload. He also believes that it facilitates information retention through repetition techniques [59]. One of the most successful examples of microlearning is the Duolingo platform. This platform allows users to learn foreign languages using short lessons and interactive exercises [60]. When using this platform, users show significant improvement in both their language and verbal skills within just a few months.

However, microlearning may be less effective in cognitively demanding fields. Ebbinghaus (2013) and Thalheimer (2017) emphasize that fragmented learning can lead to a lack of coherence and association between concepts, negatively affecting deeper understanding of knowledge [61,62].

4.4. Learning Through Virtual/Augmented Reality (VR/AR)

The fourth digital educational method refers to education through virtual and augmented reality (VR/AR Learning). This method allows learners to experience the content of the learning, through virtual environments or augmented reality, improving the understanding of abstract concepts [63]. Virtual reality creates fully virtual environments, where learners can interact with objects and data [64]. Meanwhile, augmented reality adds virtual elements to the real world, through mobile devices or special glasses [65]. Learners can explore virtual laboratories, watch historical events in 3D models, or be trained in real conditions through simulations. The method of virtual and augmented reality increases experiential learning and interaction, allows for the safe practice of skills, such as medical simulations, and improves knowledge retention, through experiential learning. Google Expeditions is a prime example of the application of the above teaching method, offering virtual and augmented reality educational experiences in history, science, and geography [66].

Although VR/AR technology offers clear advantages in the educational process, its effectiveness in practice depends largely on how it is integrated into the pedagogical strategy. Virtual and Augmented reality (VR/AR) has been shown to be effective in enhancing students’ concentration and attention, as evidenced by a number of studies. Notably, research by Parong and Mayer (2018) showed that the use of VR in teaching science subjects led to superior understanding of the material compared to traditional teaching methods [67].

A typical example of effective integration of virtual reality (VR) into the educational process is the “ClassVR” program, which was implemented in primary schools in the United Kingdom, leading to an increase in learning engagement, particularly among students with learning disabilities [68,69]. Students were given the opportunity to “walk” through ancient cities, as well as explore them up close. At the same time, they could actively participate in the educational experience. In this way, the understanding of complex concepts was enhanced, as well as the cultivation of empathy.

Despite their potential, virtual and augmented reality (VR/AR) technologies are not a solution in themselves. Without proper integration into teaching practice, they may cause disorientation in students or lead to an overreliance on audiovisual stimuli, to the detriment of the development of critical thinking. Furthermore, the inadequacy of teacher training limits the effective use of these technologies [70]. Another issue that emerges is the need for equal access opportunities. Many schools, especially in rural or underfunded areas, lack the necessary resources to acquire and maintain such technologies, thus creating a new digital divide among students.

Table 5. Comparative overview of four digital teaching methods.

Method	Strengths	Challenges	Examples of Tools
Adaptive Learning	Personalized pace, data-driven feedback	Teacher training, algorithm overreliance	Knewton, Smart Sparrow
Gamification	Increased engagement, social learning	Risk of distraction, implementation quality	Kahoot!, Quizizz
Microlearning	Bite-sized content, flexibility	Limited depth, fragmented learning	Duolingo, EdApp
VR/AR	Immersive experience, experiential learning	High cost, technical limitations	ClassVR, Nearpod

provides a comparative presentation of the four main digital teaching methods analyzed in this study: adaptive learning, gamification, microlearning, and virtual/augmented reality (VR/AR) education. As can be seen, each method comes with clear advantages that enhance the learning process, but also challenges that require careful management. Adaptive learning allows for personalization, while gamification enhances participation. Microlearning offers flexibility, and VR/AR enriches the experience with experiential elements. However, their successful integration depends on the pedagogical training of teachers, the technological infrastructure, and the selection of appropriate tools. The comparative analysis facilitates the evaluation of their potential and offers a concise picture of their application in higher education.

Modern digital methods, such as adaptive learning, gamification, microlearning, and VR/AR learning, although emerging as innovative practices in modern education, face challenges in their practical application [7,31]. Their effectiveness depends on their appropriate adaptation to the needs of students and the training of teachers [71]. Examples of successful applications highlight how the combined use of these methods can enhance the learning process, while failures highlight the need for careful design and implementation. Connecting these methods with established learning theories, such as constructivism and self-regulated learning theory, strengthens their theoretical basis and offers a clearer framework for application [72,73,74].

Student engagement and active participation are critical factors for the success of digital methods in education [75,76]. The use of technologies such as virtual and augmented reality (VR/AR) as well as gamification can enhance student engagement, cultivating their interest and promoting self-directed learning [77,78]. Despite their benefits, the application of these technologies without the appropriate conditions can lead to disorientation and lower-quality learning outcomes [79,80]. Therefore, adapting digital methods to students’ needs and enhancing their active participation are essential for the success of these practices [74].

Digital education therefore utilizes advanced technologies with the aim of creating flexible, interactive, and effective learning environments. Although the four above methods offer flexible solutions to meet educational needs, their proper implementation requires, in addition to specialized training of teachers, the removal of barriers to digital access.

Although the use of digital methods in education is increasing, inequalities in access to technological means remain a serious obstacle. In particular, students from economically weaker sections or from developing countries face restrictions in their access to the internet and technological infrastructure, which limit their educational opportunities [81]. Furthermore, teachers often face difficulties in adapting to digital tools due to a lack of adequate training. Although technology can improve teaching, the transition from traditional methods to interactive learning requires a significant restructuring of teaching practices [82]. In addition, modern learning methods collect large amounts of educational data. Student privacy and the safe use of data therefore remain important issues and require careful institutional regulation [83].

The digital divide is one of the biggest challenges in implementing modern technological methods in education [84,85]. Both unequal access to digital infrastructure and limited technological training of teachers in many countries create obstacles to the use of innovative methods [10,86]. In addition, socio-economic factors, such as low income and lack of appropriate infrastructure, exacerbate this gap, making it difficult to integrate advanced learning methods in countries with limited resources [87,88]. Understanding these differences is fundamental to developing policies that will promote equal access to education [89].

The integration of digital technologies in education requires strategies not only to ensure accessibility but also to ensure security, as well as appropriate training for teachers so that they can use them effectively. Examples of successful applications in various educational settings can also contribute to the development of best practices.

The analysis indicates that education is moving towards more personalized and flexible learning models, where digital technologies will play an important role in the future. However, their success depends on their proper integration into educational policy and appropriate training of educators.

Although quantitative data highlight countries such as Russia, China, and Ukraine as key players in digital education research, countries with proven educational leadership, such as Finland or Canada, are absent. This may be due to limitations of the Scopus database or different publication strategies. Therefore, special care is required when interpreting such trends, taking into account cultural, political, and technological contexts.

In addition, the frequency of references to adaptive learning or gamification does not guarantee their successful implementation in the classroom. The transition from theoretical know-how to pedagogical practice often encounters challenges such as lack of training, technological resistance, and logistical constraints. Therefore, future research should focus not only on the use of these methods but also on the quality of their integration into the educational environment.

5. Limitations and Further Research

Our systematic literature review highlights both the contribution and use of modern digital technological tools in education. However, it is equally imperative to acknowledge some limitations of our approach.

The exclusive focus of this study on the Scopus database, and not on the Web of Science (WoS), ScienceDirect, IEEE Xplore, or any other database, constitutes our first limitation. Although Scopus provides an extensive coverage of the scientific literature, it may nevertheless exclude relevant studies. This could potentially affect the generalizability of the findings, limiting the understanding of the global application of digital educational methods in teaching [18]. The adoption of additional databases in the analysis may provide a more detailed and accurate representation of the research landscape. At the same time, it can ensure the coverage of a broader range of studies and opinions.

This analysis focused mainly on bibliometric approaches, such as citation analysis, co-authorship networks, and keyword co-occurrence analysis. The aim was to identify central themes, leading researchers, and scientific collaborations. Although these methods provide important data, they do not fully capture the qualitative aspects of digital teaching methods. Therefore, future research could combine bibliometric analysis with qualitative studies or even systematic literature reviews. This is in order to achieve a more in-depth understanding of the impacts and applications of specific technological innovations in education.

This study focuses on modern digital teaching methods and distinguishes four main approaches: adaptive learning, gamification, microlearning, and learning through virtual and augmented reality. In future research, it is considered particularly important to incorporate “active learning” as a central concept, as this is one of the most important approaches in modern teaching practices. Further exploration of active learning techniques can enhance the understanding of the effectiveness of digital methods, as well as lead to improved educational practices.

Regarding future research directions, these could focus on many areas, the most critical of which we consider the formulation of strategies for the integration of digital technologies into the educational process. Particular emphasis should be given to the development of curricula that incorporate innovative technologies, as well as to the professional development of teachers, in order to equip them with the necessary digital skills. In addition, research could focus on the effects of digital techniques on learning objectives and on the assimilation of knowledge by students.

Finally, this study does not examine the cultural, regulatory, or organizational factors that may influence the adoption of modern technologies in teaching across countries or even academic systems. Future analysis of these parameters may provide valuable insights into how different regions approach and utilize digital technologies and innovations in teaching.

6. Conclusions

The integration of advanced technologies in education contributes significantly to its transformation. Digital technologies enhance interactivity, the possibility of personalized learning, and access to educational materials, making learning more flexible and more adaptable to the needs of learners [6]. However, the question that arises is not whether modern digital technologies will prevail, but how they will be integrated, in order to maintain the quality and essence of the educational process.

A notable issue that arises is related to digital exclusion. Although modern educational technologies promote accessibility, they also create new forms of inequality, as both teachers and students face barriers to their use, due to technological, financial, or institutional constraints [90,91,92]. This inequality is not limited to countries with low-level education systems, but can occur in countries with developed infrastructures, when financial resources or implementation policies are insufficient [93,94,95]. Moreover, education is not simply a matter of transmitting information but also of shaping critical thinking, collaboration, and creativity, skills that are not developed simply through automated digital systems.

Technology is a tool, not an end in itself, in the educational process [96,97]. Teachers must be trained to flexibly integrate digital methods, adapting them to both student needs and educational requirements [88,97]. At the same time, policymakers must invest in infrastructure and teacher training to ensure the sustainability of digital applications and address the challenges related to socio-economic inequalities [98].

As for future research, it should not only focus on the development of new technologies but also on their impact: How do they shape the educational experience? Which skills do they cultivate and which do they neglect? How can technology be integrated without losing the essential human interaction in the educational process? In any case, by assessing multi-level educational practices and in combination with qualitative and quantitative data, their impact on the learning experience can be accurately captured. In a constantly evolving environment, it is clear that technology must be treated as a tool and not as an end in itself. The essential challenge lies not simply in choosing the most modern digital method, but in ensuring that technology will function in support of education, without altering its core. If education aspires to be the foundation of a knowledge-based society, then the focus of the discussion should not be the simple digitization of learning, but the preservation of its human-centered orientation in the digital age [99].