Higher education is going through a structural transformation where pedagogical innovation and digital environments operate inseparably. Thus, institutions have had to respond to the expansion of virtuality, the ubiquity of access to information and the demand for transversal skills; readjusting its curricular architecture and its teaching-learning frameworks.¹ In this transition, recent literature shows two complementary movements: on the one hand, the adoption of active methodologies supported by technologies that enhance student agency, collaboration, and meaningful learning^2,3; on the other, the design of digital ecosystems –from LMS to laboratories and simulations– that enable experiences previously restricted to the classroom or physical laboratory.^4,5 However, these advances confront tensions related to motivation, equity, data ethics and pedagogical sustainability.^6–8 Recent evidence extends these tensions towards the adoption of generative artificial intelligence, where perceived utility, trust, privacy, enabling conditions, and institutional support influence the acceptance and continued use of these technologies by teachers and students.^9–11

The review adhered to the methodological guidelines set out in the PRISMA 2020 Declaration, which provided the framework for transparently and rigorously planning, executing and reporting the processes linked to the analysis of scientific evidence on pedagogical innovations, digital environments, and experiences and outcomes in higher education.⁴³

According to Figure 1, 1279 records were identified from databases, platforms and other sources. After removing 34 duplicates, 1245 records were examined by reading titles, abstracts, and keywords. Of these, 1119 were excluded because they did not correspond to the categories of the review (n = 402), were not developed in the context of higher education (n = 286), were not empirical publications (n = 196), were outside the established period (n = 121) or corresponded to grey literature or sources without verifiable peer review (n = 114). Attempts were made to retrieve the full text of 126 documents, but 25 could not be obtained. Consequently, 101 full texts were evaluated, of which 50 were excluded because the population or sample was not sufficiently defined (n = 14), the results were not related to the categories of the review (n = 12), the methodological description was insufficient (n = 10), the data were incomplete for extraction and synthesis (n = 8) or the risk of bias was considered critical (n = 6). Finally, 51 studies were included in the narrative and thematic synthesis.

Table 2 summarizes the methodological characteristics of the 51 included studies, published between 2020 and 2026 and developed in various geographical contexts. Spain (n = 7) and the United Kingdom (n = 6) concentrated the largest number of investigations, followed by Russia, Thailand and Saudi Arabia (n = 4), and Indonesia, Italy and Türkiye (n = 3). Studies carried out in Germany, Portugal, France, Norway, the United States, the United Arab Emirates, Costa Rica, Morocco, Mexico, Brazil, Malaysia, Vietnam, Kazakhstan, Ecuador, Pakistan, Belgium and China were also recorded, as well as multinational research. Overall, 15,188 people participated, with samples ranging from 7 to 3268 participants. Quantitative studies (n = 27; 52.9%) predominated, followed by mixed (n = 14; 27.5%) and qualitative (n = 10; 19.6%) studies. According to the methodological design, JBI Analytical Cross-Sectional (n = 17), MMAT 2018 (n = 14), ROBINS-I (n = 10) and JBI Qualitative (n = 10) were applied. Among the studies evaluated using JBI and MMAT, 23 had moderate limitations and 17 had significant limitations; while, with ROBINS-I, seven showed moderate risk and four showed serious risk. Production was mainly concentrated in 2025 (n = 13; 25.5%), 2022 (n = 10; 19.6%) and 2024 (n = 8; 15.7%).

Table 3 presents the six reports excluded during the final critical review. These reports form part of the 50 full-text exclusions shown in Figure 1 and were not counted as additional exclusions.

The search identified 1,279 records, of which 51 studies met the eligibility criteria and were included in the synthesis. The corpus brought together research carried out in various geographical contexts and was composed of 27 quantitative studies (52.9%), 14 mixed studies (27.5%) and 10 qualitative studies (19.6%). Cross-sectional designs predominated, followed by quasi-experimental studies, qualitative cases, and mixed-methods designs. Overall, the research reported 15,188 participants including university students, teachers, administrators and other actors in higher education. Sample sizes ranged from 7 to 3268 participants, with an average of approximately 297 per study.

In the innovations, those with fundamental achievements in active participation, the development of autonomous learning and improvement of digital skills stood out; in these cases, they are specified through the incorporation of flipped classrooms, the use of interactive platforms and the use of methodologies based on design and experiential learning. Even when persistence of challenges in teacher training, the rejection of change and infrastructure were identified; In general, technological integration showed positive impacts on pedagogical innovation in higher education, by providing essential foundations for the analysis of limitations, implications, and perspectives of digital environments in this sector.

In this field of pedagogical innovation, its systematic implementation was essential for the profound rethinking –with a critical and creative orientation that transcends the superficial– of the conventional paradigms that support instruction and knowledge acquisition in the university environment; that is, both educational dynamics and training goals as well as functions of the actors involved. In this, there is a remarkable cohesion and redesign of didactic strategies –such as flipped classroom, gamification, PBL and experiential and collaborative learning– which, integrated into digital environments, optimize their applicability and performance. In the flipped classroom examined by Uzun et al., analytical feedback favored awareness and perceived self-regulation, but did not produce a significant improvement in academic performance.¹⁶ In contrast, the gamified experience studied by Descamps and co-authors increased maturity on digital sobriety in both scenarios, while collective work generated a stronger perception of competence for joint environmental action.¹⁷ In addition to reconfiguring the traditional role of the teacher as transmitter, mediator and guide, the implementation of these strategies provides greater autonomy to students, empowering them as an active nucleus of the training process and promoting a meaningful, participatory and personalized assimilation of academic content.^5,14,19,50

Furthermore, the implementation of hybrid pedagogical models, based on the articulation of active methodologies and virtual platforms, has favored the diversification of training scenarios in higher education. This diversification responds not only to technological demands, but also to emerging pedagogical and social needs, such as the flexibility of learning times and spaces, the inclusion of students with different profiles, and the incorporation of current competencies in academic programs. This interpretation is reinforced by Mohammadi et al. (2025),³⁵ who found in five European universities that hybrid learning depends on standardized and easy-to-use platforms, interactive content, real-time communication, teacher training, and sustained technical support.³⁵ From the student perspective, Alsalhi et al., identified a high post-pandemic acceptance of hybrid learning, although the assessments varied according to gender, academic area, and year of study.³⁴ Additionally, to favoring access to knowledge, the face-to-face and virtual synergy of hybrid models has fostered transversal skills; for example, critical and collaborative thinking, self-management of learning and adaptability. For this reason, pedagogical innovation is conceived as a strategy aimed at enhancing the relevance, quality, and sustainability of the educational process in the contemporary university context.^12,37,59

In this framework, research underlines the potential of digital environments as mediators for the flexibility, contextualization and interactivity of training processes. Technological mediation that, in addition to redesigning traditional teaching-learning spaces, expands the methodologies used in terms of accessibility, active participation and multiplicity. In this, the systematic and core implementation in the articulation of specific subjects –not isolated or complementary– of LMS, AR resources, online collaborative tools, digital simulators, virtual learning objects, VR laboratories and multimedia materials the findings suggest. Its implementation in several cases as a basic infrastructure for the comprehensive design of curricular programs has favored the expansion and geographical, social and cultural diversification of the scope of higher education.^{14,21,24,32,42}

Likewise, these studies underline the importance of adaptability and personalization in the design of virtual environments, through the use of developing technologies –AI, educational big data and learning analytics– as a dynamic and individual response to student requirements.⁵⁸ Furthermore, to positive effects on accessibility and equity, these proposals enhance essential elements for autonomy in learning (intrinsic motivation, self-regulation and sustained academic commitment).⁶² However, the contribution of analytics should not be overestimated. Uzun et al. found that students valued analytical feedback to monitor and regulate their behavior, but its use was not significantly related to performance and did not always adequately represent the quality of learning.¹⁶ Similarly, Fayda-Kinik showed that the influence of digital environments is not uniform, as different forms of support produce differentiated effects on disposition towards technology, satisfaction, motivation and perceived usability.³⁶ More than repositories of content, digital environments act as catalysts for student self-management and the enhancement of metacognitive competencies vital for contemporary higher education, so that they function in the current pedagogical context as authentic complex ecosystems.^27,56,61

Furthermore, technological mediation in university processes is verified as a phenomenon of global scope, given the transversality of the category of higher education found in each of the materials included, as well as the multiplicity of university contexts represented. In addition to its globalization, this notes a concurrence of concerns that occupy the attention of higher education. These convergences point towards the necessary adaptation of pedagogical methodologies to the current training needs of a university student body with a critical spirit and a greater orientation towards virtuality and experiential learning. Consequently, environments that enhance interactivity, relevant curricular programs and strategies that situate academic content in order to solve specific problems are needed; that is, approaches with flexible models, which place the student in a central role of the training process.^26,33,52

In this sense, pedagogical innovation is more strongly needed in technical, scientific and professional profiles, where the management of emerging technologies has had a significant impact on the expansion of academic options. Today’s students have the opportunity to strengthen the theory-practice link through technologies that allow them to simulate, experiment and represent phenomena in complex environments; while promoting the deep apprehension of training content, they also develop skills demanded by the labor market.^40,53,60

Moreover, to the assimilation of virtual tools, in the university context these innovations promote a complex process of comprehensive reformulation that enhances a training ecosystem of greater coherence and reflexibility, focused on the student. Essential dimensions such as instructional design, formative assessment, and the teacher’s mediating accompaniment are involved in this empowerment. From a constructive orientation, it is seen how these innovations are interested in a rigorous and conscious alignment of training with pedagogical strategies and evaluation components, which favors the development of specific competencies and the acquisition of deep, transmittable and lasting learning.^7,38

The results indicate that pedagogical innovations in digital environments demand conditions that go beyond the mere will of teachers, while highlighting the importance of their continuous professional development, oriented towards technical skills and the formative apprehension of technology. They also agree on the need to implement sustained university policies that stimulate continuous training and counseling programs, as well as the creation of environments for pedagogical experimentation and feedback. In this regard, recent studies on generative AI reinforce this institutional dimension. Among teachers, adoption depends on perceived usefulness, trust and social reinforcement, while continuity of use is also conditioned by satisfaction, privacy, security and facilitating conditions.^9,10 Transnational and mixed-methods evidence also indicates that skills development, pedagogical support and coordinated ethical governance are necessary to prevent the integration of AI from remaining fragmented or relying exclusively on individual initiatives.^30,35 This institutional vision of innovation allows for the consolidation of a culture of continuous improvement, where technologies are not an end, but a means to promote more relevant, inclusive and contextualized pedagogical practices.^4,32,55

From the methodological point of view, these studies present a remarkable diversity of approaches and designs, which enriches the understanding of phenomena linked to pedagogical innovation in digital environments within higher education. This methodological variety not only reflects the progressive maturity of the field, but responds to the multifaceted and contextualized nature of technology-driven educational transformation processes. Research developed under quantitative, qualitative and mixed approaches is identified, encompassing experimental, quasi-experimental, exploratory, descriptive designs, case studies and design-based research. This variety, more than a limitation, was associated with the complexity of educational innovation practices and makes it possible to analyze their impacts, meanings and contradictions from different positions and epistemological points of view.^18,51,54,57

The strength of the results is also supported by highly complex and robust analysis techniques –from the statistical or qualitative point of view– of some of these studies. In addition to contributing to analytical soundness, these techniques promote the establishment of explanatory and relevant relationships between the variables studied, the detection of emerging patterns and the understanding of dynamic interactions present in the teaching-learning processes with technological mediation. Overall, the analysis of epistemic networks, the modeling of structural equations, focus groups and clusters stand out. The evidence included expands methodological diversity through structural equation models applied to the acceptance of generative AI and the sustainable adoption of AI and the metaverse, transnational qualitative interviews, behavioral recordings on learning platforms, and sequential mixed designs that combined surveys, focus groups, and thematic analysis.^{10,11,30,31,35} The plurality and rigor of this methodological approach strengthen the internal/external validity of these investigations, providing a holistic vision on the construction, implementation and evaluation of pedagogical innovation in the contemporary field of higher education.^25,37,68

These results corroborate on various variables linked to technology-mediated university education. These include motivation, commitment, satisfaction with the training process, academic performance and assimilation of key competencies; on the digital, communicative, collaborative and metacognitive level. These findings suggest that the strategic integration of pedagogical innovations in digital environments has the potential to the evidence points to the experience of university education; overcoming the traditional one-way transmission of knowledge. However, studies underline the need to design and implement these innovations from rigorous standards of quality, relevance, contextualization and institutional sustainability as the only way to avoid superficiality in the technification of pedagogical processes.^19,22,65 However, acceptance and favourable attitudes should not be interpreted as evidence of problem-free educational integration. The growing use of generative AI among Italian students coexisted with ethical concerns and with the demand for clearer institutional guidance.²⁹ Likewise, the interest of university staff in synthetic avatars was mainly driven by hedonic motivation, but accompanied by concerns about professional identity, ethical implications and institutional power relations.²⁸ Similarly, the sustainable adoption of AI and the metaverse depended on the interaction of environmental, social, and governance conditions, and not solely on their technological performance.³¹

Over and above that, to the individual benefits of learning, several studies highlight the structural potential of these experiences to promote fundamental principles such as equity, inclusion, and universal access to higher education, especially in historically vulnerable, lagging, or isolated populations. Technological mediation is revealed as a powerful tool to democratize educational opportunities, expand spaces for participation and overcome physical, economic or cultural barriers that limited the educational trajectory of certain groups. This inclusive and transformative approach reinforces the role of universities not only as centres of knowledge, but as active agents in the construction of a fairer society with higher levels of social cohesion.^2,15,63

Some studies also report no minor limitations, tensions and structural challenges associated with the implementation of pedagogical innovations in digital environments within higher education. Difficulties that show that the processes of educational transformation do not always develop in ideal conditions. Among the most frequent obstacles are resistance to change on the part of some teachers –who may perceive innovations as a threat to their consolidated practices– deficient technological infrastructure, little training in digital skills, cognitive overload generated by the simultaneous or excessive use of platforms, as well as the urgency of guaranteeing accessibility, usability and pedagogical quality in the digital resources used.^3,6,41 Concerns related to the accuracy and personalization of analytical feedback, privacy and security in the use of generative AI, competency gaps between university actors, and the governance of synthetic or immersive technologies also coexist.^10,16,28,30 These findings broaden the meaning of digital inequality, as it includes not only access to infrastructure, but also the ability to evaluate, regulate and responsibly use emerging technologies. These limitations call for rethinking innovation not as a mere technological addition, but as a systemic and integral process that requires the coherent articulation of pedagogical, technological, organizational, ethical, and formative dimensions of university practice.

The included studies suggest that technology-mediated pedagogical innovations can promote motivation, participation, self-regulation and certain skills. However, the evidence is insufficient to conclude that these results are constant or attributable exclusively to technological intervention. In several cases, improvements were limited to perceptions of acceptance, satisfaction, or usefulness, with no equivalent changes in academic performance. This difference is striking and substantive: accepting a platform or valuing a tool positively does not necessarily mean learning more or better. In addition, the predominance of cross-sectional, descriptive, qualitative, and quasi-experimental designs in the corpus forces us to interpret the findings as situated associations and not as generalizable causal effects.

The evidence also questions the idea that expanding technological access automatically produces educational inclusion, especially when connectivity and the availability of devices have been found to be necessary, but insufficient, conditions. In this sense, inequalities are reproduced when students and teachers participate with different digital skills, times, support and decision-making possibilities. In the same way, personalization can favor learning, but also transfer to the student an excessive responsibility for difficulties caused by deficient designs or institutional restrictions. In this context, the flexibility of digital environments can become overload, isolation or fragmentation if there is no meaningful interaction, teaching accompaniment and sustained technical support.

The results also show that the expansion of learning analytics and artificial intelligence is neither pedagogically nor ethically neutral. Collection of digital traces, profiling, and recommendation automation can reinforce surveillance practices and shift teacher judgement towards indicators whose logic is not always transparent. Added to this are the biases built into platforms and algorithmic models, risks to privacy, academic integrity, and professional identity, as well as reliance on third-party technology providers. The environmental and organizational cost of maintaining increasingly complex digital infrastructures should also not be ignored. As a result, innovation cannot be measured solely by its novelty, ease of use, or level of acceptance, but also by who controls the data, what decisions it automates, what inequalities it reproduces, and what institutional capacities it requires.

Finally, the evidence does not allow us to affirm that digital pedagogical innovation reconfigures higher education by itself towards greater humanism, inclusion or sustainability. Rather, it indicates that it can contribute to these purposes when technology is subordinated to explicit educational purposes and is accompanied by teacher training, student participation, data protection, independent evaluation and accountability mechanisms.

The main contribution of this review consists, therefore, in shifting the discussion from the incorporation of tools to the pedagogical, ethical and institutional conditions that determine their educational value. This requires more methodologically sound longitudinal, comparative and experimental studies, capable of distinguishing between acceptance, use and effective learning, examining unintended consequences and establishing which innovations work, for whom, in what contexts and under what conditions.

These findings contribute to a more conditioned understanding of pedagogical innovation and digital environments in higher education. Its educational value seems to depend on the coherence of pedagogical design, sustained teacher support, institutional capacity, equitable access and transparent data governance. Rather than attributing to them an inherent transformative effect, evidence suggests that digital innovations can reproduce existing inequalities or generate new forms of dependency, surveillance, and exclusion when these conditions are not present. Future research should prioritize longitudinal, comparative, and experimental studies capable of distinguishing between technological acceptance, frequency of use, and effective learning. Greater attention is also required to algorithmic bias, data privacy, platform dependency, environmental costs, and the institutional sustainability of emerging technologies.

Extended data: This project contains the following underlying data:

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The author(s) declared that no grants were involved in supporting this work.

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© 2026 Casimiro Urcos CN et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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