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Article

Teachers’ Resilience Scale for Sustainability Enabled by ICT/Metaverse Learning Technologies: Factorial Structure, Reliability, and Validation

by
Vassilios Makrakis
1,2
1
School of Education and Social Sciences, Frederick University, Nicosia 1036, Cyprus
2
Department of Primary Education, University of Crete, Gallos University Campus, 74100 Rethymnon, Greece
Sustainability 2024, 16(17), 7679; https://doi.org/10.3390/su16177679
Submission received: 26 July 2024 / Revised: 29 August 2024 / Accepted: 31 August 2024 / Published: 4 September 2024

Abstract

:
A significant trend in education is the increasing recognition of the need to shift from transmissive teaching to incorporating reflexive practices associated with real-life issues in learning, curriculum, and teaching. Merging Information and Communication Technologies (ICTs) and Metaverse learning technologies in Education for Sustainability (ICT/MeEfS) is critical in responding to current sustainability crises such as climate change. This research article focuses on the factorial structure, reliability, and validity of a teachers’ ICT/MeEfS resilience scale. It examines the predictive value of teacher self-efficacy and transformative teaching beliefs in merging ICTs and education for sustainability. The respondents were 1815 in-service teachers in Indonesia, Malaysia, and Vietnam. The principal component analysis showed a two-factor model (factor 1: “personal ICT/MeEfS resilience” and factor 2: “reflexive practice”), with a significant amount of extracted variance (68.26%). The overall Cronbach’s alpha reliability analysis of the teachers’ resilience scale enabled by ICT/MeEfS was 0.90, indicating a high score and excellent internal consistency. Similarly, the stepwise multiple regression analysis revealed that the two hypothesized predictors, teacher self-efficacy and transformative teaching beliefs, significantly contributed to teachers’ ICT/MeEfS resilience, explaining 73% of its variability. The implications of the research results are discussed in terms of research and in developing the capacity of teachers to embed sustainability issues and SDGs in teaching practices, learning environments, and course curricula enabled by ICTs and Metaverse learning technologies.

1. Introduction

The globalization of the UN 2030 Agenda for SDGs has created a comprehensive global dialogue that questions the unsustainable economic growth paradigm that prevailed in the 20th century. Research shows that the effects of environmental problems, such as global warming, air and water pollution, deforestation, ecological destruction, and loss of biological diversity, are all seen as part of climate change, which is threatening the sustainability of the planet [1,2,3], positioning climate change as the most significant environmental challenge currently facing humanity [4,5,6]. Recent studies demonstrate the harmful effects of climate change across all natural and social systems [7,8,9], which makes resilience a critical factor to address in tackling the climate crisis.
Previous research shows that one aspect of resilience that is now gaining increased attention is the capacity of education systems to transform from a stage of passivity driven by a transmissive teaching methodology to a transactive method that could pave the way toward a transformative pedagogy [10,11,12]. However, today, 20th-century education is part of the driving forces that have led the world to the current climate crisis and injustices regarding sustainability [13,14]. This turns teacher education for sustainability resilience into a critical factor in restoring the role of education as an agent of change [15,16,17]. Resilience thinking toward sustainability provides a basis for understanding the global sustainability injustices and shifting from the 20th-century unsustainable socio-economic growth paradigm to building a more sustainable and just society. Sustainability-oriented resilience can be thus defined as the capacity to deal with sustainability issues and, more notably, the climate crisis and unlock opportunities for transformative change at the personal and societal levels. It is worth pointing out that the problem is not just the climate crisis per se but the whole spectrum of global sustainability changes needed to sustain human eudemonia and turn education into a transformative changemaker.
Thus, the concept of resilience has become increasingly popular in the current sustainability discourse, research, and practice, connected to theories of change and driven by three key principles: (a) persistence, (b) adaptability, and (c) transformability [18,19,20]. These three principles connected to education for sustainability (EfS) enabled by ICTs and Metaverse learning technologies could refer to: (1) learning to maintain function and structure (persistence); (2) learning to exist (adaptability); and (3) learning to transform oneself and society (transformability). In particular, developing transformative teachers’ resilience is critical for building a sustainable society. Such a kind of concept gives meaning to the capacity of teachers to reflect on “who they are and why”, “what they want to become”, and “where they want to go”. Knowing oneself, learning to become, and envisioning a sustainable and just world are key competencies neglected in 20th-century education. Turning teachers as transmitters of knowledge into transformative intellectuals, coined by Henry Giroux [21], is essential to making the pedagogical more political and the political more pedagogical. For teachers, the political perspective of education refers to their agency to transform current practices to enhance education for sustainability; in other words, turning both teachers and learners into changemakers. This line of thinking gives teachers the theoretical basis to rethink and restructure their teaching, learning, and curriculum to address sustainability challenges. In this context, ICTs and especially Metaverse (merging the “meta” and “universe”) technologies, including VR (Virtual Reality), AI (Artificial Intelligence), and AR (Augmented Reality), can make a difference. The “meta” concept originated in ancient Greek philosophy and means “with”, “after”, or “going beyond”, while “universe” captures “the whole world”. These innovations are underpinned by a holistic and transformative perspective poised to stir up conventional teaching and learning practices [22,23,24]. Compared to traditional teaching and learning methods, the Metaverse thinking and associated technologies could enable a personalized, immersive, and experiential learning environment [25,26], making learning more meaningful [27]. Thus, developing a construct referring to the teacher’s ICT/Metaverse-enabled Education for Sustainability (ICT/MeEfS) resilience demands teachers to be self-confident in dealing with sustainability issues that could, for example, refer to environmental racism, sexism, unfair wages, poverty, and other violations of human rights: unequal distribution of income and opportunities between different groups in society and the lack of respect and recognition of certain people and groups in society. Such issues seem to reflect the four dimensions or constituencies of the newly developed concept of sustainability justice that unifies environmental justice, social justice, economic justice, and cultural justice into a coherent construct entitled sustainability justice by Makrakis [28,29], associated with the fourth bottom pillars of environment, society, economy, and culture.
Based on previous research, resilient teachers, besides being more positive toward their work, experience less stress [30], and express positive attitudes to job satisfaction contrasted with less resilient teachers [31]. They also tend to value active learning processes, learner-centered pedagogies, and interactive learning experiences that demand problem-posing [32,33], collective responsibility [34], critical reflectivity, and discourse [35]. Problem-posing is a teaching methodology driven by active and transformative learning, knowledge construction, and civic engagement by examining solutions to real-life issues that can be elicited mainly through the 17 SDGs. Thus, attempting to construct and validate a new concept addressing teachers’ ICT/MeEfS resilience would significantly contribute to shifting from a transmissive to a constructivist and transformative pedagogy. This transition is essential in positioning education as an agent of change. While international research has revealed some personal factors and resources that are important for developing and sustaining teachers’ resilience [36,37], there is a lack of research focusing on teachers’ transformative and reflective perspectives of resilience in education for sustainability enabled by ICTs/Metaverse technologies. The concept of transformative teaching was first discussed by Slavich [38,39,40] to promote meaningful learning and students’ lives. This was further elaborated by Mezirow’s notion of perspective transformation driven by critical reflection, action, and change [41,42,43]. Thus, teachers’ resilience in connection to Education for Sustainability and SDGs enabled by ICT/Metaverse learning technologies not only turns out to be an essential research area but also necessitates the inclusion of factors with which it could interact, such as self-efficacy in dealing with sustainability issues and transformative teaching beliefs [44]. Previous research also shows the positive relationship between self-efficacy and transformative teaching perceptions of resilience, and two scales were developed and validated [29,45]. The ICT/MeEfS self-efficacy refers to teachers’ capacity to use interactive teaching and learning methods to address sustainability and use learners’ personal life experiences to deal with sustainability issues. In contrast, transformative learning beliefs refer to independent, autonomous, and meaningful learning, fighting sustainability injustices at any cost, view the curriculum as a living content (process or praxis) and not as a fixed and prescribed package of knowledge to be transmitted.
As ICTs and Metaverse technologies are, along with climate change challenges, increasingly integrated across all societal domains, they generate higher expectations in education in general and education for sustainability in particular. In this study, the contextualization of ICTs with education for sustainability (EfS) is conceived as an innovation that promotes sustainability consciousness and action. Moreover, previous studies show that ICTs help learners make informed and conscious decisions for responsible behavior toward the integrity of the four pillars of sustainability justice [46,47]. The quest for new and innovative educational approaches that can promote transformative teaching and reorientate educational curricula to embed SDGs has been highly acknowledged in recent years [48,49,50,51]. Through the literature review, resilience, in general, has been defined variously in different social contexts and academic disciplines. In our case, it refers to strategies, processes, and abilities to successfully embed SDGs in educational processes and practice enabled by ICTs and Metaverse learning technologies. Developing teachers’ resilience in merging ICTs and Metaverse learning technologies with Education for Sustainability (EfS) is critical. Thus, this study’s primary objective is to develop and validate a newly constructed scale measuring teacher ICT/Metaverse resilience to embed sustainability and SDGs in learning, course curricula, and teaching practices. It also purports to test the predictive value of two independent factors, namely self-efficacy and transformative teaching beliefs, on teachers’ resilience enabled by ICT/Metaverse learning technologies.
In line with these objectives and previous research, it is hypothesized that self-efficacy in ICT/MeEfS (H1) and transformative teaching beliefs (H2) could be significant predictors of the newly constructed and validated concept of ICT/MeEfS teachers’ resilience.

2. Methodology

2.1. Background of Subjects and Procedure

As pointed out, this study was designed for and carried out in the context of the ICT/MeEfS project funded by the European Commission, focusing on seven higher education institutions in Indonesia, Malaysia, and Vietnam, which were affiliated with local primary and secondary schools. The participants were selected based on a convenient sample of 1815 in-service teachers working either as ICT coordinators and/or knowledgeable in ICTs. In terms of working place, the majority were working in urban schools (43%), followed by semi-urban schools (27%), and finally, rural schools (30%) in Indonesia (N = 360), Malaysia (N = 1253), and Vietnam (N = 202). There were 726 male teachers (40%) and 1089 female teachers (60%) representing multiple teaching subjects. Of the teachers participating in the survey, 51% declared they had experience using ICTs in teaching, while 39% worked as ICT teacher coordinators and 10% as ICT coordinators in the past. Regarding the type or school level, 56% worked in primary school education and 44% in secondary school education. The data distribution in terms of educational background shows that the great majority (76%) graduated from faculties of education, 12% from sciences, and the remaining from other academic fields. Regarding working experiences, 40% had more than 15 years of teaching, 37% declared the minimum experience in using ICTs as teaching and learning tools, and 54% declared enough knowledge in the field of education for sustainability. Before conducting the data collection that lasted from March to April 2020, permission was requested from the relevant authorities. Participants were also provided with the aims and objectives of this research, their voluntary participation, and anonymity.

2.2. Instrument and Measures

In this study, resilience, besides referring to strategies, processes, and abilities to succeed in embedding SDGs in educational processes and practice enabled by ICTs and Metaverse learning technologies, can also be understood as a metaphor for learning to transform oneself and society and as a process that could help to promote education for sustainability through the support of ICTs. This is why this study was used as a resource for developing, implementing, and assessing the ICT/MeEfS capacity-building project in Southeast Asia financed by the European Commission in 2019–2022. The constructed resilience scale was based on a 10-item list supported by the literature review. Participants were asked to rate their level of agreement on a 5-point Likert measure from 1 (“strongly disagree”) to 5 (“strongly agree”).

2.3. Type of Analysis

For the validation of the teachers’ ICT/Metaverse-enabled EfS transformative resilience scale, Exploratory Factor Analysis (EFA), and in particular, the principal component analysis (PCA) with varimax rotation, were adopted, including the Kaiser–Meyer–Olkin (KMO) test that is used for checking data sample adequacy and the Bartlett’s Test of Sphericity used for testing the validity of the collected data. A scree plot assessed the number of components/factors to be extracted. Items with factor loading greater than 0.40 were decided to be retained. The internal consistency of the retained items was examined using Cronbach’s alpha reliability statistics. The examination of multicollinearity was carried out using the Variance Inflation Factor (VIF) supplemented by tolerance metrics. Descriptive statistics assessed the data distribution regarding normality, including the kurtosis and skewness. Subsequently, correlation analysis and stepwise multiple regression were used to examine the impact of the hypothesized predictors of ICT self-efficacy and transformative teaching beliefs on ICT/MeEfS teachers’ resilience.

3. Results

3.1. Constructing and Validating the Teacher’s ICT/MeEfS Resilience Scale

One of the key objectives of this research was the construction and validation of the teacher’s ICT/MeEfS resilience scale. Exploratory factor analysis (EFA) with the principal component method was carried out to explore the factor structure of the newly constructed scale. The Kaiser–Meyer–Olkin (KMO) value was found to be 0.91, and the Bartlett’s Test of Sphericity showed a significant result (χ2 = 10,311.50, df = 45, p < 0.001), indicating that the data were suitable for carrying out an EFA. The extracted communalities ranged from 0.488 to 0.785, and all the pre-defined items for constructing the teacher’s ICT/MeEfS resilience measurement were retained. The PCA (Principal Component Analysis) revealed a two-factor solution with a direct varimax rotation method and eigenvalues > 1.0, accounting for a substantial (68.26%) amount of the extracted variance. Factor 1 accounted for 42.41% of the extracted variance, and factor 2 accounted for 25.85%. Looking into Table 1, the seven items composing Factor/Component 1 can be labeled “ICT/MeEfS personal competence”, reflecting mastery and self-reliance in contextualizing ICTs with EfS driven by experiential, constructivist, and transformative teaching and learning methodologies. Factor 2 can be labeled “reflexive practice”, consisting of three items reflecting a teacher’s capacity for reflection, action (individual and collective), and change.
According to the results, the two-factor structure seems well-defined, clear, sensible, and theoretically based, with an eigenvalue of 5.39 for factor 1 and 1.43 for factor 2. All the other factors were found to be below 1.00 and thus did not add anything significant to the measurement. Accordingly, the two significant factors are sufficient to express all the characteristics highlighted by the ten stated items. This is made clear in the scree plot graph (Figure 1), which shows that the curve starts to flatten between the two and three components. From factor 3 onwards, the eigenvalue is less than one, indicating that only three factors could be retained, supporting the convergent validity of the construct.
The results of Cronbach’s alpha reliability analysis of the teacher’s ICT/MeEfS resilience scale, including all ten items, show the value of 0.90, indicating a very high reliability index and excellent internal consistency. The reliability measures for the two components were found to be 0.91 for the “ICT/MeEfS personal competence” component with means of 3.06 and 0.74 for the “reflexive practice” component with a mean of 3.25.

3.2. Multiple Regression Analysis

Before carrying out the multiple regression analysis, it was necessary to check missing data, the normality of the data, and possible outliers. The results showed that only a few data were missing. The value of standard deviations (SDs) ranged from 0.40 to 1.0, the size of skewness ranged from 0.41 to ±1.0, and most of the kurtosis values were within the acceptable range of ±2.0 [52]. These results show relatively narrow data spread around the mean; the tails somehow deviated from the normality that can be accepted in this type of study and analysis [53,54]. The teacher’s ICT/MeEfS resilience average score (mean) was slightly above 3.00, showing a relatively medium ICT/MeEfS resilience score. The results concerning collinearity measured by the VIF metrics for the regressed variables ranged from 1.00 to 1.44, and the tolerance score was between 0.72 and 0.69. There is thus no problem of multicollinearity when carrying out a regression analysis. As shown in the correlation matrix presented in Table 2, there is a positive and significant relationship (r = 0.83) between self-efficacy and ICT/MeEfS resilience (p < 0.01) and between resilience and transformative teaching beliefs (r = 0.29, at p < 0.01).
The stepwise multiple regression analysis revealed that the two hypothesized predictors, regressed self-efficacy (H1) and transformative teaching beliefs (H2), significantly contributed to teachers’ ICT/MeEfS resilience. More specifically, the results presented in Table 3 show that both predictors were retained. The total coefficient of determination achieved was R2adj = 0.730, explaining 73% of the variability in the ICT/MeEfS resilience measure. In terms of the predictors’ contribution, the regression analysis revealed that teacher self-efficacy in dealing with education for sustainability alone explained 66% of the teacher’s ICT/MeEfS resilience (R2Change = 0.660, FChange (1,1809) = 3522.12 with a standardized beta = 0.81 at p = 0.000) followed up by transformative teaching beliefs, which added 7% (R2Change = 0.070, FChange (1,1808) = 137.86, with a standardized beta = 0.26, at p = 0.000).

4. Discussion

In the last decade, higher educational institutions have been experiencing significant challenges, trends, and changes derived from (a) the accelerated proliferation of ICTs and Metaverse learning technologies across all education domains, largely intensified during the COVID-19 period; (b) the quest for sustainability education; and c) digitization trends. As ICTs are, along with climate change challenges, increasingly integrated across all societal domains, they generate higher expectations in education in general and education for sustainability in particular. In this study, the contextualization of ICTs with education for sustainability (EfS) is conceived as an innovation that promotes sustainability consciousness and action. Moreover, previous studies show that ICTs help learners make informed and conscious decisions for responsible behavior toward the integrity of the four pillars of sustainability justice [46,47]. The quest for new and innovative educational approaches that can promote transformative teaching and reorientate educational curricula to embed SDGs has been highly acknowledged in recent years [51,52,53,54]. Developing teachers’ resilience in merging ICTs and Metaverse learning technologies with Education for Sustainability (EfS) was conceived as critical.
Thus, this study focused on constructing and validating a new scale measuring teachers’ ICT/Metaverse-enabled Education for Sustainability (ICT/MeEfS) resilience. The principal component analysis carried out in this study showed a two-factor model (factor 1: “personal ICT/MeEfS resilience” and factor 2: “reflexive practice”. Personal ICT/MeEfS resilience refers to the teacher’s ability to use ICTs and Metaverse learning technologies to enhance learners’ local sustainability experiences, exploit the use of cross-cutting sustainability learning resources, encourage learners’ active involvement in solving real-life problems enabled by ICTs, especially of regional and global concern, and to strengthen outdoor and place-based learning activities. Reflexive practice, the second component of the scale, seems to be connected to “teacher agency”, which can be perceived as a process, context, and practice enabling the teacher to view teaching as ethical and political praxis. This perspective transcends the narrow or surface-level conception of learning and teaching practices by integrating more meaningful features into the broader learning and curriculum ecosystem in which the teaching of SDGs could be embedded. In this context, teacher reflexive practices enabled by ICTs and Metaverse learning technologies can make a difference not only to the teacher’s conscious choices of what to teach and how to teach but also to the whys of making confident choices grounding the act of deciding and doing in theory. Conversely, when used with local learning activities, ICTs, especially MOOCs can open up new opportunities for local-global connections [55].
As it has also been pointed out in previous research, “reflexive practice” constitutes a process in which a teacher functioning as an agent of change is engaged not only in questioning his/her theories and practices but also in attempting to transform the structures that provide obstacles to such a function [56,57,58]. Accordingly, reflexive practice is much more transformative than constructional because it is driven by emancipatory reflection, merging critical reflection and action [59,60,61]. Navigating through reflecting on action, engaging in critical thinking planning, and taking action can generate transformative teaching and learning [62,63]. To create transformative learning, teachers must be given opportunities to reflect and act. Accordingly, the institutionalization of reflexivity assumes the creation of “reflexive standards and action competencies” for addressing complex sustainability problems [64]. It is also argued that there is a need to develop a comprehensive index of responsible behavior regarding sustainability that can be explained by social/cultural conditions and meta-reflexivity [65].
It may be assumed from the research results that reflexive practitioners should have a higher self-awareness of “who they are” and “what they could become”. With reflexive practice, there is a level of responsibility and co-responsibility that is not reached by mere reflective practice. In other words, reflexivity implies critical reflection and action that can shape the ways of being, thinking, and behaving enabled by ICTs and Metaverse learning technologies. This corresponds to previous studies documenting that when ICTs and metaverse technologies are used with local and global sustainability issues, these tools can open up opportunities for building sustainability [66,67,68,69]. Moreover, incorporating online digital resources into the learning process, such as wikis, digital storytelling, participatory video, and discussion boards, has been found to enforce student civic engagement and be a starting point for meaningful in-class conversations [70,71].
Other previous research findings related to virtual reality tools and climate change learning issues show a positive impact of such tools on students’ awareness and concern for sustainability [72], mainly if supported by ICTs [73]. Applying active learning tools and transformative teaching methodologies grounded in real-life problems, such as widespread poverty, violence, and a widening wealth–poverty divide, can reinforce the notion that education is the cornerstone of sustainable development [74,75,76]. The results of this study are also substantiated by previous research, which shows that addressing real-world sustainability problems and challenges, complex systems thinking, multiple views of knowledge, and reflexivity can be best achieved by shifting from disciplinarity to interdisciplinarity, leading toward cross-disciplinarity and trans-disciplinarity [77,78]. Thus, sustaining teachers’ resilience in merging ICTs and Metaverse learning technologies with sustainability education becomes imperative, especially in teacher professional development. This is why this research, besides developing and validating the teacher’s ICT/MeEfS resilience, investigated the predictive value of the teacher’s ICT/MeEfS self-efficacy and transformative teaching beliefs to the teacher’s ICT/MeEfS resilience.
The multiple regression analysis results indicated that teacher self-efficacy and transformative teaching beliefs significantly predict teachers’ ICT/MeEfS resilience. This implies that these two constructs or predictors should receive more attention in research and teacher professional development. These constructs can affect teachers’ resilience in merging ICTs and Metaverse learning technologies with education for sustainability. Specifically, the structure and content of teacher education programs should focus on transformative teaching, reflective teaching and learning practices, and resilience-building strategies to provide future teachers with the knowledge, skills, and action competencies to cope with humanity’s sustainability challenges. Similarly, in-service training should focus on training teachers to reorient university study programs and individual courses to embed sustainability and SDGs. This can be achieved through professionalizing academic teaching by merging ICTs and Metaverse learning technologies with education for sustainability. Considering that the ecological structure of human development is at risk, it is essential to focus on reflexive emancipation, which overcomes the contradictions between submission to nature and technical mastery of nature [79]. An international study carried out by Makrakis [80] based on a large sample (N = 3.080) of pre-service teachers from Finland, Greece, Sweden, Japan, and Holland documented prevailing no-stance and pessimistic attitudes toward the impact of technology and science on sustainable development. This seemed to be interpreted from the use of technology and science for profit-making at the expense of nature. In the same study, a strong connection was also found between environmental consciousness and attitudes toward the role and impact of science and technology on society. These results indicated a need to place higher critical concerns about the overoptimism of technological progress concerning sustainable development. In another study, it was argued that technology is a historically and contextually diverse phenomenon, which means that technology can serve sustainability. However, to understand it, we have to abandon the prevailing linearity and one-dimensionality in viewing technology and sustainable development [81]. Further elaboration is necessary to capture the complexities of technology, society, and sustainable development, particularly the dialectics of ICTs and Metaverse learning technologies in contextualizing sustainability issues in teaching, learning, and curricula.

5. Conclusions

This study revealed that teacher self-efficacy and transformative teaching beliefs can significantly predict their resilience in ICT/MeEfS. The findings implied that in-service teachers must improve their self-efficacy and transformative teaching capacities to merge ICTs and Metaverse learning technologies to embed sustainability issues in teaching processes, practices, and course curricula. In addition, given that teachers’ ICT/MeEfS resilience is predicted by self-efficacy and transformative teaching beliefs, applying strategies to enhance both the two identified components, namely personal ICT/MeEfS and reflexive practices, and the two predictors are pivotal for teachers to manage the challenges associated with the embedment of SDGs in education processes and practices. The results of this study also serve as empirical support for establishing training interventions and constructing and implementing suitable education for sustainability capacity-building models. However, it is necessary to consider the critical importance of teacher-level, system-level, and school-level barriers to implementing ICT/MeEfS [82].
The insights gained from this study provide valuable suggestions for teacher trainers, teachers, and policymakers aiming to integrate ICTs and Metaverse technologies as enablers for embedding education for sustainability in teaching, learning, and curricula. This study also outlines limitations and suggests directions for future research, highlighting the need for further investigations into the longitudinal impacts and cultural adaptability of Metaverse applications in education.
Despite its merits, the current study has limitations that should be pointed out. One is that this study relies solely on self-reported quantitative data. However, the large number of respondents and the achieved high-reliability indices in terms of consistency and validity minimize this shortcoming. It is recommended that self-reported data be supplemented with qualitative methodologies such as semi-structured interviews that will help illuminate the quantitative results. Moreover, the data were gathered only from a particular sample with specific characteristics (e.g., ICT coordinators), which may undermine the generalizability of the outcomes to other teacher subjects and functions. Additionally, despite the high variance extracted from the two predictors, additional predictors could be added in future studies. Furthermore, as teachers’ beliefs and practices are not static, longitudinal research could be applied to investigate and predict possible changes. Notwithstanding these limitations, the results of this study show that teachers’ ICT/MeEfS resilience is a reliable and valid construct for assessing teachers’ capacity to merge ICTs and Metaverse learning technologies with education for sustainability. This study also identifies factors associated with resilience, which may provide insights into the design, development, and implementation of suitable resilience capacity-building interventions. Another significant contribution from the findings is the importance of transformative teaching and learning contrasted with the transmissive pedagogies and curricula as products. It is also commonly assumed that teachers’ resilience is associated with transforming teachers’ appraisals [83]. Resilient teachers can thrive in difficult circumstances [30,84,85]. It is, thus, essential to eliminate contradictions in the nexus of ICTs and Metaverse learning technologies and education for sustainability.

Funding

This study was funded by the European Commission Erasmus+ CBHE Strand 2 project (No. 598623-EPP-1-2018-1-CY-EPPKA2-CBHE-JP).

Institutional Review Board Statement

According to the GDPR (General Data Protection Regulation), no ethical approval was necessary for this study. The local coordinating institution approved the research instrument through a letter dated 8 June 2019, reference number KPM.600-3/2/3-eras (4267).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The data are available upon request.

Acknowledgments

The content of this article reflects the views of the author and the European Commission as the co-funding agency, and they cannot be held responsible for any use that may be made of the results contained therein.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Abd-Elaty, I.; Sallam, G.; Pugliese, L.; Negm, A.; Straface, S.; Scozzari, A.; Ahmed, A. Managing coastal aquifer salinity under sea level rise using rice cultivation recharge for sustainable land cover. J. Hydrol. Reg. Stud. 2023, 48, 101466. [Google Scholar] [CrossRef]
  2. Azadi, Y.; Yazdanpanah, M.; Mahmoudi, H. Understanding smallholder farmers’ adaptation behaviors through climate change beliefs, risk perception, trust, and psychological distance: Evidence from wheat growers in Iran. J. Environ. Manag. 2019, 250, 109456. [Google Scholar] [CrossRef]
  3. Lange, F.; Dewitte, S. Measuring pro-environmental behavior: Review and recommendations. J. Environ. Psychol. 2019, 63, 92–100. [Google Scholar] [CrossRef]
  4. IPCC Climate Change 2023-Synthesis Report Summary for Policymakers. Available online: https://www.ipcc.ch/report/sixth-assessment-report-cycle/ (accessed on 17 May 2023).
  5. Khatter, A. Challenges and solutions for environmental sustainability in the hospitality sector. Sustainability 2023, 15, 11491. [Google Scholar] [CrossRef]
  6. Nüchter, V.; Abson, D.J.; vonWehrden, H.; Engler, J.-O. The Concept of resilience in recent sustainability research. Sustainability 2021, 13, 2735. [Google Scholar] [CrossRef]
  7. Leal Filho, W.; Balasubramanian, M.; Abeldaño Zuñiga, R.A.; Sierra, J. The effects of climate change on children’s education attainment. Sustainability 2023, 15, 6320. [Google Scholar] [CrossRef]
  8. Khine, M.M.; Langkulsen, U. The implications of climate change on health among vulnerable populations in South Africa: A systematic review. Int. J. Environ. Res. Public Health 2023, 20, 3425. [Google Scholar] [CrossRef]
  9. Li, C.; Zhang, X.; He, J. Impact of climate change on inflation in 26 selected countries. Sustainability 2023, 15, 13108. [Google Scholar] [CrossRef]
  10. Makrakis, V.; Larios, N.; Kaliantzi, G. ICT-enabled climate change education for sustainable development across the school curriculum. J. Teach. Educ. Sustain. 2012, 14, 54–72. [Google Scholar] [CrossRef]
  11. Asadzadeh, A.; Khavarian-Garmsir, A.R.; Sharifi, A.; Salehi, P.; Kötter, T. Transformative resilience: An overview of its structure, evolution, and trends. Sustainability 2022, 14, 15267. [Google Scholar] [CrossRef]
  12. Blake, J.; Sterling, S.; Goodson, I. Transformative learning for a sustainable future: An exploration of pedagogies for change at an alternative college. Sustainability 2013, 5, 5347–5372. [Google Scholar] [CrossRef]
  13. Makrakis, V. Using the DREAM methodology for course assessment in the field of ICT-enabled education for sustainability. Eur. J. Investig. Health Psychol. Educ. 2023, 13, 1378–1391. [Google Scholar] [CrossRef]
  14. Probst, L. Higher Education for Sustainability: A critical review of the empirical evidence 2013–2020. Sustainability 2022, 14, 3402. [Google Scholar] [CrossRef]
  15. Marouli, C. Sustainability education for the future? Challenges and implications for education and pedagogy in the 21st century. Sustainability 2021, 13, 2901. [Google Scholar] [CrossRef]
  16. Lim, C.K.; Haufiku, M.S.; Tan, K.L.; Farid Ahmed, M.; Ng, T.F. Systematic review of education sustainable development in Higher Education institutions. Sustainability 2022, 14, 13241. [Google Scholar] [CrossRef]
  17. Haider, L.J.; Cleaver, F. Capacities for resilience: Persisting, adapting and transforming through bricolage. Ecosyst. People 2023, 19, 2240434. [Google Scholar] [CrossRef]
  18. Darnhofer, I. Farming resilience: From maintaining states towards shaping transformative change processes. Sustainability 2021, 13, 3387. [Google Scholar] [CrossRef]
  19. Cote, M.; Nightingale, A.J. Resilience thinking meets social theory. Prog. Hum. Geogr. 2012, 36, 475–489. [Google Scholar] [CrossRef]
  20. Folke, C.; Carpenter, C.R.; Walker, B.; Scheffer, M.; Chapin, T.; Rockström, J. Resilience thinking: Integrating resilience, adaptability and transformability. Ecol. Soc. 2020, 15, 20. Available online: http://www.ecologyandsociety.org/vol15/iss4/art20/ (accessed on 15 March 2024). [CrossRef]
  21. Giroux, H. Teachers as transformative intellectuals. In Kaleidoscope: Contemporary and Classic Readings in Education; Ryan, K., Cooper, J.M., Eds.; Belmont: Wadsworth, OH, USA, 2010; pp. 35–40. [Google Scholar]
  22. De Felice, F.; Petrillo, A.; Iovine, G.; Salzano, C.; Baffo, I. How does the metaverse shape education? A systematic literature review. Appl. Sci. 2023, 13, 5682. [Google Scholar] [CrossRef]
  23. Damaševicius, R.; Sidekerskiene, T. Virtual worlds for learning in metaverse: A narrative review. Sustainability 2024, 16, 2032. [Google Scholar] [CrossRef]
  24. Lee, J.; Kim, Y. Sustainable educational metaverse content and system based on deep learning for enhancing learner immersion. Sustainability 2023, 15, 12663. [Google Scholar] [CrossRef]
  25. Park, S.; Kim, S. Identifying world types to deliver gameful experiences for sustainable learning in the metaverse. Sustainability 2022, 14, 1361. [Google Scholar] [CrossRef]
  26. Son, J.; Lee, S.; Han, J. The effectiveness of collaborative learning in SW education based on the Metaverse platform. J. Korean Assoc. Inf. Educ. 2022, 26, 11–22. [Google Scholar] [CrossRef]
  27. Makrakis, V. Unlocking the potentiality and actuality of ICTs in developing sustainable–justice curricula and society. Knowl. Cult. 2017, 5, 103–122. [Google Scholar] [CrossRef]
  28. Makrakis, V.; Kostoulas-Makrakis, N. The quest for meaningful learning. In Humanistic Futures of Learning: Perspectives from UNESCO Chairs and UNITWIN Networks; UNESCO: Paris, France, 2020; pp. 143–147. [Google Scholar]
  29. Makrakis, V.; Biasutti, M.; Kostoulas-Makrakis, N.; Ghazali, M.; Othman, W.; Ali, M.; Fitriyanto, N.A.; Mavrantonaki, K. ICT-enabled education for sustainability justice in South East Asian universities. Sustainability 2024, 16, 4049. [Google Scholar] [CrossRef]
  30. Mansfield, C.F.; Beltman, S.; Broadley, T.; Weatherby-Fell, N. Building resilience in teacher education: An evidenced informed framework. Teach. Teach. Educ. 2016, 54, 77–87. [Google Scholar] [CrossRef]
  31. Daniilidou, A.; Platsidou, M.; Gonida, E. Primary school teachers’ resilience: Association with teacher self-efficacy, burnout and stress. Electron. J. Res. Educ. Psychol. 2020, 18, 549–582. [Google Scholar] [CrossRef]
  32. Freire, P. The Pedagogy of the Oppressed; Continuum: New York, NY, USA, 1990; Original Work Published 1970. [Google Scholar]
  33. Houser, N.O. Problem posing in teacher education: A Freirian approach. Action Teach. Educ. 2007, 29, 43–49. [Google Scholar] [CrossRef]
  34. Makrakis, V.; Kostoulas-Makrakis, N. Responsibility and co-responsibility in light of COVID-19 and education for sustainability through an Aristotelian lens. Sustain. Clim. Change 2021, 14, 158–165. [Google Scholar] [CrossRef]
  35. Hyde, B. Critical discourse and critical reflection in Mezirow’s theory of transformative learning: A dialectic between ontology and epistemology. Adult Educ. Q. 2021, 71, 373–388. [Google Scholar] [CrossRef]
  36. Lundhaug, T. Building resilience and teaching learners about sustainable living through outdoor swimming and water safety learning. J. Adventure Educ. Outdoor Learn. 2024, 1–14. [Google Scholar] [CrossRef]
  37. Kamran, M.; Siddiqui, S. Roots of Resilience: Uncovering the secrets behind 25+ years of inclusive education sustainability. Sustainability 2024, 16, 4364. [Google Scholar] [CrossRef]
  38. Slavich, G.M. Transformative teaching. Excell. Teach. 2005, 5. Available online: http://www.teachpsych.org/ebooks/eit2005/eit05-11.html (accessed on 15 May 2024).
  39. Slavich, G.M. Transformative teaching. In Essays from Excellence in Teaching; Zinn, T., Saville, B., Williams, J., Eds.; American Psychological Association: Washington, DC, USA, 2005; Volume 5. [Google Scholar]
  40. Slavich, G.M.; Zimbardo, P. Transformative teaching: Theoretical underpinnings, basic principles, and core methods. Educ. Psychol. Rev. 2012, 24, 569–608. [Google Scholar] [CrossRef] [PubMed]
  41. Mezirow, J. Transformative Dimensions of Adult Learning; Jossey-Bass: San Francisco, CA, USA, 1991. [Google Scholar]
  42. Mezirow, J. Understanding transformation theory. Adult Educ. Q. 1994, 44, 222–232. [Google Scholar] [CrossRef]
  43. Mezirow, J. Transformative learning: Theory to practice. In Transformative Learning in Action: Insights from Practice. New Directions for Adult and Continuing Education; Cranton, P., Ed.; Jossey-Bass: San Francisco, CA, USA, 1997; pp. 5–12. [Google Scholar]
  44. Trigueros, R.; Padila, A.; Argilar-Para, J.; Mercader, A.; Lopez-Liria, R. The influence of transformative teacher leadership on academic motivation and resilience, burnout and academic performance. Int. J. Environ. Res. Public Health 2020, 17, 7687. [Google Scholar] [CrossRef]
  45. Ghazali, M.; Makrakis, V.; Kostoulas-Makrakis, N.; Yakob, N.; Rashid, R.A.A.; Othman, W.; Fitriyanto, N.A. Predicting teacher’s Information and Communication Technology-enabled education for sustainability self-efficacy. Sustainability 2024, 16, 5323. [Google Scholar] [CrossRef]
  46. González-Zamar, M.-D.; Abad-Segura, E.; López-Menese, E.; Gómez-Galán, J. Managing ICT for sustainable education: Research analysis in the context of Higher Education. Sustainability 2020, 12, 8254. [Google Scholar] [CrossRef]
  47. Abulibdeh, A.; Zaidan, E.; Abulibdeh, R. Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. J. Clean. Prod. 2024, 437, 140527. [Google Scholar] [CrossRef]
  48. Yuner, B. Transformative teaching in higher education: The relationship between the transformative teaching of academic staff and students’ self-efficacy for learning. Educ. Policy Anal. Strateg. Res. 2020, 15, 350–366. [Google Scholar] [CrossRef]
  49. Makrakis, V. ICTs as transformative enabling tools in education. In ICT in Education in Global Context (101–119); Huang, R., Kinshuk, Price, J., Eds.; Springer: Berlin/Heidelberg, Germany, 2014; pp. 101–115. [Google Scholar]
  50. Leal Filho, W.; Raath, S.; Lazzarini, B.; Vargas, V.R.; de Souza, L.; Anholon, R.; Quelhas, O.L.G.; Haddad, R.; Klavins, M.; Orlovic, V.L. The role of transformation in learning and education for sustainability. J. Clean. Prod. 2018, 199, 286–295. [Google Scholar] [CrossRef]
  51. Scarff, C.; Ceulemans, K. Teaching sustainability in Higher Education: Pedagogical styles that make a difference. Can. J. High. Educ. 2017, 47, 47–70. [Google Scholar] [CrossRef]
  52. Tabachnick, B.G.; Fidell, L.S.; Ullman, J.B. Using Multivariate Statistics; Pearson: Boston, MA, USA, 2013. [Google Scholar]
  53. Byrne, B.M. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming; Routledge: New York, NY, USA, 2010. [Google Scholar]
  54. Burdenski, T. Evaluating univariate, bivariate, and multivariate Normality using graphical and statistical procedures. Multi. Linear Regres. Viewp. 2000, 26, 15–28. [Google Scholar]
  55. Sosa-Díaz, M.-J.; Fernández-Sánchez, R. Massive Open Online Courses (MOOC) within the framework of international developmental cooperation as a strategy to achieve sustainable development goals. Sustainability 2020, 12, 10187. [Google Scholar] [CrossRef]
  56. Robson, I. From reflection to reflexivity. In The Reflective Leader; Emerald Publishing Limited: Leeds, UK, 2022; pp. 47–68. [Google Scholar] [CrossRef]
  57. Muthanna, A.; Alduais, A. The interrelationship of reflexivity, sensitivity and integrity in conducting interviews. Behav. Sci. 2023, 13, 218. [Google Scholar] [CrossRef]
  58. Knickel, M.; Knickel, K.; Galli, F.; Maye, D.; Wiskerke, J. Towards a reflexive framework for fostering co-learning and improvement of transdisciplinary collaboration. Sustainability 2019, 11, 6602. [Google Scholar] [CrossRef]
  59. Taylor, B. Technical, practical, and emancipatory reflection for practicing holistically. J. Holist. Nurs. 2004, 22, 73–84. [Google Scholar] [CrossRef] [PubMed]
  60. He, J.; Wen, Y.; Zhou, Y.; Ji, C. How to use emancipatory reflection to guide professional practice at work. World J. Public Health 2022, 7, 56–60. [Google Scholar] [CrossRef]
  61. Lyu, C.M.; Zhang, L. Critical emancipatory reflection on a practice-based issue in relation to nurses’ communicative role with unsatisfied clients in Chinese hospitals. Front Nurs. 2019, 6, 41–45. [Google Scholar] [CrossRef]
  62. Oo, T.Z.; Habók, A.; Józsa, K. Empowering educators to sustain reflective teaching practices: The validation of instruments. Sustainability 2023, 15, 7640. [Google Scholar] [CrossRef]
  63. Sullivan, B.; Glenn, M.; Roche, M.; McDonagh, C. Introduction to Critical Reflection and Action for Teacher Researchers; Routledge: London, UK, 2016. [Google Scholar]
  64. Schuitmaker-Warnaar, T.J.; Gunn, C.J.; Regeer, B.J.; Broerse, J.E.W. Institutionalizing reflexivity for sustainability: Two cases in health care. Sustainability 2021, 13, 11712. [Google Scholar] [CrossRef]
  65. Golob, T.; Makarovic, M. Meta-reflexivity as a way toward responsible and sustainable behavior. Sustainability 2022, 14, 5192. [Google Scholar] [CrossRef]
  66. Baena-Morales, S.; Martinez-Roig, R.; Hernádez-Amorós, M. Sustainability and educational technology—A description of the teaching self-concept. Sustainability 2020, 12, 10309. [Google Scholar] [CrossRef]
  67. Colás-Bravo, P.; Conde-Jiménez, J.; Reyes-de-Cózar, S. Sustainability and digital teaching competence in Higher Education. Sustainability 2021, 13, 12354. [Google Scholar] [CrossRef]
  68. Al-kfairy, M.; Ahmed, S.; and Khalil, A. Factors impacting users’ willingness to adopt and utilize the Metaverse in education: A systematic review. Comput. Hum. Behav. Rep. 2024, 15, 100459. [Google Scholar] [CrossRef]
  69. Das, P.; Barman, P. Does ICT contribute towards sustainable development in education? An overview. Int. J. Res. Publ. Rev. 2023, 4, 544–548. [Google Scholar]
  70. Makrakis, V.; Kostoulas-Makrakis, N. Enabling education for sustainable development through digital storytelling. In Digitalization, New Media, and Education for Sustainable Development; Keller, L., Michelsen, G., Dür, M., Bachri, S., Zint, M., Eds.; IGI Global: Hershey PA, USA, 2023; pp. 131–142. [Google Scholar]
  71. Rohmah, Z.; Makrakis, V.; Kostoulas-Makrakis, N.; Hidayati1, L.; Fitriyanto, N.; Projosasmito, S.R.; Auwibi, B.R.; Prijambada, I. Sustainable development goals through participatory video and digital storytelling. Sustain. Econ. 2024, 2, 176. [Google Scholar] [CrossRef]
  72. Hajj-Hassan, M.; Chaker, R.; Cederqvist, A.-M. Environmental education: A systematic review on the use of digital tools for fostering sustainability awareness. Sustainability 2024, 16, 3733. [Google Scholar] [CrossRef]
  73. Makrakis, V. Transforming university curricula towards sustainability: A Euro-Mediterranean initiative. In Handbook of Research on Pedagogical Innovations for Sustainable Development; Tomas, K., Muga, H., Eds.; IGI Global: Hershey, PA, USA, 2014; pp. 619–640. [Google Scholar]
  74. Garzon, P.; Inga, E. Advancing primary education through active teaching methods and ICT for increasing knowledge. Sustainability 2023, 15, 9551. [Google Scholar] [CrossRef]
  75. Lampropoulos, I.; Astara, O.-E.; Skordoulis, M.; Panagiotakopoulou, K.; Papagrigoriou, A. The contribution of education and ICT knowledge in sustainable development perceptions: The case of Higher Education students in Greece. J. Hum. Resour. Sustain. Stud. 2024, 12, 15–31. [Google Scholar] [CrossRef]
  76. Novoa-Echaurren, A. Teacher agency in the pedagogical uses of ICT: A holistic perspective emanating from reflexive practice. Educ. Sci. 2024, 14, 254. [Google Scholar] [CrossRef]
  77. Baumber, A. Transforming sustainability education through transdisciplinary practice. Environ. Dev. Sustain. 2022, 24, 7622–7639. [Google Scholar] [CrossRef]
  78. Evans, T.L. Transdisciplinary collaborations for sustainability education: Institutional and intragroup challenges and opportunities. Policy Futures Educ. 2015, 13, 70–96. [Google Scholar] [CrossRef]
  79. Jochum, G. Dialectics of technical emancipation-Considerations on a reflexive, sustainable technology development. Nanoethics 2021, 15, 29–41. [Google Scholar] [CrossRef]
  80. Makrakis, V. Scientific and technological progress, political beliefs and environmental sustainability. Discourse Commun. Sustain. Educ. 2012, 3, 63–74. [Google Scholar] [CrossRef]
  81. Ruuska, T.; Heikkurinen, P. (Eds.) Technology and sustainability: An Introduction. In Sustainability beyond Technology: Philosophy, Critique, and Implications for Human Organization; Oxford Academic: Oxford, UK, 2021. [Google Scholar] [CrossRef]
  82. Othman, W.; Makrakis, V.; Kostoulas-Makrakis, N.; Hamidon, Z.; Keat, O.C.; Abdullah, M.L.; Shafie, N.; Mat, H. Predictors of motivation and barriers to ICT-enabling education for sustainability. Sustainability 2024, 16, 749. [Google Scholar] [CrossRef]
  83. Clarà, M. Teacher resilience and meaning transformation: How teachers reappraise situations of adversity. Teach. Teach. Educ. 2017, 63, 82–91. [Google Scholar] [CrossRef]
  84. Betancourt-Odio, M.A.; Sartor-Harada, A.; Ulloa-Guerra, O.; Azevedo-Gomes, J. Self-perceptions on digital competences for m-learning and education sustainability: A study with teachers from different countries. Sustainability 2021, 13, 343. [Google Scholar] [CrossRef]
  85. Li, S. The effect of teacher self-efficacy, teacher resilience, and emotion regulation on teacher burnout: A mediation model. Front. Psychol. 2023, 14, 1185079. [Google Scholar] [CrossRef]
Figure 1. Scree plot.
Figure 1. Scree plot.
Sustainability 16 07679 g001
Table 1. Rotated Component Matrix for the ICT/MeEfS Resilience Scale.
Table 1. Rotated Component Matrix for the ICT/MeEfS Resilience Scale.
Items, Components, and LoadingsComp 1Comp 2
Using ICTs to enhance learners’ local sustainability experiences.0.823
Using ICT-enabled cross-cutting sustainability learning resources.0.796
Using ICTs for learners’ active involvement with real-life problems.0.783
Using ICTs to engage learners in dealing with local/global issues.0.772
Using life experiences to develop ICT knowledge and skills.0.751
Adjusting educational content for real-life learning.0.727
Using ICTs to strengthen outdoor learning activities. 0.698
Reflective practice has led me to rethink, revise, and change. 0.866
Using reflection to change thinking and behavior. 0.840
Reflecting critically on others’ actions increased my co-responsibility. 0.814
Table 2. Descriptive results and correlation coefficients between dependent and independent variables.
Table 2. Descriptive results and correlation coefficients between dependent and independent variables.
VariablesMeanS.D.No123
1. ICT/MeEfS resilience 3.140.5718121.0
2. ICT/MeEfS Self-efficacy3.530.4418130.83 **1.0
3. Transformative teaching beliefs3.960.4018140.29 **0.55 **1.0
** p < 0.01.
Table 3. Multiple regression analysis results.
Table 3. Multiple regression analysis results.
Hypotheses VerifiedR2AjDfR2ChFChBetaTp
H1: Self-efficacy → ICT/MeEfS Resilience0.66018090.6603522.120.8159.350.000
H2: Transformative teaching beliefs → ICT/MeEfS Resilience0.73018080.070137.760.2611.730.000
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Makrakis, V. Teachers’ Resilience Scale for Sustainability Enabled by ICT/Metaverse Learning Technologies: Factorial Structure, Reliability, and Validation. Sustainability 2024, 16, 7679. https://doi.org/10.3390/su16177679

AMA Style

Makrakis V. Teachers’ Resilience Scale for Sustainability Enabled by ICT/Metaverse Learning Technologies: Factorial Structure, Reliability, and Validation. Sustainability. 2024; 16(17):7679. https://doi.org/10.3390/su16177679

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Makrakis, Vassilios. 2024. "Teachers’ Resilience Scale for Sustainability Enabled by ICT/Metaverse Learning Technologies: Factorial Structure, Reliability, and Validation" Sustainability 16, no. 17: 7679. https://doi.org/10.3390/su16177679

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