Introduction

In the last decade, Higher Education has opted for a methodological approach based on competences, since this is a training strategy that allows us to respond to the uncertainties of a changing reality (Corral-Ruso, 2021; García, 2020), to solve problems (Sá & Serpa, 2018), find suitable methods to diagnose and prevent educational problems from a scientific point of view (Chernikova et al., 2020), or to transform teaching–learning processes based on digital innovation (Fernández-Cruz & Rodríguez-Legendre, 2021). Therefore, competence-based training implies the possession of knowledge, skills, abilities and attitudes that are displayed in the context of a carefully selected set of professional tasks (Gonczi et al., 1990).

In this sense, the professional development of university teaching staff involves competence development in relation to teaching and research, since creativity and scientific innovation are building blocks of the modernisation of education in the twenty-first century (Treffinger et al., 2021), although in this case the focus is on research. According to Thiel and Böttcher (2014), a researcher must develop specific competences for formulating problems, hypothesising, experimenting, including ways of problem solving, analysing data, as well as the ability to communicate findings to the scientific community (Lagunes et al., 2016). In other words, university teachers are the builders of scientific knowledge (Numminen et al., 2020) and it is therefore necessary to prioritise teacher training in research skills.

This type of teacher training can be considered as a key factor that changes the destiny of countries, since, if university teachers provide future graduates with quality education (Leonard & Wibawa, 2020), every society will flourish and develop in expansion and development (Amirova et al., 2020; Ryndak & Saldaeva, 2019). However, at this point in time there is a lack of clear policies for the development of entrepreneurial competences in the scientific sector of Higher Education institutions (Viloria, 2017) which would stimulate the creation of innovative products, patents or even technology transfer.

In this study, teacher training as a researcher focuses on a more specific debate related to digital competences. In other words, teachers need to possess conceptual, procedural and attitudinal skills to initiate research or start up innovation projects (Guzman & Nussbaum, 2009). At the same time, they need to have the digital knowledge required to integrate digital resources to search for and interpret information more efficiently to compile and communicate scientific knowledge (Guillén-Gámez et al., 2020).

It is true that the digital skills of university teachers have been studied in depth over the last few decades (Oguguo et al., 2023; Şimşek & Ateş, 2022), finding a skills level ranging from basic to intermediate (Cabero-Almenara et al., 2021; Santos et al., 2021). However, although studies on research skills have been published, resulting in findings of average levels (Abykenova et al., 2016; Rubio et al., 2018), it is true that most of these studies focus on university students or master-doctorate students, with very little literature available on teacher-researchers. Moreover, there is hardly any scientific literature that has focused on the interconnections between digital competences and research work, where ICT is little used to strengthen research skills, evidencing basic levels (Robelo et al., 2018; Sánchez & Bucheli, 2020). In addition, it has not been studied whether factors such as the entrepreneurial spirit of teachers to start a research project, where creativity plays a key role in the emergence of new ideas, could affect digital competences in research work. Therefore, the aims of this study are:

  • O1. To know the level of digital competence of the teacher in research work, depending on whether their level of creativity and entrepreneurship is bad/good.

  • O2. To analyse if there are significant differences in the digital skills of teachers (with a bad and good level of creativity and entrepreneurship), between those who had used on emerging technologies and those who have not.

  • O3. To identify in what order the use of different emerging technologies or the combination of several of them affect the digital competences of teachers.

Theoretical framework: creativity, entrepreneurship and ICTs

Creativity is one of the skills seen as a priority for teachers in the twenty-first century (Nebot & Álvarez, 2020), as it allows them to adapt to situations of uncertainty, and to respond to the educational demands of the environment. Cho et al. (2017) assert that creativity is the ability to develop and implement new and better solutions to resolve the issues they came across; moreover, teachers must be creative to promote learning environments that foster creativity in students (Hung & Sitthiworachart, 2020). Conceptually, Cropley (2001) defines it as the competence to make a project or a new idea out of an individual's own imagination.

In a digital environment, creativity is on a par with innovation, since its purpose is to improve people's quality of life. Moreover, the use of technology fosters creativity (Parise et al., 2015), especially its use in the teaching–learning process (Henriksen et al., 2021; Onyekwere & Enamul Hoque, 2023), because certain technologies such as mobile applications, social networks or Internet use favour creativity and open-mindedness (Galiç & Yıldız, 2023; Hegarty, 2015). In relation to research processes, creativity is one of the main key elements (Rodríguez et al., 2019). The task of a researcher on the formulation of new questions and hypotheses, deductive and inductive reasoning bearing in mind what is not yet known a priori is related to the creative thinking of the teacher (Barrow, 2010). Moreover, as early as 2009, the European Commission (EU, 2009) showed through a survey that 94% of teachers believe that creativity is an essential competence to be developed, where 88% of the participants stated that they could be creative with ICT being a key element to achieve this goal (80%).

New technologies have a lot to offer to the world of creativity. Nikolopoulou (2018) stated that the creative use of ICT is no longer confined to a specific space and time, but also makes use of mobile technologies (Mobile Learning) or virtual reality environments, being spaces for potentially creative collaboration. For example, Chang et al. (2020) found that virtual reality (VR) has significant positive effects on creative design processes, particularly at the design and planning stages, but also in respect of testing and review, and reflection and feedbacks. Specifically, Yang et al. (2018) explored the effects of using virtual reality on the creativity of 60 university students from China, finding that those students who used VR produced more creative designs compared to those who did not use this technology. In relation to another emerging technology, Mee et al. (2020) explored the perceptions of 55 trainee teachers from Malaysia regarding the benefits of using gamification. The results showed that it improved creative, critical and problem-solving skills. Alt and Raichel (2020) gathered similar findings, testing the potential of gamified learning to increase digital skills and creativity identity in a sample of 94 secondary school students from Israel.

Another educational component that was considered essential to research processes is the presence of entrepreneurial researchers, who are responsible for transferring scientific knowledge through technological innovation (Goodman et al., 2014). In other words, one of the significant predictors of ICT integration in any type of context are the skills related to having an entrepreneurial spirit (Mfon et al., 2018). Nevertheless, little attention has been paid to analysing how an academic researcher involved in the academic field develops the intention to initiate a scientific project (Prodan & Drnovsek, 2010). In other words, what Africano and Africano (2012) defined as academic management: researchers and academics act as entrepreneurs as they are not only involved in research but also in the multiple activities that are inherent to a project: acquiring public funding, hiring talent, accessing resources and materials, and so on.

Teachers' use of digital resources has also been related to entrepreneurship, although the creativity aspect was very much in the background. For example, Blázquez and Marín (2021) found that teachers only made use from time to time of digital resources such as robotics, augmented reality or virtual reality to promote entrepreneurship. In the same context, Viloria (2017), through a sample of 44 teacher-researchers from public universities (Venezuela), demonstrated that the teaching staff showed an intermediate level in both entrepreneurial and creative competence, although their technological ability related to entrepreneurship was rated medium to high.

However, no related studies exist that identify emerging technologies as significant predictors of teachers' digital research capabilities as a function of their entrepreneurial and creative skills. This issue becomes the main contribution of this study, previously described in the introduction section together with the objectives to be achieved.

Method

Design and samples

An ex post facto design was used. The sample was purposively selected through non-probabilistic sampling, by seeking email contact with the teaching staff of different universities throughout Spain, achieving a response rate of 1740 participants. The survey was completed anonymously, retaining the confidentiality of the data. Regarding gender, 56.40% were male teachers (n = 981), with a mean age of 49.61 years (± 29.53), where their level of creativity was medium (5.19 ± 3.38) as was their level of entrepreneurship (5.39 ± 5.11); whilst 43.6% were female teachers (n = 759), where their level of creativity was medium (4.99 ± 4.20), similar to their level of entrepreneurship (5.43 ± 6.29).

Instrument

In order to meet the objectives, the instrument developed by Guillén-Gámez et al. (2023) was used. This instrument assesses the digital skills of Higher Education teachers in relation to the use of digital resources in research work, through a causal model. The questionnaire was composed of a total of 29 items classified into seven dimensions, with a seven-point Likert scale. Figure 1 shows the causal model with these factors. The dimensions of the instrument were:

  • DIM 1 (Digital skills) Relates to the researcher's digital skills for searching, analysing and communicating scientific results, such as item 5 "I know how to use Boolean operators (AND, NOT, OR, XOR) to refine my searches". This was measured with values from value 1 (I am notable to) to value 7 (I am able to)

  • DIM 2 (Digital Ethics) This refers to the good digital practices that a researcher has to follow to comply with the ethical principles of research, such as item 9 "I apply copyright rules when sharing the results of my studies through scientific social networks". This was measured with values from value 1 (I never do it) to value 7 (I do it frequently).

  • DIM 3 (Flow Digital) Focuses on the researcher's perceptions of their enjoyment of using technology in their research, e.g., item 27 "I find it enjoyable to use software for both quantitative and qualitative data analysis when conducting research". This was measured with values from value 1 (Totally disagree) to value 7 (Totally agree).

  • DIM 4 (Anxiety towards ICT) Focusing on the researcher's attitudes, specifically on their state of anxiety when using digital software for research and communication, e.g. no. 32 "I get tired of having to constantly use ICT to position and share scientific publications and improve my digital reputation through the h-index and/or the i-index10". This was measured with values from value 1 (Totally disagree) to value 7 (Totally agree).

  • DIM 5 (Quality). Relates to the faculty's perception of the quality of their institution's digital resources and infrastructure to be able to carry out their research, such as item no. "23. My department or research group buys licences for ICT resources that require additional payment". This was measured with values from value 1 (It is poor) to value 7 (It is excellent).

  • DIM 6 (Intention to use ICT) This refers to the researcher's perceptions of their intention to use digital resources, such as item 37 "I plan to continue learning how to use ICT resources in the near future, which will help me to expand my research work". This was measured with values from value 1 (Totally disagree) to value 7 (Totally agree).

  • DIM 7 (Integration ICT) Refers to the researcher's perceptions of their actual integration (use) of digital resources, e.g., item 20 "I use Google + collaborators to host my research data”. This was measured with values from value 1 (I never do it) to value 7 (I do it frequently).

Fig. 1
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Causal model of the instrument elaborated by Guillén-Gámez et al. (2023)

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The instrument had satisfactory psychometric properties (Table 1). Regarding reliability, this was measured through Cronbach's alpha and composite reliability (CR). Regarding validity, the following aspects were tested: (1) convergent validity, measured through the average variance extracted (AVE), showing values above 0.50; (2) discriminant validity where the Fornell-Larcker and HTMT criteria were adequate; (3) cross-loading analysis showing an adequate correlation of the items of the corresponding factor; and (4) SRMR criterion yielding a coefficient of 0.78, which is lower than the value of 0.8 recommended by Hu and Bentler (1999).

Table 1 Psychometric properties of the instrument
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Data analysis procedure and techniques and variables analysed

The data analysis was carried out using the following procedures:

  • To meet the first objective (O1), a descriptive, comparative and statistical analysis of teacher levels of digital competence in research work was conducted for each dimension of the instrument. This analysis was carried out according to the level of creativity and entrepreneurship to carry out a research project. First of all, the participants were asked about the level of creativity to start new research projects, as well as the entrepreneurial spirit about new research projects. Both questions were prepared with a 10-point Likert scale where the value 1 is associated with "minimum level" and the value 10 is associated with "maximum level". Subsequently, the authors classified these levels into dichotomic variables (bad/good level). For the low-level category, all the values with the range from 1 to 6.99 points were classified, whilst for the good level category, the range from 7 to 10 points was classified. For the statistical contrast between low and good level, non-parametric techniques (Mann–Whitney) were used, because there was no normality in the distribution of the data (p < 0.05).

  • To meet the second objective (O2), the level of overall digital competence in research work was tested for each of the variables previously described in Fig. 1, classifying the level of competence according to whether the teacher had used on emerging technologies from the Horizon Report, which may have a short-term impact on the teaching–learning processes (Brown et al., 2020). Table 2 shows the variables analysed. In those cases where there were significant differences between the categories yes/no, effect sizes were calculated. Hattie (1992) has interpreted the effect size for educational contexts according to Cohen's (ES) formula: values less than 0.1 with “small effect”, between 0.2 and 0.3 with “medium effect”, and values greater than 0.4 with “large effect”.

  • To meet the third objective (O3), the classification trees were applied using the CHAID method (Chi-square automatic interaction detection). This technique was used to detect relationships between pairs of significant variables using the maximum likelihood technique. CHAID was chosen as it allows the automatic detection of interactions using Chi-square. At each step, CHAID selects the independent variable showing the strongest interaction with the dependent variable.

Table 2 Variables analysed in the study in relation to whether the researcher has used emerging technologies
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Results

This section is divided into three parts: the first section analyses and compares the digital research competence of teachers in terms of high or low creativity and entrepreneurship in initiating research; the second section analyses the significant variables of digital competence across a range of emerging technologies; and the third section identifies the order of how emerging technologies or the combination of some of them affect the digital skills of teachers.

Analysis of digital skills in research work based on the level of creativity and entrepreneurial spirit

Figure 2 shows the level of teachers' digital competence in research work as a function of their level of creativity and entrepreneurship (bad vs. good). In both Fig. 1A, B the level of research competence is high for those teachers who perceived themselves to have a good level of creativity and entrepreneurship in relation to conducting research, in all dimensions of the instrument as well as in overall competence. However, the level of competence is medium for those teachers who perceive themselves to have a low level of creativity and entrepreneurship. With regard to the entrepreneurship variable, for example, it is observed that those teachers who had a high level of entrepreneurship had a good comprehension and integration of digital resources in their research work, compared to those who had a low level of entrepreneurship. Similarly, it is observed that the higher the level of creativity or entrepreneurship of the teachers, the higher their level of digital skills; the opposite is also true when their level is low.

Fig. 2
figure 2

A Digital competence in research in line with the level of creativity of the teaching staff. B Digital competence in research in line with teachers' entrepreneurial spirit. DIM. 4: reverse scoring

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Table 3 shows the statistical contrast for each variable (bad vs. good level), in relation to the level of digital competence in research. Specifically, significant differences were found in the level of research competence between the low and high level, for each variable and for each dimension of the instrument. For the creativity variable, the effect sizes were medium for all dimensions of the instrument except 1.7 and total, whereas the effect sizes on the entrepreneurship variable were high. In other words, the differences were larger in the level of research competence for those teachers who rated themselves as low or high in entrepreneurship compared to those who rated themselves as high in creativity.

Table 3 Research competence by comparing the level of creativity, spirit and entrepreneurship
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Statistical contrast of digital skills according to different emerging technologies, for each level of creativity and entrepreneurial spirit

Table 4 shows teachers' level of digital competence in research, depending on whether they have used a range of emerging technologies, depending on their level of creativity. It can be observed that the level of teachers' digital competence in research is higher amongst teachers who have used the different emerging technologies compared to those who have not (for both types of creativity), with their level of competence being higher when their level of creativity is also high. It can be seen that there are significant differences, for both types of creativity, in the level of research competence when investigating or using all the emerging technologies, except in the Flipped Classroom. Specifically, it is observed that in these differences, the effect sizes are large when the level of creativity is low, but small when the level of creativity is high. In other words, the higher the level of creativity in conducting research, the higher the level of digital competence in research.

Table 4 Research competence as a function of whether they have used emerging technologies, for both types of creativity
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Table 5 shows the teachers' level of digital competence in research, depending on whether they have used different emerging technologies, as a function of their level of entrepreneurship. In general, it can be seen that the level of digital competence in research is higher when they teachers’ entrepreneurial spirit is also higher, whether or not they have used emerging technologies. Specifically, it is observed that in both categories of entrepreneurship, the level of digital and research competence is higher if teachers have used in emerging technology. Whilst there are significant differences in the level of digital and research competence of teachers in all emerging technologies when their level of entrepreneurship is low, the same does not occur when the level of entrepreneurship is high, with significant differences in Mobile Learning, Robotics, Wearables, Blockchain, XR Technology. It is also observed that in these differences, the effect sizes are large when the level of entrepreneurship is low, but small when the level of entrepreneurship is high. That is, the higher the level of entrepreneurship in research work, the better the level of digital competence.

Table 5 Research competence as a function of whether they have used emerging technologies, when entrepreneurship is low and high
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Results of classification techniques (trees) according to the level of creativity and entrepreneurship.

So far, it has been found that there are significant differences in the level of digital competence of teachers in research work, in relation to the level of creativity and entrepreneurship, as well as those significant variables that affect its acquisition. However, in what order do these significant variables affect digital competence in research, and is there a relationship between variables that prompts a higher success rate (probability) on the level of digital competence in research? Classification trees are the ideal method to answer this question and consequently achieve objective 3.

The dependent variable was the global level of digital competence of teachers regarding the use of digital resources in research tasks. This was calculated through the arithmetic mean of all the items that make up the seven dimensions of the instrument. Regarding the levels of the variable’s creativity and entrepreneurial spirit, as described in "Data analysis procedure and techniques and variables analysed" section, we classified these levels into dichotomic variables (bad/good level). The independent variables are described in Table 2 and all of them were categorized as dichotomous variables. The value 1 was associated when the teacher had not previously used any of these emerging technologies in their research, whilst the value 2 was associated when the teacher had used them.

The tree in Fig. 3 focuses on the level of teachers' research digital competence, classified according to whether their level of creativity is high or low. It can be seen that the overall level of digital competence in research is medium–high (node 0, M = 4.96 ± 0.99). If the researcher has a high level of creativity in planning new research (node 1), his/her level of competence increases slightly (M = 5.27), but if his/her level of creativity is low, his/her level of competence is lower (node 2, M = 4.72 ± 1.07), compared to the average of the participants in this study (node 0).

Fig. 3
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Classification tree of emerging technologies when the researcher has a low or high creativity to initiate research

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On the other hand, the level of competence decreases considerably if the researcher, in addition to having low creativity, has not done any research on XR technology during his or her career (node 6, M = 3.69 ± 0.92). If the researcher possesses the two previous characteristics (low creativity and no use of XR technology) and has not researched digital trading with cryptocurrencies either, their level of digital competence in research becomes medium–low (node 14, M = 3.24 ± 0.96). On the other hand, this tendency is reversed when the researcher has a high level of creativity in initiating new research. It is observed that if the researcher, in addition to possessing high creativity, researches XR technologies, his competence increases slightly (node 3, M = 5.43 ± 0.63). But if in addition to possessing these two previously described characteristics, he also researches facial authentication systems in LMS access, his digital competence in research increases to a high level (node 7, M = 5.55 ± 0.52).

The tree in Fig. 4 focuses on teachers' digital competence in research as a function of their level of entrepreneurship. If the researcher's level of entrepreneurship to initiate new projects is low, his or her digital competence in research is slightly lower (node 1, M = 4.63 ± 0.95) than the average of the participants in this study (node 0, M = 4.86 ± 0.99). But if the researcher possesses a high entrepreneurial spirit to initiate new research, his or her level of competence increases considerably (node 2, M = 5.74 ± 0.50).

Fig. 4
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Classification tree of emerging technologies when the researcher has a low or high entrepreneurial spirit to initiate research

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On the other hand, the level of competence decreases considerably if the researcher, in addition to having a low level of entrepreneurship, has not done any research on XR technology during his or her career (node 4, M = 3.81 ± 0.88). If the researcher, in addition to not applying these two previous characteristics, has not done any research on digital commerce with cryptocurrencies, his or her level of digital competence in research becomes medium–low (node 9, M = 3.40 ± 0.98). On the other hand, if the researcher, in addition to possessing a good level of entrepreneurship, also does research on the digital use of cryptocurrencies, his or her competence increases to a high level (node 6, M = 5.89 ± 0.52). However, the level of competence in digital research can increase if he/she also researches Mobile Learning (node 13, M = 6.03 ± 0.48) or games and gamification (node 11, M = 5.50 ± 0.43).

Discussions

Higher Education institutions have undergone a substantial change due to the integration of ICT in every aspect of people’s lives. Set against this background, there is an increasing need for teacher training in a multitude of competences, including research. This comes with two provisos. On the one hand, teachers must learn to use digital resources to carry out their research work; and, on the other hand, they must develop personal skills that lie at the basis of the entrepreneurial spirit, such as creativity, initiative and the ability to face new goals (Treffinger et al., 2021). Both aspects are closely linked as the use of technology will foster the teacher's own creativity (Parise et al., 2015).

In this context, digital competence in research represents a prerequisite as the importance of research has changed dramatically in recent years in the knowledge society. The triad of entrepreneurship and creative research skills, paired with the digital role of the researcher, is the central driver for the successful transfer of scientific knowledge into the digital society. In this study, the digital competences of teachers in the use of digital resources in research work has been analyzed, based on their levels of creativity and entrepreneurial spirit. In addition, the impact of the use of emerging technologies on the digital skills of teachers was analyzed, as well as the order that they affect the skills of teachers.

In relation to the first purpose (O1), the results have shown that the teachers' level of digital competence in relation to the use of technology to carry out a research project is medium–high, regardless of the transversal competences they possess. These results are contradictory to those of Sánchez and Bucheli (2020) and Robelo and Bucheli (2018) which showed that the use of ICT as a resource in research work to generate information processes is still at the development stage. A plausible explanation for these results might be the type of group analysed, since studies with university students show that research training using digital media is only in its infancy. In this sense, we agree with the statements of Leonard and Wibawa (2020), who state that it is a priority for teachers to provide future graduates, even students, with a quality education, where research and innovation are key factors in the society of the future.

With regard to specific and transversal competences, it is worth noting that teachers with higher levels of both creativity and entrepreneurship also have better digital competence in research, with higher scores for the latter. These findings are in line with the evidence of Parise et al., 2015, Hegarty, 2015 and Rodríguez et al., 2019), where the use of open digital resources, social networks or apps stimulates people's open-mindedness and, therefore, their own creative capacity. Such is the importance of this that well over a decade ago, the European Union (EU, 2009) showed that teachers feel they have to develop this transversal competence, where the use of ICT is a key element to achieve this goal. However, we agree with the statements of Goodman et al. (2014) in affirming that to be a creative teacher, it is also essential to enhance the entrepreneurial spirit of teacher-researchers, with the aim not only of acquiring public funding, hiring talent, or access to resources and materials (Africano & Africano, 2012), but also of transferring scientific knowledge to a more developed society.

In relation to the second purpose (O2), all the emerging technologies analysed were identified as variables of digital competence in research when classified according to the level of creativity, except for the Flipped Classroom. Regarding the level of entrepreneurship, all the emerging technologies analysed were variables when the level was low. These results are in line with the statements of both Chang et al. (2020) and Yang et al. (2018) when they establish a link between XR (virtual reality) technologies with creative thinking; as well as with the findings of Alt and Raichel (2020) when linking gamification-based creative learning with digital skills. Regarding the findings in respect of entrepreneurship, perhaps these are consequences of the little use that teachers still make of it today. In this sense, we would agree with the words of Blázquez and Marín (2021) in evidencing in their study that teachers still use emerging technologies such as robotics or XR technology on an intermittent basis, which as a result may affect the acquisition of adequate digital competence in research work. A plausible explanation for the results in relation to the Flipped Classroom could be that it is a type of methodology that has been widely used by teachers in recent years, so perhaps it would not have the same impact as other more emerging technologies whose use is not yet fully educational, such as cryptocurrencies or facial authentication systems. In this sense, we agree with Viloria's (2017) assertions that there is still a need for further educational policies that invest in teacher training in respect of all the innovative technologies that are emerging more and more strongly in the social and personal spheres of humanity.

In relation to the third purpose (O3), it has been shown that the differences in digital competences in research work are smaller when creativity is higher, whilst the opposite is true when this transversal competence is low. These results would indicate that not only are emerging technologies identified as variables of teacher competence, but this also applies to the level of creative thinking, especially when this is low. However, these ideas should be taken with caution, and further research in this line of work is of vital importance. Regarding the order in how these technologies affect the skills of teachers, it was evidenced that when the teacher has high creativity, and they also use XR technologies and Artificial Intelligence, their digital skills are superior. These technologies were also identified when teachers had low creativity. These results are in line with those of Chang et al. (2020) on the positive effects of virtual reality on the creative abilities of the teacher. A plausible explanation may be related to the need to design and plan the stages or scenarios of the virtual world, requiring a high creative capacity to achieve these virtual designs, and at the same time having an impact on better digital skills in research work. Regarding entrepreneurship skills, the results were different from the previous ones. That is, the digital skills of teachers would be higher when a teacher has, in addition to a high spirit of entrepreneurship, they also use Blockchain and m-Learning systems. A plausible explanation of these results may be since the use of these technologies is not yet sufficiently established, neither in educational contexts nor in social contexts. However, those teachers who, if they have opted to include them in their educational contexts and research, their digital and transversal skills have also been superior in parallel.

Conclusions

In this study, the authors have analyzed the digital skills of Higher Education teachers regarding the use they make of digital resources in research tasks, considering the levels of creativity and spirit entrepreneur to start new research projects; and we have identified if the use of emerging technologies affects the acquisition of these digital skills, as well as the joint use of various emerging technologies.

Amongst the main findings, the perceptions of teachers regarding their digital skills in research tasks have been medium–high, both for those teachers who have a low and high level of creativity and entrepreneurial spirit. Specifically, it was evidenced that teachers had superior digital skills in both the DIM. 1 (Digital skills) as in DIM. 2 (Digital Ethics) when they also had good levels of creativity and entrepreneurial spirit. It was also evidenced that teachers had lower skills in the DIM. 3 (Flow Digital), DIM. 5 (Quality) and DIM. 7 (Integration ICT) when they had low levels of creativity and entrepreneurial spirit. These results highlight the fact that teachers are not sufficiently trained to meet this challenge, at least in terms of transversal competences. There is, therefore, a need for specific training, both in specific competences in educational technology related to research, as well as in transversal competences that help teachers respond to the uncertainties of an increasingly changing reality (Corral-Ruso, 2021; García, 2020).

It was also evidenced that the use by teachers of all the emerging technologies analyzed in this study (both for those with low and high creativity) affect the digital skills of teachers, except for the flipped classroom methodology. However, teachers' digital skills were higher when the level of creativity was also higher. Similar results were also found in relation to entrepreneurship, although a lower number of emerging technologies had a significant impact on digital competences (Mobile Learning, Robotics, Wearables, Blockchain and XR Technology). Finally, it was found that having high creativity, the use of XR technologies and Artificial Intelligence cause an increase in the digital competences of teachers; whilst a high entrepreneurial spirit, use of blockchain and mobile Learning also cause an increase in these digital competences.

Introducing the use of these emerging technologies in educational contexts, as well as the development of these interpersonal skills is quite a challenge. To meet this challenge, teaching staff must be motivated through bonuses for scientific excellence, reduced workloads in exchange for time dedicated to research work, but, above all, qualifications in emerging technologies, since these have proven to be significant variables in the acquisition and development of digital skills of teachers for the use of digital resources in research work.

The findings may have several implications on an educational and research level. From the perspective of the educational institution, with the aim of focusing on training actions in those transversal and digital competences that teachers are most lacking, which could be carried out through MOOC courses, with pre-test and post-test designs that help to ascertain whether these skills have actually been improved. Moreover, if the Digital Education Action Plan (2021–2027) (EU, 2009), in its strategic priority 2—Enhancing digital skills and competences for the digital transformation—highlights the need for the development of digital skills, including creativity and entrepreneurship in all types of people and all age groups. Higher Education must provide quality education (Leonard & Wibawa, 2020), not only in its teaching and research staff, but also in its students, who will be the researchers of the future.

In respect of the limitations of this study, it is necessary to reflect on what its weaknesses are and how to improve them through future work. Perhaps the main weakness is the type of sample used, which was purposive. Therefore, the results should be taken with caution and not be extrapolated to the general population. It would be interesting to have representative samples of teachers from different continents, in order to be able to give a collective view on the level of digital competence in research, where perhaps the socio-economic level of the country in which teachers work is a variable of the continuity of the digital divide.

In brief, research training requires a balanced education in digital skills paired with creativity and entrepreneurship. But what other competences are essential to train successful researchers to continue on the path of scientific and technological knowledge transfer? It would be interesting and valuable for the disciplinary fields to pursue further research in this direction.