
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13349-X
10.1016/j.heliyon.2024.e37318
e37318
Research Article
Digital competence of lecturers and its impact on student learning value in higher education
Dang Tran Dong trandongdang16@gmail.com
a
Phan Thanh Tú tu.pt@tmu.edu.vn
b
Vu Thi Nhu Quynh quynh.vtn@tmu.edu.vn
c
La Tien Dung latiendung@tmu.edu.vn
c
Pham Van Kiem kiem.pv@tmu.edu.vn
d⁎
a Faculty of Economics and Management, University of Hai Duong, QL37, Lien Hong, Gia Loc, Hai Duong, 170000, Viet Nam
b Centre of Science and Technology Research and Development, Thuongmai University, 79 Ho Tung Mau, Hanoi, 100000, Viet Nam
c Institute of Business Administration, Thuongmai University, 79 Ho Tung Mau, Hanoi, 100000, Viet Nam
d Faculty of Economics and International Business, Thuongmai University, 79 Ho Tung Mau, Hanoi, 100000, Viet Nam
⁎ Corresponding author: Van Kiem Pham, kiem.pv@tmu.edu.vn, Thuongmai University, Viet Nam. kiem.pv@tmu.edu.vn
03 9 2024
15 9 2024
03 9 2024
10 17 e3731828 3 2024
26 8 2024
31 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This paper explores the relationship between lecturers' digital competence and the learning value of students in higher education. By conducting an empirical study with a sample of 626 lecturers, we validated the positive impact of the six dimensions of digital competence outlined in the DigCompEdu framework, including: (i) Professional engagement, (ii) Digital resources, (iii) Teaching and learning, (iv) Assessment, (v) Empowering learners, and (vi) Facilitating learners' digital competence on the student learning value. Our findings underscore the profound significance of these dimensions in shaping students' learning experiences and outcomes, particularly within the dynamic context of Industry 4.0. Based on these findings, we propose recommendations to enhance lecturers’ digital competence, targeting not only the lecturers themselves but also university administrations and governmental agencies responsible for educational oversight.

Keywords

Digital competence
Digital skills
Learning value
Higher education
Industry 4.0
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pmc1 Introduction

Industry 4.0 is closely associated with technological breakthroughs, including advancements in artificial intelligence, the era of digitization, and the rapid development of interdisciplinary and multi-industry technologies. Although it is still in the early stages of digital transformation, the Industry 4.0 era has presented numerous opportunities and significant challenges across countries and sectors, including higher education [1,2]. During the Industry 4.0 era, Higher Education 4.0 has emerged and undergone profound changes due to the need for reskilling and upskilling. These changes span from the educational environment, the role of lecturers, and learners to teaching and learning methods, in comparison to previous higher education models [3,4]. In addition to its traditional roles of training and scientific research, Higher Education 4.0 focuses on a third mission: directly contributing to local socio-economic development [5]. This involves leveraging the learning value of graduates collected at the institution, which is then applied, utilized, and developed into practical work to enhance the local economy and society.

In Industry 4.0, the evolving model of Higher Education 4.0 has highlighted a pressing need to enhance the digital competence of university faculty members [6]. This is crucial for ensuring the quality of education in institutions and enhancing student learning value in the context of modern higher education [[7], [8], [9]]. Research on this issue clarifies how lecturers utilize technology in teaching, foster interaction in online classrooms, and apply digital tools to enhance teaching quality [1]. This insight supports the development of more effective teaching methods that meet the needs of digital students, ranging from creating online lectures to promoting interaction and collaboration across digital platforms [10,11].

However, in their literature review, Smestad et al. [12] highlighted that research on lectures' digital competence remains unclear, particularly concerning who stands to benefit from it and the specific role of lecturers. Therefore, research on lecturers’ digital competence also contributes to the development of a knowledge framework and essential skills needed for effectively using digital technology. This includes mastering online learning tools, software, and platforms, as well as the ability to evaluate and optimize digital teaching and learning processes. Furthermore, such research facilitates the identification of necessary measures to support the education and development of digital competence among lecturers [13,14]. This, in turn, enhances the quality of teaching and student learning value in the industry 4.0, thereby better preparing lecturers for the changes and advancements in the field of education.

In this context, our study focuses on the crucial importance of lecturers' digital competence in higher education and proposes actionable measures for stakeholders to address the challenges and capitalize on the opportunities arising from the digital transformation of learning in the Industry 4.0 era. Subsequently, the following sections will present a literature review on higher education trends in the Industry 4.0, lecturers’ digital competence, and hypothesis development. The subsequent section on research methodology will elaborate on the approach taken, including research design and analytical procedures. Following this, the sections on research results, discussions, and conclusion will present the empirical findings and provide detailed discussions and recommendations for theory, practice, and future research directions.

2 Literature review

2.1 Higher education in fourth industrial revolution

The history of human development has been closely associated with technological breakthroughs, which have significantly accelerated with the industrial revolutions, impacting not only the economy but also social life, including higher education. The current Industry 4.0 is characterized by the convergence of technologies across physics, digital technology, and biology, leading to the creation of entirely new production capabilities and significantly affecting the economy, politics, and society [15]. Industry 4.0 facilitates the creation of smart factories, smart products, and smart supply chains, thereby enhancing the flexibility and customer responsiveness of production and service systems. The nature of Industry 4.0 is fundamentally based on digital technology, integrating smart technologies to optimize production methods and processes, focusing on technologies with the greatest current and future impact, such as 3D printing, biotechnology, automation, robotics, etc. Thus, it can be affirmed that digital transformation is the foundation of Industry 4.0 and represents its initial step [16].

To analyze higher education in Industry 4.0, it is essential to consider the target audience or future “customers” of universities: the Alpha generation. This generation, born from the early 2010s to the mid-2020s, has been exposed to digital technology from a young age [17]. For them, technology is an integral part of life; thus, they are progressively developing skills to address technological challenges, as well as logical reasoning and problem-solving abilities. These digital natives actively integrate technology into their daily lives, with their positive learning behavior being enhanced by their digital competence [18]. Moreover, Generation Alpha is predicted to be more committed to education, engage in deeper learning, and pursue more promising careers than previous generations. This necessitates digital transformation in higher education to align with Industry 4.0 trends and meet the needs of these highly motivated learners [19,20].

Today, universities undertake a third mission: to support and/or facilitate the transformation of knowledge into intellectual property assets that can be exploited and commercialized in social life [5]. In contrast to the traditional education model, where the primary roles of universities are education and scientific research, the University 4.0 model represents a significant shift in focus [3,4]. It aims to fulfill the third mission of modern higher education by directly contributing to the socio-economic development of the country. Furthermore, this model enables the application, exploitation, and development of Industry 4.0 advancements within the university framework.

In fact, Industry 4.0 is driving the emergence and development of Higher Education 4.0. This model includes several key elements such as: internet connectivity (Internet of Things), intelligence (including smart hardware and software tools for education and learning, school management, and student support), and human factors involved in the model (such as lecturers, assistants, students, and experts …). At the same time, many smart tools, such as robots and artificial intelligence-based specialized software, are expected to replace humans in higher education activities. Self-directed study and research by students are continuously encouraged. The educational content is aligned with Industry 4.0 principles, with a focus on the application of digital transformation and technology in education [4,19].

Furthermore, Industry 4.0 and digital transformation have a significant impact on key stakeholders in higher education, such as lecturers, teaching assistants, students, and experts, etc. Emerging new disciplines, particularly those that integrate and leverage information technology, changes in occupational priorities, the influence of globalization, and rapid technological advancements are creating substantial pressure on these stakeholders. Lecturers must equip students with problem-solving and decision-making skills in digital are, and provide opportunities for them to engage in real work environments [21]. Additionally, students are expected to be more proactive and adaptable in their learning process and the application of their knowledge. In Industry 4.0, all relevant stakeholders must collaborate effectively to fulfill their responsibilities and support the evolving role of universities. This includes transitioning from being mere providers of knowledge to society to becoming active adapters to societal changes and problem solvers [1].

2.2 Digital competence of lecturers in Higher Education 4.0

Currently, the Industry 4.0 and the digital era are shaping the trend toward the Higher Education 4.0 model, which offers significant advantages. In this model, teaching programs are evolving and being regularly updated to align with the advancements of Industry 4.0. Moreover, Higher Education 4.0 serves as an ecosystem that enables lecturers and students to teach and learn anytime, anywhere, through connected devices, thereby making learning more personalized. In this context, universities tend to experiment with new technologies, continuously enhance teaching methods, and develop innovative forms of learning that remove constraints on time and place, thereby equipping students with more relevant skills [13,22].

This reality has led to changes in the roles of university lecturers. Lecturers are now empowered to be creative in responding to major changes in educational objectives and methods, shifting from the role of knowledge transmitters to unlocking students’ potential. At the same time, they design, catalyze, mentor, and create learning environments for learners. In the context of Industry 4.0 and the digital era, students are expected to engage in self-directed learning. Instructors guide students in learning through projects and in solving real-life problems [8]. This requires lecturers to enhance their practical knowledge to effectively guide students. Additionally, experts believe that online training, virtual training, simulation, and lecture digitization will be key trends in career training within Higher Education 4.0. Such changes necessitate that lecturers improve both their knowledge and digital skills to ensure high teaching quality and to effectively utilize digital educational resources [1].

In Higher Education 4.0, interactions among devices, as well as between devices, instructors, and learners, create new teaching methods. Some new skills are becoming essential for university lecturers, including problem-solving, creativity, and innovation. Given the trend of automation and machines replacing human roles, lecturers must be equipped with appropriate knowledge and skills to meet the demands of the evolving job market. This requires lecturers to actively research, develop, and innovate training programs to meet the demands of Industry 4.0 and the new pedagogical methods of higher education [1]. Job changes for lecturers necessitate the development of certain adaptive capabilities in the digital era, known as digital competence, which “… involves the confident and critical use of Information Society Technology (IST) for work, leisure and communication. It is underpinned by basic skills in ICT: the use of computers to retrieve, assess, store, produce, present and exchange information, and to communicate and participate in collaborative networks via the Internet” [23].

In higher education, the digital competencies of lecturers include the essential skills and practices needed to effectively utilize new technologies in the teaching process. These competencies are regarded as tools for self-directed learning, enabling lecturers to enhance their knowledge and work [7,24]. Digital competence extends beyond merely possessing technical skills to include the effective application of these skills in alignment with teaching strategies and pedagogical knowledge. Lecturers must not only manage technical resources proficiently but also integrate them meaningfully into their instructional practices [25]. They also allow lecturers to grasp key issues related to digital technology in both higher education and social life [8,13]. In essence, digital competency motivates lecturers to engage with the digital world and apply digital technologies in teaching, positioning themselves as active and responsible participants in the context of digital transformation and Industry 4.0.

2.3 Hypothesis development

The third mission of Higher Education 4.0, alongside teaching and research, emphasizes the importance of serving society and fostering students' holistic development [5]. In Industry 4.0, it is imperative to prioritize and enhance student learning value as a central aspect of higher education. According to SEEQ (Students' Evaluations of Educational Quality) framework, student learning value is defined as the perceived worth and effectiveness of the educational experience from the students' perspective [26,27]. This concept encompasses several dimensions: the effectiveness of teaching in achieving learning objectives, the relevance of course content to students’ goals and career needs, the applicability of acquired knowledge to real-world situations, and the overall assessment of the educational value received. It highlights the significant impact of university courses in shaping students into informed, engaged, and enthusiastic learners, well-prepared for the challenges and opportunities in their academic and professional journeys. Therefore, by placing a strong emphasis on student learning value, higher education institutions can ensure that graduates are well-prepared to address real-world problems and make meaningful contributions to society. These learning values benefit not only individual students but also contribute to a more globally competent and interconnected society, aligning with the broader goals of the third mission of modern higher education.

To analyze the role of lecturers' digital competence in relation to student learning value, we rely on the DigCompEdu (European Framework for the Digital Competence of Educators) framework developed by Redecker and Punie [28]. This framework specifies six dimensions of lecturers’ digital competence, which cover different aspects of their professional activities in higher education [29,30]. These dimensions have been recognized as having an impact on student learning value, specifically:

Lecturers' professional engagement, which refers to the commitment and dedication exhibited by prospective lecturers as they begin their teaching careers and their continued determination to stay in the profession [31], encompasses communication, collaboration, and professional development. This dimension focuses not only on teaching but also on professional interactions with colleagues, learners, learners’ parents, and other relevant parties, aimed at advancing their individual careers and contributing to the overall welfare of the university [28]. Lecturers can utilize digital resources for continuous professional development in Industry 4.0, as well as enhance communication with learners, their parents, and other stakeholders. Consequently, student learning value is significantly improved.

Empirical studies supported that, with professional engagement competence, lecturers can engage in more effective collaboration with their peers, share and exchange knowledge and experience, and collaborate on innovations and creative methods in pedagogical practices [32]. Núñez-Canal et al. [33] emphasize that lecturers' attitudes and commitment to integrating information and communication technology into their teaching practices play a significant role in shaping the learning outcomes of students, thereby highlighting the critical influence of lecturer engagement with technology on educational performance. De Obesso et al. [6] highlight that lecturers' engagement in the digital ecosystem, particularly through professional learning communities, enhances their teaching methods and use of digital tools, ultimately improving students’ learning experiences.

In support of the above arguments, we propose the following hypothesis:Hypothesis H1 Lecturers’ professional engagement positively influences student learning value in higher education.

Competence in digital resources involves the lecturers’ competence in sourcing, creating, and sharing resources to enhance student learning value. Lecturers in higher education have access to a diverse array of digital educational resources for teaching. They must thoroughly understand this diversity to accurately identify resources that align with their learning objectives, learner demographics, and teaching styles. Such understanding enables them to effectively mobilize, manage, and create resources to support their teaching [28]. Essentially, competence in digital resources pertains to how lecturers select, create, modify, manage, protect, and share digital resources in their teaching activities [1].

Empirical evidence supports that lecturers' competence in digital resources positively impacts student learning value by enhancing the quality and interactivity of educational materials. This competence allows lecturers to provide more engaging and relevant content, which students perceive as increasing the value of their learning experience. De Obesso et al. [6] emphasize that lecturers' use of digital resources for communication, monitoring, and assessment positively influences students’ learning perception, as their satisfaction is closely tied to assessment methods and support for learning progress. Ramírez-Montoya et al. [25] suggest that lecturer education programs on digital competence must systematically train them to effectively integrate digital resources into their teaching practices. In Industry 4.0, this dimension contributes to the development of high-quality learning resources in higher education. It serves as a fundamental premise for enhancing the quality of teaching content, addressing the shortage of teaching resources, and ensuring the suitability of resources for various teaching subjects, thereby increasing the student learning value [22].

Based on these arguments, we propose the following hypothesis:Hypothesis H2 Lecturers’ competence in digital resources positively influences student learning value in higher education.

Teaching and learning competence of lecturers in the Industry 4.0 era focuses on managing teaching and learning activities and coordinating the use of digital technology in these processes. This dimension facilitates the effective integration of digital technology across different stages and contexts of teaching in higher education. It involves teaching, designing, planning, and implementing the use of digital technology at various stages of the teaching process, including: teaching, guidance, instruction, collaborative learning, and self-regulated learning [28]. Núñez-Canal et al. [33] assert that the integration of technology in the teaching and learning process has been shown to have a significant impact on student learning outcomes.

The teaching and learning competence of lecturers contributes to enhancing the performance of planning and deploying digital tools and resources in the teaching process, as well as managing and coordinating teaching strategies appropriately, thereby increasing student learning value. With this competence, lecturers are able to experiment with and develop new pedagogical models and methods for teaching. Additionally, this competence facilitates interactions between lecturers and learners on both individual and collective levels, both inside and outside the classroom. It also enables the use of digital technology to provide timely, targeted guidance and support, as well as the testing and development of new models and methods for guiding and supporting learners [8]. Additionally, the teaching and learning competence of lecturers promotes and strengthens learner cooperation by enabling the use of digital technology to enhance communication, collaboration, and collaborative knowledge creation [34]. This competence allows learners to plan, track, and reflect on their own learning, provide evidence of progress, share insights, and offer creative solutions.

Therefore, the third hypothesis is proposed as follows:Hypothesis H3 Lecturers’ teaching and learning competence positively influences student learning value in higher education.

Learning assessment competence of lecturers involves the implementation of assessment strategies, analysis of evidence, and feedback and planning in higher education. This dimension integrates all three aspects to enhance the effectiveness of teaching assessment [28]. Goss [35] highlights the importance of effective assessment in evaluating student learning outcomes, emphasizing the need for higher education professionals to understand and implement assessment practices that contribute to improving student learning value and other related outcomes. In Industry 4.0, learning assessment competence enables lecturers to deliver assessments and develop new forms and methods that are suitable for emerging contexts. At the same time, it contributes to providing more accurate information for teaching and learning through the generation, selection, critical analysis, and interpretation of evidence regarding learners' activities, performance, and progress in higher education. Additionally, lecturers’ learning assessment competence provides targeted and timely feedback to learners and contributes to the adjustment of evidence-based support and instructional strategies [8].

Empirical studies support the positive impact of lecturers' learning assessment competence on student learning value. Ibarra-Sáiz et al. [36] demonstrates that the quality of assessment tasks, which reflects lecturers' learning assessment competence, significantly influences student learning value by mediating factors such as feedback, participation, empowerment, and self-regulation, thereby affecting students' perceptions and learning outcomes. Herppich et al. [37] clarify how lecturers' assessment competence, being context-specific and learnable, affects the effectiveness of assessment processes and enhances student learning value. Andersson and Palm [38] indicates that professional development in formative assessment significantly improves lecturers' formative classroom practices, which in turn enhances student achievement, demonstrating the positive impact of lecturers' assessment competence on student learning value. Karlen et al. [39] show that lecturers’ competence in accurately assessing self-regulated learning skills is essential for effectively supporting students, with improved diagnostic skills potentially enhancing student learning value.

Supporting the above perspective, we propose the following fourth hypothesis:Hypothesis H4 : Lecturers’ learning assessment competence positively influences student learning value in higher education.

Lecturers' competence in empowering learners encompasses innovative and creative activities designed to enhance learners’ ability to integrate, personalize, and actively use digital technologies in the higher education environment. This dimension revolves around learner-centered pedagogical strategies that promote active participation in the learning process. Competence in empowering learners focuses on accessibility and inclusion, differentiation and personalization, and actively engaging learners [28]. With the changes brought about by Industry 4.0, this competence of lecturers contributes to ensuring that learners have access to learning resources and activities. It addresses the diverse learning needs of students by supporting their progress across different educational levels, while following individual learning paths and goals.

In the literature, Sun and Yang [40] indicate that learner empowerment, as facilitated by lecturers, positively affects student learning outcomes and mediates the relationship between teaching, social, and cognitive presences and learning outcomes, highlighting its significant role in enhancing student learning value in online learning environments. Runge et al. [41] assert that lecturers' beliefs about their competence in empowering learners are positively associated with their reported use of technology to enhance instructional quality. Competence in empowering learners also promotes active and creative engagement with digital technology in Industry 4.0 through pedagogical strategies designed to foster learners’ transformational skills, critical thinking, and creative expression. Additionally, this competence provides opportunities for learners to practice and apply these skills in new and evolving contexts [19].

Therefore, the fifth hypothesis is proposed as follows:Hypothesis H5 Lecturers’ competence in empowering learners positively influences student learning value in higher education.

Lecturers' competence in facilitating learners’ digital competence involves finding and implementing effective and innovative methods to support and enable learners to use digital technologies creatively and responsibly for information, communication, content creation, and problem-solving. This dimension encompasses the innovation and creativity of information & media literacy, communication, content creation, responsible use, and problem solving [28].

Competence in facilitating learners' digital skills enables lecturers to assist learners in finding information and resources, organizing, processing, analyzing, and interpreting information, and comparing and assessing the reliability of information and sources [22]. Núñez-Canal et al. [33] highlight that fostering students' digital skills has been identified as a key factor influencing their learning outcomes. With this competence, lecturers can implement initiative measures to ensure the physical, psychological, and social well-being of learners while using digital technologies in Industry 4.0. They can also empower learners to manage risks and use digital technology safely and responsibly. In Industry 4.0, competence in facilitating learners’ digital competence contributes to effective teaching by helping learners identify and solve problems creatively in new situations, thereby enhancing the learning value for students.

Based on the above arguments, the sixth hypothesis is proposed as follows:Hypothesis H6 Lecturers’ competence in facilitating learners’ digital competence positively influences student learning value in higher education.

3 Research methodology

3.1 Research design

In this study, we employed a comprehensive research design to explore the relationship between lecturers' digital competence and student learning value in higher education. This approach involved a structured quantitative methodology based on survey data collected through a detailed questionnaire. The survey was carefully designed to capture the six dimensions of digital competence as outlined in the DigCompEdu framework. By targeting a sample of lecturers from Vietnamese universities, we ensured a diverse representation, allowing the findings to be both reliable and generalizable across different educational contexts in an emerging country. Ethical considerations were given high priority throughout the research process. All participants were informed about the study's objectives and provided their consent before participation. We ensured confidentiality by anonymizing the data and following ethical guidelines for data collection and storage.

For data analysis, we employed multiple linear regression to assess the impact of digital competence dimensions on student learning value. Confirmatory factor analysis (CFA) was conducted to validate the measurement model and ensure that the constructs accurately represent the dimensions of digital competence. We also applied reliability checks, such as Cronbach's alpha, to confirm the internal consistency of the survey items. These rigorous statistical techniques ensured the robustness of our findings, providing strong evidence for the positive influence of lecturers' digital competence on student learning value.

3.2 Data collection and research sample

Vietnam has over 200 universities, providing a wide array of academic programs and research opportunities. These higher education institutions range from large national universities, such as Vietnam National University, Hanoi, and Ho Chi Minh City University of Technology, to specialized institutions focusing on fields like technology, economics, and the arts.

To collect data, we conducted a questionnaire survey among lecturers at Vietnamese universities during the third quarter of 2023. We gathered data on lecturers from the official websites of Vietnamese universities. Following this, we distributed questionnaires via email and postal mail to those lecturers for whom contact information was available. To further enhance response rates, we also contacted some lecturers by phone or through in-person visits to their universities in major provinces of Vietnam, encouraging them to complete the surveys. Consequently, we received approximately 800 completed questionnaires. After processing and cleaning the completed questionnaires, we obtained 626 valid ones, which constitute our research sample. A descriptive analysis of the research sample is summarized in the table below.

In the research sample, respondents are lecturers from 126 Vietnamese universities, primarily concentrated in key provinces such as Hanoi, Ho Chi Minh City, Da Nang, Hai Phong, and Hue. The majority of these lecturers specialize in economics and management, accounting for 42.17 % of the sample. Regarding their professional experience, 33.87 % of lecturers have worked for 5 to less than 10 years, while the proportion of lecturers with less than 3 years of experience is the lowest (seeTable 1).Table 1 Research sample.

Table 1Criteria	Quantity	(%)	Criteria	Quantity	(%)	
Job position	626	100 %	Educational experience	626	100 %	
Lecturers	478	76.36	<3 years	72	11.50	
Lecturer cum manager	148	23.64	3 to less than 5 years	86	13.74	
Teaching majors	626	100 %	5 to less than 10 years	212	33.87	
Economics – Management	264	42.17	10 to less than 20 years	162	25.88	
Engineering - Industry – Technology	136	21.73	20 years or more	94	15.02	
Society - Language - Law – Medicine	126	20.13				

3.3 Variable measurement and regression method

The dependent variable of learning value consists of four aspects derived from lecturers' self-assessments using the SEEQ (Students' Evaluations of Educational Quality). This instrument has been widely used to assess the learning value of students in higher education [27,42,43]. The lecturers were asked to provide self-assessments on a Likert-type scale ranging from 1 (very poor) to 5 (very well), regarding aspects of learning value, including: (i) students' perceptions of lecturers' courses as intellectually challenging and stimulating; (ii) students' perceptions of valuable knowledge gained from lecturers' courses; (iii) students' increasingly interest in the subject as a result of lecturers' courses; and (iv) students’ learning and understanding of the course materials.

The independent variables are based on six dimensions of lecturers’ digital competence in DigCompEdu framework [28], including:(i) Professional engagement, consisting of four sub-competencies: organizational communication; professional collaboration; reflective practice; and digital continuous professional development;

(ii) Digital resources, consisting of three sub-competencies: selecting digital resources, creating and modifying digital resources; and managing, protecting, and sharing digital resources;

(iii) Teaching and learning, consisting of four sub-competencies: teaching; guidance; collaborative learning; and self-regulated learning;

(iv) Assessment, consisting of three sub-competencies: assessment strategies; analyzing evidence; and feedback and planning;

(v) Empowering learners, consisting of three sub-competencies: accessibility and inclusion; differentiation and personalization; and actively engaging learners;

(vi) Facilitating learners' digital competence, consisting of five sub-competencies: information and media literacy; digital communication and collaboration; digital content creation; responsible use; and digital problem solving.

In terms of variable measurement, based on the results of the Confirmatory Factor Analysis (CFA), both the dependent and independent variables exhibit Cronbach's Alpha coefficients exceeding 0.7, and the Kaiser-Meyer-Olkin (KMO) coefficients also exceed 0.7. Additionally, the extraction sums of squared loadings of the first component of all variables in the CFA exceed 60 % (Table 2). These findings confirm the validity of the variable scales for use in the regression analysis conducted in this research.Table 2 Variable measurement.

Table 2No	Variable	Label	Items	Cronbach's Alpha	Kaiser-Meyer-Olkin	Sig.	Extraction Sums of Squared Loadings of the first component (%)	
1.	PRofessional ENgagement	PREN	4	0.910	0.800	0.000	78.971	
2.	Competence in DIgital REsources	DIRE	3	0.879	0.713	0.000	81.229	
3.	TEaching and LEarning competence	TELE	4	0.848	0.803	0.000	68.693	
4.	Learning ASSEssment competence	ASSE	3	0.925	0.754	0.000	87.702	
5.	EMpowering LEarners competence	EMLE	3	0.820	0.714	0.000	73.622	
6.	Competence in FAcilitating LEarners' digital competence	FALE	5	0.941	0.786	0.000	80.970	
7.	EDUcational Experience	EDUE	1				100	
8.	LEarning Value	LEVA	4	0.879	0.780	0.000	73.455	

Based on the validity of the variable measurements, we conducted a regression analysis to verify the research hypotheses. The regression model was designed with student learning value as the dependent variable, representing the primary focus of the study. The six independent variables, corresponding to the dimensions of digital competence as outlined in the DigCompEdu framework, were included to measure the impacts of each dimension on student learning value. Additionally, a control variable of lecturers’ educational experience was included in the model to account for its potential influence on the relationship between digital competence and learning outcomes. This control variable helps to isolate the effect of the digital competence dimensions, thereby ensuring a more accurate interpretation of their impact. Specifically, the regression equation is formulated as follows:Y=a0+a1X1+a2X2+…+a7X7+ɛ

with: Y: leaning value (LEVA) of students in higher education; a0, a1, …, a11: coefficients to estimate; X1, X2 …, X6: six dimensions of lecturers' digital competence, including professional engagement (PREN), competence in digital resources (DIRE), teaching and learning competence (TELE), learning assessment competence (ASSE), competence in empowering learners (EMLE), competence in facilitating learners' digital competence (FALE). X7: lecturers' educational experience (EDUE) in higher education. ԑ: error term.

The regression analysis was performed using multiple linear regression methods to test the strength and significance of each hypothesis. This approach enabled us to rigorously assess the model's predictive power and provided a nuanced understanding of how each aspect of lecturers' digital competence contributes to enhancing student learning value in higher education.

4 Research results and discussions

Table 3 presents the regression results, including an F-statistic of 312.236 with a p-value of 0.000, showing that the model is statistically significant and provides a good fit to the data. The adjusted R-squared value is 0.777, indicating that the independent variables can explain 77.7 % of the variation in the dependent variable. This high value reflects a strong model fit, suggesting that the model accounts for a substantial proportion of the variation in the data. Moreover, an adjusted R-squared of this magnitude implies that the regression model strikes an appropriate balance between explanatory power and complexity, further indicating that the selected independent variables contribute meaningfully to explaining the dependent variable. The Durbin-Watson statistic of 2.048 indicates minimal autocorrelation in the residuals, suggesting that the residuals are approximately independent. This supports the validity of the model's estimates and aligns with the assumption of residual independence. Additionally, the multicollinearity analysis indicates that all VIF values are less than 4, confirming the absence of multicollinearity in the regression model. These results validate the regression model by allowing us to assess the validity of research hypotheses (see Table 4).Table 3 Regression results.

Table 3Model	Unstandardized Coefficients	t	Sig.	Collinearity Statistics	
B	Std. Error	Tolerance	VIF	
(Constant)	0.007	0.055	0.124	0.902			
PREN	0.305***	0.025	12.061	0.000	0.557	1.795	
DIRE	0.266***	0.024	11.204	0.000	0.633	1.581	
TELE	0.177***	0.027	6.510	0.000	0.485	2.062	
ASSE	0.158***	0.025	6.416	0.000	0.588	1.702	
EMLE	0.077***	0.019	4.018	0.000	0.976	1.025	
FALE	0.220***	0.026	8.386	0.000	0.520	1.923	
EDUE	−0.002	0.016	−0.132	0.895	0.947	1.056	
R = 0.883; R Square = 0.780; Adjusted R Square = 0.777; Std, Error = 0,472; Durbin-Watson = 2.048; F = 312.236; Sig. = 0.000.

* Significant at p < 0.05; **p < 0.01; ***p < 0.001.

Table 4 Summary of research findings.

Table 4	Variable	Hypothesis	Finding	
1.	Lecturers' professional engagement	Positive impact on student learning value	Supported	
2.	Lecturers' competence in digital resources	Positive impact on student learning value	Supported	
3.	Lecturers' teaching and learning competence	Positive impact on student learning value	Supported	
4.	Lecturers' learning assessment competence	Positive impact on student learning value	Supported	
5.	Lecturers' competence in empowering learners	Positive impact on student learning value	Supported	
6.	Lecturers' competence in facilitating learners' digital competence	Positive impact on student learning value	Supported	
7.	Lecturers' educational experience		No impact	

Regarding the first hypothesis, the regression results indicate that the independent variable PREN has a positive impact on student learning value (LEVA) at the 95 % confidence level (with B = 0.305; p-value = 0.000). So, hypothesis H1 is supported: the higher the professional engagement of lecturers, the higher the learning value of students, and vice versa. This finding aligns with existing literature on the DigCompEdu framework and empirical studies [6,32,33], particularly its emphasis on professional engagement as a key dimension of digital competence. It further supports the theoretical perspective that lecturers with higher engagement in their professional networks tend to improve student learning value.

In fact, by demonstrating high levels of professional engagement, lecturers will strive to innovate and develop activities for communication, collaboration, and professional development with colleagues, students, students’ parents, and other relevant stakeholders. As a result, they will collaborate more effectively with their colleagues by sharing and exchanging knowledge and experiences, as well as working together to innovate and create pedagogical practices. Thus, in the Industry 4.0 era, high levels of professional engagement enable lecturers to effectively utilize digital resources to enhance their teaching quality, thereby improving student learning value.

In line with the DigCompEdu framework, this study emphasizes the critical role of collaboration and innovation in the digital age. Lecturers who are professionally engaged not only foster better communication with peers and students but also utilize digital tools to refine pedagogical strategies. Such proactive engagement allows lecturers to better integrate digital resources and methods into their teaching, improving the overall quality of instruction and, consequently, student learning value. Therefore, these findings add to the growing body of literature affirming the significant role that professional engagement, as conceptualized in DigCompEdu, plays in enhancing the effectiveness of digital teaching in higher education.

Regarding the second hypothesis, the regression results reveal that the digital resources (DIRE) competence of lecturers significantly influences student learning value (LEVA), with a positive coefficient (B = 0.266) and strong statistical significance (p-value = 0.000). We can validate hypothesis H2: As lecturers’ competence in digital resources increases, the learning value of students also increases, and vice versa. When lecturers are proficient in utilizing digital resources such as online learning platforms, interactive simulations, and cutting-edge software tools, they can create more engaging and interactive learning environments.

The regression results align with the perspective of DigCompEdu framework and empirical studies [6,22,25], showing that when lecturers utilize digital resources effectively, they promote student engagement, critical thinking, and motivation, ultimately improving the overall learning experience. In the context of Industry 4.0, lecturers in higher education must actively manage and explore digital resources by staying current with rapid advancements in knowledge. They should take advantage of opportunities to access digital resources as universities seek partnerships, develop international cooperation projects, and mobilize resources through various means to supplement, update, and develop learning resources. These resources can facilitate active participation, personalized learning pathways, and real-world problem-solving experiences for students. Consequently, students are more likely to understand complex concepts, develop critical thinking skills, and remain motivated throughout their educational journey.

Moreover, the DigCompEdu framework emphasizes the growing importance of open educational resources in modern pedagogy. By contributing to the development and sharing of these resources, lecturers expand the accessibility and relevance of learning materials. Through interactive activities, learning, and research, universities' digital resources have become increasingly useful and interconnected, enhancing their effectiveness in various aspects of use. Consequently, lecturers’ competence in finding and exploring digital resources contributes to improving their teaching quality, thereby enhancing the learning value for students.

Regarding the third hypothesis, the regression results indicate that teaching and learning (TELE) competence significantly impacts student learning value (LEVA), with a positive coefficient (B = 0.177) and a p-value of 0.000. This finding supports hypothesis H3, confirming that the higher the lecturers' teaching and learning competence, the greater the learning value students derive. This aligns closely with the DigCompEdu framework and empirical studies [8,34], which emphasizes the role of teaching and learning competence as a core dimension of lecturers’ digital competence.

In fact, teaching competence encompasses the ability to convey complex concepts effectively, create engaging and inclusive learning environments, and adapt to various teaching modalities, including online and blended learning formats. Lecturers with high teaching competence equip students with the skills, knowledge, and critical thinking abilities needed to thrive in a rapidly changing world. Conversely, learning competence focuses on empowering students to become active, self-directed learners. Lecturers who foster learning competence encourage students to take ownership of their education, seek out resources, and engage in continuous learning beyond the classroom. This is especially crucial in an era where the ability to acquire new knowledge and adapt is paramount.

The regression results and the DigCompEdu framework collectively underline that the interplay between teaching and learning competence creates dynamic, impactful student learning value. Lecturers who are proficient in both areas not only impart knowledge but also cultivate skills that enable students to think critically and independently. In contrast, lecturers lacking these competencies may struggle to engage students or prepare them for the rapidly evolving demands of the Industry 4.0 era, ultimately diminishing the learning value and long-term success of students.

Regarding the fourth hypothesis, the regression results indicate that the independent variable ASSE has a positive impact on student learning value (LEVA) at the 95 % confidence level (with B = 0.158; p-value = 0.000). This validate hypothesis H4. Lecturers who prioritize and excel in this competency create an educational environment that encourages critical thinking, problem-solving, and adaptability. This aligns with the DigCompEdu framework and empirical studies [[36], [37], [38]], which emphasizes assessment as a key component of digital competence. Lecturers who excel in this area not only measure learning outcomes but also foster critical thinking, problem-solving, and adaptability, which are essential in the digital age.

The regression findings and the DigCompEdu framework together underscore the importance of assessment competence in modern education. In the context of Industry 4.0, lecturers with strong assessment skills develop innovative methods that go beyond traditional exams. They develop innovative and meaningful assessments that challenge students to apply their knowledge, engage in critical thinking, and solve real-world problems. Moreover, lecturers proficient in learning assessment competence excel in providing timely and constructive feedback to students. This feedback loop not only helps students understand their strengths and weaknesses but also motivates them to engage more deeply with the learning process. These contribute to providing more accurate and timely information for teaching and learning, facilitating the adjustment of teaching strategies and enhancing student learning value.

Regarding the fifth hypothesis, the regression analysis shows that the independent variable of empowering learners (EMLE) has a positive impact on student learning value (LEVA) at the 95 % confidence level (B = 0.077; p-value = 0.000). Therefore, Hypothesis 5 is supported. This finding is consistent with the DigCompEdu framework and empirical studies [40,41], which highlights empowering learners as a crucial dimension of digital competence. Lecturers who excel in this competency enhance the educational experience by fostering adaptability, innovation, and lifelong learning among students. The reciprocal nature of this relationship is evident: as lecturers become more adept at empowering learners, students benefit from increased learning value.

Lecturers proficient in empowering learners create environments where students are not merely passive recipients of knowledge but active participants in their educational journey. This approach encourages curiosity, critical thinking, and problem-solving skills, aligning with the DigCompEdu emphasis on student-centered learning. Such lecturers instill confidence in students to navigate the evolving world of information and technology. The literature supports this, suggesting that effective empowerment helps students develop a growth mindset, view challenges as opportunities for growth, and build resilience. Conversely, in a scenario where lecturers lack competence in empowering learners, students may miss the opportunity to develop the skills and mindset necessary to thrive in the digital age. They may encounter challenges in adapting to rapidly changing technologies, industries, and job roles.

In the face of the rapid transformations of Industry 4.0, lecturers are adopting innovative and creative approaches to empower students. The DigCompEdu framework advocates for student-centered pedagogical strategies that promote active engagement and initiative. By implementing these strategies, lecturers help students become more proactive in seeking resources, conducting research, and exploring personalized learning pathways. As a result, students' learning value increases, reflecting the positive impact of lecturers’ competence in empowering learners on their overall educational experience.

Confronted with the significant changes brought about by Industry 4.0, lecturers in higher education actively adopt innovative and creative approaches to empower students. These efforts establish a crucial foundation for students to develop positive thinking and enhance their initiative in the learning process. Such activities are undertaken by lecturers through the implementation of student-centered pedagogical strategies. As a result, students have become increasingly active in the learning process, actively seeking out resources, conducting research, and implementing learning pathways with greater initiative. Consequently, the learning value that students gain from higher education will increase.

Regarding the sixth hypothesis, the regression results indicate that the independent variable FALE has a positive impact on student learning value (LEVA) at the 95 % confidence level (with B = 0.220; p-value = 0.000). This confirms hypothesis H6: the higher the lecturers' competence in facilitating learners’ digital competence, the greater the student learning value in higher education. This aligns with the DigCompEdu framework and empirical studies [22,33], which emphasizes the importance of digital competence in enhancing educational outcomes.

In fact, lecturers who excel in facilitating learners' digital competence not only possess a deep understanding of digital technologies but also have the capacity to teach students how to navigate, evaluate, and leverage these tools effectively. They create an environment that promotes digital literacy, critical thinking, and ethical use of technology, as outlined in the DigCompEdu framework. The literature supports this, highlighting that such facilitation equips students to leverage technology for research, collaboration, and problem-solving. Conversely, when lecturers lack competence in facilitating learners’ digital competence, students may struggle to adapt to the demands of the digital age. They might miss opportunities to leverage technology for research, collaboration, and problem-solving, which can hinder their preparedness for future careers and limit their overall learning value.

In the context of Industry 4.0, lecturers in higher education must be actively innovative in their methods of supporting students, including finding and implementing effective new strategies to facilitate students’ use of digital technologies. As a result, lecturers will adopt new measures to ensure optimal conditions for students to use digital technology safely and responsibly. This improvement in teaching practices will enhance the quality of education and, consequently, the learning value for students.

Regarding the control variable, we find that the variable EDUE has no significant impact on student learning value (LEVA) at the 95 % confidence level (with B = −0.002; p-value = 0.895). This suggests that lecturers' educational experience may not be a determinant of student learning value in the Industry 4.0 era. The value of a lecturer's educational experience may diminish if they are unable to adapt quickly to the latest technologies and trends. Students often rely on up-to-date information and skills that may not necessarily align with a lecturer's past educational experiences. In the digital era, students have access to online lectures, courses, and tutorials from experts worldwide. Consequently, the impact of any individual lecturer's educational experience may be diminished by the broader educational landscape available to students.

Moreover, students in the Industry 4.0 era exhibit diverse learning styles and preferences. While some may benefit from a lecturer's extensive educational experience, others may thrive with alternative approaches, such as hands-on projects, peer collaboration, or self-directed learning. Students often learn most effectively through direct engagement with real-world challenges and practical experiences. In this context, a lecturer's educational background may play a less significant role compared to the practical skills and experiences they facilitate in the classroom. Thus, a lecturer's educational experience may not be the sole determinant of learning value.

5 Research implications

5.1 Research implications for lecturers in higher education

In the context of Industry 4.0 and digital transformation, lecturers must first clearly understand the levels of digital competency and identify which of the three levels - technology knowledge, deepening knowledge, and creation knowledge - they need to focus on in order to enhance their digital competency. Understanding the characteristics of each competency level is crucial for lecturers, as it helps them advance their skills and make a significant contribution to the digital transformation process at universities.

Secondly, lecturers need to focus on improving six groups of digital competencies in higher education to enhance teaching quality through the effective application of digital transformation in the teaching process. Digital competency groups (including application to professional practice, digital resources, teaching and learning, assessment, empowering learners, and promoting learners’ digital competencies) play an equally important and mutually complementary role. Therefore, lecturers need to actively improve each of these competency areas.

Thirdly, lecturers need to actively raise awareness and change mindsets regarding the role of digital transformation and Industry 4.0 in educational activities. This awareness will enable them to recognize the importance of digital competency for higher education, particularly in teaching activities within the current context. Enhancing awareness and changing mindsets are essential prerequisites for lecturers to be more proactive and engaged in applying digital transformation to their professional practices.

Fourthly, to enhance digital competency in the current context, each lecturer needs to define the professional characteristics relevant to their responsibilities and select teaching methods that align with their expertise. Additionally, lecturers should consider learners’ characteristics, preferences, and adaptability to different teaching methods. They must also stay updated on new trends in learning and development, as well as advancements in learning technology, education, and training.

Fifthly, enhancing lecturers’ digital skills is essential in the context of Industry 4.0 and digital transformation. Digital skills should be flexible, encompassing not only theoretical knowledge but also practical vocational skills. This ensures that learners can immediately apply their skills in their profession and meet social demands effectively.

5.2 Research implications for universities

Universities must prioritize investment in advanced digital infrastructure to support both lecturers and students, including improved internet connectivity, access to e-learning platforms, and software licenses for educational tools. The findings highlight the importance of lecturers’ ability to access and use digital resources effectively. Universities should ensure that all lecturers have access to high-quality digital tools, such as online learning platforms, educational software, and multimedia resources. By providing a robust digital environment, universities can empower lecturers to integrate these tools into their teaching practices, which will, in turn, enhance student learning value.

Universities need to actively develop digital competencies for lecturers to meet job requirements. This involves implementing training programs, fostering professional growth, and aligning recruitment and employment practices with strategic planning. Additionally, universities should apply policies that motivate lecturers, encourage dedication, and foster creativity. Furthermore, universities need to enhance international integration and collaborate with leading pedagogical training institutions both globally and regionally. This will create opportunities for lecturers to exchange knowledge and develop their digital competencies within the context of Industry 4.0 and digital transformation.

Universities should foster a culture that encourages the adoption and innovation of digital technologies in teaching. This requires leadership to actively promote and support the integration of digital resources and teaching strategies across departments. Universities can foster collaboration by establishing digital innovation hubs where lecturers exchange best practices, explore new technological tools, and share digital teaching strategies. These hubs can be supported by interdisciplinary teams that assist with digital integration across various disciplines and faculties.

Universities need to establish mechanisms and policies, and create favorable conditions to attract and utilize both domestic and foreign investment for training and developing lecturers’ digital competencies in the digital era. To more effectively mobilize investment resources for digital competency development in higher education, universities must uphold their responsibilities to the state, learners, and society. Additionally, universities should ensure transparency in their operational structures and achieve financial autonomy.

5.3 Research implications for government agencies

Government agencies should develop and implement national standards for digital competence in education, emphasizing the critical role this competence plays in enhancing student learning value. By establishing and enforcing clear benchmarks, including guidelines and assessment criteria for lecturers, government agencies can ensure that lecturers across higher education institutions are equipped to meet contemporary demands. These standards should be regularly updated to reflect technological advancements and emerging educational needs, thereby promoting uniform and high-quality teaching practices nationwide.

To support the integration of digital tools and resources in higher education, government agencies should establish dedicated funding programs specifically for digital education initiatives. This funding should encompass grants for upgrading digital infrastructure, purchasing educational software, and supporting professional development programs for lecturers. By providing financial support for these areas, government agencies can enable higher education institutions to implement and sustain digital innovations, thereby enhancing the overall quality of teaching and also student learning value.

Government agencies should facilitate partnerships between higher education institutions and technology companies to advance digital education. Collaborations with the private sector can provide schools and universities with access to the latest technologies, training resources, and technical expertise, while also fostering innovation in teaching methods and digital tools. To support these partnerships, government agencies should create incentives such as tax benefits for technology companies that contribute to educational initiatives and develop programs that match higher education institutions with tech firms to pilot new digital solutions.

To ensure lecturers remain proficient in digital competencies, government agencies should implement policies that mandate continuous professional development and regular digital skills training. These policies should include requirements for annual professional development credits related to digital competencies and provide support for universities to offer relevant training opportunities. Additionally, to support the development of digital competencies, agencies should ensure universities have autonomy in selecting and approving lecturers and encourage policies that attract qualified individuals to higher education institutions. This approach will promote lifelong learning among lecturers, improve the effectiveness of digital education, and provide a solid foundation for advancing digital skills within the academic context.

6 Conclusion

This paper examines the impact of lecturers' digital competence on the learning value of students in higher education. Through an empirical study involving 626 lecturers in Vietnamese universities, we validated the positive effects of the six dimensions of digital competence as outlined in the DigCompEdu framework: (i) Professional engagement, (ii) Digital resources, (iii) Teaching and learning, (iv) Assessment, (v) Empowering learners, and (vi) Facilitating learners’ digital competence.

This research contributes to the understanding of how lecturers' digital competence enhances students' learning value in higher education. By empirically validating the six dimensions of digital competence from the DigCompEdu framework with a sample of 626 lecturers in Vietnamese universities, the findings provide valuable insights for lecturers, universities, and policymakers by emphasizing the critical importance of these dimensions in enhancing students' learning experiences and outcomes, particularly within the evolving context of Industry 4.0. Specifically, it provides practical recommendations for lecturers to enhance their digital skills, thereby fostering an environment that promotes improved student learning experiences. Additionally, the research advocates for institutional and governmental support through training programs, resource allocation, and policy initiatives designed to promote the development of lecturers’ digital competence. By implementing these recommendations, stakeholders can significantly contribute to advancing educational quality and student learning value in the Industry 4.0.

Our study has certain limitations inherent in the research methodology and scope. The primary limitation lies in the focus on Vietnamese universities and the reliance on self-reported data, which may introduce biases or inaccuracies in measuring lecturers' digital competence and student learning value. Additionally, the study's focus on higher education settings may limit the generalizability of the findings to other educational levels or contexts. Furthermore, the study primarily examines the direct impact of lecturers' digital competence on student learning value, without considering certain confounding variables, potential mediating or moderating factors that could influence the research findings.

In terms of research perspectives, several promising avenues for future inquiry emerge. Firstly, longitudinal studies could investigate the long-term effects of interventions aimed at enhancing lecturers’ digital competence on student learning trajectories. Secondly, comparative studies across different educational systems or cultural contexts could provide insights into the variability of these effects and inform tailored approaches to digital pedagogy. Additionally, qualitative research methodologies, such as in-depth interviews or case studies, could offer rich insights into the experiences and perceptions of both lecturers and students regarding digital teaching and learning practices.

Funding information

This research is funded by Thuongmai University, Hanoi, Vietnam (Grant ID: NNC23-10 ).

CRediT authorship contribution statement

Tran Dong Dang: Writing – original draft, Project administration, Conceptualization. Thanh Tú Phan: Methodology, Formal analysis, Data curation. Thi Nhu Quynh Vu: Writing – original draft, Formal analysis, Conceptualization. Tien Dung La: Writing – original draft, Supervision. Van Kiem Pham: Writing – review & editing, Visualization.

Declaration of competing interest

The authors declare that there is no conflict of interest!
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