Digital learning in Sciences education: A literature review

Abstract

This study looked at 8760 Web of scientific research publications about digital learning in scientific education. The researchers discovered seven clusters with 59 affiliations, 36 keywords, and 135 authors from 28 countries using bibliometric and text analysis approaches. The study provides useful insights into the present status of digital learning literature, providing recommendations to scholars and educators in this sector. The research highlighted the use of technology to improve scientific teaching by evaluating the data. The findings have consequences for academics, educators, and policymakers, allowing them to better understand current research and propose prospective topics for future study in digital learning in scientific education.

Keywords:

• digital learning
• sciences education
• vosviewer
• biblioshiny
• bibliometric analysis

PUBLIC INTEREST STATEMENT

This research explores the fascinating world of digital learning in scientific education. Imagine a classroom where technology enhances the way we teach and learn about the sciences. The study delves into 8760 scientific publications, uncovering trends and insights from researchers in 28 countries.

What’s intriguing is the discovery of seven distinct clusters of research, shedding light on how digital tools are transforming science education. This isn’t just for academics; it matters to educators and policymakers too. By harnessing technology effectively, we can revolutionize the way we teach and learn about the world around us.

So, whether you’re a curious parent, a tech enthusiast, or someone passionate about improving education, this research offers valuable insights into the future of scientific learning. It’s a glimpse into how we can make science more engaging, accessible, and exciting for everyone.

1. Introduction

Digital learning has been highlighted as a revolutionary force in science education, providing new chances for students and teachers to connect with scientific topics in novel ways (Iivari et al., 2020). As technology advances, so does the opportunity for digital learning to improve the quality and accessibility of science education. Recent study has looked into the advantages and disadvantages of digital learning in scientific education, such as the usage of digital simulations, online resources, collaborative learning, customized learning, and gamification (Lee et al., 2020). Some research has demonstrated that digital learning can boost student engagement, motivation, and learning results, while others have expressed worry about the potential for technology to replace conventional teaching techniques and limit social connection (Kurt et al., 2022; Melgaard et al., 2022). Despite these obstacles, many educators and researchers are working to find meaningful and successful strategies to include digital learning into scientific education (Bidarra & Rusman, 2017). Digital learning has the ability to alter the way we teach and learn about science by utilizing the power of technology to create immersive and interactive learning experiences (Peimani & Kamalipour, 2021).

Digital learning in scientific education has several advantages, including greater engagement and motivation, improved accessibility, individualized learning, collaborative learning, and gamification (Jovanović & Milosavljević, 2022). Digital tools and platforms may be used to build interactive and immersive learning experiences that can help students’ better grasp scientific topics and apply them in real-world circumstances. However, there are some drawbacks to digital learning, such as the cost and accessibility of technology, technical difficulties, limited social interaction, the potential for digital distractions, and the risk of undervaluing traditional teaching methods (Dazhi & Baldwin, 2020; Kamiska et al., 2019). Despite these challenges, educators and researchers are investigating strategies to incorporate digital learning into scientific education in meaningful and successful ways, using the benefits of technology while addressing possible downsides (Williamson et al., 2020). As a result, digital learning has the potential to alter scientific education and assist students in developing the skills and knowledge required to flourish in a fast-changing environment (Solís et al., 2022).

Science education might change due to digital learning, both in developed and developing countries. The advantages and difficulties of digital learning change based on the situation. High-quality scientific education may be accessed in developing countries despite obstacles like scarce resources and remote locations thanks to digital learning (Keskin et al., 2022). Digital learning in developed countries may provide individualized and interactive learning experiences that encourage participation and cooperation (Louis et al., 2021; Tapalova & Zhiyenbayeva, 2022). Lack of access to technology and online resources, technical difficulties, and cultural resistance to change are obstacles to digital learning in both contexts (Faturoti, 2022; Febrianto et al., 2020; Ferri et al., 2020; Ludwig & Giovanna Tassinari, 2023; Mulenga & Marbán, 2020; Yan et al., 2021). To guarantee that digital learning can be successfully included into scientific education in all situations, it is crucial to acknowledge and overcome these issues.

Traditional scientific teaching methods such as textbooks, lectures, and hands-on experiments may not adequately interest students or prepare them for the current world (Simpson et al., 2017). Digital learning has emerged as a viable answer, allowing students to connect with scientific issues in innovative and immersive ways (Bidarra & Rusman, 2017; Rapanta et al., 2021). However, concerns have been raised about its effectiveness and the potential for it to exacerbate existing inequalities. The purpose of this research is to survey the present literature on digital learning in scientific education, identify research trends, and evaluate its evolution over time (Yawei et al., 2019; Zhao et al., 2023). The purpose is to lead future research initiatives and contribute to a better understanding of the digital learning research environment in scientific education.

Traditional approaches to scientific education may not adequately interest students or equip them for the requirements of modern society. Digital learning has emerged as a potential alternative, but incorporating it within scientific education is difficult. Understanding the advantages and disadvantages of digital learning, as well as establishing effective ways for bringing technology into the classroom, is crucial for success (Agoritsa et al., 2021; Al-Azawei et al., 2016; Maatuk et al., 2022; McDiarmid & Zhao, 2022; Radianti et al., 2020). Change resistance may also be a big hindrance, making good change management leadership and communication strategies essential. The purpose of this study is to examine the present state of research on digital learning in scientific education, identify trends and gaps, and make recommendations for successful integration.

Science education was chosen as our research focus due to its fundamental role in shaping the future of society and the transformative potential of digital learning (Bidarra & Rusman, 2017; Rapanta et al., 2021). Science is the foundation of our understanding of the world, informs decision-making, and helps us to address global challenges. However, traditional teaching methods often struggle to engage students and prepare them for the rapidly evolving technological landscape (McDiarmid & Zhao, 2022; Radianti et al., 2020). Digital learning offers interactive, personalised experiences that cultivate curiosity and critical thinking (Agoritsa et al., 2021). As education adopts digital technologies worldwide, it is imperative to explore their effective integration in science education while addressing potential disparities (Al-Azawei et al., 2016; Maatuk et al., 2022). This research aims to bridge the gap between digital learning’s promise and practical implementation, ensuring equitable access to quality science education, fostering innovation, and inclusivity for a brighter future.

The purpose of this literature review is to contribute to the field of digital learning in scientific education by giving a thorough assessment of existing research on the advantages, limits, and best practices of digital learning. It also identifies significant research trends and gaps in the subject, emphasizes the importance of suitable change management strategies, and offers recommendations for effective digital learning integration in the classroom. The introduction of the research emphasizes the importance and relevance of digital learning in scientific education and sets the tone for the literature review. This study summary is a helpful resource for educators, policymakers, and researchers interested in understanding how digital learning has the potential to alter scientific instruction and enhance students’ learning results.

The study is divided into five sections. The second part summarizes prior bibliometric studies on the subject issue. The final section goes into great depth on the research process. The fourth section summarizes the findings of the research, providing an overview of the field’s evolution and contemporary change management trends in corporate settings. The fifth and final part analyzes the study’s findings, limitations, and recommendations for further research. The article’s format allows readers to grasp the study procedure, outcomes, and areas that need additional examination.

1.1. Digital learning in sciences education bibliometric review

Digital Science Education In recent years, education has become an increasingly significant issue, and the academic community has been actively exploring it. Bibliometric studies have been conducted to investigate trends and patterns in this subject’s study. The findings of these bibliometric evaluations can give useful insights into the present status of research in this field, as well as help to build successful digital learning techniques for scientific education.

In recent years, digital learning in scientific education has received a lot of attention, and bibliometric research has been very helpful in finding trends and patterns in this sector. The effectiveness of digital learning in improving student learning outcomes (Tibaná-Herrera et al., 2018), its impact on teacher-student interactions (Chen et al., 2021), and the role of instructional design in creating effective digital learning environments (Behl et al., 2022) have all been studied. Scholars stress the significance of digital literacy and technical competences in both teachers and students (Behl et al., 2022; Chen et al., 2021; Tibaná-Herrera et al., 2018). Maria et al. (2021) and Basilotta-Gómez-Pablos et al. (2022) discovered that the use of technology and the development of digital skills were critical themes in scientific education digital learning study. These papers give important insights into the present state of research and can help to design successful digital learning strategies in scientific teaching.

The usage of digital tools and technology is altering the scientific education scene. Key trends and subjects in this discipline have been highlighted through bibliometric study. According to Faruk et al. (2019), augmented reality in scientific education is a popular topic, with learning outcomes, motivation, and attitude being regularly investigated factors. Sudakova et al. (2022) highlighted formative assessments in postsecondary education as an important topic of study, citing key sources such as Assessment and Evaluation in Higher Education and Computers and Education. Zhang et al. (2022) performed a survey of peer-reviewed publications on online learning in higher education during the COVID-19 epidemic, showing different research themes such as technology utilization, curriculum creation, and student views. Schöbel et al. (2021) carried out a bibliometric analysis on digital learning, emphasizing the significance of game concepts and providing a research agenda for future studies.

Subsequently, recent bibliometric studies have underlined the relevance of digital learning in scientific education, looking at crucial areas such as technology use, influence on student outcomes, the efficacy of online platforms, and teacher professional development. Best practices were also found in the research, such as student-centered learning, active learning approaches, and the utilization of multimedia assets. Applying these findings can improve the efficacy of digital learning in science education and better prepare students for modern-day challenges.

2. Methodology

The study employed a two-phase research process that included bibliometric analysis. The first step comprised utilizing bibliometric methods to assess the performance of the research field on digital learning in scientific education, while the second part concentrated on developing a visual map of the references in this subject. Bibliometric analysis is a valuable approach for mapping and measuring the academic influence of authors, institutions, nations, and journals in a certain topic (Drijvers et al., 2020).

For bibliometric analysis, several databases are accessible, including Google Scholar, Scopus, Dimensions Database, and Web of Science. The authors investigated digital learning in scientific education using the Web of scientific Core Collection for their study. To undertake the bibliometric analysis on the journals listed in the database, the authors employed the Science Citation Index Expanded and the Social Sciences Citation Index. Web of Science was chosen because of its broad coverage of publications and journals in comparison to other databases, as well as the wealth of bibliographic information it provides, such as author affiliations, publication year, title, abstract, subject categories, source journal, and references (van Eck & Jan, 2010).

The reliability and validity of the 8,760 articles selected for analysis were ensured through a rigorous screening and eligibility process. Initially, a comprehensive search strategy was employed to identify relevant articles using specific keywords related to digital learning in science education. Subsequently, the Web of Science Core Collection database was utilised, known for its extensive coverage and reliable bibliographic data. The inclusion criteria were applied consistently to filter out irrelevant records, resulting in the final dataset of 8,760 articles. This stringent selection process, in conjunction with the use of established and widely recognised databases, enhances the reliability of the dataset. Moreover, the inclusion of articles published over a 30-year period (1992–2022) further supports the validity of the dataset, as it encompasses a broad and representative range of research on the topic. Overall, the careful selection and comprehensive nature of the dataset contribute to the reliability and validity of the articles included in the bibliometric analysis (van Eck et al., 2018).

To analyze articles about digital learning in science education, the authors used the keywords ((“Digital” OR “Technology” OR “Learning”) AND (“Science Education” OR “Technological Education”) to search the Web of Science Core Collection database for English language articles published between 1992 and 2022. Bibliographic data from the search were exported in Bibliography TeX (.bib) format and processed in R Studio (version 4.2.2) using the bibliometric R package. This R package is a strong tool for analyzing and displaying bibliometric data, employing efficient mathematical techniques and delivering high-quality computational procedures. van Eck et al. (2018). The Web of Science database core collection, which includes all fields, document types, and dates up to 2022, was searched in the study’s second phase by the researchers. They eliminated 32,243 entries from their screening of 41,286 records that had a title, abstract, and keywords. The eligibility of the whole articles was then determined, yielding 9,043 items. The quantitative synthesis was completed using the 8,760 articles that remained after 283 records were excluded as shown in Figure 1. The researchers utilized the exported data to produce visual maps of co-occurring keywords, nations for co-authorships, the most pertinent affiliations, a three-field plot, and most global cited documents using the VOSviewer and biblionshiny program, developed by Nees Jan van Eck and Ludo Waltman (van Eck & Jan, 2010).

Figure 1. Flowchart illustrating the process of including and excluding papers.

2.1. General information

The general information extracted from the Web of Science Core Collection database is shown in Table 1. The data analyzed spanned from 1992 to 2022 and were sourced from 37 journals, books, and other documents. The dataset included 50 documents, with an annual growth rate of 6.94% and an average document age of 9.06 years. The average number of citations per document was 17.36, and there were a total of 2,290 references. The dataset included 134 authors, with nine single-authored documents. The average number of co-authors per document was 2.78, and 20% of co-authorships were international. The document types included articles, book chapters, proceedings papers, and reviews (Liu et al., 2021).

Table 1. Web of science core collection general information

Description	Results
Main Information About Data
Timespan	1992:2022
Sources (Journals, Books, Etc)	37
Documents	50
Annual Growth Rate %	6.94
Document Average Age	9.06
Average Citations Per Doc	17.36
References	2290
Document Contents
Keywords Plus (Id)	107
Author’s Keywords (De)	143
Authors
Authors	134
Authors Of Single-Authored Docs	9
Authors Collaboration
Single-Authored Docs	9
Co-Authors Per Doc	2.78
International Co-Authorships %	20
Document Types
Article	29
Article; Book Chapter	3
Article; Proceedings Paper	1
Proceedings Paper	12
Review	5

3. Findings

3.1. Keywords analysis

The study utilized bibliographic data from the Web of Science Core Collection database to conduct bibliometric analysis and mapping using the VOSviewer program. To determine the strength and significance of keywords, co-occurrence analysis was conducted, and the resulting map revealed 7 clusters with the science education term being the strongest and most impactful, appearing 33 times and being closely related to almost every other keyword. Other significant clusters included technology, inquiry-based learning, school, and knowledge students, with each cluster containing multiple related keywords listed in order of strength. Overall, there were 242 text-data terms and 36 of them met the 2 threshold criteria and were able to form 7 clusters: cluster 1 (red), cluster 2 (green), cluster 3 (blue), cluster 4 (yellow), cluster 5 (purple), cluster 6 (light blue), and cluster 7 (orange). The significance of the circles and texts within each cluster indicates how often they are mentioned alongside other keywords, reflecting the strength of their co-occurrence. On the other hand, the distance between the items and the lines on the map reveals the level of relatedness and linkages between the different keywords. Figure 2 shows the resulting keyword co-occurrence map.

Figure 2. Keyword co-occurrence.

Figure 3 illustrates a timeline of e-learning culture and reform initiatives since its inception in 2010. The timeline indicates that the school had a well-planned and deliberate approach towards implementing e learning, starting in 2014 with the application of science education methods through technology-enhanced learning. The focus shifted towards inquiry-based learning using technology in 2016, and after 2018, the school recognized the importance of technology, a framework, and an environment. The map suggests that science and education were developed simultaneously to create an effective approach to teaching electronic and digital concepts by early 2020. However, evaluating the effectiveness of these efforts would require considering additional factors such as specific objectives, strategies, and outcomes.

Figure 3. Growth of keyword co-occurrence.

The software was used to analyze each keyword, which involved computing the links, total link strengths, and co-occurrences of the keyword with other keywords. As per Guo et al. (2019), links refer to how often one item (such as a keyword) is mentioned alongside another, while total link strength measures the overall number of references between one item and the others. Additionally, occurrences indicate how many times the keyword appears in the articles analyzed. Table 2 of the VOSviewer statistical technique shows that “science education” is the most commonly used author keyword in the literature, followed by “students.” However, other keywords such as “knowledge,” “simulations,” “cultural-historical theory,” “education,” and “science” are also associated with “science education,” resulting in a total frequency of 49 occurrences when combined. Therefore, “science education” and “students” can be considered the two most frequently used author keywords in the literature. The mean year of publication indicates the typical time scholars have used these keywords in their works. Collaboration-related papers received more attention in the latter part of 2018, while inquiry-based learning-, technology-, and teacher-related publications were more popular in 2016 and 2018. With the emergence of learning technologies during the pandemic in 2020, it is expected that science education will be replaced by literacy. The links between nodes indicate how many nodes are connected to a particular node, while the total link strength represents the strength of all the linkages connected to that node. The keyword “science education” has the highest total link strength of 33, indicating the strongest interrelatedness with digital learning in science education.

Table 2. Most highly keyword-based network parameters

Keywords clusters	Links	Total Links Strength	Occurrences	Cluster color
Science Education	31	64	33	Purple
Students	45	26	10	Orange
Technology	16	26	8	Blue
Knowledge	15	23	7	Orange
Conceptual Change	13	18	5	Yellow
Inquiry-Based Learning	14	17	4	Red
School	10	11	4	Light Blue
Science	13	16	3	Blue
Achievement	12	15	3	Green
Classroom	10	14	3	Blue
Technology-Enhanced Learning	6	7	3	Yellow
Instruction	13	15	2	Red

Moreover, the study also analyzed the keywords within each cluster to determine the distinctive theme of the cluster based on the specific topic represented by its respective keywords.

Cluster 1 focuses on virtual inquiry-based learning (VIBL) in interdisciplinary environments, as shown in the paper “Enhancing Science Education through Virtual Inquiry-based Learning in Interdisciplinary Environments” (Delgado et al., 2021). VIBL enables students to engage in scientific inquiry through virtual simulations, experiments, and data analysis, and encourages collaboration and communication skills (Al Ghamdi, 2017). VIBL has been successfully used in a variety of science subjects, such as biology, chemistry, physics, and environmental science, and has been shown to enhance scientific instruction and help students acquire essential skills for success in the twenty-first century (Alvarez, 2021; Coleman & Smith, 2019; Costabile, 2020; Delgado et al., 2021).

Cluster 2 investigates the ability of culturally responsive pedagogy (CRP) to promote academic accomplishment and literacy performance, as demonstrated by the publication “Culturally Responsive Pedagogy for Improving Children’s Education Achievement and Literacy Performance.” CRP recognizes and celebrates students’ diverse cultural backgrounds and experiences, and has been shown to promote academic success in literacy education by using culturally appropriate books and texts, fostering inclusive classroom environments, and strengthening students’ sense of identity and pride in their cultural heritage (Bishop & Vass, 2021; Greg & Watson, 2016; Harrison & Skrebneva, 2020; Underwood & Moore Mensah, 2018; Williams et al., 2021). CRP can improve academic attainment and help students realize their best potential by establishing a pleasant and engaging learning environment.

Cluster 3 focuses on culturally informed classroom practices, with Galperin’s Cultural Historical Theory (CHT) as a central theme, as demonstrated in the paper “The Role of Technology and Teacher Commitment in Fostering Culturally-Informed Classroom Practices through Galperin’s Cultural-Historical Theory in Science Education.” CHT highlights the need of culturally aware teaching strategies in engaging students and promoting their learning in scientific education (Engeness & Lund, 2020). Technology, such as digital simulations, online collaboration platforms, and multimedia materials, plays an important part in this process by enabling culturally relevant and meaningful linkages to scientific themes (Grosvenor & Pataki, 2017; Prins et al., 2018). The effective use of technology in building culturally conscious classroom practices, on the other hand, is contingent on teacher dedication and ongoing professional development (Edwards et al., 2019). Through culturally conscious teaching approaches, including CHT and technology has the potential to boost students’ engagement and achievement in science study.

Cluster 4 focuses on technology-enhanced discourse, specifically its function in encouraging conceptual change in scientific education, as demonstrated by the publication “Examining the Impact of Technology-Enhanced Discourse on Conceptual Change in Science Education: The Role of Simulations.” The research emphasizes the efficacy of simulations in generating conceptual transformation and investigates the significance of technology-enhanced discourse around their use. Claire et al. (2017) and Potvin et al. (2020) examine several types of technology-enhanced discourse, such as online chats or collaborative group work, which can help in connecting simulations with scientific ideas. Furthermore, Yen et al. (2018) show how technology-enhanced discourse may help students build metacognitive abilities, critical thinking skills, and argumentation skills, resulting in a stronger knowledge of scientific themes. Future research should focus on the impact of simulations on conceptual change in scientific education, as well as the development of effective methods for encouraging high-quality technology-enhanced classroom dialogue (Claire et al., 2017; Potvin et al., 2020; Wade‐Jaimes et al., 2018; Yen et al., 2018).

Cluster 5 is concerned with e-learning evaluation discourse in scientific education, as evidenced by the publication “Enhancing Evaluation Practices in E-Learning for Science Education through Virtual Reality Simulations.” By building immersive and appealing learning environments, VR simulations can improve e-learning experiences in scientific education. Traditional evaluation methodologies, however, may not capture all of the advantages of these simulations, emphasizing the need for mixed-methods approaches that integrate both qualitative and quantitative data collection techniques (Faruk et al., 2019; Mystakidis et al., 2021). Encouragement of self-reflection and metacognition is also necessary, as is consideration of the setting in which VR simulations are used when evaluating their usefulness in fostering learning outcomes (Sood & Singh, 2018). Improving evaluation approaches can assist us in better understanding the benefits of VR simulations and guiding their effective implementation in scientific education.

Cluster 6 is concerned with digital learning reform discourse in scientific education, as evidenced by the publication “The Potential of Digital Learning in Science Education Reform: The Role of Teachers and School Practices.” Digital learning has the potential to improve scientific education by providing more interesting and individualized learning experiences, but its success is dependent on teacher support and best practices in the classroom. Teachers have an important role in guiding, criticizing, and supporting students’ digital learning experiences (Maria et al., 2021; Starkey, 2020). Good school practices, such as giving access to high-quality digital materials and fast digital assessment methods, are also critical for increasing the effectiveness of digital learning in scientific education. It is critical to provide instructors with professional development and assistance in order to successfully incorporate digital tools and resources into their teaching practices (Instefjord & Munthe, 2016; Skantz-Åberg et al., 2022).

Cluster 7 is concerned with digital scientific education discourse, as illustrated by the publication “Leveraging Learning Technologies to Enhance Student Knowledge in Digital Science Education.” The review investigates the potential benefits of learning tools in digital scientific education, focusing on how these technologies can improve students’ engagement with and understanding of scientific concepts via digital simulations, models, data analysis and visualization tools, and collaborative learning technologies (Sarker et al., 2019; Walanda et al., 2023). Furthermore, personalized learning experiences via customized resources and feedback have been identified as a promising strategy. The review also highlights the crucial role that teachers play in deploying these technologies to improve student-learning experiences, emphasizing the necessity of teacher support and development (Yeung et al., 2021).

3.2. Affiliation

Figure 4 shows the distribution of articles across various affiliations and highlights those that are most pertinent to the subject of the research. The University of Central Florida Orlando has the most publications out of all the affiliations, with four. The study subject was covered by articles from 10 distinct affiliations in total, which represents 58.33% of all publications. There were at least two articles from each of the seven separate affiliations.

Figure 4. Highest quality affiliations.

3.3. Three fields plot

The analysis looked at the most popular research terms across various associations and nations. Four keywords were found to be often utilized for science education, evolution, e-learning and interdisciplinary science education, according to the research. According to the Sankey diagram in Figure 5 four universities—University of Central Florida Orlando, National Taiwan Normal University, Nanjing University, Gazi University, and University of Jan Evangelista—supported four nations—the United States of America, China, Turkey, and Romania (Kumar & Goel, 2022).

Figure 5. Three field plot keywords (left), affiliations (middle), and countries (right).

3.4. Country collaboration map

The study employed a two-phase research process that included bibliometric analysis. The first step comprised utilizing bibliometric methods to assess the performance of the research field on digital learning in scientific education, while the second part concentrated on developing a visual map of the references in this subject. Bibliometric analysis is a valuable approach for mapping and measuring the academic influence of authors, institutions, nations, and journals in a certain topic (Alqudah et al., 2023; Drijvers et al., 2020; Qudah et al., 2023).

A country collaboration map is used to assess a nation’s level of international cooperation. The USA, China, Turkey, Romania, Japan, Spain, and the UK are the countries that have made the most substantial contributions to the discipline. Dark blue in particular is used to symbolize China and the USA. According to Figure 6 the USA published the most papers with three co-authors, followed by China with two co-authors (Alqudah et al., 2023; El Baz & Iddik, 2022; Qudah et al., 2023).

Figure 6. A global collaboration map for literature using keywords.

3.5. Most global cited documents

The information on the citation metrics for 10 distinct works about digital learning in scientific education is shown in Figure 7. Each paper’s total number of citations, average number of citations per year, and normalized citation ratings are supplied. Megan et al. (2013), which has 208 citations overall, is the paper with the most citations. Additionally, this publication has the highest normalized citation score of 3.09 and the greatest average number of citations each year (17.33). Lee (2005), a baseline work with a normalized citation score of 1.00, has the second-highest number of citations overall.

Figure 7. Most global cited documents.

The works Lin et al. (2019) and Clark et al. (2015) with scores of 3.24 and 4.19, respectively, are two more with reasonably high normalized citation values. In contrast, the normalized citation ratings for Bustamante et al. (2018) and Kaptan and Timurlenk (2012) are just 0.73 and 0.25, respectively. Overall, the chart gives a quick overview of the effects of several articles on digital learning in scientific education, highlighting those that have had a big impact over time.

4. Discussion

Several important findings that need further investigation are revealed by the study on the publishing patterns and geographical distribution of digital learning innovation in scientific education journals. Firstly, the study’s identification of North America, Asia, and Europe as the primary research regions, while noting the absence of research from South America and Africa, highlights a notable geographical disparity in the field. This disparity raises important questions about equitable global access to and engagement with digital learning innovations. It suggests that there may be structural or resource-related barriers preventing South American and African regions from participating fully in this area of research. Further investigation into the reasons behind this disparity is crucial to ensuring that digital learning innovations benefit students and educators worldwide. Secondly, the study’s alignment with previous research by Sweileh (2021) and Djeki et al. (2022), which also focused on adoption barriers rather than addressing broader issues within digital learning in science education, suggests a recurring trend in the field. This alignment raises concerns about whether the research community is adequately addressing the holistic challenges of integrating digital learning tools effectively into science education. A balanced approach that considers not only adoption barriers but also the overall effectiveness of digital learning methods may be essential for advancing the field.

The study’s recommendations for more research in underrepresented regions and a more comprehensive examination of the unique challenges faced by these regions are pivotal. They underscore the need for a more inclusive and context-specific approach to digital learning innovation in science education. To bridge the research gap, efforts should be directed towards understanding the distinct difficulties and requirements of these underrepresented areas. Furthermore, the study highlights the utility of bibliometric data analysis for research organisations. This analytical approach can assist institutions in managing their finances, evaluating research outputs, and gaining insights into the impact of their work. Organisations may strategically allocate resources and give higher priority to areas that need greater attention or investment by detecting trends and patterns in research output. In terms of research trends, the analysis of 8760 papers in the Web of Science database reveals a consistent increase in publications related to digital learning in scientific education since 1992, with notable peaks in 2010 and 2021. This growth suggests a growing recognition of the significance of digital learning in contemporary education. However, the dominance of works in education and educational research, with a relatively smaller proportion dedicated to the history and philosophy of science, implies that there may be room for a more multidisciplinary approach to the study of digital learning’s impact on science education.

The study’s identification of key collaborating nations, such as the United States, China, Turkey, Romania, Spain, and the UK, highlights the importance of international cooperation in advancing research in this field. Collaborative efforts among these countries can lead to more diverse and comprehensive insights into digital learning innovations. Lastly, the recognition of influential authors and highly cited publications within the field can guide scholars and institutions in identifying key voices and references. This knowledge can inform research directions, facilitate knowledge dissemination, and contribute to the field’s overall growth and impact. The study’s findings shed light on regional disparities, recurring research trends, and the need for inclusive and comprehensive research efforts in digital learning innovation in scientific education. Additionally, it underscores the benefits of bibliometric data analysis for research organisations and offers insights into growth trends, research focus areas, collaboration patterns, and influential voices in the field. These findings collectively provide valuable direction for future research, policy-making, and collaborative initiatives in digital learning innovation within the realm of scientific education.

The identification of these seven distinct clusters within the analysis of 8,760 articles has significant implications for both future researchers and educators in the field of digital learning in science education. These clusters provide a valuable roadmap for researchers to explore specific scholarly themes and trends, helping them to delve deeper into potential research gaps and opportunities. For educators, these clusters offer practical insights into diverse approaches for integrating digital learning in science education, enabling them to align pedagogical strategies with their teaching goals and student needs. Moreover, these clusters empower educators to adopt evidence-based practices and adapt them to their specific educational contexts, fostering inclusive and effective learning environments. In essence, these clusters serve as a bridge between research and practice, guiding efforts to advance the field of digital learning in science education and enhance the overall quality of science education experiences for students.

4.1. Future research directions

In academic publications, there is a section called “Future Research Directions” that describes possible lines of inquiry that could expand on the findings of the present study. Based on the limits of the present study, information gaps, and new developments in the area, this section offers ideas for future researchers to investigate. It gives a path for future study and a roadmap for academics to follow in order to increase our understanding of digital learning in scientific education.

Future study in Cluster 1 might look at the efficacy of virtual inquiry-based learning (VIBL) in various educational environments and with varied student demographics. This might include creating and testing VIBL activities that encourage critical thinking and deeper learning, as well as investigating techniques for reliably measuring student-learning outcomes in VIBL environments. Furthermore, research could look into the viability of interdisciplinary VIBL approaches in fields other than science, such as the social sciences and humanities. Finally, research may look into approaches to encourage and assist teachers’ use of VIBL in the classroom, as well as potential adoption hurdles. In Cluster 2, further study may investigate the usefulness of various teaching methods and approaches used to adopt culturally responsive pedagogy (CRP) in the classroom, as well as how CRP might be utilized in disciplines other than literacy education. Studies may also look into how CRP affects student outcomes such as academic success, engagement, and sense of identity. Furthermore, research could focus on developing strategies to assist and train teachers in successfully implementing CRP in their classrooms.

Cluster 3 future study might look on the usefulness of technology and instructional techniques in developing culturally aware classroom practices in scientific education. Examining how historical events and cultural practices affects students’ views and involvement with science, as well as how this information might shape teaching approaches, is one example. Furthermore, research may investigate measures to support teachers’ commitment to culturally responsive teaching, such as professional development and training, as well as the influence of culturally relevant scientific education on students’ academic achievement and long-term engagement with science. In Cluster 4, scholars might work to create simulations that aid conceptual transformation in certain scientific domains such as biology or chemistry. Furthermore, research may be conducted to study how various types of technology-enhanced discourse, such as teacher-led lectures or peer feedback, impact conceptual growth in scientific education. It may also be beneficial to investigate how simulations and digitally enhanced discourse might be utilized to facilitate conceptual change in students from various cultural backgrounds and with varying learning demands. Finally, the long-term impact of these methods on students’ scientific thinking and problem-solving abilities may be assessed.

Future research in Cluster 5 might look at the potential of virtual reality (VR) simulations to improve e-learning experiences in scientific education, as well as effective techniques for monitoring their performance. This may include using mixed-methods approaches to collect both qualitative and quantitative data in order to acquire a more thorough knowledge of the learning effects of VR simulations. Furthermore, study might look at how VR simulations foster self-reflection and metacognitive methods in e-learning environments, as well as how successful they are in different educational settings, contexts, and student groups. Future study in Cluster 6 might focus on the influence of digital learning on different student groups, such as those with special learning needs or from different socioeconomic backgrounds. This might involve looking at successful methods for assisting instructors in implementing digital learning techniques, such as coaching, mentorship, or online resources. Research may also focus on developing and implementing effective digital assessment methods that align with digital learning practices, as well as investigating the long-term consequences of digital learning on students’ academic attainment and learning outcomes outside of the classroom. Finally, future Cluster 7 research could look into the effectiveness of various learning technologies in increasing student engagement and knowledge of scientific topics. This might include creating and executing personalized learning experiences using digital resources and feedback, as well as discovering successful teaching strategies and assisting instructors in utilizing learning technology to improve student-learning results. Furthermore, research could address potential barriers to learning technology adoption in scientific education and propose solutions to overcome them.

The seven groups of scientific education are interconnected and mutually dependent. Clusters 1 and 4 are concerned with simulations in scientific education, whereas Clusters 2 and 3 stress the significance of culturally sensitive teaching. Clusters 5 and 7 look into the possibility of virtual reality simulations in scientific education, while Cluster 6 looks more broadly at digital learning. These linkages highlight the intricacies of scientific education and underscore the importance of taking into account numerous elements when designing effective learning experiences for students.

5. Practical implications, limitations recommendations, and conclusions

The practical implications for scientific education are numerous for each of the seven groupings. Teachers may encourage their students to think critically and learn more deeply by using virtual inquiry-based learning (VIBL) activities. They can also incorporate culturally responsive pedagogy (CRP) into their lessons to make sure that all students, regardless of their cultural background, feel respected and motivated to learn science. Teachers can also make use of technology to improve student engagement and comprehension of scientific ideas, such as virtual reality simulations and online learning materials. Teachers could need professional development programs and training to help them apply these tactics in an efficient manner. Finally, it is important to create and execute assessment systems that take into account digital learning activities and monitor long-term learning results. Overall, these useful ramifications can promote student-learning achievement in science and serve to improve science teaching.

This study’s bibliometric analysis is restricted to the Web of Science database. The results offer information on the current level of digital learning in scientific education, but a subsequent research should think about broadening the search to incorporate other reliable databases like Scopus. This will provide a more thorough comprehension of the study environment. However, by emphasizing the significance of social capital, technology, and leadership in allowing the effective implementation and acceptance of digital learning, this study adds to the body of knowledge on digital learning in scientific education.

This study has contributed to the field of digital learning in scientific education by highlighting important research areas and proposing fresh areas of study. The study contributes significant knowledge for future scholars to analyze the topic’s evolution by topic, context, and measurement by examining articles and journals in the WoS core collection. The results show that the use of qualitative research techniques is still in its infancy in the field of digital learning in scientific education. However, the report notes that its importance has expanded greatly in commerce and information systems library science, whereas it has only marginally increased in development studies and educational administration. Furthermore, the study emphasizes the need of taking into account the cultural element of education in digital learning in science education in order to build interpersonal ties.

Based on the study’s limitations, future research might go beyond the Web of Science database and incorporate additional trustworthy sources such as Scopus and Google Scholar. Furthermore, while the study concentrated on articles and journals from the WoS core collection, future research might expand the scope to include conference proceedings, books, and book chapters. Another idea for future study is to look at the efficacy of different digital learning tools and tactics in scientific teaching. Analyzing the influence of virtual labs, simulations, and online discussion forums on student learning outcomes should be included. Furthermore, study might look at how to successfully use technology into scientific curriculum design and pedagogy.

Furthermore, more qualitative research in the field of digital learning in scientific education is required. Future research might include qualitative methodologies such as case studies, interviews, and focus groups to acquire a better understanding of students’ and instructors’ experiences and opinions.

To effectively incorporate digital learning into science education and provide concrete recommendations for future researchers or educators, it is imperative to emphasise the strategic selection and seamless integration of digital learning tools and platforms, illustrating their practical applications across various science disciplines, including virtual labs, interactive simulations, data analysis software, and educational games. Furthermore, highlighting pedagogical strategies aligned with digital learning, such as blended learning and flipped classrooms, is essential, while concurrently emphasising the need for robust teacher training and ongoing professional development to equip educators with the requisite skills and confidence. Additionally, advocating for adaptive and personalised learning approaches to cater to diverse student needs, underlining innovative assessment methods, promoting inclusivity and accessibility, referencing research-based best practices, encouraging interdisciplinary collaboration, emphasising continuous evaluation and improvement, and addressing ethical considerations such as data privacy and responsible technology use collectively form a comprehensive guide that empowers stakeholders in science education to embrace digital learning effectively, fostering enhanced engagement and learning outcomes in the digital age.

Finally, because the study emphasizes the relevance of cultural concerns in digital learning, future research might look at how cultural context affects digital learning in science education. This might include investigating how cultural characteristics influences student engagement and success in digital learning settings, as well as how to develop and execute culturally responsive digital learning experiences efficiently. Due to limited financial resources, the study has certain limitations, including the sole use of the Web of Science database for bibliometric analysis. A future study should look into the literature on change management, utilizing all credible databases such as WoS and Scopus. Consequently, this study broadens exposure to change management research and deepens awareness of interconnected relationships and their effects on social capital, technology, and leadership.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Manal Abdul Karim Al Momani

Manal Abdul Karim Al Momani is a member of the Department of Educational Sciences at Al-Balqa Applied University, specifically affiliated with Ajloun University College in Jordan. For further information or contact, please reach out via email to [email protected].

Kawther Aboud Alharahasheh

Kawther Aboud Alharahasheh is affiliated with the Department of Curriculum and Teaching at the Faculty of Educational Sciences, Al al-Bayt University in Jordan. Her research and expertise lie in the field of education, specifically curriculum development and teaching methodologies. Unfortunately, no further information is available regarding her qualifications, research interests, or publications. For more detailed and up-to-date information about her work, it is recommended to reach out to her directly via email at [email protected].

Mohammad Alqudah

Mohammad AlQudah is a Ph.D. student in the Accounting and Finance Department at the Faculty of Economics and Business, Universitat Rovira i Virgili in Spain. To contact him, please use the email address [email protected].