Trend and Issues in Educational Video Research: A Bibliometric Mapping Analysis

Influential Sources

Table 2 presents the top ten journals based on the number of educational video-use articles in the current study. Computers & Education had the highest number of such articles, followed by the British Journal of Educational Technology, Education and Information Technologies, Educational Technology Research and Development, and the International Review of Research in Open and Distributed Learning. These journals published a considerable number of articles on educational video use.

Table 3 summarizes the most cited sources from reference lists of educational video use articles in the document set. A cited source refers to a journal cited by one or more research papers in the document set (Aria & Cuccurullo, 2017). The journal Computers & Education remains the primary source cited by educational video-use articles. Additionally, certain journals that did not appear in the top ten list based on the number of articles on educational video use are found among the most cited sources, including Cambridge University Press, Applied Cognitive Psychology, and Learning and Instruction. This suggests a foundation of educational video use rooted in educational psychology.

Researchers used source impact measures to identify core journals in the field of educational video use. Table 4 ranks journals based on their h-index and total citations from the document set. The h-index indicates the number of a journal’s published papers cited at least h times in other papers (Aria & Cuccurullo, 2017). Computers & Education journal emerges as the most influential source for publishing articles on educational video use. Consequently, the findings indicate that instructional videos are extensively covered in educational technology journals, highlighting their significant role in advancing the field (Hjorth, 2023). This finding is aligned with the previous review studies investigating technology use in education such as Durak et al., (2024) and Talan (2021) since these journals included educational technology-related publications and they are leading journals focused on technology in education (Arici et al., 2019). Researchers conducting educational video studies should note the influential journals identified in this study.

Influential Articles

Using the bibliometrix package, the researchers identified the primary articles in instructional video use based on local citations. Table 5 presents information about the top articles, considering local and global citations. Local citations count how many documents within the analyzed collection have cited a specific article, while global citations count how many documents in the entire database (e.g., Web of Science) have cited it (Aria & Cuccurullo, 2017). The table reveals that the top articles primarily explore the effects of educational videos on various dependent variables, such as attention, cognitive load, and performance. These findings suggest that research in the field focuses on manipulating specific video-related features or pedagogical elements within instructional videos to observe their impact on cognitive learning outcomes.

Core terms

The researchers conducted data cleaning to identify the most frequently used words. They examined keywords from keyword plus, author’s keywords, titles, and abstracts, combining synonymous words into single terms. The keyword “educational videos” and its synonyms were excluded from the analysis since they were the main focus and dominated the lists. Additionally, generic or meaningless words were removed (e.g., found, control). Appendix 1 lists the synonyms and words removed from keyword plus and author’s keywords.

Table 6 presents the top ten most frequently used words in the field of keyword plus and authors’ keywords. In keyword plus, the most recurring words are performance, cognitive load, impact, attention, and multimedia. The most common words in the authors’ keywords are online learning, learning performance, cognitive load, lectures, and attention. Notably, performance, cognitive load, and attention are common keywords in both lists. The most used keywords found in the current study are similar to the systematic review of Soydan-Oktay and Güler (2024). From the analysis of the most used keywords based on authors’ keywords, it is possible to argue that the use of videos for educational purposes was investigated in online learning environments. This could be attributed to the fact that instructional videos were the primary materials in online courses (Harrison, 2020; Mayer, 2021).

Figure 4 illustrates the word growth of the keyword plus field over time, providing insights into the accumulation of words. Keyword plus was chosen for the figure due to its greater depth and diversity than the authors’ keywords (Zhang et al., 2016). The figure reveals that educational video-use studies primarily focused on performance since 2013, reaching their highest point among other keywords in 2022. The most studied words in educational video-use research papers are student, cognitive load, impact, attention, design, multimedia, technology, education, and lecture.

Figure 4

The literature indicates that researchers have predominantly focused on the cognitive aspect of learning, as evidenced by their examination of “keyword-plus” and “author’s keywords.” Within this context, variables such as learning performance, cognitive load, and attention have received significant attention. However, to comprehensively explore learning, it is necessary to conduct video-oriented studies considering the social and affective aspects of learning.

Additionally, the findings highlight the prevalent use of learning environments and the frequently targeted learner groups for video usage. Notably, online learning environments and university students have emerged as prominent areas of focus. The prevalence of online learning opportunities and the effectiveness of videos in such environments (Fyfield et al., 2022) may explain this trend. Furthermore, it can be inferred that universities worldwide are increasingly integrating online learning methodologies, relying notably on videos (Noetel et al., 2021), which has led to increased participation of university students in studies. However, this trend also underscores the relatively little emphasis placed on other learner groups, such as K-12 students, within the context of online learning and video-based educational approaches. This argument was supported by the bibliometric review conducted by Balıkçı (2020), which focused on the use of videos in K-12 education and found a small number of publications compared to the current study. Therefore, future research should broaden our understanding of the topic by focusing on diverse learner groups.

The Co-occurrence Network of Educational Video Use Articles

Figure 5 displays the co-occurrence network of keyword plus, indicating the main nodes and their connections. Node size represents the frequency of appearance in the dataset, with larger nodes appearing more frequently. To ensure clarity in the analysis, the researchers limited the number of nodes to 50 and set the minimum number of connections between nodes to three. Isolated nodes were removed from the network, and the “walktrap clustering algorithm” proposed by Lancichinetti and Fortunato (2009) was employed. The figure reveals three distinct clusters denoted by the colors red, green, and blue, with the red cluster exhibiting a higher level of centrality.

Figure 5

The red cluster centers on learning performance, the green cluster on cognitive load, and the blue cluster on attention. The red cluster reflects the focus of educational video-use studies on student performance, with numerous connections among its nodes. The green cluster explores design elements and evaluates videos as multimedia materials concerning cognitive load. The blue cluster examines the attention variable in educational videos associated with recall and cognitive learning outcomes. Studies in this cluster evaluate video modeling examples in terms of attention. The structure of the blue and red clusters is aligned with the structure of Balıkçı’s (2020) bibliometric study except for the green cluster. Moreover, the blue and green clusters are interconnected through the link between cognitive load and attention nodes.

The co-occurrence network reveals the close alignment between prominent nodes and core terms in the educational video literature. The relationships between these terms can be interpreted in various ways. However, examining the interconnection of primary nodes within each cluster highlights the association between learning performance, cognitive load, and attention. This finding is consistent with theoretical assumptions and empirical evidence from previous studies.

Theoretically, the cognitive theory of multimedia learning (CTML) emphasizes the goal of understanding in multimedia learning environments (Mayer, 2009), which aligns with the focus on learning performance in educational videos. Additionally, managing internal cognitive load, reducing external cognitive load, and increasing germane cognitive load have been recognized as crucial for meaningful learning (Sweller et al., 2019). The close relationship between learning performance and cognitive load is reflected in Figure 5 and is supported by existing literature.

Attention is another variable associated with cognitive load, as it influences the transfer of learning stimuli to short-term memory. In multimedia learning, attention management is vital in preventing the split attention effect, which increases cognitive load and hinders learning performance (Sweller et al., 2019). Therefore, there is a close relationship between learning performance and cognitive load. As seen in Figure 5, this link is also prominently reflected in the literature on educational videos.

In summary, the findings from the co-occurrence network analysis indicate a remarkable emphasis on cognitive variables such as learning performance, cognitive load, and attention in the existing educational video literature. The CTML and Cognitive Load Theory are widely referenced and extensively investigated within these variables. The prevalence of research in this framework suggests a thorough synthesis of the subject matter within the theoretical context. However, when considering learning holistically, it becomes evident that there is a need for new studies focusing on affective and social variables to provide a comprehensive understanding of the topic.

The Thematic Map of Educational Video Use Articles

Researchers selected the keyword plus for analysis to reveal the thematic map of educational video-use articles. Parameters were set to ensure a thorough understanding of educational video utilization: limited to 200 words, minimum cluster frequency of 20, 3 labeled terms per cluster, and the “walktrap clustering algorithm” (Lancichinetti & Fortunato, 2009). Each bubble represents a cluster, with the bubble’s name being the most frequently occurring term. Bubble size corresponds to term occurrences in the cluster.

Figure 6 shows the thematic map based on centrality (x-axis) and density (y-axis). Centrality indicates the importance of a theme, while density reflects its level of development (Cobo et al., 2011). The figure consists of four quadrants. The upper-right quadrant represents motor themes, which are both important and well-developed. The upper-left quadrant contains niche themes, which are well-developed but have marginal importance. The lower-left quadrant includes emerging or declining themes, which are isolated and weakly developed. The lower-right quadrant represents basic themes, which are important but need to be well-developed.

Figure 6

Table 7 corresponds to the clusters depicted in Figure 6. The first cluster revolves around “performance” and encompasses cognitive variables and design-related aspects of videos, including cognitive load, impact, attention, and design. This cluster is found in both basic and motor themes, exhibiting high centrality and medium density on the thematic map. These findings suggest that research on instructional videos predominantly concentrates on their influence on various cognitive learning outcomes. The position of the cluster in the map implies that the literature in this area is not yet saturated, indicating the necessity for additional studies.

The second cluster, represented by “education,” primarily belongs to the basic themes, while a smaller fraction is categorized as motor themes. The research topics within this theme pertain to learning environments such as technology, podcasts, higher education, and online, and certain affective learning outputs like motivation and engagement. This result indicates the relevance of literature focusing on affective variables in higher education, particularly technology-driven learning environments. However, the development degree of this cluster is not high, suggesting that further study with more focus on the affective aspect of learning in different learning environments. In recent years, this situation has drawn the attention of researchers in the field (e.g., Köster, 2018), highlighting the need to examine the issue, particularly from its affective dimension.

The theoretical aspect of instructional video literature, found within the basic themes, is covered by the “multimedia” representation. It includes various research topics such as cognitive load theory, text, and working memory. This result shows that the topic is closely related to the multimedia and cognitive load theory literature. This phenomenon was similarly highlighted in the bibliometric study conducted by Li et al. (2019), where “cognitive load” was identified as the most frequently co-occurring keyword in multimedia learning research. Accordingly, the findings of this study align with previous research within the established theoretical framework. Moreover, cognitive load remains a critical factor in the design of multimedia instruction, with numerous strategies suggested to mitigate it across diverse overload scenarios (Mayer & Moreno, 2003). This emphasis on managing cognitive load likely played a significant role in shaping the theoretical foundation of the instructional videos. However, the density of the topic is lower in the thematic map, indicating that there are still many unanswered questions in the instructional video literature in line with the relevant theoretical orientations.

The “student” appears in the motor theme in the instructional video literature, closely intertwined with the topics of classroom and support. This result suggests that instructional videos have found widespread utilization as a supportive tool within classroom settings. The literature documents successful applications of videos in classroom settings, where videos can supplement lectures, enhance initial learning, lower dropout rates, and offer tutorial support (Brecht, 2012). For optimal integration of videos to support student learning, however, it is essential to adhere to principles such as multimedia, coherence, signaling, redundancy, spatial and temporal contiguity, segmenting, pre-training, modality, personalization, voice, image, embodiment, and generative activity (Mayer, 2021).

The “modeling examples” are considered a highly developed but isolated representation. It is associated with topics related to emotion and face. The thematic map implies abundant room for further progress in determining the role of video modeling examples and the instructor’s face in video lectures. In this regard, research has highlighted that the instructor’s face is a key element in capturing students’ attention, particularly in video lessons that utilize video modeling examples (van Wermeskerken, Grimmius, et al., 2018; van Wermeskerken, Ravensbergen, et al., 2018). However, further studies are needed to understand how the combination of video modeling behaviors and the instructor’s presence impacts learning processes. This need has emerged as a guiding factor for future research in the present study. It also shows that there has been substantial growth in the number of studies addressing the emotional aspect of instructional videos.

The cluster represented by “attitudes” has a high density and medium centrality level. The main dimensions of this theme are the topics of conceptual change and knowledge. This result indicates that a substantial body of research exists in the literature regarding these topics, but they are moderately important in the field. For instance, the knowledge domain may play an important role in determining the effectiveness of videos as multimedia learning tools (Hong et al., 2018). Research indicates that the type of knowledge conveyed in a video can impact learning outcomes differently across cognitive, sensory, and social contexts (Polat et al., 2024). This study highlights that while extensive research exists on moderating factors like knowledge type, there remains a need to more closely connect such moderators to foundational sources within the field. Therefore, future studies should establish connections between these topics and the subjects covered in the basic and motor themes.

Two emerging themes, namely “instruction” and “comprehension,” are present in the thematic map. However, both themes lack substantial interconnections as no adequate clusters link them. Furthermore, these themes exhibit low development and centrality within the field. This result is, in fact, closely aligned with the goals of multimedia learning. One of the primary objectives in multimedia learning is to observe changes in cognitive processes, such as “recall” and “transfer” (Mayer, 2009). Mayer (2009) suggested that transfer may play a particularly critical role, especially in applying learning to new contexts. In this regard, the prominence or decline of the comprehension theme in the current study could be interpreted in two ways. First, researchers may have recently begun to place as much emphasis on comprehension as on transfer. This result may suggest that the instructional aspect of videos should be further explored with more emphasis on the dimension of “comprehension.” Alternatively, comprehension might be less widely accepted as a core learning goal compared to others.

A highly developed but isolated theme is “emotional design.” This result indicates several studies have been conducted on “emotional design” in instructional videos. However, these studies are not commonly linked to the topics specified in the basic themes. Emotional design in multimedia learning contributes to improved outcomes like retention, transfer, comprehension, and motivation, while also decreasing perceived difficulty (Wong & Adesope, 2021). Integrating emotional design principles into learning materials can evoke positive emotions, which aid cognitive processing and enhance learning (Um et al., 2012). Although emotional design is recognized for its positive impact on learning results, there is still a limited amount of theoretical analysis regarding its role in the learning process, especially within the context of educational videos. Thus, examining educational videos from a theoretical perspective focused on emotional design is needed.

The Thematic Evaluation of Educational Video Use Articles

A “Thematic Evaluation” analysis was conducted to observe the thematic evolution of studies using Keyword Plus. Prior to the analysis, essential deletions were made from the word list provided in Appendix 1, and synonymous terms were consolidated. The analysis employed default parameters for thematic evaluation, utilizing the Walktrap clustering algorithm. Additionally, four cutting points were selected within the biblioshiny interface, specifically for the years 2014, 2017, 2019, and 2021. These years were algorithmically determined by biblioshiny without any manual adjustments. The thematic evolution graph based on these selected years is presented in Figure 7.

Figure 7

The Figure 7 shows how study themes in student performance, cognitive elements, and educational procedures evolved between 1988 and 2022. Between 1988 and 2014, research first concentrated mostly on fundamental subjects like “instruction” and “cognitive load,” with a little amount of attention paid to “attendance,” reflecting attempts to comprehend efficient teaching strategies and cognitive limitations in learning. The topics changed by 2015–2017 to include “multimedia,” “performance,” and “education,” indicating a move toward using digital resources and assessing student progress. While “performance” and “comprehension” remained important, the emphasis shifted from 2018 to 2019 to “engagement” and “achievement,” indicating an interest in how students connect with educational content and the outcomes of those interactions. The research environment grew increasingly sophisticated between 2020 and 2021, with concepts like “perceptions,” “attention,” “desynchronization,” and “education” gaining. The shift toward online learning and the growing need to address student experiences and attentional challenges, particularly in asynchronous learning environments, may have contributed to the complexity of the research landscape during 2020–2021, with themes like “perceptions,” “attention,” “desynchronization,” and “education” gaining prominence. Consistent with the findings of this study, Soydan-Oktay and Güler (2024) observed an increasing trend in the utilization of videos within online learning environments. Recent topics such as “multimedia perceptions,” “impact,” “learner control,” and “education” in 2022 demonstrate an emphasis on analyzing the impact of multimedia and customizing learning experiences. A growing interest in student agency and self-regulated learning in contemporary, digital educational contexts is highlighted by the recent emphasis on learner control and multimodal perspectives. Overall, the theme evolution demonstrates how, in response to evolving educational dynamics and technology advancements, the traditional instructional focus has given way to a complex investigation of engagement, perceptions, multimedia, and personalized learning.