## 5 Discussion
The top-10 keywords with the highest total link strength are presented in Table 14. Of the keywords used, \"learning analytics\" (155), \"virtual reality\" (144), \"e-learning\" (139), \"students\" (112), and \"augmented reality\" (91) had the highest total link strength. These outcomes showcase, once again, the close relationship of learning analytics with virtual reality and augmented reality technologies. The outcomes of these networks highlight the versatile nature and wide applicability of both augmented reality and virtual reality, as well as of learning analytics and educational data mining. Additionally, they depict their ability to support both students and teachers and be integrated in various subjects and education levels. Their close relationship with machine learning and artificial intelligence is also evident. Their ability to promote technology-enhanced learning, to provide personalized and adaptive computer-aided instructions and feedback, to be used together with other educational and pedagogical approaches as well as to capitalize on the real-time identification and processing of multi-modal data is displayed. These outcomes are further validated and expanded through the topic modeling analysis. Specifically, LDA was used and the title and abstract of the documents were examined. In total, five main topics emerged. These topics were related to (1) Interactive and immersive content and activities (e.g., content creation (3.18), maker activities (3.11), learning activities (0.46), immersive technologies (0.44), etc. ); (2) Data collection and processing (e.g., real time (7.52), data collected (3.6), learning process (0.56), learning data (0.16), etc. ); (3) Learning process and outcomes (e.g., learning process (8.06), students' learning (0.17), learning environment (0.17), learning outcomes (0.17), immersive technologies (0.17), etc. ); (4) Immersive learning and immersive learning environments (e.g., learning environments (8.25), immersive technologies (3.70), real world (3.50), students learning (0.17), learning activities (0.17), etc. ); and (5) Game-based learning (e.g., based learning (4.20), learning outcomes (4.13), game based (3.56), students learning (1.50), immersive technologies (0.17), etc.). The outcomes of the topic modeling better highlight the ability of these technologies and methods to provide interactive and immersive content and activities and their ability to identify, collection, and process data in real time. Additionally, they reveal their potential to support and enrich learning processes and learning outcomes through the immersive learning environments that they offer and their ability to support other educational approaches, such as gamification and game-based learning. \begin{table}
\begin{tabular}{l l l l l l} \hline
**Keywords** & **Occurrences** & **Total Link Strength** & **Keywords** & **Occurrences** & **Total Link Strength** \\ \hline learning analytics & 45 & 155 & machine learning & 6 & 27 \\ virtual reality & 41 & 144 & multi-modal learning & 6 & 25 \\ e-learning & 31 & 139 & multimodal learning analytics & 7 & 25 \\ students & 23 & 112 & teaching & 4 & 25 \\ augmented reality & 27 & 91 & eye-tracking & 4 & 23 \\ learning systems & 12 & 62 & artificial intelligence & 4 & 19 \\ computer-aided & 9 & 52 & mobile learning & 4 & 17 \\ instruction & 7 & 48 & stem education & 4 & 16 \\ computing education & 10 & 45 & technology-enhanced learning & 5 & 16 \\ data mining & 5 & 37 & serious games & 5 & 15 \\ teachers & 7 & 36 & content creation & 4 & 13 \\ engineering & 8 & 32 & language learning & 4 & 12 \\ educational data mining & 7 & 30 & evaluation & 4 & 10 \\ \hline \end{tabular}
\end{table} 
Table 14: Co-occurrence analysis—total link strength. Based on the aforementioned, it can be inferred that the combination of learning technologies and educational data mining within augmented reality and virtual reality environments can significantly improve teaching and learning activities and enrich the overall educational process.