Advances in smart and intelligent technologies have been driving a profound transformation in the educational landscape. From artificial intelligence (AI) to immersive technologies such as virtual reality (VR) and augmented reality (AR), these innovations are reshaping teaching and learning as well as institutional decision-making processes. For example, the increasing adoption of AI in education and learning analytics has demonstrated its potential to enhance learner engagement, identify students requiring additional support and provide personalised feedback.
This special issue, titled “Innovating education with smart and intelligent applications,” brings together cutting-edge research that explores the potential of these technologies to foster educational innovation. The seven papers featured in this issue reflect the diversity and depth of applications that smart and intelligent technologies offer to education. They collectively illustrate how these applications can address challenges, create opportunities and redefine traditional paradigms in teaching and learning.
The first paper, “Connecting the dots: The interplay between individual and environmental factors on learning engagement and student performance via goal orientation” by Kwong and Kwok, addresses the complexities of online learning engagement. Grounded in the expectancy-value theory, the study examines how individual factors such as self-efficacy and institutional academic support influence engagement through the mediating role of goal orientation. The findings reveal the indirect impact of online collaborative tools on learning performance, offering insights for navigating the post-pandemic shift to online learning environments.
Immersive technologies have emerged as powerful tools for transforming learning experiences. In their paper, “Virtual reality as a didactic tool for teaching history to early childhood teachers in training,” Merchán et al. demonstrate how VR can bridge theoretical knowledge and experiential learning. By immersing trainee teachers in local cultural heritage sites, the study highlights VR’s potential to enhance historical understanding, emotional engagement, motivation and technical skills.
Similarly, Mohammadpur Rowzekhani et al., in their paper “The effect of immersive technologies in educational methods on the recall and recognition of sixth-grade students,” evaluate the impact of AR on memory retention and recognition. Their findings confirm that AR-based teaching methods significantly improve students’ ability to recall and apply learned information, emphasising the role of immersive technologies in creating engaging and effective learning experiences.
In “Examining the effect of augmented reality attributes on student vocational equity,” Wahyuni et al. explore how AR can promote vocational equity by tailoring learning experiences to individual needs. By integrating theories of mental imagery and cognitive load, the study reveals how AR attributes – such as bespoke personalisation knowledge, ephemeral elevation experiences and transversal skills – mediate the relationship between technology and vocational equity. This research highlights the potential of AR to empower students in vocational education, fostering equity and inclusivity in skill development.
The paper “Determinants of students’ adoption of AI chatbots in higher education” by Rahman et al. investigates the factors influencing students’ acceptance of AI chatbot applications. The study identifies perceived usefulness, subjective norms, tech simplicity and tech literacy as key drivers of chatbot adoption. It also examines the mediating effects of students’ intention to use AI chatbots. The results provide actionable insights for institutions seeking to implement AI-driven student support systems effectively.
In “MOOC-based blended learning: A new paradigm in translation technology education,” Chan introduces a blended learning approach that combines MOOCs with face-to-face workshops, live online seminars and guest lectures. The study demonstrates how this hybrid model effectively addresses the practical and hands-on nature of translation technology education. By assessing student satisfaction across multiple dimensions, the research offers valuable guidance for designing blended learning experiences that balance flexibility, connectivity and instructional quality.
The final paper, “Development of a multi-model analytics system to enhance decision-making in student admission” by Li et al., presents a novel approach to support institutional planning. By integrating multiple predictive models and interactive dashboards, the analytics system provides insights into student admission trends and outcomes. Beyond student recruitment, the system supports strategic planning and resource allocation, showcasing how data-driven approaches can optimise institutional operations.
The contributions to this special issue collectively illustrate the transformative potential of smart and intelligent applications in education. From predictive analytics and AI chatbots to immersive technologies and blended learning models, these innovations serve as catalysts for reimagining education. They empower educators to personalise learning, enhance engagement and foster equity, while enabling institutions to make data-driven decisions and adapt to the evolving needs of learners.
We hope that the insights presented in this special issue inspire educators, researchers and institutions to explore new possibilities and embrace the opportunities offered by smart and intelligent applications. By leveraging these technologies, we can innovate education to better serve learners and prepare them for the complexities of a rapidly changing world.
