Editorial: Enhancing Student Engagement Through Artificial Intelligence (AI): Understanding the Basics, Opportunities, and Challenges

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The integration of digital technology into higher education has been met with both enthusiasm and skepticism, characterised by challenges such as user resistance, lack of necessary skills, policy complications, and ethical and privacy concerns.

“The invasion of digital technology into higher education, spanning several decades, has been met with both enthusiasm and skepticism, characterised by challenges such as user resistance, lack of necessary skills, policy complications, and ethical and privacy concerns (Essien et al., 2024;Nguyen, Gardner, et al., 2020).”

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Strategies that bridge skill gaps, consider ethical implications, and ensure alignment with existing policies are required for AI integration in higher education.

“This requires strategies that bridge skill gaps, carefully consider ethical implications, and ensure alignment with existing policies (Nguyen et al., 2023).”

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AI systems such as intelligent tutoring systems, adaptive learning systems, or personalised learning platforms can customize instruction, provide timely feedback, and aid in developing adaptive learning resources tailored to individual student needs.

“They might include intelligent tutoring systems (ITS), adaptive learning systems, or personalised learning platforms, which can customize instruction, provide timely feedback to learners, and aid in developing adaptive learning resources tailored to individual student needs.”

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Generative AI can be used to create personalised learning resources, model real-life situations for hands-on learning, and develop detailed simulations or models for scientific investigation.

“In educational environments, this type of AI can be used to create personalised learning resources, model real-life situations for hands-on learning, and develop detailed simulations or models for scientific investigation.”

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Generative AI can formulate mathematical or physics practice questions, construct historical recreations, or develop language exercises that adjust to a student's level of proficiency.

“For instance, generative AI can formulate mathematical or physics practice questions, construct historical recreations, or develop language exercises that adjust to a student's level of proficiency.”

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Multimodal deep learning approaches have been explored for predicting intricate learning activities, such as shared regulation during collaborative learning.

“For example, multimodal deep learning approaches have been explored for predicting intricate learning activities, such as those involved in shared regulation during collaborative learning scenarios.”

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AI, machine learning, and deep learning advancements offer potential to deeply understand and enhance the learning process based on individual learner data and interactions.

“These technological advancements in AI, machine learning, and deep learning open new horizons for personalised and adaptive learning experiences in education, offering the potential to deeply understand and enhance the learning process based on individual learner data and interactions.”

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Generative AI and M-LLMs have profound implications for learning and teaching.

“Generative AI (GenAI) and (Multimodal-)Large Language Models (M-LLMs) represent significant advancements in the field of artificial intelligence, offering profound implications for learning and teaching.”

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Recent advancements in AI, particularly generative AI, have a transformative impact on higher education.

“The recent advancements in AI, particularly with generative AI, emphasise the transformative impact on higher education, raising critical questions about the future of learning and teaching with AI technologies.”

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Generative AI and M-LLMs have the potential to revolutionise educational practices by providing innovative tools for content creation, personalised learning, and interactive engagement.

“These technologies have the potential to revolutionise educational practices by providing innovative tools for content creation, personalised learning, and interactive engagement.”

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AI has potential in facilitating adaptive learning systems, personalisation, and intelligent tutoring systems, catering to diverse learning needs and styles.

“Furthermore, the comprehensive review by Zawacki-Richter et al. (2019) emphasised AI's potential in facilitating adaptive learning systems, personalisation, and intelligent tutoring systems, underscoring the technology's capability to cater to diverse learning needs and styles.”

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LLMs can comprehend and produce text in ways that are contextually relevant and syntactically coherent, making them particularly useful for a variety of educational applications.

“These models can comprehend and produce text in ways that are contextually relevant and syntactically coherent, making them particularly useful for a variety of educational applications.”

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Deployment of AI in educational contexts introduces ethical concerns, including data privacy, bias in AI algorithms, and implications of AI-mediated interactions on student learning experience.

“However, the deployment of AI in educational contexts also introduces ethical concerns, including data privacy, bias in AI algorithms, and the implications of AI-mediated interactions on the student learning experience (Essien et al., 2024).”

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AI has the capacity to unveil critical indicators previously overlooked by stakeholders at various levels of the educational hierarchy, suggesting a transformative role in shaping strategic decisions and educational outcomes.

“Nguyen et al. (2020) highlighted the capacity of AI to unveil critical indicators previously overlooked by stakeholders at various levels of the educational hierarchy, suggesting a transformative role for AI in shaping strategic decisions and educational outcomes.”

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AI advancements demonstrate potential for revolutionary change in education, creating learner-centred environments that could significantly boost student engagement.

“These advancements demonstrate the potential for a revolutionary change in education, creating learner-centred environments that could significantly boost student engagement.”

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LLMs can support personalised learning by offering tutoring or feedback on written assignments, generating practice essay prompts, and facilitating language learning through conversation simulations.

“LLMs can support personalised learning by offering tutoring or feedback on written assignments, generating practice essay prompts, and facilitating language learning through conversation simulations.”

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Machine learning can be harnessed for learning analytics to analyse student data, offering personalised instruction recommendations, identifying trends in student behaviour, and forecasting academic performance.

“Within the context of education, machine learning can be harnessed for learning analytics to analyse vast amounts of student data, offering personalised instruction recommendations, identifying trends in student behaviour, and forecasting academic performance.”

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Generative AI allows educators to offer varied, engaging, and customised learning experiences.

“This technology allows educators to offer varied, engaging, and customised learning experiences.”

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Incorporation of AI technology in higher education to enhance student engagement offers immersive opportunities but also presents several challenges that need to be addressed.

“The incorporation of AI technology in higher education to enhance student engagement offers immersive opportunities but also presents several challenges that need to be addressed.”

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MLLMs have the potential to transform educational content delivery by making it more interactive and engaging.

“MLLMs have the potential to transform educational content delivery by making it more interactive and engaging.”

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An MLLM can analyse a scientific text and generate corresponding visual aids, such as diagrams or animations, to help students better understand complex concepts.

“For example, an MLLM can analyse a scientific text and generate corresponding visual aids, such as diagrams or animations, to help students better understand complex concepts.”

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MLLMs increase the accuracy of educational research and enhance the quality of the learning experiences provided.

“This method not only increases the accuracy of educational research but also enhances the quality of the learning experiences provided.”

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LLMs can assist in the creation of instructional content, summarise academic texts, and help in drafting research papers or educational resources, thereby reducing the workload on educators and enabling more focused and effective teaching strategies.

“Additionally, LLMs can assist in the creation of instructional content, summarise academic texts, and even help in drafting research papers or educational resources, thereby reducing the workload on educators and enabling more focused and effective teaching strategies (Dwivedi et al., 2023;Nguyen et al., 2024).”

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ITS can assess student submissions, identify errors, and provide targeted feedback to help students improve.

“These systems can assess student submissions, identify errors, and provide targeted feedback to help students improve (Mousavinasab et al., 2021;Tchounikine et al., 2010).”

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Multimodal approach caters to visual learners and can aid in the retention of information by providing multiple reference points for understanding material.

“This multimodal approach caters to visual learners and can aid in the retention of information by providing multiple reference points for understanding material.”

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ITS can enhance student engagement and lead to learning outcomes by offering support tailored to the student's current level of understanding.

“By offering support that is tailored to the student's current level of understanding, ITS can enhance student engagement and lead to learning outcomes (VanLehn, 2011).”

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A recent study by Nguyen et al. (2024) demonstrated patterns of collaboration between humans and AI in AI-assisted academic writing.

“A recent study by Nguyen et al. (2024) has demonstrated the patterns of collaboration between humans and AI in AI-assisted academic writing.”

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By generating personalised content, assessments, and feedback dynamically, GenAI supports a variety of learning styles and schedules, thereby increasing engagement and making education more responsive to the diverse needs and lifestyles of students.

“By generating personalised content, assessments, and feedback dynamically, GenAI supports a variety of learning styles and schedules, thereby increasing engagement and making education more responsive to the diverse needs and lifestyles of students.”

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Integration of AI, particularly Generative AI, into education brings substantial benefits but also raises significant ethical issues and challenges to academic integrity.

“The integration of AI, particularly Generative AI, into education brings substantial benefits but also raises significant ethical issues and challenges to academic integrity that need to be thoughtfully examined and managed (Crawford, Cowling, & Allen, 2023;Holmes et al., 2021;Nguyen et al., 2023).”

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Recent availability of GenAI technologies has further propelled the personalised learning experience by facilitating real-time interactions with each learner.

“The recent availability of GenAI technologies has further propelled the personalised learning experience by facilitating real-time interactions with each learner.”

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MOOC resources are often static and do not truly cater to the unique needs of each learner.

“However, these resources are often static and do not truly cater to the unique needs of each learner.”

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Personalised learning is an effective method that customises educational experiences to meet the specific needs of individual learners.

“While personalised learning has been acknowledged as an effective method that customises educational experiences to meet the specific needs of individual learners (Xie et al., 2019;Zheng et al., 2021), the significant resources needed to put this model into practice make it challenging to adopt on a large scale (Nguyen, Gardner, et al., 2020).”

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Numerous studies have explored the development of personalised learning, resulting in various prototypes that aim to enhance its feasibility and effectiveness.

“Numerous studies have explored the development of personalised learning, resulting in various prototypes that aim to enhance its feasibility and effectiveness (Denny et al., 2015;Hsieh et al., 2012).”

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GenAI can assist in evaluating students' work by examining written assignments, presentations, and spoken responses, providing comprehensive feedback that covers both textual and auditory elements.

“Moreover, GenAI can assist in evaluating students' work by examining written assignments, presentations, and spoken responses, providing comprehensive feedback that covers both the textual and auditory elements of the content.”

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GenAI accessibility allows for broader integration into various educational settings, supporting a more dynamic and responsive learning environment.

“This accessibility allows for broader integration into various educational settings, supporting a more dynamic and responsive learning environment.”

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AI-powered tools can automatically generate captions for lecture videos or provide realtime language translation, removing barriers to access and engagement for a broader spectrum of students.

“For instance, AI-powered tools can automatically generate captions for lecture videos or provide realtime language translation, removing barriers to access and engagement for a broader spectrum of students.”

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Generative AI is transforming the educational field, making it more interactive and adaptable to the needs of today's learners.

“Thus, generative AI is transforming the educational field, making it more interactive and adaptable to the needs of today's learners.”

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GenAI can serve as dynamic teaching assistants, offering educators a range of tools to enhance their teaching methods.

“GenAI can serve as dynamic teaching assistants, offering educators a range of tools to enhance their teaching methods.”

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GenAI capability to provide instantaneous feedback and tailor learning materials according to individual student needs represents a transformative step towards true personalised learning.

“This capability of GenAI to provide instantaneous feedback and tailor learning materials according to individual student needs represents a transformative step towards true personalised learning.”

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GenAI enhances educational accessibility and convenience, allowing students to interact with learning materials anytime and anywhere.

“Moreover, GenAI enhances educational accessibility and convenience, allowing students to interact with learning materials anytime and anywhere.”

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Round-the-clock availability of tailored educational resources through GenAI makes learning more accessible and substantially enriches the overall learning experience.

“This round-the-clock availability of tailored educational resources through GenAI not only makes learning more accessible but also substantially enriches the overall learning experience.”

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Teachers can use GenAI to create diverse educational materials that incorporate text, visuals, and audio, making lessons more dynamic and engaging.

“Teachers can use GenAI to create diverse educational materials that incorporate text, visuals, and audio, making lessons more dynamic and engaging.”

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This flexibility is particularly beneficial for learners who need to balance educational pursuits with other commitments or those who prefer studying outside conventional classroom settings.

“This flexibility is particularly beneficial for learners who need to balance educational pursuits with other commitments or those who prefer studying outside conventional classroom settings.”

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Institutional leadership plays a crucial role in ensuring the ethical deployment and management of ChatGPT by establishing standards and practices that prioritize transparency, accountability, and the protection of user data.

“Institutional leadership plays a crucial role in ensuring the ethical deployment and management of ChatGPT by establishing standards and practices that prioritize transparency, accountability, and the protection of user data (Crawford, Cowling, & Allen, 2023).”

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Reliance on AI tools raises concerns about students' development of critical thinking and problem-solving skills, as the ease of access to information might deter deeper engagement with learning materials.

“This reliance on AI tools also raises concerns about students' development of critical thinking and problem-solving skills, as the ease of access to information might deter deeper engagement with learning materials.”

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One of the foremost ethical concerns involves data privacy.

“One of the foremost ethical concerns involves data privacy.”

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As students increasingly rely on AI-generated content, there is a risk that it could facilitate academic dishonesty, making it difficult to ascertain whether work submitted is truly indicative of a student's own understanding and effort.

“As students increasingly rely on AI-generated content, there is a risk that it could facilitate academic dishonesty, making it difficult to ascertain whether work submitted is truly indicative of a student's own understanding and effort.”