AI-Powered Education: The Future of Teaching in the Digital Age
By Rashi Bansal, Lecturer in Business, LSST Elephant & Castle
Artificial Intelligence (AI) is revolutionising nearly every aspect of human life, and education is no exception. From personalised learning experiences to automated marking, AI is reshaping the way educators teach, and students learn. In today’s digital era, lecturers must adapt to new AI-driven teaching methodologies to enhance student engagement and optimise educational outcomes (Wikoom, 2022). The relationship marketing model (Larsson & Viitaoja, 2017) and the e-loyalty model (Srinivasan et al., 2002) provide valuable insights into how digital interactivity and customised experiences foster engagement—a principle that can be applied to AI in education.
The Role of Lecturers in Modern Education
The traditional role of lecturers as sole providers of knowledge is shifting. With AI-powered platforms offering instant access to information, lecturers must focus on becoming facilitators rather than simply dispensers of knowledge. AI-based systems can analyse students’ learning behaviours and provide personalised content recommendations, much like how digital platforms tailor user experiences in marketing (Larsson & Viitaoja, 2017).
For example, AI-driven Learning Management Systems (LMS) such as Coursera, Udemy, and EdX use adaptive learning algorithms to customise courses based on students’ performance. Lecturers can utilise these insights to identify struggling students and tailor their teaching approaches accordingly.
Source: Udemy
E-Loyalty and Student Engagement in AI-Based Learning
The e-loyalty model (Srinivasan et al., 2002) identifies key factors that influence user retention on digital platforms, including customisation, contact interactivity, and convenience—elements that are highly relevant in AI-powered education.
Customisation: AI-driven platforms personalise learning experiences by adapting content to individual needs. Just as e-commerce platforms recommend products based on previous purchases, AI-powered education tools suggest study materials tailored to students’ strengths and weaknesses. For example, platforms like Duolingo use machine learning algorithms to assess a learner’s progress and provide customised exercises in language learning. Similarly, platforms such as Squirrel AI in China use adaptive learning systems to adjust difficulty levels and content in real-time based on each student’s performance.
Contact Interactivity: AI chatbots and virtual tutors provide 24/7 academic support, much like digital customer service representatives in online businesses. IBM’s Watson, for instance, has been used to assist students by answering questions and providing explanations in real-time. For example, Georgia State University implemented an AI chatbot named “Pounce” that successfully answered over 200,000 student queries in its first year, helping to reduce summer melt and improve student enrolment outcomes. Similarly, the University of Murcia in Spain employed a virtual assistant to answer FAQs, improving response efficiency and student satisfaction.
Convenience: AI-based platforms enable students to learn at their own pace, anytime and anywhere. This flexibility aligns with the growing preference for digital education over traditional classroom settings. For example, Coursera and EdX offer AI-enhanced learning pathways that allow students to access course materials, video lectures, and quizzes on demand. Khan Academy also provides personalised dashboards where learners can set goals and progress through content at their own convenience.
AI-Powered Assessment and Feedback Mechanisms
Assessment has always been a challenge in education, often limited by time constraints and human bias. AI can revolutionize grading and feedback through automated systems that assess assignments, quizzes, and even essays with greater accuracy.
For example, Turnitin’s AI-powered grading system not only detects plagiarism but also provides writing improvement suggestions. Similarly, platforms like Gradescope use machine learning to analyze student responses and offer instant feedback, enhancing the learning process (Gradescope. 2024).
Challenges and Ethical Considerations
Despite its benefits, AI in education comes with challenges:
Bias in AI Algorithms: AI tools must be carefully designed to prevent biases that may disadvantage certain student groups. For example, research has shown that facial recognition algorithms used in remote proctoring tools like Proctorio or ExamSoft may misidentify or fail to recognise students with darker skin tones or those from non-Western backgrounds, leading to unfair testing experiences.
Loss of Human Connection: While AI enhances efficiency, excessive reliance on automated systems may reduce personal interactions between students and lecturers. For instance, some students using AI-marked assignments on platforms like Gradescope have reported feeling disconnected from instructors, citing a lack of feedback with a “human touch” that helps build academic relationships.
Data Privacy Concerns: AI-driven platforms collect vast amounts of student data, raising concerns about privacy and security. Institutions must implement strict data protection measures. For example, in 2020, Zoom was scrutinised for sharing user data with third parties without sufficient transparency. In educational settings, such incidents raise red flags about how AI platforms manage sensitive student information.
The Future of AI in Education
As AI continues to evolve, its potential in education is limitless. Future advancements may include AI-driven holographic teachers, VR-based immersive learning experiences, and emotional AI that detects students’ moods and adapts lessons accordingly (Wikoom, 2023).
Lecturers who embrace AI and integrate it into their teaching methodologies will not only improve student engagement but also future proof their careers in an increasingly digital world.
AI is not here to replace lecturers—it is here to empower them. By leveraging AI-powered tools, educators can create personalized, interactive, and efficient learning experiences that align with modern digital expectations. Just as relationship marketing and e-loyalty models highlight the importance of engagement in customer retention, AI-based education relies on interactive, customised, and convenient experiences to foster student success.
References
Coursera (2023) Personalized AI-powered learning. Available at: https://www.coursera.org.
Dryden, W. and Ellis, A. (1987) ‘Rational‐emotive therapy and the inner dialogue’, British Journal of Guidance & Counselling, 15(1), pp. 52–63. Available at: https://www.tandfonline.com/doi/abs/10.1080/03069888708253532.
EdX (2023) Adaptive learning algorithms in education. Available at: https://www.edx.org.
Gradescope (2023) AI-driven assessment tools. Available at: https://www.gradescope.com.
Harvard Business Review (2022) The role of AI in modern education. Harvard Business Review. Available at: https://hbr.org.
IBM (2022) How Watson is transforming education. Available at: https://www.ibm.com/education.
Larsson, A. and Viitaoja, Y. (2017) ‘Relationship marketing model: A depiction of interactive marketing via digital platforms’, Journal of Financial Services Marketing, 22(3), pp. 120–135. https://doi.org/10.1057/s41264-017-0024-5
London School of Science and Technology (LSST) (n.d.) Are you teaching or joking? Can we ask the robots to help? Available at: https://www.lsst.ac/blogs/are-you-teaching-or-joking-can-we-ask-the-robots-to-help/.
London School of Science and Technology (LSST) (n.d.) Connecting with ChatGPT as an educator. Available at: https://www.lsst.ac/blogs/connecting-with-chatgpt-as-an-educator/.
Srinivasan, S.S., Anderson, R. and Ponnavolu, K. (2002) ‘Customer loyalty in e-commerce: An exploration of its antecedents and consequences’, Journal of Retailing, 78(1), pp. 41–50. https://doi.org/10.1016/S0022-4359(01)00065-3
Turnitin (2023) AI-assisted grading and feedback. Available at: https://www.turnitin.com.
Udemy (2023) The future of AI in digital education. Available at: https://www.udemy.com.
UNESCO (2023) AI in education: Opportunities and challenges. Available at: https://www.unesco.org.