Open Category Submission

993 – BUILDING AND EMBEDDING A CUSTOMIZED AI CHATBOT INTO MOODLE TO SUPPORT STUDENTS’ SELF-REGULATED LEARNING

This project introduces customizable AI chatbots tailored to specific courses, ensuring relevant and accurate student support. Unlike general AI chatbots like ChatGPT or Gemini, customized chatbots can integrate seamlessly into learning management systems like Moodle to provide students with on-demand assistance within a familiar environment. The project is built on the use of low-code or no-code chatbot development platforms such as Chatbase, allowing teachers to create customized chatbots without requiring advanced programming skills. These tailored chatbots can generate AI-driven responses based on structured course materials that teachers provide, so it can enhance self-regulated learning while reducing teacher workload. Built using low-code or no-code platforms, they require no advanced technical expertise, so they will be more accessible to teachers and can be implemented in various educational settings.
The potential impact of this project is significant, particularly in promoting self-regulated learning by offering instant, personalized support outside the classroom. Students can access timely guidance, reinforcing their independent study habits and improving academic outcomes. Additionally, the automation of routine inquiries helps reduce teacher workload, allowing them to focus on more complex instructional tasks and student interactions. With its scalability and accessibility, this project can be adapted across various educational institutions, making AI-enhanced learning widely available and ensuring that both students and teachers benefit from more efficient and effective educational support systems.

The increasing reliance on AI in education has demonstrated its potential to enhance learning, yet most AI-powered chatbots, such as ChatGPT or Gemini, are designed for general purposes and lack course-specific customization. This limitation often results in responses that are too broad, irrelevant, or misaligned with students’ learning needs in a specific context. Additionally, teachers often face significant workloads, making it challenging to provide timely support to every student. Recognizing these issues, I was inspired to explore how AI chatbots could be customized to support specific courses and integrate into existing learning management systems (LMS) like Moodle.
The core hypothesis of this project is that custom AI chatbots can enhance self-regulated learning by providing relevant, on-demand support while reducing teacher workload. Unlike general AI models, these chatbots will be tailored to course content and information, making sure that their support will be accurate and aligned with instructional goals. Furthermore, by using low-code or no-code chatbot development platforms, teachers can implement this technology without requiring extensive programming knowledge, making it a feasible and scalable solution. I believe this approach will succeed because it leverages existing AI and LMS technologies in a way that is both practical and directly beneficial to students and teachers. By offering targeted, automated support, the chatbots can empower students to take greater control of their learning while allowing teachers to focus on higher-order instructional tasks.

This project leverages low-code or no-code chatbot development platforms such as Chatbase to enable teachers to create course-specific AI chatbots without requiring advanced programming skills. These chatbots will be integrated into Moodle via APIs or embedded links, ensuring smooth interaction with course materials and student inquiries. To support development, key resources include access to AI chatbot-building platforms, Moodle LMS, course content, and supplementary materials. To validate market demand, I will conduct surveys and interviews with teachers and students to assess their needs and readiness to adopt AI chatbots, alongside a pilot implementation in selected courses to gather real-world feedback.
The core functionalities of the customized AI chatbot include providing course-specific assistance, answering student queries, offering personalized learning recommendations, and tracking student engagement. To ensure a positive user experience, the chatbot will be designed with an intuitive, user-friendly interface, adaptive responses, and continuous improvements based on user feedback. Performance metrics will include student engagement rates, frequency of chatbot interactions, accuracy of responses, reduction in teacher workload (measured by fewer repetitive inquiries), and student satisfaction levels. By continuously refining the chatbot based on usage data and feedback, the project aims to deliver an effective and scalable AI-powered support system for teachers and students in higher education contexts.

NA

This project presents an innovative approach by enabling teachers to custom-build AI chatbots tailored to specific courses, unlike general AI models that lack contextual relevance. By integrating these chatbots into learning management systems (LMS) like Moodle, the project enhances student support in a familiar digital environment, allowing for on-demand, course-specific assistance. The key innovation lies in its teacher-friendly implementation, utilizing low-code or no-code platforms that eliminate technical barriers, making AI chatbot development accessible to teachers without programming expertise. This approach empowers teachers to create AI-driven learning support tools that are directly aligned with their instructional objectives and student needs.
Creativity is embedded in how this solution personalizes AI support for education. Instead of relying on generic AI responses, the chatbots are designed to engage students with structured, course-related content, interactive learning prompts, and adaptive guidance based on student queries. The ability to customize responses, integrate multimedia resources, and track student interactions adds a dynamic layer to learning, fostering greater engagement and self-regulation. Additionally, by automating responses to frequently asked questions, the project creatively reduces teacher workload, freeing up time for more meaningful student interactions. These elements of innovation and creativity not only make the project practical and scalable but also ensure its effectiveness in enhancing both teaching efficiency and student learning outcomes.

To ensure scalability, this project leverages available chatbot development platforms that allow teachers to easily create and modify AI chatbots without advanced technical skills and high costs. By integrating these chatbots into Moodle, the solution can be seamlessly expanded across multiple courses and institutions where Moodle or similar LMSs are in use. Regular feedback loops from students will help teachers refine chatbot functionality, ensuring continuous improvements as adoption grows.
For sustainability, the project prioritizes efficient AI resource management by using lightweight models that minimize computational power and energy consumption. The chatbots will also encourage long-term user engagement by incorporating adaptive learning features, allowing them to evolve based on student interactions and course updates. To maintain relevance, teachers can regularly update chatbot knowledge bases with new content and assessments. By offering open-access training resources, the project fosters teacher autonomy, enabling widespread adoption without heavy ongoing costs. Ultimately, this solution provides a future-proof, adaptable, and cost-effective AI-powered support system, ensuring its continued impact on education as technology and learning needs evolve.

This project hopes to promote equity and inclusion by providing accessible, on-demand AI-driven support for students, regardless of their background or learning pace. Many students, especially those from underprivileged communities, struggle with limited access to personalized academic assistance. By integrating custom AI chatbots into Moodle, the project can ensure that all students—regardless of socioeconomic status, geographic location, or learning ability—receive consistent, course-specific guidance beyond classroom hours. Additionally, by reducing teacher workload, teachers can focus more on supporting students who require extra help, fostering a more inclusive and equitable learning environment.
To measure social impact, key metrics will include student engagement levels, chatbot usage rates, student satisfaction surveys, and improvements in academic performance. Regular teacher and student feedback loops will ensure that the chatbots remain responsive to evolving learning needs. Moreover, the project’s scalable and adaptable design allows institutions to tailor chatbot functionalities for diverse educational settings, including those serving marginalized or special-needs learners. By continuously refining the chatbot’s content and features based on real user experiences, this initiative not only enhances educational accessibility and effectiveness but also aligns with the broader goal of leveraging AI to create a more inclusive and socially responsible learning ecosystem.

Personal Information Collection Statement (PICS):
1. The personal data collected in this form will be used for activity-organizing, record keeping and reporting only. The collected personal data will be purged within 6 years after the event.
2. Please note that it is obligatory to provide the personal data required.
3. Your personal data collected will be kept by the LTTC and will not be transferred to outside parties.
4. You have the right to request access to and correction of information held by us about you. If you wish to access or correct your personal data, please contact our staff at lttc@eduhk.hk.
5. The University’s Privacy Policy Statement can be access at https://www.eduhk.hk/en/privacy-policy.

• I have read and agree to the competition rules and privacy policy.