Section A: Project Information
This proposed project seeks to provide solution on how can enhance students’ engagement by designing online collaborative problem-based learning system through incorporating generative AI supported by community of inquiry and e-moderating model. The e-moderating model with generative AI used to guide the design learning activities during the online collaborative problem-based learning system. The community of inquiry used to guide AI to provide personalized recommendations and to evaluate the quality of students’ contribution.
Generative AI roles:
• AI acts as digital moderator for online interaction.
• Helping students to engage in collaborative problem-solving by providing questions, suggestions and brainstorming.
• Evaluating students’ contribution before submitting and providing suggestions
• Evaluating students’ cognitive, social and behavior engagement through using learning analytics techniques
• Assisting instructors to track and monitor students learning engagement
• Assisting instructors to tailor feedback to students’ work and progress based on the lens of community of inquiry.
The system also has dashboards for instructors and students. The system used learning analytics to present students’ engagement in the dashboard which involves: 1) Content analysis used to measure the level of cognitive and social engagement from the lens of community of inquiry. 2) Social network analysis is used to measure cognitive and social interaction. The dashboard provides reports and recommendations for students and instructors. This project provides guidelines and suggestions on how to incorporate two online frameworks (community of inquery and e-moderating) in designing learning activities supported by generative AI in order to facilitates collaborative learning, students’ engagements and knowledge building.
Section B: Participant Information
| Title | First Name | Last Name | Organisation/Institution | Faculty/Department/Unit | Phone Number | Contact Person / Team Leader | |
|---|---|---|---|---|---|---|---|
| Dr. | ENAS | ALWAFI | UMM AL-QURA UNIVERSITY | College of Education, Curriculum and Instruction Department | emwafi@uqu.edu.sa | 009665555304478 |
Section C: Project Details
Collaborative problem-based learning (PBL) has received increasing attention in online learning environments. The process of online collaborative PBL can engage students in an active learning process. It allowed students to share ideas and experience, find solutions and knowledge construction collaboratively (Hendarwati et al., 2021). The online collaborative PBL need students to cognitively engage through knowledge building and socially engage through social support and behaviorally through peer-to-peer interaction.
Although the value of collaborative PBL, there are some challenges to employ it in an online learning. Provided timely and effective guidance during the online process acts as an obstacle (Van Leeuwen & Janssen, 2019). Furthermore, providing guidance to all students and evaluating students’ contributions by instructors is considered time-consuming and instructors need some help in order to provide effective feedback (Kamal and Illiyan, 2021).
Previous studies mentioned the benefits of using generative AI in learning. Generative AI can help students during problem-solving by providing brainstorming and feedback to students (Meron & Araci, 2023). However, studies showed that using generative AI without considering a solid pedagogical framework may not provide effective learning experience (Yeh, 2025). Studies in online learning place great attention to use community of inquiry framework (Garrison et al., 2003) and e-moderating model (Salmon, 2002) to guide during the design online learning experience. Therefore, this proposed project seeks to provide solution on how can enhance students’ engagement by designing online collaborative problem-based learning system through incorporating generative AI supported by community of inquiry and e-moderating model.
This project seeks to design online collaborative problem-based learning system through incorporating generative AI supported by community of inquiry and e-moderating (E-tivities) model in order to enhance students’ engagement. The e-moderating model with generative AI used to guide the design learning activities during the online collaborative problem-based learning system. The community of inquiry used to guide AI to provide personalized recommendations and to evaluate the quality of students’ contribution. Generative AI roles:
• AI acts as digital moderator for online interaction.
• Helping students to engage in collaborative problem-solving by providing questions, suggestions and brainstorming.
• Evaluating students’ contribution before submitting and providing suggestion
• Evaluating students’ cognitive, social and behavior engagement through using learning analytics techniques
• Assisting instructors to track and monitor students learning engagement
• Assisting instructors to tailor feedback to students’ work and progress based on the lens of community of inquiry.
The system also has dashboards for instructors and students. The system used learning analytics to present students’ engagement in the dashboard which involves: 1) Content analysis used to measure the level of cognitive and social engagement from the lens of community of inquiry. 2) Social network analysis is used to measure cognitive and social interaction. The dashboard provides reports and recommendations for students and instructor.
The key features of the design:
• Provide real-time recommendation and feedback through the lens of community of inquiry.
• Evaluating the different types of engagement: cognitive, social and behavior engagement.
• Structure the learning activity through the lens of e-moderating model
• Tailor feedback and support
• Generative AI facilitates collaborative learning
To evaluate the effectiveness of systems: 1) examine students' engagement through learning analytics. 2) examine students’ problem-solving skills and perception for learning, 3) evaluating instructors' view. 4) evaluating students’ and instructors’ perceptions of effectiveness of the system through interview. Through this data, the validation features will be measured, and the system will be developed.
not applicable
This project is novel because it considers two solid pedagogical frameworks in designing online collaborative problem-based learning system supported by generative AI which are: community of inquiry (Garrison et al., 2003) and e-moderating (e- tivities) model (Salmon, 2002). Previous studies showed that using generative AI without considering a strong pedagogical framework may not provide effective learning experience (Yeh, 2025). It also provides guidelines on how to incorporate two online frameworks in designing learning activities supported by generative AI in order to facilitates collaborative learning, students’ engagements and knowledge building. The e-moderating model with generative AI used to guide the design learning activities during the online collaborative problem-based learning system. The community of inquiry used to guide AI to provide personalized recommendations and to evaluate the quality of students’ contribution. Although the previous study used community of inquiry with AI (Chen et al., 2024), it was used only for evaluating the students’ contribution after submitting. Another contribution in this project is that AI used to facilitate collaborative learning as previous studies focus on individual interaction with generative AI.
The system will employ the cloud platform and follow the microservice architecture in order to divide the work into parts. The natural language processing and machine learning algorithms will be used in the study. In terms of how the system fosters the user engagement, the system will tailor the feedback and recommendation to meet the learner needs and it will provide timely feedback. Learners have the opportunity to evaluate the AI moderator role in order to make future improvement. Both students’ and instructors’ perceptions of effectiveness of the system will be evaluated in order to enhance the system.
The system provides equal opportunities for learners to access and receive feedback depending on their needs. It also helps the students in building the learning community through collaboration, problem solving and discussion. The AI system guide students to consider the social practice of learning as AI system provides recommendations related to social presence and social support and facilitates social interaction. It allows learners to collectively build knowledge and develop skills and help each other. The system evaluates the social impact thorough learning analytics by measuring the amount of access to system, the level of peer-to-peer support, the level of engagement in learning activities and the social network analysis of students interaction.
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