The fourth topic focused on the design for online and blended learning, and I will emphasize the critical and ethical use of AI in learning environments due to its diffusion into education settings. Before presenting the argument, I would like to clarify that the term “facilitator” here refers to an individual who supports learners. This could be a teacher or another person who is positioned to assist them on their learning journey.
Although AI has seen widespread diffusion, there is still ongoing debate about how much it can be trusted as an effective and trustworthy tool. This concern has been raised in the field of education, as well, when it comes to considering how AI should be used and how its outcomes should be assessed. There remains uncertainty about how to reliably determine whether content is entirely AI-generated or created by humans. This discussion aligns with three paradigms represented by Ouyang & Jiao (2021). In their paper, the role of learners concerning AI evolves significantly across these three paradigms.
1. AI-Directed, learner-as-recipient. In this model, learners are considered passive recipients of AI services. The learners play a passive role, and they mainly follow instructions and feedback generated by AI. In this model, AI delivers the entire content in a structured and predefined way. In this way, the interaction is one way in which the AI assesses the learners’ progress and adjusts materials according to their learning goals; however, the learners have little control or influence over the direction of their learning (Ouyang & Jiao, 2021).
2. AI-Support, learner-as-collaborator. In this model, learners take a more active role. The approach has been shifted from one-way to co-construct knowledge. It means that learners work alongside AI tools, rather than simply receiving information. They explore and interact collaboratively within a learning environment enriched by AI support. In this paradigm, AI plays a facilitator role that influences the learning process and learners can collaborate with it.
3. AI-Empowered, learner-as-leader. In this model, learners are fully empowered and take the entire control of learning while using AI as a tool to enhance their understanding. AI acts as a partner which collaborates with the learners to facilitate the learning process. This paradigm emphasizes the constructive principle in which the collaboration is controlled between two actors, learners and AI, resulting in a meaningful engagement between them.
Based on the three mentioned paradigms and PBL discussion, this argument is raised about how can facilitate learners in becoming learners-as-leaders who collaborate with AI, rather than passively receiving information. An additional argument is raised that how can facilitator assess whether the learner collaborates with AI or passively receives information. In my opinion, assessing learners can be improved by advancing current assessment systems. For example, in addition to submitting their assignments, learners could be asked to present their work without using digital tools. This approach encourages learners to truly understand and internalize the materials, even when they use AI as part of their processes. This aligns with the core purpose of education, and I believe this approach. Furthermore, evaluating the references included in an assignment can provide insight into how extensively AI was used in completing the task.
On the other hand, this question arises as to why it is important to encourage learners to collaborate with AI rather than take on a passive role. Passive use of AI may lead to a decline in human creativity. Therefore, facilitators must assess how learners, especially junior students who are just beginning their educational journey, engage with AI. In addition, the accuracy of content is crucial, as AI inherently learns from various data sources, which doesn’t necessarily mean that all the data is accurate or valid.
The other argument is raised about how they can ensure the accuracy and validity of the data. This is a challenge that institutions, I believe, should address by changing their strategies. For instance, they should teach learners how to use AI effectively and consider incorporating it as a core subject. Learners should be knowledgeable about using AI, just the same as they are with other references. This means they should acknowledge when content is generated by AI rather than claiming it as their work. Moreover, they should ensure that this acknowledgement is not viewed as a drawback but rather as a benefit which supports knowledge development through AI-based content generation.
From my perspective, another opportunity lies in the development of AI itself. It should be developed in a way that allows it to distinguish between real-world data it has generated through its learning processes. In other words, the technology should be capable of indicating how much of the information it provides comes from real-world sources and how much is generated by the AI itself. This could be achieved by having AI include references for verifiable data and acknowledge which parts are AI-generated.
To sum up, although assessing this evolution is challenging and remains a topic of debate, there is broad agreement on the usefulness of AI. Various perspectives emphasize guiding learners to use AI as a starting point for discussion rather than as a final solution. It means to facilitate learners to collaborate with AI rather than just using it. The emphasis here is to encourage learners to learn to collaborate with AI, not merely use it.
Reference
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020