Embedded Files
No solution is perfect, especially in complex educational environments involving multiple stakeholders.
Designing an AILP requires balancing the needs of learners, teachers, administrators, and institutions. Every design decision involves trade-offs, and improving one aspect of the learning experience often introduces new challenges elsewhere (Kim & Baylor, 2006; Fan et al., 2025).
The section below outlines four important design choices that illustrate the kinds of trade-offs involved in developing an AILP. While not an exhaustive list, these examples demonstrate how improving one aspect of the learning experience often requires compromise elsewhere.
How much should it help?
How much should it help?
The Range: From "just give the answer" to "make the learner work it out."
The Trade-off: Giving answers helps learners get unstuck quickly, but it may also reduce opportunities for productive struggle and deeper learning. Encouraging learners to reason through problems promotes understanding, but it can also be slower, more challenging, and frustrating for some learners (Fan et al., 2025).
What tone should it take?
What tone should it take?
The Range: From "always supportive" to "willing to push back."
The Trade-off: A warm, encouraging tone can build confidence and reduce anxiety, but taken too far it risks becoming a "yes-machine" that reinforces incorrect ideas. A more challenging approach may promote critical thinking, but if pushed too far it can discourage learners and reduce motivation (Kim & Baylor, 2006).
Who drives the session?
Who drives the session?
The Range: from "waits to be asked" to "jumps in uninvited."
The Trade-off: Letting the learner lead the session protects their independence, but those who need help the most may not ask for it. Having the learning partner step in proactively can better support struggling learners, but it can also undercut their independence (Chiu et al., 2024).
Does it remember previous sessions?
Does it remember previous sessions?
The Choice: Either "memory of previous sessions" or "a clean slate every time."
The Trade-off: Remembering previous sessions allows the AILP to personalize future interactions, but storing learner information raises important privacy and data security considerations. Starting each session with a clean slate improves privacy and reduces implementation complexity, but limits personalization and continuity (UNESCO, 2025).
Now that you've explored these implementation challenges, it's time to apply them. In the next activity, you'll make your own design decision and experience the trade-offs involved in building an AILP.
Page updated
Google Sites
Report abuse