1- Based on their existing attitudes, students might respond differently to an AI coach.
Consider the varying degrees of anthropomorphism, from minimal human-like attributes to highly realistic human characteristics, when designing the AI coach.
Why?
Different degrees of anthropomorphism in designing an AI coach can affect student engagement, and trust. Also, anthropomorphic bots, if not transparent, might create an illusion of real human.
Examples:
A direct and to the point bot, which provides factual feedback, in a straightforward manner without emotional nuance
A friendly but professional bot, that uses basic empathy in responses with some informal language that clearly declares itself as a chatbot
A bot that uses rich emotional language, humor, and personal anecdotes and that can adapt its tone to match user's mood.
A bot that does not clearly distinguish itself as an AI and discusses past memories while discussing doing work together.
Assess and address students' preconceptions about AI before engagement. Create strategies for helping students who might over rely on AI or might have a natural deterrence towards it.
Why?
Students’ existing attitudes towards AI might vary and impact their trust. Understanding these preconceptions helps tailor the introduction and use of AI coaching to individual needs.
Examples:
Perceived knowledge of AI
Attitudes towards AI
Perceived social norms regarding AI
Perceived ease of use of AI
Perceived usefulness of AI
Intention to use AI
2- First impressions shape students’ trust and engagement with the AI coach. Here are some suggestions:
Evaluate the necessity of human facilitation during AI coach onboarding to establish trust, set clear expectations, and address initial concerns.
Why?
First impressions matter. A well-designed onboarding process, potentially involving human guidance, can significantly impact how students perceive and use the AI coach throughout their academic journey.
Provide necessary information about the state of the AI coach. But too much information might be neglected. Allow students to dig deep if they want to.
Why?
Transparency is crucial, but too much information upfront can be overwhelming. A tiered system allows students to access basic details easily while giving them the option to explore more in-depth information if they choose.
3- Coaching frequently involves repeated interactions that cannot be completed in a single session. Here is what to consider:
Consider what tasks need ongoing repeated interactions, what data is needed, and the security and privacy of those needed data.
Why?
Trust is built over time. Often, effective coaching requires identifying specific tasks that benefit from ongoing, repeated interactions. You might consider developing a consistent follow-up schedule to ensure regular interactions with students.
Be transparent when data from student-AI interaction is being saved and used
Why?
Transparency and user agency are essential to responsible AI practices. A transparent bot that provides users with enough agency can build appropriate trust towards the coaching task.
Examples:
A bot that informs the student when their data is being saved.
A bot that prompts the student, asking permission to save data.
A link to a space where all saved data are visible to the student, and can readily be deleted and updated.
Provide necessary assurances to students through education, interface, or explanations that saved data is secure.
Why?
Ensuring student data privacy is essential for maintaining trust and the integrity of ongoing coaching interactions.