AI, or artificial intelligence, has the power to transform learning and development programs. Using cognitive tutors, or intelligent tutoring systems, learners’ experiences can be personalized to their needs and performance. This adaptivity to an individual’s performance provides immediate feedback, gives insight into knowledge gaps, differentiates learning, provides support, and generates content to address the knowledge gaps identified.
The use case of AI is not to replace in-person learning, but to supplement traditional learning and development to provide highly personalized feedback to learners. Research into the development of these systems has focused on the data sets in which patterns can be identified for “correct” and “incorrect” answers. The building of these associations is similar to the neural networks created in the brain. There are some subjects in which rules and guidelines can be built in the form of logic- i.e. mathematics, science, and grammar. In others, however, the database for “correct” and “incorrect” are more complicated and can be more subjective- i.e. storytelling, conflict resolution, and artistic representations.
AI and intelligent tutoring systems can function within certain subjects or content that is well-defined with a system of logic that can be accepted as universally true. Vocabulary acquisition in learning a new language is one case in which users could personalize their experience and learn the words most pertinent to their end goals. As with any learning, the user’s motivations and goals need to be considered when creating the networks and potential pathways to allow for more personalization.
The adaptive nature of AI in learning and development has the power to meet individual needs. In the development of these systems, designers must consider the data that is defining the rules within the AI, and how diverse perspectives can be represented within the systems being created. Writing with voice is extremely personal, and if AI were to teach writing, it could lead to more formulaic narratives, rather than the individual being able to strengthen their voice and share their perspective through their chosen syntax and diction. Take for instance Zora Neale Hurston’s novel, Their Eyes Were Watching God. In this story, the author’s choice of language conveys meaning far beyond the basic vocabulary that could be used. Through her careful choice of words and phrasing, Hurston evokes the feel of tight-knit rural towns where oral storytelling traditions thrive, mirroring her characters’ identities, backgrounds, and emotional states.
Through the development of adaptive learning environments and AI within these, a logic system can be mapped out that allows for productive failure and both direct and indirect feedback so users can reflect on their performance. UNC Blue Sky Innovations has focused on developing narratives in which the user has a first-person experience in a context-bound situation.
As issues around diversity, equity, and inclusion arise, it is essential to consider how everyone contributes to the overall environment. This must include how the user’s previous life experiences change their perspectives. Through the design process of IDEA VR, users complete micro-learning sessions in which they are a leader and must navigate issues that arise in their workplace. The choices an individual makes directly affect the storyline, and this adaptivity allows users to see how their actions (or inaction) affect the workplace. In these simulations, there are no options in which everyone is entirely satisfied, since life rarely has neat endings, and it would be unrealistic to represent this within our training. Instead, users must consider how their actions and reactions to others affect a group. IDEA VR is designed to promote the understanding and development of interpersonal skills to best support equitable practices within a diverse and inclusive workplace.
AI can provide much-needed support to an individual’s learning and development, with its adaptive nature allowing for a more personalized learning experience, but the creation of AI and the systems in which it functions should be considered carefully. AI is only as good as the data set and logic it was built to mirror, and without thoughtful designers and developers, this technology could produce more cookie-cutter answers rather than develop the critical thinking necessary to solve the problems of the future.
