What are the potential drawbacks of using artificial intelligence in education?

While not k-12, integrating AI/ML tools in nursing education plays a pivotal role in fostering critical thinking skills, so there is some precedent. These technologies can be invaluable in addressing critical aspects of patient care where nurse interventions have life-or-death implications. In a collaborative effort, nurses and engineers can craft logic models that outline best practices concerning inputs, strategies, and outcome measures for successfully incorporating AI/ML in nursing education, thus enriching the critical thinking capabilities of future nurses. The same could be done with k-12 educators/ faculty.

AI cannot duplicate the effects of personal relationships. For example, a teacher wears many hats. AI will not have the ability to distinguish when a child needs a social worker. AI is also not going to have the ability to differentiate between students. For example, we know that children learn to read best when they can relate to and identify with what they are reading. AI will not have the ability to consider differences nor properly educate children according to their individual culture. AI will simply create rigid rules for everyone to follow. Those rules may not be in the best interest of every child. Not much differentiation from standard With AI in control. There will be no room in education for the individual learning experience.

AI in education does raise some ethical concerns. There is no prudent way to identify if the data is accurate or if the information is used in an offensive manner or offensive to a particular group. I also believe there should be limits on how and when it is used, we often need our scholars to think critically and AI could limit the activity of critical thinking. The information we seek in AI can't be deleted so therefore personal information can be freely accessed. Integrity becomes an issue with the data usage and storage.

According to the psychologist Lev Vygotsky, learning is a social process that is supported by interaction between individuals. Learners acquire skills during the process of interaction with mentors and peers. Isolated learning with only the guidance of machines robs learners benefits of interacting with others. On the other hand, AI used for collaboration may augment the learning process and support the learning experience for all learners.

This work requires a user-centered approach, feedback gathering, & usability testing to ensure intuitiveness. The system must be robust, with redundancy & error handling, while regular maintenance & updates enhance reliability. Scalability enables adapting to growing user needs with modular architecture and cloud infrastructure. Interoperability, employing open APIs and data standards, allows seamless collaboration with other educational systems. Data security, encryption, user authentication, and compliance with regulations protect sensitive information. Continuous monitoring tracks performance, usage, and issues, allowing proactive resolutions. Compatibility with various devices and operating systems accommodates diverse user preferences.