«Can AI Simulation and Machine Learning Improve Career Plans and Educational Expectations? »: concept by I-Chien Chen, Lydia Bradford & Barbara Schneider (Michigan State University)
Abstract and keywords
Abstract (English):
An overview of the main ideas of the chapter “Learning Career Knowledge: Can AI Simulation and Machine Learning Improve Career Plans and Educational Expectations?” is provided. by I-Chien Chen, Lydia Bradford and Barbara Schneider. This chapter is part of the collective monograph “AI in Education: Designing the Future”, scientific editors of the publication are Hannele Niemi, Roy D. Pea, Yu Lu. The concept of I-Chien Chen, Lydia Bradford and Barbara Schneider is built on increasing the role of gamification for adequate career plans and educational expectations of students. The point is that students should, long before choosing a profession, present the real requirements for the level of education for their future profession. The capabilities of the Init2Winit application with machine learning technologies to create adequate ideas about the profession and how to study in order to obtain this particular chosen profession in the future are analyzed. The authors of the concept believe that gamification with machine learning will significantly equalize the level of adequacy of career plans and educational expectations, primarily for students from low-income families.

Keywords:
modern education, career plans, artificial intelligence, machine learning, Init2Winit, gamification
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