Abstract
An autonomous smart learning environment (ASLE) is a new educational paradigm that utilizes artificial intelligence and machine learning technologies to provide personalized, adaptive, and self-directed learning experiences. Although the clinical aspects of dentistry have experienced technological advancements, the development and implementation of ASLE in dental education are scarce. The goal of this chapter is to investigate the potential of ASLE as a teaching and learning tool in dentistry education and how it can be used to improve the learning experience and outcomes for dental students. Furthermore, it will highlight the current pedagogical approaches used in dental and oral medicine as well as the processes that can be incorporated to strengthen the current training needs of Generation Z learners. Overall, this chapter will provide insights into the potential of ASLE to enhance the quality of education in dentistry, inform the development of future ASLE-based dental education programs, and introduce dental education in the information age.
TopBackground
Dentistry is an art and science dealing with oral health, function, and aesthetics to improve the overall quality of life of an individual and a community at large. The dental sciences have laid a strong emphasis on evidence-based dentistry through several decades of research into both spheres of dental pedagogy and clinical sciences. Dentistry, which is an umbrella term, is used to represent the multiple specialized faculties ranging from diagnostic fields such as oral medicine and oral pathology to highly technical fields of orthodontics and oral and maxillofacial surgery. Through the advances made in these fields (Mansoory et al., 2022; Martins et al., 2022; Mattheos et al., 2008), dentists, orthodontists, prosthodontists, and oral surgeons strive to recreate and re-establish a harmonious dynamic and functional apparatus to preserve general health.
Key Terms in this Chapter
Deliberate Practice: Refers to a special type of practice that is purposeful and systematic. While regular practice might include mindless repetitions, deliberate practice requires focused attention and is conducted with the specific goal of improving performance.
Connectivism: Connectivism is based on the theory that we learn when we make connections, or “links,” between various “nodes” of information, and we continue to make and maintain connections to form knowledge.
Extended Reality: Extended reality, or XR, is a collective term that refers to immersive technologies, including virtual reality, augmented reality, and mixed reality, and those that still haven’t been created.
Cognitive Apprenticeship: This is a model of instruction that works to make thinking visible. It is a model of instruction that incorporates elements of formal schooling into a traditional apprenticeship.
Simulation-Based Learning: Simulation-based education is an educational or training method that is used to “replace or amplify the real experience with guided experiences.
Micro-Learning: An educational strategy that breaks down complex topics into short, stand-alone units of study that can be viewed as many times as necessary as needed by the learner whenever and wherever.
Augmented Reality: An enhanced version of reality created using technology to overlay digital information on an image of something being viewed through a device (such as a smartphone camera)
Smart Learning Environment: A smart learning environment can be conceptualized as a learning environment that emphasizes learning flexibility, effectiveness, efficiency, engagement, adaptivity, and reflectiveness where both formal learning and informal learning are integrated.