Artificial intelligence applications and techniques in interactive and adaptive smart learning environments

Author(s):  
Divanshi Priyadarshni Wangoo ◽  
S. R. N. Reddy
Author(s):  
Salim Alanazy

The current study aims to develop smart learning environments in Saudi universities in line with the future requirements of artificial intelligence. To achieve this goal, a systematic review was conducted on studies published on Scopus and Google Scholar databases from 1990 until 2021 on the development of e-learning in the light of artificial intelligence (in addition to the relevant Arab studies). First, a list of challenges and opportunities for developing smart learning environments according to the future requirements of artificial intelligence was composed. Then, a questionnaire was prepared and reviewed by several academic experts in educational technology in Saudi universities. The study results include many challenges expected to be encountered in the smart learning environments in Saudi universities concerning the future preconditions for artificial intelligence. It also presented a number of opportunities and procedures for facing such challenges and exploiting the opportunities. Finally, some recommendations and suggestions were presented.


Author(s):  
Angeliki Leonardou ◽  
Maria Rigou ◽  
John D. Garofalakis

Smart learning environments (SLEs), like all adaptive learning systems, are built around the learner model and use it to support a variety of interventions such as mastery learning, scaffolding, adaptive sequencing, and adaptive navigation support. Open learner models (OLMs) “expose” the learner data to users through easily perceivable visual representations aiming to improve student self-reflection and self-regulated learning and also increase user motivation and even foster collaboration. This chapter presents the evolution and current state of OLMs, summarizes related research in the field emphasizing on OLM types, locus of control between the system and the user and visualizations categorized on the basis of quantized/continuous and structured/unstructured representations. OLM cases implementing typical SLEs features are described, along with representative real-life scenarios of incorporating OLMs in SLEs. Moreover, the chapter provides guidelines for designing effective OLMs and discusses current research trends in this active scientific field.


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