What are we Supposed to be Learning? Motivation and Autonomy in Smart Learning Environments

2021 ◽  
pp. 235-249
Author(s):  
Pen Lister
Keyword(s):  
Learning Environments ◽  
Learning Motivation ◽  
Smart Learning ◽  
Smart Learning Environments

scholarly journals A conceptual framework for designing smart learning environments

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Sirkka Freigang ◽  
Lars Schlenker ◽  
Thomas Köhler
Keyword(s):  
Conceptual Framework ◽  
Learning Environments ◽  
Smart Learning ◽  
Smart Learning Environments

Open Learner Models in Smart Learning Environments

2019 ◽  
pp. 346-368 ◽  
Author(s):  
Angeliki Leonardou ◽  
Maria Rigou ◽  
John D. Garofalakis
Keyword(s):  
Learning Environments ◽  
Adaptive Learning ◽  
Real Life ◽  
Self Reflection ◽  
Learner Model ◽  
Self Regulated Learning ◽  
Smart Learning ◽  
Smart Learning Environments ◽  
Navigation Support ◽  
Adaptive Learning Systems

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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