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.

scholarly journals Scientific production and thematic breakthroughs in smart learning environments: a bibliometric analysis

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Friday Joseph Agbo ◽  
Solomon Sunday Oyelere ◽  
Jarkko Suhonen ◽  
Markku Tukiainen
Keyword(s):  
Learning Environments ◽  
Bibliometric Analysis ◽  
Adaptive Learning ◽  
The United States ◽  
Scientific Production ◽  
Comprehensive Overview ◽  
Scientific Publications ◽  
Smart Learning Environment ◽  
Smart Learning ◽  
Smart Learning Environments

AbstractThis study examines the research landscape of smart learning environments by conducting a comprehensive bibliometric analysis of the field over the years. The study focused on the research trends, scholar’s productivity, and thematic focus of scientific publications in the field of smart learning environments. A total of 1081 data consisting of peer-reviewed articles were retrieved from the Scopus database. A bibliometric approach was applied to analyse the data for a comprehensive overview of the trend, thematic focus, and scientific production in the field of smart learning environments. The result from this bibliometric analysis indicates that the first paper on smart learning environments was published in 2002; implying the beginning of the field. Among other sources, “Computers & Education,” “Smart Learning Environments,” and “Computers in Human Behaviour” are the most relevant outlets publishing articles associated with smart learning environments. The work of Kinshuk et al., published in 2016, stands out as the most cited work among the analysed documents. The United States has the highest number of scientific productions and remained the most relevant country in the smart learning environment field. Besides, the results also showed names of prolific scholars and most relevant institutions in the field. Keywords such as “learning analytics,” “adaptive learning,” “personalized learning,” “blockchain,” and “deep learning” remain the trending keywords. Furthermore, thematic analysis shows that “digital storytelling” and its associated components such as “virtual reality,” “critical thinking,” and “serious games” are the emerging themes of the smart learning environments but need to be further developed to establish more ties with “smart learning”. The study provides useful contribution to the field by clearly presenting a comprehensive overview and research hotspots, thematic focus, and future direction of the field. These findings can guide scholars, especially the young ones in field of smart learning environments in defining their research focus and what aspect of smart leaning can be explored.

scholarly journals Personalized Dynamic Learning Plan Generator for Smart Learning Environments

2019 ◽  
Vol 8 (2) ◽  
pp. 6175-6180
Keyword(s):  
Online Learning ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Building Blocks ◽  
Successful Completion ◽  
Dynamic Learning ◽  
Smart Learning ◽  
Smart Learning Environments ◽  
Learning Plan ◽  
Learning Plans

Transition of traditional online learning towards the Smart learning environments requires adaptation of the smart features. Personalized assistance is one of the most required characteristic. Learning plans are important building blocks for any teaching learning paradigms. Often an instructor makes a learning plan keeping stakeholders into consideration. However in an online learning environment the stakeholders are not able to adapt to these static plans as there is no personalization involved. As a result there is a considerable increase in dropout rates. Hence there is a need for adaptive learning plans which aims for dynamic adjustment of schedules/learning plans that may help in successful completion of course. This paper presents an approach for dynamic learning plan generator and also proposes a revised Learning plan template to achieve personalized assistance in Smart learning environments. The responses of stakeholders on traditional learning plans and that of individualized dynamic learning plans are received. The response depicted that almost 90% of the stake holders feel that the adaptive learning approach aids in successful completion of the course along with improved motivation levels

scholarly journals THE MAIN COMPONENT FOR DESIGNING SMART LEARNING

2019 ◽  
Vol 4 (2) ◽  
pp. 85-88
Author(s):  
Iman Nurjaman
Keyword(s):  
Literature Review ◽  
Learning Environments ◽  
Technological Design ◽  
Learner Participation ◽  
Self Regulated Learning ◽  
Smart Learning ◽  
Smart Learning Environments ◽  
Main Components ◽  
Main Component ◽  
Almost All

This paper discusses key components in designing smart learning. The concept of smart learning emphasises the importance of technological design to make learning better. In fact, many different definitions can be found in almost all the articles that emphasise multiple aspects and characteristics of smart learning published since 2014 in the journal Smart Learning Environments. This finding illustrates the main components of smart learning to improve knowledge and develop smart learning designs. Based on the results of the literature review it was found that, there are some common and crucial elements identified by most researchers in this field. The first highlights that smart learning is technology. In addition to technology, there are other important components, that is self regulated learning, the needs and characteristics of learner, participation & feedback

scholarly journals Teaching through urban sensorium: urban spatiality as a smart learning environment

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Gaana Jayagopalan ◽  
Sweta Mukherjee
Keyword(s):  
Learning Environments ◽  
Urban Studies ◽  
Real Life ◽  
Urban Spaces ◽  
Built Environments ◽  
Smart Learning Environment ◽  
Smart Learning ◽  
Smart Learning Environments ◽  
Bangalore City ◽  
Sensory Learning

AbstractThis paper qualitatively analyses the implication of urban sensorium as a pedagogic mode in the teaching of Urban Studies. Underpinned by the frames of smart learning environments, the paper reiterates experiencing urban ontologies as spatial learning environments. By drawing from a range of transdisciplinary and experiential modes of learning, this paper maps how an undergraduate course on Bangalore city in India served learners to critically engage with and experience spatial urban ontologies both digitally, and in real-world experiences of learning, furthering learner autonomy and reflection. The methodological prisms of this paper are autoethnography and critical reflection. It is organised around enabling learners recognize the experiential, embodied urban spaces through the urban sensorium via real-life engagements with urban spaces, and creation of digital portfolios that map this learning. Findings from the learners’ knowledge of sensory learning, the city’s intersectional aspects, and the student’s embodied and emplaced self in built environments and digital spaces are analysed via cognitive and affective-reflection levels; the course instructor's reflection is analysed via a process-reflection level. These reflections hold implications for the pedagogy of urban studies in undergraduate classrooms by foregrounding spatiality and urban sensorium as significant critical and affective pedagogic tools. The paper has also accommodated critical engagement with an external faculty member as a co-author, in order to manage any bias or researcher subjectivity in the design.

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