scholarly journals Smart Learning Environments y ergonomía: una aproximación al estado de la cuestión

2020 ◽  
Vol 9 (2) ◽  
pp. 245
Author(s):  
Pedro Antonio García-Tudela ◽  
María Paz Prendes-Espinosa ◽  
Isabel María Solano-Fernández

Educational technology evolves constantly, in line with the innovative technologies we implement, but always catering for the improvement of teaching and learning. For this, Smart Learning Environments (SLE) emerge as an optimal alternative to traditional teaching as, through ergonomics, an inclusive outlook which is bound to enhance the educational experience of every student is provided. The method utilized is based on a systematic review of the existing literature which has allowed us to analyze in depth a final sample of 19 documents after an initial review of 633, being these all the works published between 2013 and 2019. Therefore, the principal objective of the present work is carrying out an analysis of the state of the art in relation to ergonomics, inclusiveness and the SLE. The analysis of results is performed utilizing a semantic network, generated through atlas.ti. v.8, by means of which 3 categories, 10 codes and 33 quotes are extracted. Namely, the results reveal the emerging nature of the thematic line researched and how ergonomics is linked to inclusiveness and stands out as one of the most defining components when designing an educational proposal based on SLE. 

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):  
Lana Hiasat ◽  
Anthony John Pollitt

Smart learning environments for the Emirati learners are defined as a combination of blended learning and experiential learning approaches to create joyful educational environments. The current case study is an investigation into what generation Y of Emirati learners in one of the largest tertiary educational institutions in the United Arab Emirates consider joyful learning. The case study was based on mixed method surveys of educators and students. The case study investigation resulted in four important recommendations for creating smart learning environments where context and situated learning are essential considerations for mindful teaching and learning.


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.


Author(s):  
S. Manjit Sidhu

Student in today’s undergraduate level classrooms often display widely varying characteristics that extremely affect learning outcome. Although student characteristics have been widely studied in the more traditional teaching and learning environments, educators have just begun exploring the applications in interactive multimedia and its associated technological techniques. This article first describes some pedagogical characteristics that could affect students in their learning and than discuss some student learning styles.


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