Culturally Sensitive Instructional Design Principles for Online Learning Environments

2018 ◽  
pp. 292-326
Author(s):  
Gülten Kartal ◽  
Elif Toprak ◽  
Evrim Genc Kumtepe
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Cultural Diversity ◽  
Learning Environments ◽  
Design Principles ◽  
Culturally Sensitive ◽  
Online Learning Environments ◽  
E Learning ◽  
Efficient Learning ◽  
Instructional Design Principles

Distance education and e-learning practices are preferred by increasing number of people and institutions in the recent years all around the globe. It's clear that there are different interests, expectations, needs, characteristics, and backgrounds of participants in these learning environments. In this connection, it is important that courses are designed, taking cultural diversity into account, optimizing self-learning in such environments. The instructional designs that support multiculturalism in learning environments, lead to more efficient learning. Based on the awareness about cultural diversity, this chapter focuses on culturally sensitive instructional design principles for online learning environments. Firstly, “culture” as a concept and its components, based on various prominent definitions in literature are given. Then, the design principles are discussed with a critical look on online learning environments, with an eye to different theories and studies of leading researchers in the field.

Culturally-Sensitive E-Learning Practices for Library Education

2013 ◽  
Author(s):  
Leslie Farmer
Keyword(s):  
Online Learning ◽  
Learning Environments ◽  
Culturally Sensitive ◽  
Cultural Dimensions ◽  
Educational Model ◽  
Cultural Impact ◽  
Online Learning Environments ◽  
Library Education ◽  
Learning Practices ◽  
E Learning

With globalization, library educators should address culturally-sensitive instruction design and curriculum, particularly in online learning environments. Hofstede’s cultural dimensions and Bigg’s educational model provide frameworks for addressing cultural impact on library education. Specific techniques are suggested for handling language and online learning issues.Avec la mondialisation, les professeurs de bibliothéconomie devraient incorporer les différences culturelles dans leurs cours ainsi que dans le cursus, notamment en milieu d'apprentissage en ligne. Les dimensions culturelles de Hofstede et le modèle éducatif de Bigg offrent un cadre permettant de traiter de l'impact culturel sur l'éducation. Seront présentées différentes techniques pour aborder les questions de langue et d'apprentissage en ligne.

An Ecological Model of Student Interaction in Online Learning Environments

2020 ◽  
pp. 387-415
Author(s):  
Genevieve Marie Johnson ◽  
Audrey Cooke
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Learning Environments ◽  
Ecological Model ◽  
Ecological Theory ◽  
Ecological Systems ◽  
Student Interaction ◽  
Online Learning Environments ◽  
University Culture ◽  
Environmental Systems

Ecological theory conceptualized the student as surrounded by a series of environmental systems and the processes of learning as interaction between the student (i.e., bioecology) and the systems (i.e., microsystem, exosystem and macrosystem). This chapter synthesizes the literature and proposes an ecological model of student interaction in online learning environments. Specifically, learner-learner, learner-instructor and learner-content interactions occur in the microsystem and are mediated by the interface subsystem. Student microsystemic interactions influence and are influenced by the instructional design exosystem. The macrosystem reflects the indirect influence of university culture on all aspects of the microsystem, exosystem and interface subsystem. The chronosystem captures the effect of time on the student and on all ecological systems (e.g., students mature and university culture evolves)

Online Learning and Metacognition

2020 ◽  
pp. 310-331
Author(s):  
Geraldine Torrisi-Steele
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Instructional Design ◽  
Student Success ◽  
Learning Environments ◽  
Learning Experiences ◽  
Great Emphasis ◽  
Education Students ◽  
Online Learning Environments ◽  
Metacognitive Scaffolding

Online learning experiences are becoming the norm for an increasing number of higher education students. Although there are clear advantages to online learning in terms of flexibility and access, many students struggle to succeed, especially in purely online learning environments. To a large extent student success in online learning environments is dependent on students' ability to self-regulate and ‘learn for themselves'- both abilities related to academic metacognition. Unfortunately, even at university, many students do not have well developed metacognition. It is therefore important to consider carefully metacognitive scaffolding in the design of online learning experiences. However, the models of instructional design commonly used in online learning tend not to place great emphasis on the importance of metacognitive scaffolding. The aim of the present chapter is therefore to increase awareness of metacognition, as one of the important considerations in the design of online learning environments that can help to maximize chances of student success. Towards this end, a framework of instructional design that is more sensitive to metacognition is developed.

A Conceptual Educational Data Mining Model for Supporting Self-Regulated Learning in Online Learning Environments

2021 ◽  
pp. 278-292
Author(s):  
Eric Araka ◽  
Robert Oboko ◽  
Elizaphan Maina ◽  
Rhoda K. Gitonga
Keyword(s):  
Data Mining ◽  
Online Learning ◽  
Learning Environments ◽  
Domain Knowledge ◽  
Educational Data Mining ◽  
Online Learning Environments ◽  
Student Activities ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
E Learning

Self-regulated learning is attracting tremendous researches from various communities such as information communication technology. Recent studies have greatly contributed to the domain knowledge that the use self-regulatory skills enhance academic performance. Despite these developments in SRL, our understanding on the tools and instruments to measure SRL in online learning environments is limited as the use of traditional tools developed for face-to-face classroom settings are still used to measure SRL on e-learning systems. Modern learning management systems (LMS) allow storage of datasets on student activities. Subsequently, it is now possible to use Educational Data Mining to extract learner patterns which can be used to support SRL. This chapter discusses the current tools for measuring and promoting SRL on e-learning platforms and a conceptual model grounded on educational data mining for implementation as a solution to promoting SRL strategies.

Applying Constructivism to Online Learning

2009 ◽  
pp. 58-73 ◽  
Author(s):  
Jennifer Lee ◽  
Lin Lin
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Learning Environment ◽  
Learning Environments ◽  
Learning Models ◽  
Online Learning Environments ◽  
Design Models ◽  
The Past ◽  
Environment Assessment ◽  
Five Elements

Based on constructivist principles, this chapter provides a new instructional design map for online learning environments. This instructional design map includes considerations of five elements, namely, learner, knowledge, learning environment, assessment, and technology. Considerations of these elements are based on analyses of the past and existing instructional design models, online learning models, and constructive principles. Applications of the instructional design map are also discussed in the chapter.

Online Learning Environments

2011 ◽  
pp. 678-685 ◽  
Author(s):  
Riu Hu ◽  
Shuyan Wang
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Learning Environments ◽  
Communication Systems ◽  
The Internet ◽  
Electronic Communications ◽  
Online Learning Environments ◽  
Computer Communication ◽  
E Learning ◽  
The Web

Online learning, which was defined as a learning environment using computer communication systems for learning delivery and interaction (Harasim, 1990), has been involved into all facets of society’s education. Online learning can be considered as a subset of the category of e-learning because it refers specifically to learning that is occurring via the Internet or Intranet. Online learning environment normally refers to learning via electronic communications, coursework, and/or information posted on the Web, and through other instructional activities by using Internet.

Online Learning and Metacognition

2016 ◽  
pp. 221-241
Author(s):  
Geraldine Torrisi-Steele
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Instructional Design ◽  
Student Success ◽  
Learning Environments ◽  
Learning Experiences ◽  
Great Emphasis ◽  
Education Students ◽  
Online Learning Environments ◽  
Metacognitive Scaffolding

Online learning experiences are becoming the norm for an increasing number of higher education students. Although there are clear advantages to online learning in terms of flexibility and access, many students struggle to succeed, especially in purely online learning environments. To a large extent student success in online learning environments is dependent on students' ability to self-regulate and ‘learn for themselves'- both abilities related to academic metacognition. Unfortunately, even at university, many students do not have well developed metacognition. It is therefore important to consider carefully metacognitive scaffolding in the design of online learning experiences. However, the models of instructional design commonly used in online learning tend not to place great emphasis on the importance of metacognitive scaffolding. The aim of the present chapter is therefore to increase awareness of metacognition, as one of the important considerations in the design of online learning environments that can help to maximize chances of student success. Towards this end, a framework of instructional design that is more sensitive to metacognition is developed.

Sign in / Sign up

Export Citation Format

Share Document