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)

An Ecological Model of Student Interaction in Online Learning Environments

2016 ◽  
pp. 1-28
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.

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.

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 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.

Improving the Quality of Online Learning Environments

2017 ◽  
pp. 278-300
Author(s):  
Komar Parveen Khan
Keyword(s):  
Online Learning ◽  
Instructional Design ◽  
Learning Environments ◽  
Teaching And Learning ◽  
Specific Model ◽  
Design Guidelines ◽  
Online Learning Environments ◽  
Design Models ◽  
Design For Learning

In spite of the numerous changes in technology in the past decades, designers continue to utilize traditional instructional design models as a foundation for designing teaching and learning materials, which may not be suited for the design and development of online learning environments. A study was conducted to investigate the characteristics of an online-specific design model called Proactive Design for Learning (PD4L) (Sims, 2012; Sims & Jones, 2003) and its ability to address limitations of traditional design models. The study was conducted to examine in what ways the PD4L model would contribute to enhance the quality of online learning. Based on this research, this chapter will be able to provide readers with ideas on the ways the elements of an online specific model can serve as design guidelines, a framework or “a set of guiding principles” (Sims, 2011) for designers and developers to create quality teaching and learning environments.

scholarly journals Content, language and intercultural challenges in engineering education: (E-)strategies to improve instructional design

2018 ◽  
Vol 4 (8) ◽  
pp. 153-161 ◽  
Author(s):  
Margarida Morgado
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Instructional Design ◽  
Engineering Education ◽  
Learning Environments ◽  
Teaching And Learning ◽  
Learning Processes ◽  
Special Focus ◽  
Design Strategies ◽  
Online Learning Environments

Intercultural, multilingual and culturally and academically diverse classrooms are a common reality in current higher education (HE) landscapes, as globalisation is effectively taking place in all major schools. Rethinking instructional design strategies that contribute to the overcoming of communication and cultural differences in both online and blended learning processes may help not only improve the development of more efficient online learning environments but also meet the challenges of current teaching and learning processes. Special focus will be put into engineering education through the medium of English and the training of engineering lecturers in HE through communities of practice (CoPs), which present, integrate and discuss how to integrate content and language (through what is known as the content and language integrated learning (CLIL) approach) as well as trends, challenges and opportunities related to recent technological developments on students’ learning ourcomes. The desciption of the pedagogical training shared through a CoP describes E-strategies to improve instructional design in engineering courses in online learning environments when English is used as a medium of instruction and integrated with content in a CLIL approach. Keywords: Higher education, CLIL/ICLHE, English Lingua Franca, instructional E-design, online learning environments, training of engineering teachers.

scholarly journals The Impact of Students’ Perceptions of Online Learning Environments on Students’ Satisfaction in the Context of Covid-19 Pandemic

2021 ◽  
Vol 2 (3) ◽  
pp. 61-72
Author(s):  
Sunipa Ghosh Dastidar
Keyword(s):  
Online Learning ◽  
Active Learning ◽  
Student Satisfaction ◽  
Learning Environments ◽  
Student Interaction ◽  
Online Learning Environments ◽  
Student Autonomy ◽  
Instructor Support ◽  
The Impact ◽  
Students Satisfaction

In the context of the Covid-19 pandemic, the present study aimed to examine students’ perceptions of online learning environments and students’ satisfaction based on their academic stream. The study also investigated the impact of students’ perceptions of online learning environments on students’ satisfaction. A quantitative descriptive survey method was applied. This study included 230 students (130 undergraduate and 100 postgraduate students) from colleges and universities of West Bengal. Online Learning Environments Survey, an adapted and translated (Bengali) version of the Distance Education Learning Environments Survey (DELES) by Scott L Walker (2003), was used for collecting data. For data analysis, statistical techniques, ANOVA and regression analysis were performed. The results revealed significant mean differences among arts, commerce, and science students’ perceptions of online learning environments in the dimensions of student interaction and collaboration, personal relevance, authentic learning, active learning, and student autonomy except in instructor support. Furthermore, a significant mean difference in student satisfaction was found based on the academic stream. The result revealed that overall students’ perceptions of online learning environments had a significant impact on student satisfaction, with student interaction and collaboration being the most significant predictor of all; however, instructor support, active learning, and student autonomy were not found to be significant predictors of student satisfaction.

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