Online Learning Readiness

2016 ◽  
Vol 12 (1) ◽  
pp. 51-62
Author(s):  
Min-Ling Hung
Keyword(s):  
Online Learning ◽  
Survey Data ◽  
Self Efficacy ◽  
Online Courses ◽  
Learner Control ◽  
Learning Motivation ◽  
Online Course ◽  
Motivation For Learning ◽  
Final Exams ◽  
Online Learning Readiness

The purpose of this study was to examine whether online students' course-related readiness would undergo changes between midterm exams and final exams, and which student-readiness factors might predict students' willingness to take an online course again. The analysis used survey data from 217 students enrolled in an online course that was presented three times over three consecutive semesters. The results of this study were as follows: (1) an increase in communication self-efficacy and a decrease in learner control and in motivation for learning from middle of the semester to the end of the semester; (2) communication self-efficacy and learning motivation were statistically significant predictors of the students' willingness to take future online courses.

scholarly journals Do teamwork experience and self-regulated learning determine the performance of students in an online educational technology course?

2021 ◽  
Author(s):  
Solomon Sunday Oyelere ◽  
Sunday Adewale Olaleye ◽  
Oluwafemi Samson Balogun ◽  
Łukasz Tomczyk
Keyword(s):  
Educational Technology ◽  
Online Learning ◽  
Self Efficacy ◽  
Multivariate Regression ◽  
Quantitative Research ◽  
Online Courses ◽  
Online Course ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Technology Course

AbstractThis study uses the quantitative research approach to examine the connection between students’ teamwork experience, self-regulated learning, technology self-efficacy, and performance in an online educational technology course. Sixty-three (63) students participated in this study. The study data were collected through an online questionnaire that included background information, course satisfaction, motivation strategies for learning, and online technology self-efficacy, to study the variables’ interactions using quantitative research. To realize this study’s aims, multivariate regression and correlation approaches were employed to analyze the online students’ data. The multivariate regression analysis results show a relationship between self-regulated learning, the online course level, and the number of online courses that the students have completed. Right self-regulated learning strategies in online courses motivate students to strive for a good teamwork experience, leading to increased interest in online learning. In addition, the results also show that there is a relationship between satisfaction and the level of the online course. Achieving good grades makes the student more satisfied and improves the level of technology use. Finally, this study established a relationship between the students’ motivation and the online course level. Therefore, teachers and course designers should implement learning objects that promote students’ engagement and motivation in online learning environments.

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

scholarly journals Applying the Matrix Model in an English for Presentation Online Class during COVID-19 Pandemic: A Case Study of an Undergraduate Class in Thailand

2021 ◽  
Vol 14 (9) ◽  
pp. 12
Author(s):  
Prapaporn Sompakdee ◽  
Wichuta Chompurach ◽  
Werachai Thanamaimas ◽  
Siraprapa Kotmungkun
Keyword(s):  
Online Learning ◽  
Matrix Model ◽  
Online Courses ◽  
Private University ◽  
Online Course ◽  
The Matrix ◽  
Online Course Development ◽  
Data Collections ◽  
Class Presentation ◽  
Academic Year

During the COVID-19 pandemic, online learning was an important topic for scholars. A private university in Khon Kaen Province, Thailand followed a policy to create online courses for every subject to ensure that education could proceed effectively. To correspond with the policy, the Matrix Model was integrated with the online course development of an English for Presentation class at this private university. The Matrix Model is also known as SAMR which refers to Substitution, Augmentation, Modification, and Redefinition. The online course was presented in the third semester of the academic year of 2019 with 77 participants who volunteered to participate in this course. The research instruments used in this study were observation, surveying, and interview. The data collections were done at the beginning, during, and after the course to provide a comprehensive study of online learning. The data revealed both positive opinions and obstacles associated with this online learning. The results of using the SAMR model in this study do provide benefits to students and educators and show that 84% of the participants prefer online presentation over in-class presentation.

scholarly journals Understanding Learner Behaviour in Online Courses through Learning Analytics

2021 ◽  
pp. 381-390
Author(s):  
D. Thammi Raju ◽  
G. R. K. Murthy ◽  
S. B. Khade ◽  
B. Padmaja ◽  
B. S. Yashavanth ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Learning Experience ◽  
Training Needs ◽  
Online Course ◽  
Quality Of Education ◽  
Time Data

Building an effective online course requires an understanding of learning analytics. The study assumes significance in the COVID 19 pandemic situation as there is a sudden surge in online courses. Analysis of the online course using the data generated from the Moodle Learning Management System (LMS), Google Forms and Google Analytics was carried out to understand the tenants of an effective online course. About 515 learners participated in the initial pre-training needs & expectations’ survey and 472 learners gave feedback at the end, apart from the real-time data generated from LMS and Google Analytics during the course period. This case study analysed online learning behaviour and the supporting learning environment and suggest critical factors to be at the centre stage in the design and development of online courses; leads to the improved online learning experience and thus the quality of education. User needs, quality of resources and effectiveness of online courses are equally important in taking further online courses.

Using Learning Analytics to Enhance Student Learning in Online Courses Based on Quality Matters Standards

2016 ◽  
Vol 45 (2) ◽  
pp. 165-187 ◽  
Author(s):  
Florence Martin ◽  
Abdou Ndoye ◽  
Patricia Wilkins
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Descriptive Data ◽  
Quality Matters ◽  
Frequency Of Use ◽  
And Performance ◽  
Enhance Student Learning

Quality Matters is recognized as a rigorous set of standards that guide the designer or instructor to design quality online courses. We explore how Quality Matters standards guide the identification and analysis of learning analytics data to monitor and improve online learning. Descriptive data were collected for frequency of use, time spent, and performance and analyzed to identify patterns and trends on how students interact with online course components based on the Quality Matters standards. Major findings of this article provide a framework and guidance for instructors on how data might be collected and analyzed to improve online learning effectiveness.

Preparing Online Learning Readiness with Learner-Content Interaction

2016 ◽  
pp. 586-614
Author(s):  
Juhong Christie Liu ◽  
Elaine Roberts Kaye
Keyword(s):  
Online Learning ◽  
Learning Environments ◽  
Online Courses ◽  
Learning Readiness ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
Content Interaction ◽  
Online Learning Readiness ◽  
Synchronous Online

Online learning readiness is fundamental to student successful participation, presence, and interaction in online courses. Effective facilitation of these key components depends on sound instructional design. In self-directed online environments, learner-content interaction and scaffolding self-regulated learning have been found of primary importance to generate meaningful learning. To provide a solution to the challenges of interoperability of various functions in synchronous online learning environments, this chapter presents a case study about the design and development of a self-paced orientation to help students acquire online learning readiness. Learner-content interaction is strategically utilized in the design to scaffold self-regulated learning. The results of the case study demonstrate that this orientation positively prepares students to be ready for learning in a synchronous online environment. The approach can be of practical use to individuals and groups.

Understanding learner participation at scale: How and why

2020 ◽  
Vol 17 (3) ◽  
pp. 236-252
Author(s):  
Samaa Haniya ◽  
Luc Paquette
Keyword(s):  
Teaching And Learning ◽  
Large Scale ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Learner Participation ◽  
Massive Open Online Course ◽  
Motivation For Learning ◽  
E Learning

Understanding learner participation is essential to any learning environment to enhance teaching and learning, especially in large scale digital spaces, such as massive open online courses. However, there is a lack of research to fully capture the dynamic nature of massive open online courses and the different ways learners participate in these emerging massive e-learning ecologies. To fill in the research gap, this paper attempted to investigate the relationship between how learners choose to participate in a massive open online course, their initial motivation for learning, and the barriers they faced throughout the course. This was achieved through a combination of data-driven clustering approaches—to identify patterns of learner participation—and qualitative analysis of survey data—to better understand the learners’ motivation and the barriers they faced during the course. Through this study we show how, within the context of a Coursera massive open online course offered by the University of Illinois, learners with varied patterns of participation (Advanced, Balanced, Early, Limited, and Delayed Participation) reported similar motivations and barriers, but described differences in how their participation was impacted by those factors. These findings are significant to gain insights about learners’ needs which in turn serve as the basis to innovate more adaptive and personalized learning experiences and thus advance learning in these large scale environments.

Most courses are not born digital

2014 ◽  
Vol 31 (4) ◽  
pp. 217-229 ◽  
Author(s):  
Evangeline Marlos Varonis
Keyword(s):  
Online Learning ◽  
Peer Review ◽  
Review Process ◽  
Course Design ◽  
Online Courses ◽  
Peer Review Process ◽  
Online Course ◽  
Shared Services ◽  
Online Course Design ◽  
Content Type

Purpose – The purpose of this paper is to discuss benefits of and barriers to online learning and describe utilization of the Quality Matters (QM) peer review process as a method to assure the quality of online courses. It outlines the QM higher education rubric, explains how the collaborative QM peer review process facilitates online course design and certification, reports on the development of a statewide consortium in Ohio, and explores future directions in online courses. Design/methodology/approach – This paper offers a brief historical review of the incorporation of technology into teaching and learning. It describes attitudes toward online learning and the creation of the non-profit QM program as a vehicle for improving online course design. It summarizes the eight standards of the QM rubric, describes the QM peer review process, and discusses the implementation of the Ohio QM Consortium (OQMC) as a shared services model. Findings – Given existing barriers to online learning, the QM program can improve learning outcomes by offering best practices in online course design, validating the quality of online courses, encouraging faculty buy-in through a focus on design rather than content, and facilitating degree completion through recognition of quality courses. Practical implications – Institutions that seek to validate online course quality in a cost-effective manner can explore a shared services model such as that developed by the OQMC. Originality/value – This paper introduces to an international audience a program and process, widely implemented in the USA, which encourages inter-institutional cooperation and promotes a supportive culture among online educators.

scholarly journals Strategies for innovative teaching and learning Part 2: How to deliver a distance education online course

2021 ◽  
Vol 11 (9) ◽  
pp. 39
Author(s):  
Constance E. McIntosh ◽  
Diana Bantz ◽  
Cynthia M. Thomas
Keyword(s):  
Distance Education ◽  
Online Learning ◽  
Distance Learning ◽  
Teaching And Learning ◽  
Online Courses ◽  
Online Course ◽  
Innovative Teaching ◽  
Advantages And Disadvantages ◽  
Learning Platform ◽  
History Of

The second article in a three-part series discusses how to deliver a distance education online course by i) assuring understanding of the learning platform, ii) developing a course model, iii) creating individual assignment rubrics for courses, iv) requiring active participation from both instructor and students, and v) setting-up quality communication. This paper is a continuation of the first paper whereby the history of distance learning, the positives and negatives of online learning, advantages and disadvantages of online learning, and the initial considerations for establishing online courses.

scholarly journals Online Learning as Teaching - Learning Pedagogy in B.ED. Colleges

2021 ◽  
Author(s):  
Yusra Farooqui ◽  
Darshana Shah ◽  
Rabiya Saboowala
Keyword(s):  
Online Learning ◽  
Student Teachers ◽  
Prospective Teachers ◽  
Self Efficacy ◽  
Online Communication ◽  
Self Directed Learning ◽  
Motivation For Learning ◽  
Control Dimension ◽  
The Government ◽  
Teaching Learning

Abstract In the 21st century, the attainment of knowledge and education goes far beyond the boundaries of educational institutions. Learning takes place in many diversified forms, be it in form of location or time or course content. This makes it easy to facilitate learning across the globe with ease so that the learners can pursue what they wish to. Among these various diversified and facilitated forms of learning, the most adopted and acceptable way of promoting academics in reputed educational setup undoubtedly is online learning. The concept of online learning has been implemented in all educational sectors throughout the globe due to the prevailing COVID-19 pandemic. The present action research aimed at examining the attitudes of second year Prospective teachers who are working as well as those who are not working towards online learning during the prevailing pandemic in Mumbai. A questionnaire with 5-point Likert scale was adopted for data collection from a sample of 54 prospective teachers. Findings of the study reveal the working prospective teachers have a higher attitude towards adopting online learning as teaching-learning pedagogy for B.Ed. teachers as compared to non-working Prospective teachers. Also, working Prospective teachers had a higher attitude towards Computer/Internet self-efficacy, Self-directed learning and Online communication self-efficacy dimension of online learning when compared with non-working Prospective teachers. Not-Working B.Ed. Teachers had a higher attitude towards the Learner Control dimension of online learning, whereas both working and non-working Prospective teachers had a similar attitude towards Motivation for learning (in an online context) dimension of online learning. Policy makers should include online learning topics in the B.Ed. curriculum not just theoretically but also practically in order to help learners develop a positive attitude towards adoption of online learning not just for learning but also for teaching. Also, the government and educational institutes need to organize workshops and seminars for teachers and student-teachers in order to equip them with knowledge and application of computers in the academic process which is the need of the hour during the prevailing pandemic.

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