Developing a Dynamic and Responsive Online Learning Environment

Charles Stuart University adopted the open source software, Sakai, as the foundation for the university’s new, integrated Online Learning Environment. This study explores whether a pedagogical advantage exists in adopting such an open source learning management system. Research suggests that the community source approach to development of open source software has many inherent pedagogical advantages, but this paper examines whether this is due to the choice of open source software or simply having access to appropriate technology for learning and teaching in the 21st century. The author also addresses the challenges of the project management methodology and processes in the large-scale implementation of an open-source courseware management solution at the institutional level. Consequently, this study outlines strategies that an institution can use to harness the potential of a community source approach to software development to meet the institutional and individual user needs into the future.

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Post‐error slowing: Large scale study in an online learning environment for practicing mathematics and language

Developmental Science ◽

10.1111/desc.13174 ◽

2021 ◽

Author(s):

Susanne M.M. Mooij ◽

Iroise Dumontheil ◽

Natasha Z. Kirkham ◽

Maartje E.J. Raijmakers ◽

Han L.J. Maas

Keyword(s):

Online Learning ◽

Learning Environment ◽

Large Scale ◽

Online Learning Environment ◽

Large Scale Study

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Trajectories of engagement: a repeated cross-sectional investigation of student perceptions of an online learning environment

Research in Learning Technology ◽

10.3402/rlt.v20i0.17143 ◽

2012 ◽

Vol 20 ◽

Cited By ~ 5

Author(s):

Stuart Palmer ◽

Dale Holt

Keyword(s):

Online Learning ◽

Learning Environment ◽

Student Perceptions ◽

Large Scale ◽

Online Learning Environment ◽

Cross Sectional ◽

Short Period ◽

Significant Difference ◽

System Use ◽

Over Time

Evaluations of online learning environments (OLEs) often present a snapshot of system use. It has been identified in the literature that extended evaluation is required to reveal statistically significant developments in the evolution of system use over time. The research presented here draws on student OLE evaluations surveys run over the period 20042011 and include nearly 6800 responses exploring students’ perceptions of importance of, and satisfaction with elements of their OLE. Across the survey period, satisfaction ratings with all OLE elements rose significantly, suggesting a positive student engagement with the OLE over time. The corresponding ratings of importance of OLE elements generally rose significantly, though a number of elements registered no significant difference in the first two years of the survey, suggesting that short period surveys may struggle to reveal statistically significant trends. OLE element use appeared to be closely linked to perceived value. The OLE elements with the highest mean importance and satisfaction ratings related to student access of online learning resources. Other detailed results are also reported. We demonstrate a method for, and one large-scale case study of, quantifying and visualising the trajectories of engagement that students have had with an institutional OLE over time.Keywords: online learning environment; learning management system; repeated cross-sectional evaluation; student survey(Published: 24 September 2012)Citation: Research in Learning Technology 2012, 20: 17143 - http://dx.doi.org/10.3402/rlt.v20i0.17143

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Community@Brighton

Technology-Supported Environments for Personalized Learning ◽

10.4018/978-1-60566-884-0.ch004 ◽

2010 ◽

pp. 50-73 ◽

Cited By ~ 3

Author(s):

Stan Stanier

Keyword(s):

Online Learning ◽

Social Network ◽

Learning Environment ◽

Social Networking ◽

Open Source ◽

Case Studies ◽

Shared Learning ◽

Learning And Teaching ◽

Strategic Vision ◽

Network Platform

This chapter details the implementation of a university-wide social networking platform “Community@ Brighton” – using the open source Elgg platform and describes the technical, institutional and educational issues arising from the two years of experience in running the platform. The strategic vision of providing a social network platform alongside an institutional VLE to provide an integrated Shared Learning Environment is also explored, including key case studies and discussion on the challenges such technologies place on existing models of online learning and teaching.

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Deploying Digital Educational Resources with Free and Open Source Technologies

Open-Source Technologies for Maximizing the Creation, Deployment, and Use of Digital Resources and Information ◽

10.4018/978-1-4666-2205-0.ch007 ◽

2013 ◽

pp. 101-114

Author(s):

Jason G. Caudill

Keyword(s):

Online Learning ◽

Learning Environment ◽

Open Source ◽

Organizational Effectiveness ◽

Educational Resources ◽

Financial Resources ◽

Online Learning Environment ◽

Educational Resource ◽

Total Cost ◽

Resource Deployment

Digital educational resources are an increasingly visible and important component of the online learning environment. Concurrently, many organizations are faced with limited financial resources with which to provide their materials to the learners. In order to continue delivering materials but reduce the total cost of delivery organizations can implement free and open source technologies for digital educational resource deployment. Open source software and free online services, properly employed, can enhance organizational effectiveness while also reducing organizational expense.

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Academic Emotion Classification and Recognition Method for Large-scale Online Learning Environment—Based on A-CNN and LSTM-ATT Deep Learning Pipeline Method

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17061941 ◽

2020 ◽

Vol 17 (6) ◽

pp. 1941 ◽

Cited By ~ 1

Author(s):

Xiang Feng ◽

Yaojia Wei ◽

Xianglin Pan ◽

Longhui Qiu ◽

Yongmei Ma

Keyword(s):

Online Learning ◽

Learning Environment ◽

Large Scale ◽

Well Being ◽

Online Learning Environment ◽

Subjective Well Being ◽

Emotion Classification ◽

Model Accuracy ◽

Academic Emotions ◽

Academic Emotion

Subjective well-being is a comprehensive psychological indicator for measuring quality of life. Studies have found that emotional measurement methods and measurement accuracy are important for well-being-related research. Academic emotion is an emotion description in the field of education. The subjective well-being of learners in an online learning environment can be studied by analyzing academic emotions. However, in a large-scale online learning environment, it is extremely challenging to classify learners’ academic emotions quickly and accurately for specific comment aspects. This study used literature analysis and data pre-analysis to build a dimensional classification system of academic emotion aspects for students’ comments in an online learning environment, as well as to develop an aspect-oriented academic emotion automatic recognition method, including an aspect-oriented convolutional neural network (A-CNN) and an academic emotion classification algorithm based on the long short-term memory with attention mechanism (LSTM-ATT) and the attention mechanism. The experiments showed that this model can provide quick and effective identification. The A-CNN model accuracy on the test set was 89%, and the LSTM-ATT model accuracy on the test set was 71%. This research provides a new method for the measurement of large-scale online academic emotions, as well as support for research related to students’ well-being in online learning environments.

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Students’ Activity in an Online Learning Environment for Mathematics: The Role of Thinking Levels

Journal of Educational Computing Research ◽

10.1177/0735633120972057 ◽

2020 ◽

pp. 073563312097205

Author(s):

Livnat Haleva ◽

Arnon Hershkovitz ◽

Michal Tabach

Keyword(s):

Online Learning ◽

Learning Environment ◽

Large Scale ◽

Online Learning Environment ◽

Digital Learning ◽

Strongly Correlated ◽

Online Activity ◽

Grade Levels ◽

Log Files ◽

Digital Learning Environments

Understanding students’ behavior while solving tasks at various levels is essential for the support educators may provide to students. The current study reports on a large-scale exploration of students' activity in an online learning environment for mathematics, while comparing between lower-order thinking (LOT) and higher-order thinking (HOT) applets, and between grade levels. We analyzed log files of N = 32,581 5th- and 6th-grade students from all over Israel (a full sample of users in the studied platform), specifically comparing scores, completion rates, completion times, and repetition levels in LOT and HOT applets. Using within-subject and between-subject t tests, we found that students' performance and completion rate on the LOT applets were overall higher than those of the HOT applets, which, combined with other findings, may point to meta-cognitive or motivational processes involved. We also point out to the high rates of students' manipulation of the system in a way that allow them to increase their score. Finally, we found that the various measures we used to characterize students' online activity are not necessarily strongly correlated with each other. These findings will help teachers to take informed decisions regarding the incorporation of digital learning environments in their classrooms.

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Predicting Fraction and Algebra Achievements Online: A Large-Scale Longitudinal Study Using Data from an Online Learning Environment

10.31234/osf.io/rw6b9 ◽

2021 ◽

Author(s):

Markus Spitzer ◽

Korbinian Moeller

Keyword(s):

Online Learning ◽

Learning Environment ◽

Large Scale ◽

Mathematical Problem ◽

Online Learning Environment ◽

Academic Skill ◽

Mathematical Skills ◽

Face To Face ◽

Using Data ◽

And Algebra

Background: Mastering fractions seems among the most critical academic skill for students to acquire in school as fraction understanding significantly predicts later academic and vocational prospects. As such, identifying longitudinal predictors of fraction understanding (e.g., mastery of numbers and operations) is highly relevant. However, almost all existing studies identifying more basic numerical skills as predictors of fraction understanding rest on data acquired in face-to-face testing - mostly in classrooms. Objectives: In this article, we evaluated whether obtained results generalize to data from the curriculum-based online learning environment Bettermarks for mathematics used in schools in the Netherlands. In particular, we i) evaluated whether fraction understanding can be predicted by prior skills on different more basic mathematical topics before we ii) examined whether fraction understanding predicted achievements in algebra over and beyond the influence of basic mathematical skills. Methods: We considered data from more than 5,000 students who solved over 1 million mathematical problem sets. Results and Conclusions: In line with previous findings, we found that fraction understanding was predicted significantly by prior skills on basic mathematical topics. Our analyzes also revealed that algebra achievements were predicted significantly by fraction understanding beyond influences of basic mathematical skills. Implications: Together, these findings substantiated previous results based on face-to-face testing and, thus, indicate that data from large-scale online learning environments may well qualify to provide significant insights into the development of mathematical skills.

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