Investigating the Emergence of Online Learning in Different Countries
using the 5 W's and 1 H Approach
- URL: http://arxiv.org/abs/2204.12650v1
- Date: Wed, 27 Apr 2022 01:29:31 GMT
- Title: Investigating the Emergence of Online Learning in Different Countries
using the 5 W's and 1 H Approach
- Authors: Nirmalya Thakur, Isabella Hall, and Chia Y. Han
- Abstract summary: E-learning 3.0 is expected to become the norm of learning globally in almost all sectors in the next few years.
The work specifically involved investigating relevant web behavior data to interpret the 5 W's and 1 H - Who, What, When Where, Why, and How related to online learning.
The results presented and discussed help to interpret the emergence of online learning in each of these countries in terms of the associated public perceptions, queries, opinions, behaviors, and perspectives.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The rise of the Internet of Everything lifestyle in the last decade has had a
significant impact on the increased emergence and adoption of online learning
in almost all countries across the world. E-learning 3.0 is expected to become
the norm of learning globally in almost all sectors in the next few years. The
pervasiveness of the Semantic Web powered by the Internet of Everything
lifestyle is expected to play a huge role towards seamless and faster adoption
of the emerging paradigms of E-learning 3.0. Therefore, this paper presents an
exploratory study to analyze multimodal components of Semantic Web behavior
data to investigate the emergence of online learning in different countries
across the world. The work specifically involved investigating relevant web
behavior data to interpret the 5 W's and 1 H - Who, What, When Where, Why, and
How related to online learning. Based on studying the E-learning Index of 2021,
the study was performed for all the countries that are member states of the
Organization for Economic Cooperation and Development. The results presented
and discussed help to interpret the emergence of online learning in each of
these countries in terms of the associated public perceptions, queries,
opinions, behaviors, and perspectives. Furthermore, to support research and
development in this field, we have published the web behavior-based Big Data
related to online learning that was mined for all these 38 countries, in the
form of a dataset, which is avail-able at
https://dx.doi.org/10.21227/xbvs-0198.
Related papers
- From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents [78.15899922698631]
MAIC (Massive AI-empowered Course) is a new form of online education that leverages LLM-driven multi-agent systems to construct an AI-augmented classroom.
We conduct preliminary experiments at Tsinghua University, one of China's leading universities.
arXiv Detail & Related papers (2024-09-05T13:22:51Z) - A Retrospective of the Tutorial on Opportunities and Challenges of Online Deep Learning [10.886568704759657]
We provide a retrospective of our tutorial titled Opportunities and Challenges of Online Deep Learning held at ECML PKDD 2023.
We provide a brief overview of the opportunities but also the potential pitfalls for the application of neural networks in online learning environments.
arXiv Detail & Related papers (2024-05-27T14:40:03Z) - Social Intelligence Data Infrastructure: Structuring the Present and Navigating the Future [59.78608958395464]
We build a Social AI Data Infrastructure, which consists of a comprehensive social AI taxonomy and a data library of 480 NLP datasets.
Our infrastructure allows us to analyze existing dataset efforts, and also evaluate language models' performance in different social intelligence aspects.
We show there is a need for multifaceted datasets, increased diversity in language and culture, more long-tailed social situations, and more interactive data in future social intelligence data efforts.
arXiv Detail & Related papers (2024-02-28T00:22:42Z) - Artificial Intelligence for Web 3.0: A Comprehensive Survey [76.06151253928171]
We explore the current development state of Web 3.0 and the application of AI Technology in Web 3.0.
Our investigation delves into the major challenges and issues present in each of these layers.
We illustrate the crucial role of AI in the foundation and growth of Web 3.0.
arXiv Detail & Related papers (2023-08-17T12:36:01Z) - Web 3.0: The Future of Internet [53.234101208024335]
Web 3.0 is a decentralized Web architecture that is more intelligent and safer than before.
Web 3.0 is capable of addressing web data ownership according to distributed technology.
It will optimize the internet world from the perspectives of economy, culture, and technology.
arXiv Detail & Related papers (2023-03-23T15:37:42Z) - A Large-Scale Dataset of Twitter Chatter about Online Learning during
the Current COVID-19 Omicron Wave [0.0]
The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally.
Social media platforms such as Twitter are seeing an increase in conversations related to online learning in the form of tweets.
This work presents a large-scale open-access Twitter dataset of conversations about online learning from different parts of the world since the first detected case of the COVID-19 Omicron variant in November 2021.
arXiv Detail & Related papers (2022-07-20T18:01:18Z) - Investigating the impact of COVID-19 on Online Learning-based Web
Behavior [0.0]
The study specifically focused on investigating Google Search-based web behavior data as Google is the most popular search engine globally.
The impact of COVID-19 related to online learning-based web behavior on Google was studied for the top 20 worst affected countries in terms of the total number of COVID-19 cases.
arXiv Detail & Related papers (2022-04-27T01:38:10Z) - A New Era: Intelligent Tutoring Systems Will Transform Online Learning
for Millions [41.647427931578335]
AI-powered learning can provide millions of learners with a highly personalized, active and practical learning experience.
We present the results of a comparative head-to-head study on learning outcomes for two popular online learning platforms.
arXiv Detail & Related papers (2022-03-03T18:55:33Z) - Web-Based Learning [0.0]
Information Technology (IT) has had a number of positive impacts in various fields.
IT has become the backbone of the modern learning process.
Web-based learning is often also called online learning or e-learning.
arXiv Detail & Related papers (2021-07-26T12:33:08Z) - Comparative Study of Learning Outcomes for Online Learning Platforms [47.5164159412965]
Personalization and active learning are key aspects to successful learning.
We run a comparative head-to-head study of learning outcomes for two popular online learning platforms.
arXiv Detail & Related papers (2021-04-15T20:40:24Z) - SARS-CoV-2 Impact on Online Teaching Methodologies and the Ed-Tech
Sector: Smile and Learn Platform Case Study [50.591267188664666]
The study analyzes the importance of online methodologies and usage tendency of an educational resource example: The Smile and Learn platform.
Thereby, the study presents the different models implemented to support education and its impact in the use of the platform.
arXiv Detail & Related papers (2020-07-15T10:06:51Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.