Investigating the impact of COVID-19 on Online Learning-based Web
Behavior
- URL: http://arxiv.org/abs/2205.01060v1
- Date: Wed, 27 Apr 2022 01:38:10 GMT
- Title: Investigating the impact of COVID-19 on Online Learning-based Web
Behavior
- Authors: Nirmalya Thakur, Saumick Pradhan, Chia Y. Han
- Abstract summary: 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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: COVID-19, a pandemic that the world has not seen in decades, has resulted in
presenting a multitude of unprecedented challenges for student learning across
the globe. The global surge in COVID-19 cases resulted in several schools,
colleges, and universities closing in 2020 in almost all parts of the world and
switching to online or remote learning, which has impacted student learning in
different ways. This has resulted in both educators and students spending more
time on the internet than ever before, which may be broadly summarized as both
these groups investigating, learning, and familiarizing themselves with
information, tools, applications, and frameworks to adapt to online learning.
This paper takes an explorative approach to further investigate and analyze the
impact of COVID-19 on such web behavior data related to online learning to
interpret the associated interests, challenges, and needs. 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, and
the findings have been published as an open-access dataset. Furthermore, to
interpret the trends in web behavior data related to online learning, the paper
discusses a case study in terms of the impact of COVID-19 on the education
system of one of these countries.
Related papers
- Human Behavior in the Time of COVID-19: Learning from Big Data [71.26355067309193]
Since March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million deaths.
The pandemic has impacted and even changed human behavior in almost every aspect.
Researchers have been employing big data techniques such as natural language processing, computer vision, audio signal processing, frequent pattern mining, and machine learning.
arXiv Detail & Related papers (2023-03-23T17:19:26Z) - DBE-KT22: A Knowledge Tracing Dataset Based on Online Student Evaluation [6.341812549259541]
We propose a new knowledge tracing dataset named Database Exercises for Knowledge Tracing (DBE-KT22)
It is collected from an online student exercise system in a course taught at the Australian National University in Australia.
arXiv Detail & Related papers (2022-08-19T00:10:11Z) - 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 Emergence of Online Learning in Different Countries
using the 5 W's and 1 H Approach [0.0]
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.
arXiv Detail & Related papers (2022-04-27T01:29:31Z) - Disadvantaged students increase their academic performance through
collective intelligence exposure in emergency remote learning due to COVID 19 [105.54048699217668]
During the COVID-19 crisis, educational institutions worldwide shifted from face-to-face instruction to emergency remote teaching (ERT) modalities.
We analyzed data on 7,528 undergraduate students and found that cooperative and consensus dynamics among students in discussion forums positively affect their final GPA.
Using natural language processing, we show that first-year students with low academic performance during high school are exposed to more content-intensive posts in discussion forums.
arXiv Detail & Related papers (2022-03-10T20:23:38Z) - Artificial Intelligence-Based Analytics for Impacts of COVID-19 and
Online Learning on College Students' Mental Health [0.0]
COVID-19, the disease caused by the novel coronavirus (SARS-CoV-2), first emerged in Wuhan, China late in December 2019.
The virus spread worldwide and was declared a pandemic by the World Health Organization in March 2020.
This paper seeks to understand how the COVID-19 pandemic and increase in online learning impact college students' emotional wellbeing.
arXiv Detail & Related papers (2022-02-07T05:24:52Z) - COVID-19 and Online Learning Tools [0.0]
COVID-19 has created a new era of distance education.
Due to the increasing demand, various distance learning solutions have been introduced for different distance education purposes.
We used Google Trend search queries as a proxy to quantify the popularity and public interest towards different distance education solutions.
arXiv Detail & Related papers (2021-12-28T12:03:26Z) - 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) - Peer-inspired Student Performance Prediction in Interactive Online
Question Pools with Graph Neural Network [56.62345811216183]
We propose a novel approach using Graph Neural Networks (GNNs) to achieve better student performance prediction in interactive online question pools.
Specifically, we model the relationship between students and questions using student interactions to construct the student-interaction-question network.
We evaluate the effectiveness of our approach on a real-world dataset consisting of 104,113 mouse trajectories generated in the problem-solving process of over 4000 students on 1631 questions.
arXiv Detail & Related papers (2020-08-04T14:55:32Z) - 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) - A Study of Knowledge Sharing related to Covid-19 Pandemic in Stack
Overflow [69.5231754305538]
Study of 464 Stack Overflow questions posted mainly in February and March 2020 and leveraging the power of text mining.
Findings reveal that indeed this global crisis sparked off an intense and increasing activity in Stack Overflow with most post topics reflecting a strong interest on the analysis of Covid-19 data.
arXiv Detail & Related papers (2020-04-18T08:19:46Z)
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.