Online transfer learning with multiple source domains for multi-class classification

Kang, Zhongfeng; Yang, Bo; Yang, Shantian; Fang, Xiaoyun; Chang, Zhao

doi:10.1016/j.knosys.2019.105149

Cited by 31 publications

(15 citation statements)

References 25 publications

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“…The term Integrates online learning define as an access to learning experience using certain technologies (Benson, 2002;Conrad, 2002;Saul Carliner.2004). In this regard, (Edwards and Robinson, 2019;Kang, Yang, Fang, and Zhao, 2020) urged that as Internet access is important. On the other hand, researchers did not mention accessibility when integrating online learning, but rather its flexibility, connectivity, and ability to interact (Ally, 2004;Hiltz & Turoff, 2005;Oblinger, Oblinger, & Lippincott, 2005).…”

Section: Overview Of Online Classesmentioning

confidence: 99%

Students’ and teachers’ attitude towards online classes during Covid-19 pandemic

Afroz¹,

Islam²,

Rahman³

et al. 2021

IJRBS

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In this paper, students, and teachers' attitudes towards shifting to an entirely online learning environment were assessed due to COVID-19. The main objective of the study was to investigate the students’ and teachers' attitudes towards Online learning during the COVID-19 situation in Bangladeshi Government Colleges. Findings revealed that cost and time-effectiveness, safety, convenience, and improved participation were the most frequently cited positive aspects of the online learning experience, while distraction and reduced focus, heavy workload, problems with technology and the internet, lack of ICT knowledge, and poor network infrastructure, limited availability of educational resources, low attendance of learners, uncooperative learners and insufficient support from instructors and colleagues were the most recurrent negative aspects. The qualitative and quantitative research method was adopted, with semi-structured interviews conducted via Zoom with 10 College teachers and Focus group discussion conducted via Zoom with 18 and survey 100 college students via Google platform from three Bangladesh renowned Government College from Hons 1st year to masters’ level located in Rajshahi divisional district town of the country. A sample of these essays was analyzed using open coding. The findings of the study help instructors and institutions understand students’ and Teachers' attitudes regarding online teaching & learning under abnormal circumstances. Several recommendations informed by the interpretation of the participants’ feedback are offered to assist instructors, administrators, and policymakers improve future online learning experiences. After conducting the whole study, it can be said that though have some problems adapting to online classes in three regarding BGCs colleges affiliated to the National University of Bangladesh, they are slowly becoming accustomed to it.

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Section: Overview Of Online Classesmentioning

confidence: 99%

Students’ and teachers’ attitude towards online classes during Covid-19 pandemic

Afroz¹,

Islam²,

Rahman³

et al. 2021

IJRBS

View full text Add to dashboard Cite

show abstract

“…However, this paper only concentrated on knowledge transfer from a single source domain. [105] then developed the online multi-source transfer learning for multi-class classification (OMTL-MC) system, which incorporated data from multiple domains. While the OMTL-MC structure is similar to that of the HetOTLMS framework described in [107], there are two significant differences:…”

Section: Single Source Multi-class Classification (Ss-mc) Otl and Mul...mentioning

confidence: 99%

Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning

Dai¹,

Meng²

2022

Preprint

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Online federated learning (OFL) and online transfer learning (OTL) are two collaborative paradigms for overcoming modern machine learning challenges such as data silos, streaming data, and data security. This survey explored OFL and OTL throughout their major evolutionary routes to enhance understanding of online federated and transfer learning. Besides, practical aspects of popular datasets and cutting-edge applications for online federated and transfer learning are highlighted in this work. Furthermore, this survey provides insight into potential future research areas and aims to serve as a resource for professionals developing online federated and transfer learning frameworks.

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“…Fischer et al (2020) gathered data from 23,610 students of a public sector university and found that students' grades point average were slightly higher in face-to-face courses as compared to online courses. Kang et al (2020) addressed the issue of online learning and revealed that every source domain has an effect on target domain task. In the context milieu of the COVID-19 epidemic, Wang et al (2020) advocated that the teaching system must be flexible and modifiable by way of research, practical, and discussion using information technology.…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing the Underlying Structure of Online Teaching During the COVID-19 Pandemic Period: An Empirical Investigation of Issues of Students

et al. 2021

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The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling (ISM) is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (MICMAC analysis) is used as a technique for classifying issues on the basis of driving–dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators’ guidelines, stress of pandemic situation, and abrupt (not planned) start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 (i.e., connectivity issue, shy to use technology, lack of institutional guidelines, and stress of pandemic situation) are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues.

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Online transfer learning with multiple source domains for multi-class classification

Cited by 31 publications

References 25 publications

Students’ and teachers’ attitude towards online classes during Covid-19 pandemic

Students’ and teachers’ attitude towards online classes during Covid-19 pandemic

Addressing modern and practical challenges in machine learning: A survey of online federated and transfer learning

Analyzing the Underlying Structure of Online Teaching During the COVID-19 Pandemic Period: An Empirical Investigation of Issues of Students

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