Research on the effectiveness of information technology in reducing the Rural–Urban Knowledge Divide

Chen, Ruey-Shin; Liu, I-Fan

doi:10.1016/j.compedu.2013.01.002

Cited by 38 publications

(27 citation statements)

References 30 publications

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“…However, attention to intergroup differences that are finer grained than national boundaries is also important (see Paez & Vergara, ) because there could be substantial intra‐national differences between regions or even between groups within a region. Gender, race and socio‐economic status (SES) are commonly investigated in sociological research, but categories like urbanicity may be particularly relevant to educational software usage patterns because previous research has shown that rural students may have less access to technology (Chen & Liu, ; Wilson, Wallin & Reiser, ). These and other differences may contribute to widening gaps in mathematics achievement in the USA that have also been shown to correlate with urbanicity (Graham & Provost, ; Wenglinsky, ).…”

Section: Introductionmentioning

confidence: 99%

Population validity for educational data mining models: A case study in affect detection

Ocumpaugh¹,

Baker²,

Gowda³

et al. 2014

Brit J Educational Tech

125

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Information and communication technology (ICT)‐enhanced research methods such as educational data mining (EDM) have allowed researchers to effectively model a broad range of constructs pertaining to the student, moving from traditional assessments of knowledge to assessment of engagement, meta‐cognition, strategy and affect. The automated detection of these constructs allows EDM researchers to develop intervention strategies that can be implemented either by the software or the teacher. It also allows for secondary analyses of the construct, where the detectors are applied to a data set that is much larger than one that could be analyzed by more traditional methods. However, in many cases, the data used to develop EDM models are collected from students who may not be representative of the broader populations who are likely to use ICT. In order to use EDM models (automated detectors) with new populations, their generalizability must be verified. In this study, we examine whether detectors of affect remain valid when applied to new populations. Models of four educationally relevant affective states were constructed based on data from urban, suburban and rural students using ASSISTments software for middle school mathematics in the Northeastern United States. We found that affect detectors trained on a population drawn primarily from one demographic grouping do not generalize to populations drawn primarily from the other demographic groupings, even though those populations might be considered part of the same national or regional culture. Models constructed using data from all three subpopulations are more applicable to students in those populations than those trained on a single group, but still do not achieve ideal population validity—the ability to generalize across all subgroups. In particular, models generalize better across urban and suburban students than rural students. These findings have important implications for data collection efforts, validation techniques, and the design of interventions that are intended to be applied at scale.

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Section: Introductionmentioning

confidence: 99%

Population validity for educational data mining models: A case study in affect detection

Ocumpaugh¹,

Baker²,

Gowda³

et al. 2014

Brit J Educational Tech

125

View full text Add to dashboard Cite

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“…Knowledge divides often exist among people from different socioeconomic backgrounds (Chen & Liu, 2013) and are largely due to the gap between urban and rural districts and the imbalanced allocation of educational resources (e.g., Karlsson, 2002; Li & Ranieri, 2013). CCLR, as one form of technological innovations, may serve as a social equalizer by increasing the chance for students to access quality learning and teaching resources, thereby bridging the knowledge gap among students from different socioeconomic backgrounds.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Bridging Knowledge Divides Utilizing Cloud Computing Learning Resources in Underfunded Schools: Investigating the Determinants

Wang

Wong

2018

Journal of Educational Computing Research

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This study investigated the factors that led to students adopting cloud computing learning resources (CCLR) in underfunded, rural high schools with the aim of informing future work related to effective implementation of CCLR for underprivileged students. Guided by the CCLR adoption model, survey data of 310 students from two high schools in rural districts in China were obtained and were analyzed utilizing partial least square structural equation modeling. The findings indicated that students’ use of CCLR was a function of the perceived ease of use of CCLR, external facilitating conditions from schools, and students’ voluntariness. The perceived usefulness of CCLR did not predict students’ use behavior. Regarding gender differences, voluntariness affected female students more significantly than males, and anxiety in using CCLR affected female students more negatively than males. This study should interest educational practitioners and policy makers seeking to promote equity in education, particularly in rural districts by effectively implementing new learning technologies.

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“…Enterprises, government, and other organizations play important roles in bridging digital divide and achieve social inclusion via ICTs, such as information infrastructure establishment, finance assistant, related supportive policy formulation, technology product design and training [3,20]. Their ICT-enabled development approaches benefit a lot from their profession, abundant resource, and practical capability.…”

Section: Introductionmentioning

confidence: 99%

From Digital Divide to Social Inclusion: A Tale of Mobile Platform Empowerment in Rural Areas

Yang

2020

Sustainability

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The digital divide in rural areas is an important social issue, especially in developing countries. Although Internet and broadband penetration have increased in the world generally, there are many obstacles for rural China to get access to ICT (Information and Communication Technology) and its services. The mobile platform is regarded as a novel and effective tool to reduce the digital divide. Based on a case of one mobile platform, namely WeCountry in Chinese rural areas, this study illustrates how a mobile platform bridges the digital divide and helps rural areas achieve social inclusion. Results show that: (1) the mobile platform mainly acts on the digital capability divide elimination, and it has to guide and increase users’ usage capability; (2) the mobile platform can empower villagers in structural, psychological, and resource dimensions, achieving political inclusion, social participation inclusion, and economic inclusion; (3) platform providers and government are key organizations during the divide elimination process. This paper concludes with theoretical and practical implications.

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Research on the effectiveness of information technology in reducing the Rural–Urban Knowledge Divide

Cited by 38 publications

References 30 publications

Population validity for educational data mining models: A case study in affect detection

Population validity for educational data mining models: A case study in affect detection

Bridging Knowledge Divides Utilizing Cloud Computing Learning Resources in Underfunded Schools: Investigating the Determinants

From Digital Divide to Social Inclusion: A Tale of Mobile Platform Empowerment in Rural Areas

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