The Impact of Big Data and IoT for Computational Smarter Education System

Jahangeer, Asma; Sajid, Ahthasham; Zafar, Afia

doi:10.1007/978-3-031-05752-6_17

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…These studies shed light on the potential benefits and challenges of the IoT in education and provide insights into the factors influencing its adoption. Smart education is one area that has been greatly impacted by the IoT [78,79]. IoT-enabled elearning systems have been developed to support higher education and enhance student engagement [80].…”

Section: Iot Adoption In Educationmentioning

confidence: 99%

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Ali,

Madni,

Jahangeer

et al. 2023

Sustainability

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The realm of the Internet of Things (IoT), while continually transforming as a novel paradigm in the nexus of technology and education, still contends with numerous obstacles that hinder its incorporation into higher education institutions’ (HEIs) e-learning platforms. Despite substantial strides in IoT utilization from industrialized nations—the United States, the United Kingdom, Japan, and China serving as prime exemplars—the scope of its implementation in developing countries, notably Saudi Arabia, Malaysia, Pakistan, and Bangladesh, lags behind. A significant gap exists in research centered on the trajectory of IoT integration within e-learning systems of economically disadvantaged nations. Specifically, this study centers on Saudi Arabia to illuminate the main factors catalyzing or encumbering IoT uptake within its HEIs’ e-learning sector. As a preliminary step, this research has embarked on an exhaustive dissection of prior studies to unearth critical variables implicated in the IoT adoption process. Subsequently, we employed an inferential methodology, amassing data from 384 respondents in Saudi Arabian HEIs. Our examination divulges that usability, accessibility, technical support, and individual proficiencies considerably contribute to the rate of IoT incorporation. Furthermore, our data infer that financial obstacles, self-efficacy, interactive capability, online surveillance, automated attendance tracking, training programs, network and data safeguarding measures, and relevant tools significantly influence IoT adoption. Contrarily, factors such as accessibility, internet quality, infrastructure preparedness, usability, privacy concerns, and faculty support appeared to have a negligible impact on the adoption rates within HEIs. This research culminates in offering concrete recommendations to bolster IoT integration within Saudi Arabian HEIs, presenting valuable insights for government entities, policy architects, and HEIs to address the hurdles associated with IoT implementation in the higher education sector.

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Section: Iot Adoption In Educationmentioning

confidence: 99%

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Ali,

Madni,

Jahangeer

et al. 2023

Sustainability

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“…A smart university is the evolution of a university, driven by technological advancements [20]. It provides education within an intelligent environment enhanced by smart technology [21], while also creating an enhanced academic environment for both teachers and students. The application and web-based tools offer a range of services, supported by a technological infrastructure to sustain and support operations.…”

Section: Smart Universitymentioning

confidence: 99%

Distributed Communicative Language Training Platform Using Automatic Speech Recognition Technology for Smart University

Phuengrod,

Wannapiroon,

Nilsook

2023

Int. J. Emerg. Technol. Learn.

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The purpose of this research is to achieve the following objectives: 1) Synthesize documents and international research on the characteristics of a smart university. 2) Synthesize the processes of distributed communicative language training (DCLT). 3) Design the system architecture of a DCLT platform that utilizes automatic speech recognition (ASR) technology for a smart university. 4) Evaluate the appropriateness of a DCLT platform that utilizes ASR technology for a smart university. Nine experts were selected for this research. They were required to have more than five years of relevant experience in the field, including expertise in system architecture, distributed enterprise, language teaching, and ASR. The research instruments included a suitable assessment form for evaluating the system architecture of a DCLT platform that utilizes ASR technology for a smart university. The results of this research indicate that the DCLT platform, which utilizes ASR technology, was considered suitable for a smart university.

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Research on innovation and development of university instructional administration informatization in IoT and big data environment

2023

Soft Comput

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The Impact of Big Data and IoT for Computational Smarter Education System

Cited by 5 publications

References 14 publications

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

IoT Adoption Model for E-Learning in Higher Education Institutes: A Case Study in Saudi Arabia

Distributed Communicative Language Training Platform Using Automatic Speech Recognition Technology for Smart University

Research on innovation and development of university instructional administration informatization in IoT and big data environment

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