Design on Big data Platform-based in Higher Education Institute

Pratsri, Sajeewan; Nilsook, Prachyanun

doi:10.5539/hes.v10n4p36

Cited by 18 publications

(8 citation statements)

References 16 publications

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“…The tools focus on learners and teachers, and software that were designed to provide comprehensive help in the educational process. Likewise, this tool can improve the learning experience of learners as well as makes the learning environment become a digital learning environment with limitless freedom (Artuso & Graf, 2020;Bujang et al, 2020;Pratsri & Nilsook, 2020;Faustmann et al, 2019;Iliashenko et al, 2019;Yanga & Yenb, 2016).…”

Section: Digital Learning Platformmentioning

confidence: 99%

Framework of Artificial Intelligence Learning Platform for Education

Thongprasit¹,

Wannapiroon²

2022

IES

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Nowadays, Information Technology is an integrated as a part of our life activities. It does not affect only teaching and learning methods at all levels, but also the teaching styles of each teacher with suitable for the digital age. Therefore, the standardized platform should create for all teachers to effectively serve the future education policy. This research aims to synthesize and develop a framework of an artificial intelligence learning platform for education and estimate the framework’s suitability. The research is discussed into three phases: 1) synthesizing an intelligent learning platform by using Artificial Intelligence (AI), 2) developing a framework of an artificial intelligence learning platform for education, and 3) evaluating the suitability of the framework by 15 experts. The result found that the suitability evaluation of the framework of an artificial intelligence learning platform for education was very good. The results showed that this framework could develop a learning platform for preparing transformation to the digital age.

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Section: Digital Learning Platformmentioning

confidence: 99%

Framework of Artificial Intelligence Learning Platform for Education

Thongprasit¹,

Wannapiroon²

2022

IES

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“…The data can be structured data (from an IoT source) or unstructured data (from social media) generated in real time at a large scale. Big data are often used to provide insight for analytic studies or to generate prediction models (Pratsri & Nilsook, 2020). The use of big data analytics can help reveal patterns of human behavior (Favaretto et al, 2020) and data trends for prediction purposes.…”

Section: Introductionmentioning

confidence: 99%

Internet of Things and Big Data for a Sustainable Smart University

2023

JHETP

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This study aims to analyze existing research regarding sustainable smart universities via internet of things and big data. Document analysis was conducted using 1,737 research documents relevant to the domain of smart university, smart campus, sustainable university, internet of things, and big data from international databases including Scopus, IEEE, Web of Science and ERIC. The matrix analysis method was used to identify the relevant publications produced 158 items and six cluster themes and proposed conceptual frameworks illustrating elements necessary for a sustainable smart university via internet of things and big data. The illustrated networks demonstrated that a smart campus involves a technology of internet of things and big data. The targets for a smart campus/smart university includes resource management, security management and the provision of a digital service to students and staff. By linking a smart campus with sustainability, the network models show that some research focus on applying smart technologies to improve the sustainability of a campus by concentrating on natural resource management and environmental care.

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“…The learning environment positively affects the performance of learners by facilitating the learning process and increasing learner satisfaction. It focuses on how to determine the characteristics of learners in terms of adapting to the learning environment target (Pratsri and Nilsook, 2020). Therefore, they meet the needs of the learner through interaction.…”

Section: Introductionmentioning

confidence: 99%

Interactive Tool in Digital Learning Ecosystem for Adaptive Online Learning Performance

Meepung¹,

Pratsri²,

Nilsook³

2021

HES

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The objective of this research was as follows: 1) to develop an interactive tool in a digital learning ecosystem for adaptive online learning performance; 2) to carry out a suitability assessment of this process. The documentary research method was used in this study. The results showed a model of an interactive tool in a digital learning ecosystem for adaptive online learning performance consisted of two phases. Phase 1: The development of an interactive tool in a digital learning ecosystem for adaptive online learning performance. This includes the following four design steps: 1) Reviewed literature and previous studies regarding an interactive tool, a digital learning ecosystem, and adaptive online learning performance to study the model, characteristics, and previous research. 2) Studied relevant research of an interactive tool in a digital learning ecosystem for adaptive online learning performance. 3) Designed an adaptive online learning performance model using an interactive tool in a digital learning ecosystem. 4) Developed a digital learning ecosystem. Phase 2: Evaluated the appropriateness of the interactive tool for an adaptive online learning performance model; this was checked for suitability by twelve experts and resulted in a conclusion. The results of the suitability evaluation revealed that the interactive tool for adaptive online learning performance was at the highest level.

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Design on Big data Platform-based in Higher Education Institute

Cited by 18 publications

References 16 publications

Framework of Artificial Intelligence Learning Platform for Education

Framework of Artificial Intelligence Learning Platform for Education

Internet of Things and Big Data for a Sustainable Smart University

Interactive Tool in Digital Learning Ecosystem for Adaptive Online Learning Performance

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