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Journal : International Transactions on Education Technology (ITEE)

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Utilization Of Big Data in Educational Technology Research Ninda Lutfiani; Lista Meria
International Transactions on Education Technology (ITEE) Vol. 1 No. 1 (2022): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v1i1.198

Abstract

This research aims to exploit the role and contribution of big data in normal-age learning paradigms that require online learning that was initially conducted face-to-face. Educational technology research includes research areas that require changes in learning strategies. This includes the use of technology currently occurring during the COVID-19 virus pandemic to transform face-to-face learning online. Use big data to develop learning strategies (procedures) to solve problems/facilitate learning. The use of big data can contribute to the study of education in general and educational technology in particular. Methodologies used include the analysis and potential implementation of big data in the field of educational technology research by conducting literature survey analyses. The data obtained and used are in the form of local and international journals related to the implementation of big data in the world of educational technology research. The development of technology research applications based on big data makes it easier for researchers to see the possibilities and problems of individual students. Based on this data, researchers can monitor and evaluate students, teachers, materials, and learners. The data can be used to prepare future research efforts.
Business Modeling Innovation Using Artificial Intelligence Technology Riya Widayanti; Lista Meria
International Transactions on Education Technology (ITEE) Vol. 1 No. 2 (2023): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v1i2.270

Abstract

Startups embracing artificial intelligence (AI) as a component of their business models are quickly emerging right now. The application of AI technology in business has been going on for a while, even though recent research reveals that new or alternative business models are being implemented.It might be claimed that AI technology has been used to business models for a very long time, which puts into question the uniqueness of these business models. In order to better understand how AI companies' business models may differ from traditional IT business models, this study compares them to each other. The first step is to create a taxonomy of business models for AI businesses using a sample of 162 Worldwide Stratup, from which four archetypal business models are derived: Deep technology researcher, data analytics supplier, AI product and service provider, and facilitator of AI development The following are three main elements of startup business models for AI firms that are discussed based on this descriptive analysis: (1) new value propositions made possible by AI, (2) Various uses of data to create value and (3) How AI technology affects general business reasoning. By defining their key purposes, common instantiations, and distinguishing features, this research adds to our fundamental understanding of the AI start-up business model. This study suggests intriguing directions for further investigation in the field of entrepreneurship. À It is structured to foster entrepreneurial activity. Taxonomies and models are actually instrument.
Co-Authors Antonius Ardi Fadilah Aropria Saulina Panjaitan Budi Tjahjono Isabella Maria Kundang Karsono Nastavia Putri Ninda Lutfiani Nizirwan Anwar Riya Widayanti Saukani Saukani Suryani Purnama Tatik Mariyanti, Tatik