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All Journal Technomedia Journal Startupreneur Business Digital (SABDA Journal) International Transactions on Education Technology (ITEE)
Godwin, Gelard
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Exploring the Effectiveness of E-Learning in Fostering Innovation and Creative Entrepreneurship in Higher Education Hardini, Marviola Grace; Khaizure, Tarisya; Godwin, Gelard
Startupreneur Business Digital (SABDA Journal) Vol. 3 No. 1 (2024): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v3i1.441

Abstract

This research aims to explore the effectiveness of implementing E-Learning in increasing innovation and creativepreneur skills of students in higher education. By focusing on the digital learning environment, this research wants to identify the impact of using E-Learning platforms on the development of students' creative and entrepreneurial ideas. The research method involves collecting quantitative data through online surveys and qualitative through in-depth interviews with students and lecturers. The data is then analyzed to measure the level of effectiveness of E-Learning in providing support for innovation and creativepreneurship skills. It is hoped that the results of this research will provide new insight into the potential of E-Learning in increasing students' creativity and entrepreneurial spirit in the digital era. It is hoped that the conclusions of this research can provide a basis for developing more effective online learning strategies in supporting innovation and entrepreneurship in higher education.
Pengaruh Technology Readiness Dan Satisfaction Terhadap Penerimaan Penggunaan Safe Entry Station: The Influence of Technology Readiness and Satisfaction on Acceptance of Use Safe Entry Station Godwin, Gelard; Any, Berlin; Delhi, Ariana; Sunarya, Po Abas; Nicola, Gabriela
Technomedia Journal Vol 8 No 3 Februari (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i3.2179

Abstract

The development of artificial intelligence technology has brought transformation in various sectors, including the world of health. The integration of AI in the healthcare sector has opened up new opportunities to improve diagnosis, treatment, medical data management and medical research. Safe Entry Station (SES-UR) is one of the newest technologies that has been introduced in the era of technological development that relies on the concept of artificial intelligence as the basis of its functionality, which has emerged as an innovative breakthrough in monitoring health effectively and accurately. However, new technology often involves concepts that may not yet familiar to most users. This can cause uncertainty and discomfort in using the technology. The aim of this research is to ensure that the implementation of SES-UR is successful and sustainable, so a comprehensive approach is needed in assessing the level of Technology Readiness and measuring the level of Satisfaction. The selected research focus is in the medical health sector to improve the quality of Artificial Intelligence-based health services. This research method, using the PLS-Structural Equation Modeling (SEM) method, was adopted to analyze the relationship between complex variables. To achieve accurate analysis results, this research involved the use of 25 instruments and 7 relevant constructs. The results of this research state that individuals who have a high level of Innovativeness tend to have the perception that the Safe Entry Station is easy to use, so they are more likely to accept and use this technology.
The Impact of AI on Personalized Learning and Educational Analytics Silva, Gabriel; Godwin, Gelard; Jayanagara, Oscar
International Transactions on Education Technology (ITEE) Vol. 3 No. 1 (2024): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v3i1.669

Abstract

The rapid advancement of artificial intelligence (AI) has revolutionized personalized learning and educational analytics, presenting new opportunities and challenges for adaptive education. This paper explores the impact of AI-driven technologies in creating personalized learning environments by examining how adaptive algorithms and data analytics shape educational experiences. The primary objective of this study is to assess the effectiveness of AI in enhancing learner engagement and outcomes through tailored instructional methods. Utilizing a mixed-method approach, this research gathers quantitative data from learning management systems to analyze engagement metrics, while qualitative insights are derived from interviews with educators and students. The findings indicate that AI-driven personalized learning significantly improves both student motivation and academic performance by adapting content to individual learning needs. Moreover, educational analytics enabled by AI offer educators critical insights into student progress, enabling proactive intervention and support. However, the study also highlights concerns regarding data privacy and the potential over-reliance on AI technologies in educational settings. These findings suggest that while AI holds transformative potential, a balanced approach is necessary to integrate technology with traditional teaching methods to ensure optimal educational outcomes. The study concludes that AI can serve as a powerful tool in enhancing personalized learning and educational analytics, provided that ethical considerations and data security are prioritized.
Co-Authors Any, Berlin Delhi, Ariana Hardini, Marviola Grace Jayanagara, Oscar Khaizure, Tarisya Nicola, Gabriela Po Abas Sunarya Silva, Gabriel