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All Journal International Journal of Education Educenter: Jurnal Ilmiah Pendidikan EDUCENTER JURNAL PENDIDIKAN
Kumalasari, Tety
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Arts Humanities Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences

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BASIC PSYCHOLOGICAL NEEDS, MOTIVATION, AND FOREIGN LANGUAGE VOCABULARY LEARNING STRATEGIES AND SKILLS OF INDONESIAN UNIVERSITY STUDENTS Susanto, Alpino; Oktavia, Yunisa; Kumalasari, Tety; Silitonga, Frangky
International Journal of Education Vol 17, No 1 (2024): February 2024
Publisher : Kantor Jurnal dan Publikasi Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ije.v17i1.60103

Abstract

Foreign language vocabulary learning can be pursued if the students have motivation and interest in which psychological factors play an important role in enacting learning strategies toward increased skills. This study aims to examine the integrated process model of the BasicPsychological Needs (BPN) variable as a behavioural phenomena in relation to autonomous and controlled motivation individually or collectively toward Vocabulary Learning Strategies (VLSs) and Vocabulary Skills (VSs). A total of 186 students of one university participated in this research. The Basic Psychological Needs of Second Language Scale (BPNSLS) was employed to assess the BPN, meanwhile the Self-Determination Theory of Second Language Scale (SDTSLS) was to assess the autonomous and controlled motivation. There are three questionnaires (BPNSLS, SDTSLS, VLSs) were adopted and adapted of the previous study. The fourth research instrument was Vocabulary Level Test (VLT) version b to assess vocabulary skills. A partial least square was used to contest the research model. The structural model of the relationship between the variables of basic psychological needs, self-determination theory, vocabulary learning strategies, and vocabulary mastery, revealed that vocabulary learning strategies play a crucial role in looking at the influence of motivational orientation on vocabulary skills described in the proposed model. This study suggests that further research can explore more on how motivation relates to learning strategies in general and comparing between autonomous versus controlled motivation.
Development of an artificial intelligence based fine arts learning management system using the borg & gall model to enhance learning effectiveness Hendra, Hendra; Zaitun , Zaitun; Irawan, Dody; Malik, Abdul; Kumalasari, Tety
Educenter : Jurnal Ilmiah Pendidikan Vol. 4 No. 1 (2025): Educenter: Jurnal Ilmiah Pendidikan
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v4i1.1934

Abstract

This study aims to develop an artificial intelligence (AI)-based Learning Management System (LMS) specifically designed for two-dimensional art learning. This system integrates three main AI-based features, namely learning analytics (TrackBoot), intelligent tutoring chatbot (ArtBoot), and adaptive recommendation engine. The research used the Research and Development (R&D) method with the Borg & Gall model, which includes the stages of needs analysis, planning, development, expert validation, limited and main field trials, and final product revision. Data were collected through pre-tests and post-tests, validation sheets, practicality questionnaires, and LMS activity logs. The results showed a significant increase in student learning outcomes with an average N-Gain score of 0.78 (high category). The validity of the material and media increased from the “Less Valid” category to “Very Valid,” while the practicality level reached a score of 4.49 (very practical category). Regression analysis showed that interaction with ArtBoot had a significant effect on student learning outcomes (p < 0.001). These findings prove that AI integration through learning analytics, adaptive feedback, and personalized learning is effective in increasing student motivation, conceptual understanding, and learning independence. This research contributes to the development of adaptive, contextual AI-based digital learning innovations that are in line with the spirit of the Merdeka Curriculum.
Development of an artificial intelligence based fine arts learning management system using the borg & gall model to enhance learning effectiveness Hendra, Hendra; Zaitun , Zaitun; Irawan, Dody; Malik, Abdul; Kumalasari, Tety
Educenter : Jurnal Ilmiah Pendidikan Vol. 4 No. 1 (2025): Educenter: Jurnal Ilmiah Pendidikan
Publisher : ARKA INSTITUTE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55904/educenter.v4i1.1934

Abstract

This study aims to develop an artificial intelligence (AI)-based Learning Management System (LMS) specifically designed for two-dimensional art learning. This system integrates three main AI-based features, namely learning analytics (TrackBoot), intelligent tutoring chatbot (ArtBoot), and adaptive recommendation engine. The research used the Research and Development (R&D) method with the Borg & Gall model, which includes the stages of needs analysis, planning, development, expert validation, limited and main field trials, and final product revision. Data were collected through pre-tests and post-tests, validation sheets, practicality questionnaires, and LMS activity logs. The results showed a significant increase in student learning outcomes with an average N-Gain score of 0.78 (high category). The validity of the material and media increased from the “Less Valid” category to “Very Valid,” while the practicality level reached a score of 4.49 (very practical category). Regression analysis showed that interaction with ArtBoot had a significant effect on student learning outcomes (p < 0.001). These findings prove that AI integration through learning analytics, adaptive feedback, and personalized learning is effective in increasing student motivation, conceptual understanding, and learning independence. This research contributes to the development of adaptive, contextual AI-based digital learning innovations that are in line with the spirit of the Merdeka Curriculum.
Co-Authors Abdul Malik Alpino Susanto, Alpino Frangky Silitonga Hendra Hendra Oktavia, Yunisa Zaitun , Zaitun