INOVASI PENGGUNAAN ARTIFICIAL INTELLIGENCE DALAM MENINGKATKAN MOTIVASI BELAJAR PADA PENYELESAIAN TUGAS AKHIR MAHASISWA

Ananta, Sany Ningtyas (2025) INOVASI PENGGUNAAN ARTIFICIAL INTELLIGENCE DALAM MENINGKATKAN MOTIVASI BELAJAR PADA PENYELESAIAN TUGAS AKHIR MAHASISWA. Diploma thesis, UIN RADEN INTAN LAMPUNG.

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Abstract

Innovation in the Use of Artificial Intelligence in Improving Learning Motivation in Student Final Project Completion: Inovasi Penggunaan Artificial Intelligence dalam Meningkatkan Motivasi Belajar Pada Penyelesaian Tugas Akhir Mahasiswa Ananta Sany Ningtyas Program Studi Manajemen Pendidikan Islam, Universitas Islam Negeri Raden Intan Lampung Yetri Yetri Program Studi Manajemen Pendidikan Islam, Universitas Islam Negeri Raden Intan Lampung Vandan Wiliyanti Program Studi Pendidikan Fisika, Universitas Islam Negeri Raden Intan Lampung General Background: The integration of Artificial Intelligence (AI) into education is transforming how students engage with academic tasks. Specific Background: With the growing accessibility of AI tools such as ChatGPT, Grammarly, and QuillBot, students increasingly utilize these platforms in academic writing, particularly when completing final assignments. Knowledge Gap: However, limited empirical evidence exists regarding the impact of AI usage on students’ learning motivation. Aims: This study investigates how the innovative use of AI contributes to enhancing students’ motivation in completing final assignments. 2 Method: Employing a quantitative descriptive-correlational design, data were collected from 507 students across eight study programs at the Faculty of Tarbiyah and Teacher Training, UIN Raden Intan Lampung, selected via purposive sampling. A five-point Likert scale questionnaire was used, with data analyzed using the Orange Data Mining application through box plot visualizations and ANOVA tests. Results: The findings indicate a positive correlation between the intensity of AI usage and students’ learning motivation. Novelty: This study provides one of the first quantitative insights into the motivational effects of AI tools in higher education settings. Implications: The results offer valuable input for educational institutions in designing AI-integrated learning strategies that foster student motivation and academic engagement. Highlights: Highlights a positive correlation between AI use and student motivation. Uses data-driven analysis with Orange Data Mining and ANOVA. Offers practical insights for AI-integrated learning strategies. Keywords: Artificial Intelligence, Learning Motivation, Final Assignment, Higher Education, Educational Technology

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