| Kode Mata Kuliah | MG5102 / 2 SKS |
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| Penyelenggara | 225 - Metallurgical Engineering / FTTM |
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| Kategori | Lecture |
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| Bahasa Indonesia | English |
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| Nama Mata Kuliah | Literasi Digital dan Etika Akademik | Digital Literacy and Academic Ethics |
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| Bahan Kajian | - Konsep digital, model dan strategi komunikasi, penelusuran, dan kolaborasi digital secara efektif dan positif
- Pemanfaatan digital tools
- Prinsip-prinsip literasi data, artificial intelligence, machine learning, dan deep learning
- Integritas dan etika akademik
- Integritas dan etika dalam riset, proyek, dan publikasi ilmiah
| - Digital concepts, communication models and strategies, digital searching, and effective and positive digital collaboration
- Utilization of digital tools
- Principles of data literacy, artificial intelligence, machine learning, and deep learning
- Academic integrity and ethics
- Integrity and ethics in research, projects, and scientific publications
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| Capaian Pembelajaran Mata Kuliah (CPMK) | - Mampu memahami konsep digital, model dan strategi untuk berkomunikasi, berkolaborasi, melakukan penelusuran, mengkonsumsi, membuat, dan mendistribusikan informasi dalam dunia digital secara efektif dan positif serta kemampuan memanfaatkan digital tools secara efektif dan positif.
- Mampu memanfaatkan digital tools secara efektif dan positif
- Mampu memahami prinsip-prinsip literasi data, artificial intelligence, machine learning dan deep learning
- Mampu menghayati, menghormati dan menegakkan integritas dan etika akademik.
- Mampu menghayati, menghormati dan menegakkan integritas dan etika dalam melakukan riset, proyek, dan publikasi ilmiah.
| - Able to understand digital concepts, models and strategies to communicate, collaborate, search, consume, create, and distribute information in the digital world effectively and positively and the ability to utilize digital tools effectively and positively.
- Able to utilize digital tools effectively and positively
- Able to understand the principles of data literacy, artificial intelligence, machine learning and deep learning
- Able to live, respect and uphold academic integrity and ethics.
- Able to live, respect and uphold integrity and ethics in conducting research, projects and scientific publications.
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| Metode Pembelajaran | Pembelajaran asinkron, kerja kelompok, kerja mandiri | Asynchronized Learning, Group Work, Independent Work |
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| Modalitas Pembelajaran | Video pembelajaran, studi kasus, topik-topik khusus kajian. | Lecture Video, Case Study, Specialty Topics Study |
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| Jenis Nilai | Pass/Fail |
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| Metode Penilaian | Ujian tertulis, karya tulis, presentasi. Penilaian secara pass and fail (P or F) | Written Exam, Literary Work, Presentation, Pass and Fail Grading |
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| Catatan Tambahan | | |
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