Pengembangan Desain Solusi Dasbor Learning Analytics sebagai Input pada Model Personalized Learning
DOI:
https://doi.org/10.57096/edunity.v1i04.23Keywords:
Dasbor, gaya belajar, Learning AnalyticsAbstract
Gaya belajar berperan penting dalam sistem pembelajaran adaptif. dengan memahami gaya belajar yang beragam, sistem ini dapat memberikan rekomendasi atas gaya belajar peserta didik. Tujuan dari penelitian ini adalah menganalisa pengembangan desain solusi dasbor learning sebagai input pada model personalized learning. Metode yang digunakan dalam penelitian ini adalah Human-centered Design (HCD) dengan mengintegrasikan kebutuhan-kebutuhan pengembangan lingkungan belajar yang adaptif terhadap gaya belajar peserta didik. Rancangan dasbor Learning Analytics (Learning Analytics Dashboard – LAD) menghasilkan kebutuhan-kebutuhan fungsional sebuah sebagai dasar pengumpulan data yang digunakan untuk input personalisasi pembelajaran (Personalized Learning) sesuai gaya belajar mahasiswa. Kebutuhan-kebutuhan tersebut meliputi Fungsi Login, Akses daftar materi, Membuka detail materi, Evaluasi materi, Rangkuman aktivitas dan Logout. Untuk menunjang kebutuhan-kebutuhan yang mendukung pengguna sistem mencapai tujuannya, dihasilkan kebutuhan-kebutuhan non-fungsional yang meliputi penentuan platform sistem berbasis web, tampilan yang responsif, tata-letak dan kerangka desain rapi dan konsisten, pemilihan fontasi yang lugas dan tidak bermotif dengan ukuran proporsional, serta pemilihan warna yang netral dan lembut
References
Anhusadar, L. (2020). Persepsi mahasiswa PIAUD terhadap kuliah online di masa pandemi Covid 19. KINDERGARTEN: Journal of Islamic Early Childhood Education, 3(1), 44–58.
Baradwaj, B. K., & Pal, S. (2011). Mining Student Data to Analyze Students’ Performance. International Journal of Advanced Computer Science and Applications, 2(6).
Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5–6), 318–331.
Drissi, S., & Amirat, A. (2016). An adaptive E-learning system based on student’s learning styles: An empirical study. International Journal of Distance Education Technologies (IJDET), 14(3), 34–51.
Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317.
Haviz, M. (2020). Hubungan gaya belajar dengan hasil belajar siswa pada pembelajaran biologi kelas X SMAN 2 Sungai Tarab Kabupaten Tanah Datar.
Kirby, L., Tolle, H., & Brata, A. H. (2019). Perancangan User Experience Aplikasi Mobile Social Crowdsourcing Bencana Alam menggunakan Pendekatan Human-Centered Design (HCD). J. Pengemb. Teknol. Inf. Dan Ilmu Komput. e-ISSN, 2548(5), 964X.
Kristyanto, H. D. (2011). Perancangan dan Pembuatan Sistem Pendukung Keputusan Program Pengembangan Sumber Daya Manusia di Universitas xxx.
Kurilovas, E., Kubilinskiene, S., & Dagiene, V. (2014). Web 3.0–Based personalisation of learning objects in virtual learning environments. Computers in Human Behavior, 30, 654–662.
Maguire, M. (2001). Methods to support human-centred design. International Journal of Human-Computer Studies, 55(4), 587–634.
Nia, R. O. (2018). KOMPARASI PERANGKAT HIGH-FIDELITY PROTOTYPING UNTUK APLIKASI BERGERAK AUGMENTED REALITY.
Papamitsiou, Z., & Economides, A. A. (2014). Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Journal of Educational Technology & Society, 17(4), 49–64.
Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400.
Simanihuruk, L., Simarmata, J., Sudirman, A., Hasibuan, M. S., Safitri, M., Sulaiman, O. K., Ramadhani, R., & Sahir, S. H. (2019). E-learning: Implementasi, strategi dan inovasinya. Yayasan Kita Menulis.
Surjono, H. D. (2011). The design of adaptive e-learning system based on student’s learning styles. International Journal of Computer Science and Information Technologies, 2(5), 2350–2353.
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