HELEN ANJELICA SIANIPAR, . (2025) MODEL PEMBELAJARAN DENGAN PENDEKATAN PERSONALISASI GAYA BELAJAR FELDER SILVERMEN PADA BAHAN AJAR MATA KULIAH INTERNET OF THINGS PROGRAM STUDI TEKNIK INFORMATIKA UNIVERSITAS KRISTEN MARANATHA. Magister thesis, UNIVERSITAS NEGERI JAKARTA.
![[img]](http://repository.unj.ac.id/style/images/fileicons/text.png) |
Text
cover_1110822016.pdf Download (610kB) |
|
Text
bab1_1110822016.pdf Download (793kB) |
|
Text
bab2_1110822016.pdf Restricted to Registered users only Download (822kB) | Request a copy |
|
Text
BAB 3_1110822016.pdf Download (1MB) |
|
Text
bab4_1110822016.pdf Restricted to Registered users only Download (4MB) | Request a copy |
|
Text
bab5_1110822016.pdf Restricted to Registered users only Download (181kB) | Request a copy |
|
Text
daftarpustaka_1110822016.pdf Download (225kB) |
|
Text
lampiran_1110822016.pdf Restricted to Registered users only Download (928kB) | Request a copy |
Abstract
ABSTRAK Penelitian ini mengembangkan dan mengevaluasi model pembelajaran personalisasi untuk bahan ajar mata kuliah Internet of Things (IoT) pada Learning Management System (LMS) dengan mengintegrasikan Felder-Silverman Learning Style Model (FSLSM) dalam kerangka model pengembangan ASSURE. Model ini mengindikasikan perlunya pendekatan instruksional yang adaptif mengikuti tahapan ASSURE, dimulai dengan analisis karakteristik mahasiswa menggunakan Index of Learning Styles (ILS). Integrasi dengan LMS menggunakan fitur Restrict Access dan Activity Completion untuk menyesuaikan jalur pembelajaran dengan profil dan preferensi gaya belajar individu. Evaluasi menunjukkan model pembelajaran personalisasi dengan FSLSM memiliki validitas tinggi dan efektif. Penilaian kelayakan produk oleh ahli mengindikasikan kelayakan untuk pembelajaran digital yang berhasil, efektivitas pembelajaran menunjukkan peningkatan hasil belajar kognitif yang tinggi, evaluasi penggunaan produk mengonfirmasi produk sangat mudah digunakan oleh mahasiswa. Kesimpulannya, model pembelajaran personalisasi FSLSM terbukti mampu meningkatkan pemahaman konseptual mahasiswa berdasarkan preferensi gaya belajar mahasiswa pada bahan ajar Mata Kuliah IoT serta mampu menignkatkan kualitas pendidikan di era digital untuk pengembangan produk pembelajaran yang lebih adaptif. ***** This study develops and evaluates a personalized learning model for the course materials of Internet of Things (IoT) within a Learning Management System (LMS), integrating the Felder-Silverman Learning Style Model (FSLSM) into the ASSURE model development framework. This model highlights the need for an adaptive instructional approach following the ASSURE stages, beginning with an analysis of student characteristics using the Index of Learning Styles (ILS). Integration with the LMS utilizes features such as Restrict Access and Activity Completion to tailor the learning path to the profiles and learning style preferences of students. The results indicate that the personalized learning model with FSLSM has high validity and effectiveness. Expert product feasibility assessments indicate that the model is suitable for successful digital learning, and learning effectiveness shows a significant improvement in cognitive learning outcomes. Product usage evaluations confirm that the product is very user-friendly for students. In conclusion, the FSLSM-based personalized learning model proves effective in enhancing students' conceptual understanding based on their learning style preferences in IoT course materials, as well as improving the quality of education in the digital era for the development of more adaptive learning.
| Item Type: | Thesis (Magister) |
|---|---|
| Additional Information: | 1) Dr. Uwes Anis Chaeruman, M.Pd. ; 2) Dr. Indina Tarjiah, M.Pd. |
| Subjects: | Pendidikan > Media Pembelajaran Teknologi dan Ilmu Terapan > Teknologi (umum) > Teknologi Pendidikan |
| Divisions: | FIP > S2 Teknologi Pendidikan |
| Depositing User: | Users 29383 not found. |
| Date Deposited: | 06 Aug 2025 01:02 |
| Last Modified: | 14 Aug 2025 02:33 |
| URI: | http://repository.unj.ac.id/id/eprint/58104 |
Actions (login required)
 |
View Item |
