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Analisis Kebutuhan Pengembangan Model Outbound dalam Mata Kuliah PJOK untuk Meningkatkan Keterampilan Motorik Calon Guru Dyas Andry Prasetyo; Mohammad Hasan Basri; Mas'odi Mas'odi; Feri Weldani; Syawal Hari Hidayatullah
Center of Education Journal (CEJou) Vol. 4 No. 2 (2023): Central Journal of Education (CEJou) December
Publisher : Universitas Nahdlatul Ulama Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55757/cejou.v4i2.484

Abstract

Pengembangan keterampilan motorik merupakan aspek fundamental dalam pendidikan jasmani, olahraga, dan kesehatan (PJOK), khususnya bagi calon guru yang akan menjadi fasilitator pembelajaran aktif dan sehat di sekolah. Namun, model pembelajaran outbound yang terintegrasi dalam mata kuliah PJOK masih terbatas, sehingga diperlukan analisis kebutuhan untuk merancang model yang relevan dan efektif. Penelitian ini bertujuan untuk menganalisis kebutuhan pengembangan model outbound dalam mata kuliah PJOK guna meningkatkan keterampilan motorik calon guru. Metode penelitian yang digunakan adalah analisis kebutuhan dengan pendekatan deskriptif kualitatif, melibatkan observasi, wawancara, dan studi dokumentasi pada mahasiswa PJOK di salah satu universitas di Indonesia. Hasil penelitian menunjukkan bahwa mahasiswa membutuhkan model outbound yang variatif, kontekstual, dan mampu mengintegrasikan aktivitas fisik dengan pengembangan keterampilan motorik, seperti koordinasi, kelincahan, dan keseimbangan. Selain itu, ditemukan bahwa outbound berbasis pengalaman langsung dapat meningkatkan motivasi, kepercayaan diri, serta kesiapan mahasiswa dalam mengelola pembelajaran PJOK di sekolah. Implikasi dari hasil penelitian ini adalah perlunya pengembangan model outbound yang adaptif dan aplikatif dalam kurikulum PJOK, sehingga dapat mendukung peningkatan kompetensi motorik dan profesionalisme calon guru.
Intelligent Instructional Navigation: Development of a Wearable Sensor-Based Adaptive Learning Model to Improve Self-Efficacy and Aquatic Skills Feri Weldani; Masodi Masodi
Assyfa Learning Journal Vol. 4 No. 1 (2026): Assyfa Learning Journal
Publisher : CV. Bimbingan Belajar Assyfa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61650/alj.v4i1.700

Abstract

The digital transformation in higher education necessitates a shift from subjective, manual pedagogical evaluations toward objective, data-driven strategies, particularly in complex physical domains like aquatic skills. This study aims to develop and analyze an intelligent instructional navigation model using wearable sensor-based artificial intelligence (AI) to provide real-time biometric feedback and accelerate swimming competencies and student self-efficacy. Employing a quasi-experimental design, the research integrated smartwatches and AI algorithms to monitor biometric metrics and intensity zones (Z1–Z5), providing immediate haptic scaffolding during learning sessions. The results indicate that the AI-driven model significantly enhances evaluation objectivity and motor adaptation speed compared to conventional methods, with the experimental group achieving substantially higher psychomotor scores (8.8 vs. 7.1; p < 0.01). Notably, the findings reveal that training duration without precise intensity zone management does not significantly improve performance, highlighting biometric-based scaffolding as the critical variable for instructional success. This study concludes that transforming instructional frameworks through AI-driven navigation acts as a vital catalyst for achieving Sustainable Development Goals (SDGs), specifically Quality Education and Good Health, by ensuring a measurable, safe, and adaptive learning ecosystem. This model offers a scalable pedagogical framework for modernizing sports education through the scholarship of teaching and learning (SoTL).