Pengembangan Instrumen Penilaian Berbasis Project-Based Learning untuk Menilai Karakter Peduli Lingkungan pada Mahasiswa - Eka Yunita Rhomadona; Sri Latifah; Yani Suryani (SAKALIMA: Pilar Pemberdayaan Masyarakat Pendidikan, 2026)
This study aimed to develop and examine the quality of a Project-Based Learning (PjBL)-based assessment instrument for assessing and supporting university students' environmental care character in an environmental physics course. The study was motivated by preliminary findings showing low percentages in learning ease (44.4%), PjBL familiarity (39.9%), assessment-instrument availability (33.2%), and environmental care character (24.9%). The research employed a research-and-development design using the ADDIE model: analysis, design, development, implementation, and evaluation. The participants consisted of expert validators, two lecturers, 20 students in a small-group trial, and 58 sixth-semester physics education students in a field trial. The product comprised project tasks, self-assessment sheets, peer-assessment sheets, observation rubrics, project-product rubrics, and reflective journals related to appropriate technology and environmental problem solving. Data were collected through expert-validation sheets, response questionnaires, validity-reliability testing, and implementation documentation. The findings indicated that the instrument was rated highly feasible by assessment experts (92.31%), material experts (90.63%), and language experts (91.07%). Empirical testing showed that 22 of 24 items met the validity criterion and the reliability coefficient reached 0.89. Lecturer responses reached 91.25%, while student responses reached 88.84%, both in the very feasible category. In the observed implementation, the environmental care character score increased from 49.18 to 83.42 with an N-gain of 0.67. These results suggest that the developed PjBL-based assessment instrument has adequate validity, reliability, and practicality for assessing environmental care character in higher education, although broader implementation is still needed to strengthen generalizability.