Putri Zahara
Universitas Islam Negeri Syarif Hidayatullah Jakarta

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Keinovasian Mahasiswa dalam Mengadopsi Bahan Ajar Interaktif Berbasis Canva sebagai Teknologi Tepat Guna Asep Ediana Latip; Nabilah Safitra Lubis; Anisaa Eka Febiana; Putri Zahara
DIAJAR: Jurnal Pendidikan dan Pembelajaran Vol. 5 No. 2 (2026): April 2026
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/diajar.v5i2.6695

Abstract

This study aims to assess the extent to which students of the Madrasah Ibtidaiyah Teacher Education program demonstrate innovativeness in utilizing interactive instructional materials developed through canva as an appropriate technology for learning. The study was conducted in response to the rapid advancement of digital technology in higher education and the need to strengthen the innovative capabilities of PGMI students as prospective Madrasah Ibtidaiyah teachers in the digital learning era. A quantitative approach using a survey method was employed, involving PGMI students who had utilized canva in learning activities as the research population. Data were collected through an online questionnaire distributed via Google Forms, using a closed-ended Likert-scale instrument developed based on indicators of innovativeness and learning technology adoption. The collected data were analyzed using descriptive statistical methods to describe the level of student innovativeness. The results indicate that PGMI students exhibit a good level of innovativeness in adopting canva as an appropriate learning technology, as they not only use canva as a visual design tool but also creatively develop it into contextual, engaging, and interactive teaching materials aligned with the characteristics of Madrasah Ibtidaiyah learners. However, the study is limited by the relatively small number of respondents and the exclusive use of descriptive statistical analysis, which restricts the generalizability of the findings; therefore, future research is recommended to apply inferential statistical analyses and involve more diverse respondent groups.