Implementasi Model Pembelajaran Deep Learning Berbantu Blooket Pada Mata Pelajaran Ekonomi

Abstrak

The low engagement and learning outcomes of class X-I students at MAN 2 Bojonegoro in Economics stem from monotonous lectures and limited technology use. This study aims to describe the implementation of the Deep Learning model integrated with the Blooket platform and identify supporting and inhibiting factors. Using a descriptive qualitative method, data were collected through passive participant observation, in-depth interviews, and documentation. Results show that Deep Learning with Blooket successfully realized three main pillars: meaningful learning, positive emotional experience, and social-collaborative interaction. Blooket helps connect prior knowledge with new information, simplifies material, creates an enjoyable atmosphere, and encourages student discussion. Supporting factors include point systems, game elements, media novelty, collaborative discussion, academic independence, material simplification, and a conducive atmosphere. Inhibiting factors include students’ moderate level of understanding, unstable internet, time limits, platform unfamiliarity, risk of focusing solely on entertainment, and device dependence. The study concludes that Deep Learning assisted by Blooket effectively increases student engagement and motivation, but success depends on infrastructure readiness, question quality, and the teacher’s role in post-game reflection.

Keywords: Deep Learning, Blooket, economics learning outcomes, gamification, descriptive qualitative