Integrasi Google Sheet dengan Metode Evaluasi berbasis Deep Learning untuk Mengukur Kemampuan Analitis Mahasiswa PPG dalam Pembuatan Soal HOTS - Adip Wahyudi; Slamet Arifin; Evi Fitriana; Feri Fahrian Maulana; Dynda Prista; Muhammad Aris Firmansyah; Radya Wirawan Nurjati (PAKAR Pendidikan, 2026)
21st century education requires the use of creative interactive tools to make learning outcome evaluation more effective. The main challenge is low student participation due to conventional assessment practices. Technologies such as deep learning-based Google Sheet integration offer a solution by providing deep learning evaluation tools. This study focuses on developing the integration of evaluation tools with deep learning-based Google Sheets in the Learning Evaluation course in the PPG program and testing its impact on improving learning outcomes. The research method used R&D with the ADDIE model, with data collected through a pretest-posttest design on two groups, namely the experimental group that used deep learning-based Google Sheets evaluation tools and the control group that used a conventional approach. After testing for normality and homogeneity to ensure that the statistical prerequisites were met, the analysis was continued using a paired t-test. The results showed significance (p < 0.05), indicating that the deep learning-based Google Sheets evaluation tool was effective in improving learning outcomes, while also encouraging student motivation and engagement. In conclusion, the deep learning-based Google Sheets evaluation tool is suitable for implementation in the PPG program, with opportunities for further development through the enrichment of collaboration features and adaptive evaluation to strengthen the appeal and impact of learning.