IMPLEMENTATION OF DEEP LEARNING IN PACKAGE C LEARNING

Abstract

This study aims to explore how the deep learning classroom service model is implemented in Package C learning, where the availability of learning materials such as modules, student worksheets (LKS), and lesson plans (RPP) used by tutors are still based on pre–deep learning practices. These conditions are presumed to cause difficulties in the implementation process. Therefore, this research explores the following question: how is the deep learning classroom service model implemented in Package C learning? The study was conducted through observation and description of the Package C learning process implementing deep learning during the current semester. Accordingly, a qualitative research method was employed using observation as the main research instrument. The results indicate that the Package C learning process is generally considered to be in accordance with the stages of the learning process as conventionally applied, based on criteria that existed prior to the implementation of deep learning, such as the availability of modules, student worksheets (LKS), and lesson plans (RPP) that are still based on previous approaches. It is recommended that improvements be made, particularly in enhancing tutor competencies and organizing a more supportive learning environment