A STUDY OF LEARNING COMPONENTS THROUGH INTERACTIVE MEDIA BASED ON SELF-DIRECTED LEARNING TO ENHANCE DIGITAL INTELLIGENCE AMONG UPPER SECONDARY SCHOOL STUDENTS

Abstract

This study aimed to examine the components of learning through interactive media based on self-directed learning concepts in order to enhance students’ digital intelligence. The proposed model was validated using Confirmatory Factor Analysis (CFA). The sample consisted of 340 upper secondary school students from Saint Gabriel’s College, selected through simple random sampling. The research instrument was a standardized questionnaire. Data were analyzed using descriptive statistics and confirmatory statistics with the AMOS program. The interactive media learning model comprised four components: technology use (UT), interactive learning through online and offline media (ITR), learning motivation (MTV), and facilitating conditions (FT). The results indicated that, in the first-order CFA, the standardized factor loadings of the observed variables ranged from 0.86 to 0.92, exceeding the acceptable threshold and demonstrating strong construct validity. In the second-order CFA, the standardized factor loadings of the four components ranged from 0.91 to 0.98, which were within acceptable levels. Furthermore, the model demonstrated a good fit with the empirical data, as indicated by the following fit indices: χ²/df = 4.589, GFI = 0.930, AGFI = 0.905, TLI = 0.974, CFI = 0.978, and RMSEA = 0.065. These results supported both research hypotheses. The developed learning model, named the SID Model (Self-Directed Interactive Media for Digital Intelligence), consists of three stages: 1) Goal setting (Set Goal), 2) Learning within a learning ecosystem (In-process according to the goal), and 3) Reflection and achievement of digital intelligence (Get DQ Goal). The model was evaluated by experts and received the highest level of appropriateness.
The findings provide empirical evidence supporting that interactive media learning, based on self-directed learning concepts across the four components, can effectively enhance students’ digital intelligence.