Qualitative Data Requirements in the Divayana Evaluation Model

The need for qualitative data to support the evaluation process using the DIVAYANA (Description-Input-Verification-Action-Yack-Analysis-Nominate-Actualization) evaluation model is very important to obtain in-depth information about the effectiveness of e-learning platform utilization in ICT Vocational Schools. Those qualitative data are used to complete the evaluation process for the eight components of the DIVAYANA evaluation model. The eight components included Description component, Input component, Verification component, Action component, Yack component, Analysis component, Nominate component, and Actualization component. The main purpose of this study was to show the qualitative data needed in each evaluation component of the DIVAYANA evaluation model. The tools used to obtain qualitative data on the eight components of the DIVAYANA evaluation model were interview guidelines, checklists, and literature studies. This study approach was qualitative. The technique used to test the qualitative data validity in this study was theoretical triangulation. The findings of this study were the qualitative data needed in each component of the DIVAYANA evaluation model to show the effectiveness of e-learning platform utilization in ICT Vocational Schools. The findings of this study have a positive contribution to the evaluation process in the field of education, especially in strengthening the correctness of the quantitative data results which are usually obtained in the evaluation process. The novelty of this study is the presentation of qualitative data on the yack component, analysis component, and nominate component which does not have by other evaluation models.