Beyond the black box: Expert-based development and validation of learning models in the ADDIL case

Source abstract

Developing innovative learning models requires systematic and validated processes, yet the literature often emphasizes implementation outcomes while overlooking the formative design stages. This article addresses this gap by presenting a methodological case study that transparently documents the design and validation process of the Argument-Decision Driven Inquiry Learning (ADDIL) model. Its primary objective is to offer a development framework to guide other researchers and practitioners, rather than to report on the model's classroom effectiveness. Employing a mixed-methods approach, the development process commenced with a Focus Group Discussion (FGD) involving eight experts to elicit qualitative insights. Thematic analysis of the FGD identified crucial areas for refinement, such as strengthening the model's theoretical underpinnings and clarifying its syntax. Based on this feedback, the model was iteratively revised before being quantitatively validated by five experts using Aiken’s V. The validation results indicated a high expert consensus on the model's feasibility (Aiken’s V>.80) across all components. The primary contribution of this case study is a systematic framework demonstrating a novel approach to development research, offering methodological insights for the creation of future pedagogical innovations. The implications of this study highlight the value of systematic expert feedback and validation in developing reliable and theoretically grounded learning models.