AR-CODE-AT for analytical thinking in elementary coding education: Design, expert validation, and user trial
DOI:
https://doi.org/10.17977/um031v13i32026p172%20Keywords:
Augmented Reality, Coding Education, Analytical Thinking, Computational Thinking, Elementary Education, Instructional DesignAbstract
Augmented reality (AR) can make abstract programming logic more tangible, but its educational value depends on an instructional architecture that specifies how AR supports reasoning, coding, scaffolding, and assessment. This study developed, expert-validated, and empirically piloted AR-CODE-AT, a seven-stage AR-assisted coding strategy for upper-primary education. A four-phase formative design-and-validation model was used: needs analysis, design translation, expert validation and revision, and a limited user trial. Phase 1 analysed 16 valid needs responses and showed very high development support (M = 4.55/5, SD = 0.46). Phase 2 involved six experts evaluating 48 items across nine design domains; expert validation yielded M = 4.36, SD = 0.54, and mean Aiken’s V = .841 (item range = .750–.917), with 39/48 items (81.25%) reaching V ≥ .80. Phase 3 implemented the revised prototype with 15 Grade 5 students and one classroom teacher. Student practicality reached M = 3.39/4 (SD = 0.26; 84.7%), implementation fidelity was 5/7 stages (71.4%), and teacher practicality was M = 3.67/5 (73.3%). The analytical-thinking process rubric yielded M = 2.83/4 (SD = 0.54). Design-theoretically, the study specifies how AR functions, coding actions, scaffolding/fading, and process assessment are aligned across the seven stages; methodologically, it provides a traceable evidence chain from needs to expert judgment to user implementation. The pilot is descriptive and does not establish learning gains or comparative effectiveness.
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