Instructional design model of mobile augmented reality for enhancing comprehension, learning engagement and perceived motivation in students with diverse spatial visualization abilities

Despite various design models that have been proposed and adapted for mobile augmented reality (MAR) applications development, none has addressed the integration of comprehension, learning engagement, and perceived motivation elements in learning Computer System Organization (CSO) among polytechnic students’ students with diverse Spatial Visualization Abilities (SVA). This leaves a critical gap in the development of design models in educational technology for MARbased learning environments. This study aimed to develop and evaluate the Mobile Augmented Reality Instructional Design Model (MARID) for polytechnic students with diverse SVA. Based on the MARID model, two MAR applications were designed and developed; Mobile Augmented Reality Functional Realism (MARCO-FR) and Mobile Augmented Reality Physical Realism (MARCO-PR). Both were designed for the CSO course. A quasi-experimental factorial design was used to examine the effects of the independent variables of MARCO modes, which were the MARCO-FR and MARCO-PR on the dependent variables: comprehension, learning engagement, and perceived motivation, moderated by the students’ SVA. This study involved 200 polytechnic students who were assigned to use one of the MARCO modes. Research procedures included pre-tests, post-tests, expert validation, and alpha-beta testing. The data was analysed using descriptive and inferential statistics which is ANOVA. Findings revealed that students using MARCO-FR demonstrated significantly higher performance in comprehension, learning engagement, and perceived motivation compared to those using MARCO-PR, across both high and low SVA levels. High SVA students showed exceptional improvements in comprehension and learning engagement with MARCO-FR, attributed to its visual realism and emphasis on spatial procedural knowledge. Low SVA students also benefited from both MARCO modes, although their performance gains were more pronounced with MARCO-FR. This study highlights MARID as an effective instructional design model for MAR to address diverse learning needs. MARCO-FR is recommended for students across SVA levels, while MARCO-PR offers potential for broader applications. This research contributes to integrating MAR into instructional design for technical education and advancing educational technology