LOSARI: A novel R-based statistical software to facilitate students’ self-regulated learning in statistics courses

This article presents the development of LOSARI, a novel R-based statistical software designed to facilitate students' self-regulated learning (SRL) in statistics courses. LOSARI can be accessed online without installation and allows students to perform statistical analyses through a point-and-click interface without coding. It integrates several innovative features: interactive video tutorials embedded in the analysis environment, real-time error notifications that guide students in correcting mistakes, and automatic interpretation of results to support independent learning. The software was validated through a student satisfaction survey using the End-User Computing Satisfaction (EUCS) model, which indicated that most users had positive perceptions of LOSARI and found it effective for learning statistics outside the classroom. Possible extensions and enhancements are also discussed.•A structured process for developing LOSARI as an R-based statistical learning tool.•Introduction of key features, including interactive video tutorials, real-time error notifications, and automatic interpretation.•Validation method through student satisfaction measurement and comparison with manual statistical coding.