Introducing 'inrep': an R package that facilitates fully reproducible research workfows for survey-based assessments

TL;DR

The paper presents 'inrep', an open-source R package that streamlines survey-based research workflows by integrating survey design, data management, analysis, and reporting into a single reproducible framework, including support for large language models.

Contribution

It introduces 'inrep', a novel R package that consolidates all assessment stages into one flexible, reproducible tool, enhancing efficiency and accessibility for researchers.

Findings

Streamlines survey research workflows within R.

Supports tailored assessment components with large language models.

Enhances reproducibility and reduces errors in survey research.

Abstract

Conducting research often involves managing multiple disconnected tools for survey design, data collection, response analysis, and report generation, leading to inefficiencies, increased error risks, and challenges in ensuring reproducibility. To address these issues, we introduce inrep, an open-source R package that integrates the entire assessment workflow within a unified, flexible framework in R. With inrep, researchers can create customized assessments, streamline data management, and generate personalized participant reports without switching software or manually transferring data. inrep includes built-in support for generating structured prompts to guide large language models, enabling tailored adaptation of assessment components to specific study needs. By consolidating all stages of the assessment process, inrep enhances research efficiency, improves reliability, and ensures full reproducibility, making sophisticated testing methodologies accessible to researchers, educators, and practitioners regardless of programming expertise.