Methods for collecting data on participants of online programs of additional professional education in universities

Abstract

The article discusses in detail the main methods for collecting data on the participants of online programs of additional professional education (AEP) in universities, which were developed by the authors. The authors used personality-oriented, environmental, product, and data-driven approaches as the basic ones in developing these methods. The authors also took into account the main statements of evidence-based education, learning analytics, and the types of learning data (the LOTS model).The new methodological approaches presented in this article have practical value at various stages of designing and implementing training programs based on the obtained data with the help of feedback, evaluation and learning metrics. The results were tested in small groups of students (12–20 participants) as part of the implementation of programs and courses such as “Assessment and Feedback”, “Fundamentals of Pedagogical Design for Distance and Blended Learning”, and the Summer School for teachers and trainers “Data-Driven Learning Design”. A total of 146 participants were trained using the methods outlined in this article.The results of this study may be of interest to educational organization administrators that provide AEP. They can focus on developing an educational system based on data, designing programs based on current educational needs, improving training effectiveness with valid metrics, and competing with Russian and foreign EdTech companies. Additionally, the findings could be useful for professors implementing educational programs of higher education, instructional designers, and educational product developers.