The growth of private universities in the higher education system is increasing, especially in distance education. Despite this growth, research in this field remains sparse. This study aims to fill this research gap by examining the factors contributing to the success of private distance universities, utilising Self-Determination Theory (SDT) to analyse student perspectives. According to SDT, autonomy, competence, and relatedness are vital factors in motivating students and enhancing their learning experiences. Our research employs text mining and co-occurrence network analysis on over 10,000 student reviews from a public portal to identify the motivational factors influencing student satisfaction and learning experiences.

The study employs a comprehensive and robust methodological framework that combines web scraping, text mining, and co-occurrence network analysis to extract and analyse student reviews. Web scraping was utilised to compile a comprehensive data corpus of student reviews from January 2015 to January 2024. The data was systematically studied using the text analysis tool KH-Coder, which allowed the identification of patterns and frequencies of words in sentence structures. This approach facilitated an objective insight into general trends, prevailing themes, and sentiments within the student reviews.

The co-occurrence network analysis revealed significant clusters of terms, highlighting the most frequent topics in each university’s review corpus. Common clusters included terms related to the flexibility of studies, supportive staff, high staff responsiveness, organised online campuses, positive study experiences, and appropriate exam organisation. These clusters were categorised from the perspective of SDT, identifying indicators related to the satisfaction or dissatisfaction of the three basic needs: autonomy, competence, and relatedness.

The findings underscore that flexible learning environments, which empower students to control their learning pathways, are crucial. Additionally, comprehensive support structures that enhance competence and foster a sense of community are essential to meet all SDT needs. The significant role of digital technologies in fulfilling SDT needs is highlighted, showing a marked improvement in students' learning satisfaction. These results offer an understanding of the incremental rise of private distance education universities in higher education. They provide valuable insights into enhancing students' learning experiences within this increasingly prevalent educational model, with particular emphasis on integrating educational technology and advancing theoretical frameworks in learning contexts, thereby offering practical implications for educators, policymakers, and stakeholders in the field.

Further research must solidify these findings and address limitations by incorporating qualitative approaches and comparing private universities with state-funded institutions. This study serves as an initial step towards comprehensive research on the effectiveness of private distance education, highlighting the importance of addressing students’ needs for autonomy, competence, and relatedness through innovative educational practices and support mechanisms. This research contributes to a deeper understanding of student motivation and satisfaction by exploring these factors and informing future educational strategies and policies to improve distance learning experiences.

Keywords: Private Universities, Distance Education, Self-Determination Theory, Student Motivation, Text Mining.