User satisfaction

After collecting feedback, it is crucial to conduct a systematic and multi-layered analysis. Quantitative data is processed using statistical methods, such as calculating averages, identifying outliers, analyzing trends by year of study or type of activity. Such processing allows for clear identification of areas with high and low scores, as well as variations among different groups of students.

Qualitative data from open questions, interviews or focus groups are interpreted using methods of thematic analysis. Key words and recurring themes are analyzed, for example, the need for greater interaction, praise related to the structure of e-colleges or criticism of technical solutions. Of particular value are examples and narrative descriptions that reveal the context behind ratings and figures.

Interpretation should be focused on understanding students, what motivates them, what elements they perceive as obstacles, and what they find particularly useful. The results should then be presented to all stakeholders in an understandable and clear way, using graphs, infographics, summaries, and reports, so that they can serve as a starting point for decision-making and planning for improvement.