Utilizing Data from Twitter to Explore the UX of “Madrasati” as a Saudi e-Learning Platform Compelled by the Pandemic

Abstract

Purpose: When a website or application is designed and deployed rapidly as a response to an urgent need, it may not satisfy users. Therefore, we decided to investigate users’ attitudes and (dis)satisfaction towards the UX of the Madrasati platform, an e-learning system that was developed by the Saudi Ministry of Education as an alternative to traditional learning during the COVID-19 crisis. Method: The study utilizes Twitter to collect a large volume of data (177,358 tweets) related to Madrasati. Two relevant hashtags #Madrasati ( مدرستي #) and #Minaset Madrasati ( منصة مدرستي #) were used to collect data within the first two months after the launch of the platform. The two-month period was split into four phases: Pre-Semester Phase, Familiarization Phase, Interaction Phase, and Use Phase. The Microsoft Product Reaction Cards (MPRC) tool was implemented to judge user satisfaction/dissatisfaction. Results: The findings show a sudden dissatisfaction about the platform upon launch, but a gradual increase in positive UX over time. Various categories of negative UX (e.g., errors, user denial, and speed issues) gradually became less and less over the observed two months. More importantly, the results show how big data from Twitter can be used for analyzing the UX of a new product. Conclusion: UX is not static; it can change positively over time as users gain more experience with the system.