The virtual and digital learning process seems to hugely impact academic achievement due to the COVID-19 outbreak, globally. Thus, improving student performance is one of the important focuses of educational management. Mapping students’ actual conditions is a mandatory requirement before designing the performance improvement program. Therefore, this study proposed a statistical investigation to map out students’ performance and the problems they encountered during online learning using Multiple Correspondence Analysis (MCA), revealing the hidden pattern and classifying students based on their demographics (programs, CGPA, and origin) and learning environments. The data samples consist of 234 undergraduate students in the Department of Mathematics, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris (UPSI). The study findings formed from two different profiles where each profile has its respective categories. The study found that the students of the Bachelor of Education (Mathematics) with Honour, categorized as smart students, preferred to study face-to-face because of poor internet connection from using mobile data. On the other hand, the students of the Bachelor of Science (Mathematics) with Education, who were categorized as average students, had no difficulty continuing either synchronous or asynchronous online learning in the future because of stable internet access using their home Wi-Fi connection. Moreover, the preference made was also due to family interruption issues.