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Previous studies widely report the optimization of performance predictions to highlight at‐risk students and advance the achievement of excellent students. They also have contributions that overlap different fields of research. On the one hand, they have insightful psychological studies, data mining discoveries, and data analysis findings. On the other hand, they produce a variety of performance prediction approaches to assess students’ performance during cognitive tasks. However, the synchronization between these studies is still a black box that increases prediction systems’ dependency on real‐world datasets. It also delays the mathematical modeling of students’ emotional attributes. This review paper performs an insightful analysis and thorough literature‐based survey to draw a comprehensive picture of potential challenges and prior contributions. The review consists of 1497 publications from 1990 to 2022 (32 …