Mental Stress Detection Using Bidirectional Encoder Representations From Transformers

2. Related Work

L. Zhao et al., (2021) In his study a model named Augmented Education (N = 156) is led, which totals multisource social information spreading over on the web and disconnected learning as well as exercises inside and outside the homeroom. Metrics assessing linear and nonlinear behavioural changes, in particular, can be used to acquire a deeper understanding of the characteristics that lead to outstanding or poor performance. of campus lifestyles are assessed; also, characteristics that characterise dynamic Long short-term memory is used to extract changes in temporal lifestyle patterns (LSTM). Next, a classification technique based onmachine learning is being developed to predict academic success. Finally, visible feedback is being developed to help students (particularly at-risk students) improve their relationships with the university and achieve a better accuracy. Experiments show that the Augment ED model may accurately predict students' academic records.