## 4 Results and Discussion
### Changes in Students' Second-Classroom Grades  
From the experimental data, 50 students were selected as the experimental group and the other 50 students were selected as the control group. The students in the experimental group used the path recommendation system for learning throughout the second-classroom learning period, while students in the control group used the conventional method for learning. The system recommends personalized learning paths in real time based on students' historical behavior data, learning progress, interests, and emotional states, and dynamically adjusts and optimizes the paths through incremental learning technology and generative adversarial networks. By comparing the scores of the two groups of students in the mid-term final exam, it found that the scores of students using this system improved significantly, especially in the final exams. The changes in the grades of the two groups of students in the mid-term final exams are shown in Table 2. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Group** & \begin{tabular}{c} **Mid-Term Results** \\ **(Average Score)** \\ \end{tabular} & \
\begin{tabular}{c} **Final Exam Results** \\ **(Average Score)** \\ \end{tabular} &
\begin{tabular}{c} **Improvement in Grades (\%)** \\ \end{tabular} \\ \hline Experimental group & 70.5 & 85.2 & 20.8 \\ \hline Control group & 69.2 & 72.3 & 4.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Changes in students’ mid-term and final exams. As can be seen from Table 2, the experimental-group students' mid-term exam score was 70.5 and the final exam score was 85.2, with a score improvement of 20.8%. In contrast, the control-group students' mid-term exam score was 69.2 and the final exam score was 72.3, with a score improvement of only 4.5%. Compared with the control group, the performance of the students in the experimental group significantly improved, indicating that the personalized learning path recommendation system had a significant effect on the students' academic performance. In order to gain a deeper understanding of the effect of the recommendation system on different student groups, the students in the experimental group were grouped according to their grades, divided into high-score groups (above 85 points), medium-score groups (70-85 points), and low-score groups (below 70 points). After analyzing the changes in the grades of different groups after using the recommendation system, the following results were obtained. As can be seen from Figure 5, the recommendation system has different effects on students of different grades. The grades of the high-score group show a limited improvement of only 2.6%; the grades of the middle-score group improve by 14.2%, and the grades of the low-score group improve the most, reaching 31.9%. This shows that the recommendation system has a more significant learning promotion effect on students with low and medium scores. Low-scoring students receive more help through personalized recommendations, and the system adjusts the learning content according to their characteristic data to fill their knowledge gaps. For high-scoring students, the role of the system is mainly reflected in the recommendation of innovative and challenging learning tasks, which can help high-scoring students improve considerably, so the improvement in a single course is relatively minor. This study suggests that physiological signals (such as heart rate variability and skin temperature) and emotional variables (such as interest, happiness, boredom, and confusion) can be transformed into specific educational actions. First of all, the system can dynamically adjust the difficulty of learning tasks according to the HRV of students. A higher HRV indicates that students are in a better state of concentration and are suitable for recommending more challenging tasks. Lower HRV indicates that students may need simple tasks or rest time to regain their energy. It is also very important to choose suitable learning content based on emotional classification.