The high unemployment rate among university graduates is prompting universities to enhance the business skills of their students. This research aims to holistically explain the role of university support and entrepreneurial resilience in increasing students’ business innovation capabilities. To analyze phenomena and relationships between variables, a quantitative approach using partial least square structural equation modeling (PLS-SEM) was used. This research sample involved 165 student entrepreneurs who are members of the student entrepreneur community in Indonesia. Knowledge management does not significantly impact increasing business innovation capabilities. However, perceived university support and entrepreneurial resilience have been shown to significantly impact business innovation capabilities and strengthen the influence of knowledge management activities on increasing business innovation capabilities. Universities must create policies supporting extracurricular entrepreneurship programs, focusing on building entrepreneurial resilience. This can be achieved through workshops and business incubator initiatives involving partnerships with industry and the entrepreneurial community. This research provides a new perspective in analyzing higher education entrepreneurship education through a more in-depth explanation of the extracurricular activities of the student business community to build business innovation capabilities based on knowledge, institutional, and trait theory perspectives.

In the wake of the COVID-19 pandemic, the prevalence of online education in primary education has exhibited an upward trajectory. Relative to traditional learning environments, online instruction has evolved into a pivotal pedagogical modality for contemporary students. Thus, to comprehensively comprehend the repercussions of environmental changes on students’ psychological well-being in the backdrop of prolonged online education, this study employs an innovative methodology. Founded upon three elemental feature sequences—images, acoustics, and text extracted from online learning data—the model ingeniously amalgamates these facets. The fusion methodology aims to synergistically harness information from diverse perceptual channels to capture the students’ psychological states more comprehensively and accurately. To discern emotional features, the model leverages support vector machines (SVM), exhibiting commendable proficiency in handling emotional information. Moreover, to enhance the efficacy of psychological well-being prediction, this study incorporates an attention mechanism into the traditional Convolutional Neural Network (CNN) architecture. By innovatively introducing this attention mechanism in CNN, the study observes a significant improvement in accuracy in identifying six psychological features, demonstrating the effectiveness of attention mechanisms in deep learning models. Finally, beyond model performance validation, this study delves into a profound analysis of the impact of environmental changes on students’ psychological well-being. This analysis furnishes valuable insights for formulating pertinent instructional strategies in the protracted context of online education, aiding educational institutions in better addressing the challenges posed to students’ psychological well-being in novel learning environments.

Reading comprehension ability, as a key skill that needs to be developed in English teaching, has attracted high attention from teachers and students in universities. This is not only due to its relatively large proportion in English exams, but also due to the entering of the information age, people need to obtain information from the text through extensive reading and gain a profound understanding of the content of the article. Therefore, in the process of guiding students to learn English knowledge, teachers must take cultivating students' reading comprehension ability as the central link of teaching activities. Through exploring and researching it in teaching, students can improve their reading comprehension level and enable them to have a deeper understanding of the profound connotations to be expressed in future English texts.