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The emergency transition from physical to online learning during COVID-19 has affected university students in various aspects, especially their academic performance. It can be caused by many factors, such as individual, environmental and social factors. Therefore, this study aims to determine the impact of fear, stress, well-being, teacher and parents’ support (independent variables) on undergraduates’ academic performance (dependent variable) during the COVID-19 pandemic. A structured online questionnaire has been developed and administered to 400 undergraduates. A structural equation model that integrated all variables under investigation was built and statistically validated using AMOS. The results demonstrated that well-being, teacher emotional support and teacher academic support have the highest significant impact on the respondents’ academic performance. It can be concluded that teachers’ support is the most substantial influence in ensuring student learning sustainability during the COVID-19 pandemic.

Design-based learning (DBL) is a learning strategy that requires students to use their theoretical knowledge to develop an artifact or system to tackle a real-life problem. DBL has long been utilized in design-related curricula in higher education such as engineering, computer science, and architecture. However, little is known about how DBL in non-design-based courses enhances students’ learning experience, especially in recent years when the COVID-19 pandemic has compelled the worldwide education systems to adapt to online learning. Hence, this study aims to investigate the experience of science undergraduate students after one semester of participating in online DBL. The participants include 25 second-year science undergraduate students enrolling in the Managing New Technologies course. Using semi-structured interviews and thematic analysis, the findings of this study indicated that online DBL contributes to easy access to learning, enhances creativity, and allows students to think outside the box. Nevertheless, students highlighted online learning as an obstacle to their DBL experience. They claimed that online platforms as a means of communication are not practical due to insufficient interaction time and misunderstanding of information. In addition, some students stated that the online environment poses difficulties for collaborative learning.

Bayesian Structural Equation Modeling (SEM-Bayesian) was applied across different research areas to model the correlation between manifest and latent variables. The primary purpose of this study is to introduce a new framework of complexity to adolescent obesity modeling based on adolescent lifestyle through the application of SEM-Bayesian. The introduced model was designed based on the relationships among several factors: household socioeconomic status, healthy food intake, unhealthy food intake, lifestyle, body mass index (BMI) and body fat. One of the main contributions of this study is from considering both BMI and body fat as dependent variables. To demonstrate the reliability of the model, especially in terms of its fitting and accuracy, real-time data were extracted and analyzed across 881 adolescents from secondary schools in Tehran, Iran. The output of this study may be helpful for researchers who are interested in adolescent obesity modeling based on the lifestyle and household socioeconomic status of adolescents.

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