This paper presents the dataset of undergraduates learning habits during and before the occurrence of pandemic COVID-19 under the scope of sociodemographic and psychological aspects. This dataset consists of four (4) main sections which are students' demographic, psychological disruption, students' learning habits and integration of online sessions with sustainability topics. A total of 37 variables were distributed via an online survey platform. The link of the online survey was circulated to the students using few social media platforms such as WhatsApp groups, Telegram, and faculties' Facebook starting from June 1 until June 31, 2020. There was a total of 668 respondents accompanied by consent were agreed to join the survey. This dataset can have an important role for research and education in identifying the impact on learning performance among the undergraduate students during COVID-19 pandemic based on different sociodemographic and psychological aspects.
This study explores the possibility of integrating and retrieving heterogenous data across platforms by using ontology graph databases to enhance educational insights and enabling advanced data-driven decision-making. Motivated by some of the well-known universities and other Higher Education Institutions ontology, this study improvises the existing entities and introduces new entities in order to tackle a new topic identified from the preliminary interview conducted in the study to cover the study objective. The paper also proposes an innovative ontology, referred to as Student Performance and Course, to enhance resource management and evaluation mechanisms on course, students, and MOOC performance by the faculty. The model solves the issues of data accumulation and their heterogeneity, including the problem of having data in different formats and various semantic similarities, and is suitable for processing large amounts of data in terms of scalability. Thus, it also offers a way to confirm the process of data retrieval that is based on performance assessment with the help of an evaluation matrix.