Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Review
    Citation - WoS: 3
    Citation - Scopus: 4
    Predictive Video Analytics in Online Courses: a Systematic Literature Review
    (SPRINGER, 2023) Yurum, Ozan Rasit; Taskaya-Temizel, Tuğba; Yildirim, Soner
    The purpose of this study was to investigate the use of predictive video analytics in online courses in the literature. A systematic literature review was performed based on a hybrid search strategy that included both database searching and backward snowballing. In total, 77 related publications published between 2011 and April 2023 were identified. The findings revealed an increase in the number of publications on predictive video analytics since 2016. In the majority of studies, edX and Coursera platforms were used to collect learners' video interaction data. In addition, computer science was shown to be the top course domain, whilst data collection from a single course was found to be the most common. The results related to input measures showed that pause, play, backward, and forward were the top in-video interactions, whilst video transcript and subtitle were the least used. Learner performance and dropout were the primary output measures, whereas learning variables such as engagement, satisfaction, and motivation were investigated in only a few studies. Furthermore, most of the studies utilized data related to forums, navigation, and exams in addition to video data. The top algorithms used were Support Vector Machine, Random Forest, Logistic Regression, and Recurrent Neural Networks, with Random Forest and Recurrent Neural Networks being two rising algorithms in recent years. The top three evaluation metrics used were Accuracy, Area Under the Curve, and F1 Score. The findings of this study may be used to aid effective learning design and guide future research.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 8
    Urban Earthquake Vulnerability Assessment and Mapping at the Microscale Based on the Catastrophe Progression Method
    (SPRINGER, 2023) Gerçek, Deniz; Güven, İsmail Talih
    Vulnerability assessment and mapping play a crucial role in disaster risk reduction and planning for adaptation to a future earthquake. Turkey is one of the most at-risk countries for earthquake disasters worldwide. Therefore, it is imperative to develop effective earthquake vulnerability assessment and mapping at practically relevant scales. In this study, a holistic earthquake vulnerability index that addresses the multidimensional nature of earthquake vulnerability was constructed. With the aim of representing the vulnerability as a continuum across space, buildings were set as the smallest unit of analysis. The study area is in Izmit City of Turkey, with the exposed human and structural elements falling inside the most hazardous zone of seismicity. The index was represented by the building vulnerability, socioeconomic vulnerability, and vulnerability of the built environment. To minimize the subjectivity and uncertainty that the vulnerability indices based on expert knowledge are suffering from, an extension of the catastrophe progression method for the objective weighing of indicators was proposed. Earthquake vulnerability index and components were mapped, a local spatial autocorrelation metric was employed where the hotspot maps demarcated the earthquake vulnerability, and the study quantitatively revealed an estimate of people at risk. With its objectivity and straightforward implementation, the method can aid decision support for disaster risk reduction and emergency management.