ABSTRACT
In this paper, we propose a method based on multicriteria classification and a dominancebased rough set approach (DRSA) to support teachers in decision making. The objective is to use teachers' knowledge and preferences to identify ‘atrisk students', i.e. students who are likely to drop out, and ‘leader students', i.e. students who are likely to help their peers, in distance learning. The proposed method is composed of two phases: phase I builds collective decision rules from teachers' preferences, and phase II classifies students into two decision classes: ‘atrisk students' and ‘leader students'. This method was designed, tested, and validated in higher education, with teachers who have acquired rich experience in teaching in online-synchronous mode since the Covid-19 pandemic. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
From the last two years due to emergence of COVID-19, a first pandemic of the century, caused hard time to continuing normal lifestyle in all aspects including the campus lifestyle of students. All the academic activities such as classes, examinations, evaluations and placement are going as usual in online mode like earlier. In this regard, we have conducted a Web-based survey on students about their mental condition concerning corona anxiety, coping with stress, worry, and fear. In our survey, 620 students participated from different discipline and states to rejoin the campus either online or offline mode. 372 (60%) students want to attend offline classes while 248 (40%) students want online classes. Additionally, generating the rules using a rough set approach to identify corona anxiety in students. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
From the last two years due to emergence of COVID-19, a first pandemic of the century, caused hard time to continuing normal lifestyle in all aspects including the campus lifestyle of students. All the academic activities such as classes, examinations, evaluations and placement are going as usual in online mode like earlier. In this regard, we have conducted a Web-based survey on students about their mental condition concerning corona anxiety, coping with stress, worry, and fear. In our survey, 620 students participated from different discipline and states to rejoin the campus either online or offline mode. 372 (60%) students want to attend offline classes while 248 (40%) students want online classes. Additionally, generating the rules using a rough set approach to identify corona anxiety in students. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.