Online teaching–learning methods have been followed by world-class universities for more than a decade to cater to the needs of students who stay far away from universities/colleges. But during the COVID-19 pandemic period, online teaching–learning helped almost all universities, colleges, and affiliated students. An attempt is made to find the effectiveness of online teaching–learning methods for university and college students by conducting an online survey. A questionnaire has been specially designed and deployed among university and college students. About 450 students from various universities, engineering colleges, medical colleges in South India have taken part in the survey and submitted responses. It was found that the following methods promote effective online learning: animations, digital collaborations with peers, video lectures delivered by faculty handling the subject, online quiz having multiple-choice questions, availability of student version software, a conducive environment at home, interactions by the faculty during lectures and online materials provided by the faculty. Moreover, online classes are more effective because they provide PPTs in front of every student, lectures are heard by all students at the sound level of their choice, and walking/travel to reach classes is eliminated.
The education sector is witnessing a paradigm shift with the rapid and ongoing technological advancements. The online, offline, and blended modes of learning continue to evolve with time. The purpose of this survey is to collect students’ responses to understand their perspectives on the different modes of learning. The advantages, challenges, and requirements for conducting classes through online, offline, and blended learning methods are discussed. A questionnaire was designed, and a survey was conducted among undergraduate engineering students. The questions are carefully planned to understand the choice of students while selecting different modes of learning, various activities and tools, and the reasons for their preferences. 654 students took part in the survey and shared their feedback. The advantages and disadvantages of online and offline learning are presented. A chi-square test was conducted, and the association between the two questions is shown to be significant. Suggestions for enhancing teaching and learning based on the findings of the survey help faculty members to plan the teaching methodology to suit the requirements of students.
This chapter presents a novel 3D approach for patient scheduling (3D-PS) using multi-agents. Here the 3Ds refers to the Distributed, Dynamic and Decentralized nature of the patient scheduling. As in many other scheduling problems, in the hospital domain, a major problem is the efficient allocation of resources to the patients. The resources here mean the doctor, diagnosing equipments, lab tests, et cetera. Commonly, patient scheduling is performed manually by human schedulers with no automated support. Human scheduling is not efficient, because the nature of the problem is very complex; it is inherently distributed, dynamic, and decentralized. Since agents are known to represent distributed environment well and also being capable of handling dynamism, an agent based approach is chosen. The objectives are to reduce patient waiting times, minimize the patient stay in the hospital, and to improve resource utilization in hospitals. The comparison of several agent-based approaches is also reviewed, and the auction-based approach is chosen. The complete multi-agent framework given in literature is adapted to suit the patient scheduling scenario. The patient scheduling system is implemented in the JADE platform where patients and resources are represented as agents. The chief performance metric is the weighted tardiness which has to be minimized in order to obtain an effective schedule. The experiment is carried out using constant number of resources and varying number of patients. The simulation results are presented and analyzed. 3D-PS produces up to 30% reduction in total weighted tardiness in a distributed environment, as compared to other traditional algorithms. A further enhancement to this approach aims to reduce the communication overhead by reducing the number of messages passed and hence resulting in a better coordination mechanism. This auction based mechanism aims to provide the basic framework for future enhancements on patient scheduling.
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