ABSTRACT
Identifying the connection of theoretical knowledge with real-life problems helps improve learning. This work shows the effect of implementing service-learning using home-labs during COVID-19 crisis in terms student' understanding of theory in practice as well as civic commitment. The obtained results show that service-learning increases student' social justice attitude. Moreover, home labs use improves the connection of theory in practice as well as the willingness to engage in future social work with the community in the context of human factors and ergonomics. © 2022 IEEE.
ABSTRACT
In the past few years, Facebook has been increasingly studied for academic purposes due to its potential benefits to undergraduate education. Problems commonly found in university education include the lack of course engagement and the gap between theory and practice. This research contributes to the literature by investigating the impact of incorporating a non-mandatory Facebook group on learning outcomes. The analysis was done using a Taguchi method design, conducted with three two-level controlled factors (term, Facebook, and teacher). Results indicated that the students who participated in Facebook groups were more engaged with the course and applied theoretical knowledge to real-life problems better than students who learned under traditional instructional designs. Moreover, the use of Facebook groups led to better evaluation of teachers by the students. Furthermore, the student academic impact (knowledge and competence) was higher even though this complementary activity was not included in the course grade. We concluded that Facebook groups are excellent support tools that boost student engagement and their understanding of theoretical concepts and applying them in practice.
ABSTRACT
This research article is devoted to Type-II generalized Fermatean bipolar fuzzy soft sets. Type-II generalized Fermatean bipolar fuzzy soft sets approaches are a great point of view for decision making, which is a new generalization of bipolar fuzzy soft sets and generalized fuzzy soft sets. We indicate an algorithm to solve the decision making real life problem based on a soft set model. We discussed the similarity measure between Type-II generalized Fermatean bipolar fuzzy soft sets. Suppose that there are four patients in a hospital with certain symptoms of corona viruses and the universal set contains COVID-19, severe acute respiratory syndrome, middle east respiratory syndrome, usually mild respiratory illness and the set of a parameter is the set of certain symptoms of corona viruses represented by fever, cough, difficulty breathing or shortness of breath, loss of speech or mobility, or confusion and chest pain. Also, we communicate with interact Type-II generalized Fermatean bipolar fuzzy soft sets that can be applied to detecting whether the person is more affecting from a corona disease or not. © 2022 ICIC International.
ABSTRACT
This paper presents the Live Interactive Streaming Classroom (LISC) system model which can be applied to the Problem-Based Learning (PBL) and motivate students to solve problems in a real-life setting with guidance from teachers via online learning. In this study, the students used self-learning methods for interactive class. The class was managed through the online streaming system by the video conference applications. The study showed that the students' coding and real-life problem solving skills were improved from hand-on experience. The LISC system model stimulated students' learning levels. This was proved by applying the proposed method to the Data Science class at Silpakorn University, Thailand, joined by an instructor from Japan. When the course ended, the evaluation from the participating students showed that they were much satisfied that their skills were up-leveled for coding and real-life problem solving, and their attitudes towards the Data Science class improved. It implied and confirmed that the proposed method was efficient to the students' practical learning level, among the new normal living period in the Coronavirus pandemic. © 2022 ACM.
ABSTRACT
A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in general have problems striking the balance between diversification and intensification. Therefore, this paper aims to introduce a novel metaheuristic hybridization that combines the enhanced harmony search algorithm (EHSA) with the simulated annealing (SA) algorithm called the annealing harmony search algorithm (AHSA). The AHSA is used to solve NRP from a Malaysian hospital. The AHSA performance is compared to the EHSA, climbing harmony search algorithm (CHSA), deluge harmony search algorithm (DHSA), and harmony annealing search algorithm (HAS). The results show that the AHSA performs better than the other compared algorithms for all the tested instances where the best ever results reported for the UKMMC dataset. © 2022 Tech Science Press. All rights reserved.