scholarly journals Learning Ability and Supporting Capacity of Online Learning In Students during Covid-19 Pandemic

2021 ◽  
Vol 747 (1) ◽  
pp. 012080
Author(s):  
F Hermanto ◽  
N A Putri
Actuators ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 118
Author(s):  
Huu Tho Nguyen ◽  
Van Chon Trinh ◽  
Thanh Danh Le

Due to the time-varying nonlinear dynamic, uncertain model and hysteresis characteristics of the pneumatic artificial muscle (PAM) actuator, it is not easy to apply model-based control algorithms for monitoring, as well as controlling, the operation of systems driven by PAM actuators. Hence, the main aim of this work is to propose an intelligent controller named adaptive sliding controller adding compensator (ASC + C) to operate a robotic arm, featuring a pneumatic artificial muscle actuator, which assists rehabilitation exercise of the elbow joint function. The structure of the proposed controller is a combination between the fuzzy logic technique and Proportional Integral Derivative (PID) algorithm. In which, the input of fuzzy logic controller is the sliding surface, meanwhile, its output is the estimated value of the unknown nonlinear function, meaning that the model-based requirement is released. A PID controller works as a compensator with online learning ability and is designed to compensate because of the approximate error and hysteresis characteristic. Additionally, to improve convergence and to obtain stability, a fast terminal sliding manifold is introduced and online learning laws for parameters of the controller are attainted through the stable criterion of Lyapunov. Finally, an experimental apparatus is also fabricated to evaluate control response of the system. The experimental result confirmed strongly the ability of the proposed controller, which indicates that the ASC + C can obtain a steady state tracking error less than 5 degrees and a position response without overshoot.


2021 ◽  
Vol 40 (2) ◽  
pp. 374-388
Author(s):  
Nani Sutarni ◽  
M Arief Ramdhany ◽  
Achmad Hufad ◽  
Eri Kurniawan

The unprecedented changes in the education sector due to the recent pandemic demand teachers and students to adapt to new ways of learning via online platforms. A plethora of latest research has investigated various topics such as online learning platforms, online learning materials, and teacher/student perceptions; however, little is known about the link between online learning and achievement. Occupying this lacuna, this study specifically sought to examine the relationship between self-regulated learning (SRL), the digital learning environment, and student’ academic achievement during the pandemic.  The population of this research was 1,800 students (freshmen, sophomore, junior, and senior class) enrolled for the Introduction to Management course at a state university in Bandung, Indonesia. Selected using a proportionate random sampling, 317 students participated as the respondents.  The data were collected through questionnaire surveys, while the Structural Equation Model (SEM) was employed to analyze the interrelationship among the construct variables.  The results of this study show that promoting SRL may affect the optimization of the digital learning environment and academic achievements.  Students with better self-regulated learning ability can somehow optimize their digital learning environment and be more progressive in terms of academic achievement.


2021 ◽  
Vol 9 (1) ◽  
pp. 113
Author(s):  
Rahmat Yusny ◽  
Fitria Rizki ◽  
Ika Kana Trisnawati ◽  
Mulia Mulia

Given the intensified number of online learning activities and having inadequate knowledge to identify the details of how it was organized within increased students’ language learning ability; this study focused on identifying the students’ perceptions of learning in two different situations. This study investigated how students perceived working in a new learning mode (online learning activity) compared to the traditional or face-to-face learning mode (offline learning activity) in regards to the learning frameworks, including the depth and comprehensiveness of learning, appropriate length for learning, comfortability of learning, and flexibility of learning. Ten students were selected to be the participants of the current study; all of whom were sixth and eighth semester students at the Department of English Language Education of Universitas Islam Negeri Ar-Raniry Banda Aceh. They were served by several questions related to their experiences working on two different learning modes. The findings revealed that working in offline learning mode was still the common preference among the students and only a few of them preferred online learning. Even more interesting was the finding of one or two students who perceived no differences between participating in offline and online class learning activities. In addition, the findings also indicated that interaction between the course instructors and students still becomes a prominent element on the students’ satisfaction and comfort of learning. The students also suggested that the keys to their satisfactory learning experiences are access to learning materials and to their class instructors. To conclude, this study also provides new insights on what matters the most to the students’ learning experiences with respect to the current online learning trend. 


1997 ◽  
Vol 8 (5) ◽  
pp. 196-200 ◽  
Author(s):  
M.N. Polkinghorne ◽  
G.N. Roberts ◽  
B.S. Burns

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Wei ◽  
Shiyun Sun ◽  
Dan Wu ◽  
Liang Zhou

The objective of the study is to explore an effective way for providing students with the appropriate learning resources in the remote education scenario. Artificial intelligence (AI) technology and educational psychology theory are applied for designing a personalized online learning resource recommendation scheme to improve students' learning outcomes. First, according to educational psychology, students' learning ability can be obtained by analyzing their learning behaviors. Their identities can be classified into three main groups. Then, features of learning resources such as difficulty degree are extracted, and a LinUCB-based learning resource recommendation algorithm is proposed. In this algorithm, a personalized exploration coefficient is carefully constructed according to student's ability and attention scores. It can adaptively adjust the ratio of exploration and exploitation during recommendation. Finally, experiments are conducted for evaluating the superior performance of the proposed scheme. The experimental results show that the proposed recommendation scheme can find appropriate learning resources which will match the student's ability and satisfy the student's personalized demands. Meanwhile, by comparing with existing state-of-the-art recommendation schemes, the proposed scheme can achieve accurate recommendations, so as to provide students with the most suitable online learning resources and reduce the risk brought by exploration. Therefore, the proposed scheme can not only control the difficulty degree of learning resources within the student's ability but also encourage their potential by providing suitable learning resources.


Author(s):  
Noviana Desiningrum

The research was conductedon for the first semester students of mathematics education faculty at STKIP-BIM Surabaya. The purpose of this research included:1) Obtain data on Implementation of Online Learning Program (OLP) with Media Multimedia-Based Learning, 2) Obtaindataonstudentcomprehension, 3) Obtainthe datapassing gradestudents, 4) Obtain data on Student Response. The research method which is used in this research is byusing the Classroom Action Research (Classroom Action Research). The results from this study include: view sof students' understanding forthe learning ability of OLP in the first cycle of 60.2 %, where asin the second cycle of 97% resulting in an increase in the percentage of 36.8% and the learning is successful. View ed from masteryof learning out comes in the first cycle was 68.5% while the second cycle of 80.5%, an increase of 12%. The  students response for the Online Learning Program (OLP) model based multimedia which is including positive category. From this case, it can be said already managed to apply the learning for the student.


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