A Local Online Learning Approach for Non-linear Data

2018 ◽  
pp. 431-443
Author(s):  
Xinxing Yang ◽  
Jun Zhou ◽  
Peilin Zhao ◽  
Cen Chen ◽  
Chaochao Chen ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Approach ◽  
Non Linear

scholarly journals Effectiveness of Gamification in Flipped Learning

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402097983
Author(s):  
Abdullah Yasin Gündüz ◽  
Buket Akkoyunlu
Keyword(s):  
Online Learning ◽  
Learning Environment ◽  
Qualitative Data ◽  
Control Group ◽  
Online Learning Environment ◽  
Learning Approach ◽  
Interaction Data ◽  
Flipped Learning ◽  
Online Environment ◽  
Experimental Group

The success of the flipped learning approach is directly related to the preparation process through the online learning environment. It is clear that the desired level of academic achievement cannot be reached if the students come to class without completing their assignments. In this study, we investigated the effect of the use of gamification in the online environment of flipped learning to determine whether it will increase interaction data, participation, and achievement. We used a mixed-methods sequential explanatory design, which implies collecting and analyzing quantitative and then qualitative data. In the online learning environment of the experimental group, we used the gamification. However, participants in the control group could not access the game components. According to the findings, the experimental group had higher scores in terms of interaction data, participation, and achievement compared with the control group. Students with low participation can be encouraged to do online activities with gamification techniques.

scholarly journals Pelatihan Penerapan Online dan Blended Learning pada Masa Pandemi Covid-19 di Pondok Pesantren Arrahman Kabupaten Lombok Tengah

2021 ◽  
Vol 2 (2) ◽  
pp. 182
Author(s):  
Dedi Sumarsono ◽  
Taufik Suadiyatno ◽  
Muliani Muliani ◽  
Moh. Arsyad Arrafii ◽  
Abdul Kadir Bagis
Keyword(s):  
Program Evaluation ◽  
Online Learning ◽  
Blended Learning ◽  
Community Service ◽  
Learning Approach ◽  
New Knowledge ◽  
Near Future ◽  
Evaluation Sheet

This community service was aimed at training the teacher to be familiar with the usage of learning approach that can be applied in the time of covid-19. The training was conducted at Pondok Pesantren Arrahman attended by teachers of Madrasah Tsanawiyah, Aliyah, and SMK Darul Kamilin Bakan. To reach the goal of the program, the material and the application about the learning approach in detail for both online learning and blended learning was delivered to the participants. At the end of the program, evaluation was conducted by giving evaluation sheet to the participants to know whether or not the target of program is achieved. The response of the audience reveals that the program gave some good advantages for the participants as they have new knowledge about the learning approach applied in the time of covid-19. The participants also expected that the same program is conducted in the near future.

Caching in Dynamic Environments: a Near-optimal Online Learning Approach

2021 ◽  
pp. 1-1
Author(s):  
Shiji Zhou ◽  
Zhi Wang ◽  
Chenghao Hu ◽  
Yinan Mao ◽  
Haopeng Yan ◽  
...  
Keyword(s):  
Online Learning ◽  
Dynamic Environments ◽  
Learning Approach

An online learning approach for auto link-Configuration in IEEE 802.11ac wireless networks

2020 ◽  
Vol 181 ◽  
pp. 107426 ◽  
Author(s):  
Raja Karmakar ◽  
Samiran Chattopadhyay ◽  
Sandip Chakraborty
Keyword(s):  
Wireless Networks ◽  
Online Learning ◽  
Learning Approach ◽  
Ieee 802.11Ac

Case Study of the CUForum @ CUHK

2010 ◽  
pp. 238-258
Author(s):  
Peter Jakubowicz
Keyword(s):  
Online Learning ◽  
Hong Kong ◽  
Learning Environment ◽  
Online Communication ◽  
Future Research ◽  
Online Learning Environment ◽  
Communication Course ◽  
Non Linear ◽  
Group Interviews

In contrast to the formal school setting where learning is often linear, structured and controlled (be it online or face-to-face), for the ‘net generation,’ (Google, MySpace, MSN, YouTube and Yahoo) learning is often incidental and a sense of ‘fun’ is frequently of great importance. Such students’ learning is often non-linear, unstructured and explained well by the tenets of Anderson’s theory of online learning. This research discusses the benefits of fostering non-linearity in an online learning environment. A case study of an online business communication course at a university in Hong Kong is used to illustrate the importance of non-linear online learning by demonstrating how participants in this course adopted learning approaches that are consistent with, and a reflection of, the theory of online learning. Qualitative data from complete sets of online communication (including focus group interviews) collected over a one-semester, tertiary level course conducted at a university in Hong Kong are analyzed. The findings show that Chinese-speaking learners’ online interactions, categorized into three broad areas (cognitive, affective and social), demonstrate that interactivity is a key feature of an online learning environment. Its nature is exposed and discussed, not least the finding that for the participants in this study, learning was incidental and a sense of ‘fun’ was important. The study suggests ways in which online theory can contribute to, as well as help in, understanding this phenomenon and makes recommendations for future research.

scholarly journals SPSTracker: Sub-Peak Suppression of Response Map for Robust Object Tracking

2020 ◽  
Vol 34 (07) ◽  
pp. 10989-10996
Author(s):  
Qintao Hu ◽  
Lijun Zhou ◽  
Xiaoxiao Wang ◽  
Yao Mao ◽  
Jianlin Zhang ◽  
...  
Keyword(s):  
Online Learning ◽  
Object Tracking ◽  
Background Noise ◽  
State Of The Art ◽  
Response Suppression ◽  
Learning Approach ◽  
Response Distribution ◽  
Peak Response ◽  
Multi Scale ◽  
Tracking Response

Modern visual trackers usually construct online learning models under the assumption that the feature response has a Gaussian distribution with target-centered peak response. Nevertheless, such an assumption is implausible when there is progressive interference from other targets and/or background noise, which produce sub-peaks on the tracking response map and cause model drift. In this paper, we propose a rectified online learning approach for sub-peak response suppression and peak response enforcement and target at handling progressive interference in a systematic way. Our approach, referred to as SPSTracker, applies simple-yet-efficient Peak Response Pooling (PRP) to aggregate and align discriminative features, as well as leveraging a Boundary Response Truncation (BRT) to reduce the variance of feature response. By fusing with multi-scale features, SPSTracker aggregates the response distribution of multiple sub-peaks to a single maximum peak, which enforces the discriminative capability of features for robust object tracking. Experiments on the OTB, NFS and VOT2018 benchmarks demonstrate that SPSTrack outperforms the state-of-the-art real-time trackers with significant margins1

Sign in / Sign up

Export Citation Format

Share Document