Exploration in Collaborative and Group Learning of Physical Experiments

2008 ◽  
Author(s):  
Li Jiaxing
Keyword(s):  
Group Learning ◽  
Physical Experiments

PENGARUH STRATEGI BELAJAR KELOMPOK TERHADAP HASIL BELAJAR BAHASA INGGRIS SISWA KELAS VII SMP NEGERI 2 BANGKINANG KOTA KABUPATEN KAMPAR

2018 ◽  
Vol 2 (5) ◽  
pp. 682
Author(s):  
Masniar Masniar
Keyword(s):  
Learning Outcomes ◽  
Junior High School ◽  
Group Learning ◽  
Good Alternative ◽  
Observation Data ◽  
English Learning ◽  
Public Middle School ◽  
New Ideas ◽  
Almost All ◽  
Daily Test

Various difficulties in learning English which have been an obstacle for almost all students, this should be avaluable lesson to spark new ideas in group learning implementation programs. To overcome the problem of thelow level of English learning outcomes of class VII students of Bangkinang State 2 Junior High School inKampar Regency, group learning is one good alternative. The study is a classroom action research conducted inBangkinang Kota 2 Public Middle School, Kampar district. The subjects of this study were seventh gradestudents. The results of the study obtained data on teacher activity in the first cycle of the first meeting with apercentage of 57%, the second meeting with a percentage of 66.5%, in the second cycle at the third meeting thepercentage was 83.5%, and at the fourth meeting percentage obtained 90.5%. The observation data of studentsin the first cycle of the 1st meeting was 51%, the second meeting was 62.5%, in the second cycle the thirdmeeting was 80%, and the fourth meeting was 88%. Data on the improvement of learning outcomes in the initialdata obtained an average of 63, in daily I repetition of 75, and in the second daily test of 88.

Scaffolding group learning in a collaborative networked environment

2002 ◽  
Author(s):  
Amy S. Wu ◽  
Rob Farrell ◽  
Mark K. Singley
Keyword(s):  
Group Learning

scholarly journals Task space adaptation via the learning of gait controllers of magnetic soft millirobots

2021 ◽  
pp. 027836492110218
Author(s):  
Sinan O. Demir ◽  
Utku Culha ◽  
Alp C. Karacakol ◽  
Abdon Pena-Francesch ◽  
Sebastian Trimpe ◽  
...  
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Bayesian Optimization ◽  
Small Scale ◽  
Soft Robots ◽  
Modeling And Control ◽  
Walking Gait ◽  
Physical Experiments ◽  
Efficient Learning ◽  
Task Environments

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

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