scholarly journals A Criteria Based Course And Instructor Evaluation System

2020 ◽  
Author(s):  
David G. Meyer
Keyword(s):  
Evaluation System ◽  
Instructor Evaluation

scholarly journals Creating a sustainable online instructor observation system: A case study highlighting flaws when blending mentoring and evaluation

2012 ◽  
Vol 13 (3) ◽  
pp. 83 ◽  
Author(s):  
Marthann Schulte ◽  
Kay Dennis ◽  
Michael Eskey ◽  
Cathy Taylor ◽  
Heather Zeng
Keyword(s):  
Evaluation System ◽  
Evaluation Research ◽  
Faculty Evaluation ◽  
Faculty Training ◽  
Observation System ◽  
Instructor Training ◽  
Instructor Evaluation ◽  
System A ◽  
Online Instructor

Quality and accountability mandates require institutions to monitor online instruction in a uniform and complete manner. In many institutions, instructor training is sparse and faculty evaluation occurs only through end-of-course student evaluations that may or may not yield adequate information on how the instructor performs online. Consequently, the<em> online instructor evaluation system </em>(OIES) was developed to ensure the finest quality educational experience for online students via a systematic approach to faculty training, mentoring, and evaluation. Research has shown that combining mentoring and evaluation is not feasible, and therefore another approach is warranted.<br /><input id="gwProxy" type="hidden" /><input id="jsProxy" onclick="if(typeof(jsCall)=='function'){jsCall();}else{setTimeout('jsCall()',500);}" type="hidden" />

DEVELOPING AN ON-LINE COURSE/INSTRUCTOR EVALUATION SYSTEM

2006 ◽  
Vol 3 (3) ◽  
Author(s):  
V. Pougatchev ◽  
N. George ◽  
G. Lue ◽  
R. Williams
Keyword(s):  
Evaluation System ◽  
Instructor Evaluation ◽  
On Line

A proposed method for assessing the quality of sealants - the CCC Sealant Evaluation System

2001 ◽  
Vol 29 (2) ◽  
pp. 83-91 ◽  
Author(s):  
Christopher Deery ◽  
Hazel E. Fyffe ◽  
Zoann J. Nugent ◽  
Nigel M. Nuttall ◽  
Nigel B. Pitts
Keyword(s):  
Evaluation System

Intelligent system of English composition scoring model based on improved machine learning algorithm

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang
Keyword(s):  
Machine Learning ◽  
Evaluation System ◽  
Intelligent System ◽  
Learning Algorithm ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Assessment System ◽  
English Composition ◽  
Region Extraction ◽  
Constraint Model

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.

Development and Implementation of Productivity Evaluation System: Design Standard Time Ratio

2012 ◽  
Vol 2 (4) ◽  
pp. 134-137
Author(s):  
Prof. Varsha karandikar ◽  
◽  
Sameer Deshpande ◽  
Pratik Deshmukh
Keyword(s):  
System Design ◽  
Evaluation System ◽  
Design Standard ◽  
Standard Time ◽  
Time Ratio
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