scholarly journals Principals' perceptions of the Massachusetts educator evaluation system

2016 ◽  
Author(s):  
Sheila A. Muir
2017 ◽  
Author(s):  
◽  
Terri Godfrey

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The purpose of this qualitative study was to examine principals' perceptions of the Missouri Educator Evaluation System (MEES) utilized in one northwest Missouri school district. Increasing public criticism over traditional teacher evaluation systems and federal mandates prompted school districts to re-design and implement new teacher evaluation models. This study gathered principals' perceptions of the impact of the MEES model. Information gathered was grouped into themes and sub-themes using three tools from the model, Professional Growth Plans, Walkthroughs, SLO's. Data collected through individual interviews, a focus group and document analysis informed the study. The population included thirteen secondary administrators, which had implemented the MEES model. An interpretive analysis of data was completed to make the following conclusions; principals perceived the walkthrough observations to have the most impact on classroom instruction, while the professional growth plans (PGP's) and student learning objectives (SLO's) had minimal effect on classroom instruction; likely due to incomplete and improper implementation. It is recommended the district continue to train principals on the MEES teacher evaluation system to increase the impact the MEES model has on classroom instruction.


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):  

2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang

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.


2012 ◽  
Vol 2 (4) ◽  
pp. 134-137
Author(s):  
Prof. Varsha karandikar ◽  
◽  
Sameer Deshpande ◽  
Pratik Deshmukh

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