scholarly journals Prediction of Writing True Scores in Automated Scoring of Essays by Best Linear Predictors and Penalized Best Linear Predictors

2019 ◽  
Vol 2019 (1) ◽  
pp. 1-27 ◽  
Author(s):  
Lili Yao ◽  
Shelby J. Haberman ◽  
Mo Zhang
Keyword(s):  
Automated Scoring ◽  
Linear Predictors ◽  
True Scores

Validating human and automated scoring of essays against “True” scores

2018 ◽  
Vol 31 (3) ◽  
pp. 241-250
Author(s):  
Yoav Cohen ◽  
Effi Levi ◽  
Anat Ben-Simon
Keyword(s):  
Automated Scoring ◽  
True Scores

Tolerance Intervals for True Scores

1985 ◽  
Vol 10 (1) ◽  
pp. 1-17 ◽  
Author(s):  
David Jarjoura
Keyword(s):  
Confidence Intervals ◽  
Practical Implication ◽  
Educational Measurement ◽  
True Score ◽  
Tolerance Intervals ◽  
Observed Score ◽  
True Scores

Issues regarding tolerance and confidence intervals are discussed within the context of educational measurement and conceptual distinctions are drawn between these two types of intervals. Points are raised about the advantages of tolerance intervals when the focus is on a particular observed score rather than a particular examinee. Because tolerance intervals depend on strong true score models, a practical implication of the study is that true score tolerance intervals are fairly insensitive to differences in assumptions among the five models studied.

scholarly journals High-throughput behavioral screen in C. elegans reveals Parkinson’s disease drug candidates

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Salman Sohrabi ◽  
Danielle E. Mor ◽  
Rachel Kaletsky ◽  
William Keyes ◽  
Coleen T. Murphy
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
High Throughput ◽  
Potential Candidate ◽  
Automated Scoring ◽  
C Elegans ◽  
Drug Candidates ◽  
Branched Chain ◽  
Approved Drugs

AbstractWe recently linked branched-chain amino acid transferase 1 (BCAT1) dysfunction with the movement disorder Parkinson’s disease (PD), and found that RNAi-mediated knockdown of neuronal bcat-1 in C. elegans causes abnormal spasm-like ‘curling’ behavior with age. Here we report the development of a machine learning-based workflow and its application to the discovery of potentially new therapeutics for PD. In addition to simplifying quantification and maintaining a low data overhead, our simple segment-train-quantify platform enables fully automated scoring of image stills upon training of a convolutional neural network. We have trained a highly reliable neural network for the detection and classification of worm postures in order to carry out high-throughput curling analysis without the need for user intervention or post-inspection. In a proof-of-concept screen of 50 FDA-approved drugs, enasidenib, ethosuximide, metformin, and nitisinone were identified as candidates for potential late-in-life intervention in PD. These findings point to the utility of our high-throughput platform for automated scoring of worm postures and in particular, the discovery of potential candidate treatments for PD.

scholarly journals Do Learning Approaches Set the Stage for Emotional Well-Being in College Students?

2020 ◽  
Vol 12 (17) ◽  
pp. 6984
Author(s):  
Jesús de la Fuente ◽  
Francisco Javier Peralta-Sánchez ◽  
José Manuel Martínez-Vicente ◽  
Flavia H. Santos ◽  
Salvatore Fadda ◽  
...  
Keyword(s):  
Approaches To Learning ◽  
Well Being ◽  
Personality Factors ◽  
Learning Approaches ◽  
Achievement Emotions ◽  
Approach To Learning ◽  
Ex Post ◽  
Ex Post Facto ◽  
Deep Approach To Learning ◽  
Linear Predictors

The research aim of this paper was two-fold: to generate evidence that personality factors are linear predictors of the variable approaches to learning (a relevant cognitive-motivational variable of Educational Psychology); and to show that each type of learning approach differentially predicts positive or negative achievement emotions, in three learning situations: class time, study time, and testing. A total of 658 university students voluntarily completed validated questionnaires referring to these three variables. Using an ex post facto design, we conducted correlational analyses, regression analyses, and multiple structural predictions. The results showed that Conscientiousness is associated with and predicts a Deep Approach to learning, while also predicting positive achievement emotions. By contrast, Neuroticism is associated with and significantly predicts a Surface Approach to learning, as well as negative achievement emotions. There are important psychoeducational implications in the university context, both for prevention and for self-improvement, and for programs that offer psychoeducational guidance.

scholarly journals Automated scoring of fear-related behavior using EthoVision software

2009 ◽  
Vol 178 (2) ◽  
pp. 323-326 ◽  
Author(s):  
Jon Pham ◽  
Sara M. Cabrera ◽  
Carles Sanchis-Segura ◽  
Marcelo A. Wood
Keyword(s):  
Automated Scoring

A Review of Strategies for Validating Computer-Automated Scoring

2002 ◽  
Vol 15 (4) ◽  
pp. 391-412 ◽  
Author(s):  
Yongwei Yang ◽  
Chad W. Buckendahl ◽  
Piotr J. Juszkiewicz ◽  
Dennison S. Bhola
Keyword(s):  
Automated Scoring
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