[PDF] Top 20 Semantic Features for Automated Answer Scoring
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Semantic Features for Automated Answer Scoring
... consuming. Automated system can be very useful because they can provide the student with a score as well as feedback within ...of Automated answer scoring system is felt in the educational ... See full document
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Exploring Content Features for Automated Speech Scoring
... on automated speech scoring has focused on restricted, predictable ...For automated scoring of unrestricted spontaneous speech, speech proficiency has been evaluated primarily on aspects of ... See full document
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Word Embedding based Content Features for Automated Oral Proficiency Scoring
... content features for an automated scoring system of non-native En- glish speakers’ spontaneous ...The features calculate the lexical similarity between the question text and the ASR word ... See full document
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Using collocational features to improve automated scoring of EFL texts
... and semantic non-compositionality, the vast majority of them are conventional word combi- nations that display statistical idiomaticity (Bald- win and Kim, 2010; Smiskova et ... See full document
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Identifying Patterns For Short Answer Scoring Using Graph based Lexico Semantic Text Matching
... An answer containing the text diet of koalas would be coded as follows: ...Kaggle Automated Student Assessment Prize (ASAP) competition, the largest publicly available short answer dataset (Higgins ... See full document
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Paraphrase Detection for Short Answer Scoring
... deep semantic model by (Hahn and Meurers, ...using features for token and chunk alignment reaching an accuracy of ...deep semantic model reaches an accuracy of ... See full document
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Automated Essay Scoring Using Generalized Latent Semantic Analysis
... process. Scoring students’ writing is one of the most expensive and time consuming activity for educational ...of automated assessment systems has grown exponentially in the last few years [1], [2], [5], ... See full document
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Analytic Score Prediction and Justification Identification in Automated Short Answer Scoring
... Implementation We implemented the neural baseline model with Keras and TensorFlow. The code will be made publicly available at an anony- mous URL once the paper is accepted. We chose the same hyperparameters and training ... See full document
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Speech and Text driven Features for Automated Scoring of English Speaking Tasks
... The data used in this study comes from a large- scale English proficiency assessment for non- native speakers administered in multiple coun- tries. Each test-taker answers up to 6 questions: two general and four ... See full document
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The Impact of Training Data on Automated Short Answer Scoring Performance
... The system uses support vector regression (Smola and Sch¨olkopf, 2004) to estimate a model that pre- dicts human scores from vectors of binary indica- tors for linguistic features. We use the implemen- tation from ... See full document
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Effective Feature Integration for Automated Short Answer Scoring
... These two approaches can, of course, be com- bined. However, to our knowledge, the issues of how to combine the approaches and when that is likely to be useful have not been thoroughly studied. A challenge in combining ... See full document
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Semi Supervised Clustering for Short Answer Scoring
... an answer based on the simi- larity with some sort of teacher-specified target answer and those where a target answer is not used or not even avail- ...each answer that express their ... See full document
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Investigating neural architectures for short answer scoring
... To explore the effectiveness of neural network architectures on SAS, we use the basic architec- ture and parameters of Taghipour and Ng (2016) on three publicly available short answer datasets: ASAP-SAS (Shermis, ... See full document
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Computing and Evaluating Syntactic Complexity Features for Automated Scoring of Spontaneous Non Native Speech
... complexity features, based on clausal or parse tree information derived from human transcriptions of spoken test responses, can predict holistic human rater scores for combined speaker responses over a whole test ... See full document
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Reducing Annotation Efforts in Supervised Short Answer Scoring
... In this paper, we explored approaches for minimiz- ing the required amount of annotated instances when training supervised short answer scoring systems. Instead of letting a teacher annotate all instances ... See full document
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Three-stage question answering system with sentence ranking
... We explore a recently proposed question answering system. We developed a high speed modification based on dividing the question answering system into three consecutive stages. The first step is to find the candidate ... See full document
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Automated Essay Scoring for Swedish
... of features that may be directly measured from the ...the features have been dis- cussed in previous literature on AES (Attali and Burstein, 2005), and specifically in the context of Swedish high school ... See full document
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Image Features Based on Characteristic Curves and Local Binary Patterns for Automated HER2 Scoring
... Keywords: medical image classification; local binary patterns; characteristic curves; whole slide 23.. image processing; automated HER2 scoring 24.[r] ... See full document
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Word Embedding for Response To Text Assessment of Evidence
... for scoring analytical writing when the RTA is administered in large numbers of ...this scoring method to provide formative feedback to students and teachers about students’ writing qual- ...terpretable ... See full document
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Automatic Text Scoring Using Neural Networks
... diverse features to text scoring ...essay scoring performance is improved by adding to the model information about percentages of highly associated, mildly associated and dis-associated pairs of ... See full document
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