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Automatic Assessment of Students' Free-Text Answers Underpinned by the Combination of a BLEU-Inspired Algorithm and Latent Semantic Analysis
This is an electronic version of the paper presented at the International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005 about the design and implementation of convolutional neural networks for knowledge representation. Expand
In a previous work (Perez et al., 2004) we applied Bleu (Papineni et al., 2001) in assessing short essays written by students. We showed that it outperforms other keyword-based algorithms inExpand
Application of the BLEU Method for Evaluating Free-text Answers in an E-learning Environment
BLEU, a method originally designed to evaluate automatic Machine Translation systems, is applied in assessing short essays written by students and concludes that, although it is only applicable to a restricted category of questions, BLEU attains better results than other keyword-based procedures. Expand
Application of the Bleu algorithm for recognising textual entailments
The BLEU algorithm has been applied to many different fields. In this paper, we explore a new possible use: the automatic recognition of textual entailments. BLEU works at the lexical level byExpand
Automatic Assessment of Open Ended Questions with a Bleu-Inspired Algorithm and Shallow NLP
This paper compares the accuracy of several variations of the Bleu algorithm when applied to automatically evaluating student essays and proves empirically that the accuracy is kept when the student answers are translated automatically. Expand
A Study on the Possibility of Automatically Estimating the Confidence Value of Students' Knowledge in Generated Conceptual Models
A new metric is proposed to automatically evaluate the confidence that a student knows a certain concept included in his or her conceptual model so that teachers and students can instantly see which concepts have already been assimilated and which ones should still be reviewed. Expand
Automatic Generation of Students' Conceptual Models from Answers in Plain Text
Recently, we have introduced a new procedure to automatically generate students' conceptual models to assist teachers in finding out their students' main misconceptions and lack of concepts, fromExpand
Computer-assisted assessment of free-text answers
A review of the state-of-art of the field is presented, focusing on the techniques that underpin these systems and their evaluation metrics. Expand
Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children?
An experiment with 132 Primary Education Students shows a significant increase in the results on all the tests has been measured, supporting the use of metaphors and Scratch to teach computer programming concepts to Primary Education students to develop their CT. Expand
On the Dynamic Adaptation of Computer Assisted Assessment of Free-Text Answers
A new adaptive version called Willow is presented, based on Atenea, that adds the possibility of dynamically choosing the questions to be asked according to their difficulty level, the students’ profile and previous answers. Expand