Study on Automatic Scoring of Descriptive Type Tests using Text Similarity Calculations

نویسندگان

  • Izuru Nogaito
  • Keiji Yasuda
  • Hiroaki Kimura
چکیده

In this paper, we evaluate the automatic scoring of a descriptive type test. In the experiments, three test similarity measures are compared in terms of automatic scoring quality. Two of them are BLEU and RIBES, which are n-gram and word-level matching processes respectively, originally used for automatic evaluation of machine translation output. The other similarity process is Doc2Vec, which utilizes distributed representation to calculate the cosine distance. It was finally found that, according to the experimental results, the most efficient process used to calculate the text similarity depends on the type of the question.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Automatic and Human Scoring of Word Definition Responses

Assessing learning progress is a critical step in language learning applications and experiments. In word learning, for example, one important type of assessment is a definition production test, in which subjects are asked to produce a short definition of the word being learned. In current practice, each free response is manually scored according to how well its meaning matches the target defin...

متن کامل

Survey On: Theory Online Examination with Short Text Matching

In traditional Online Examination System, only objective type questions are assessed and according to that marks are given to the student. However, this technique lacks the capability of evaluating descriptive answers. In university examinations, there are many types of question included for evaluation of the students. Therefore, the automated system must be capable of evaluating the descriptiv...

متن کامل

Short Answer Grading Using String Similarity And Corpus-Based Similarity

Most automatic scoring systems use pattern based that requires a lot of hard and tedious work. These systems work in a supervised manner where predefined patterns and scoring rules are generated. This paper presents a different unsupervised approach which deals with students’ answers holistically using text to text similarity. Different String-based and Corpus-based similarity measures were tes...

متن کامل

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

متن کامل

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016