Student Response Analysis using Textual Entailment
Devanshu Arya, 10229
Ashudeep Singh, 10162
Instructor: Dr. Amitabha Mukerjee
2013-14
A major task in Educational NLP is to assess student responses to examination questions, homeworks and intelligent tutors.
Much of the related work has been done in evaluating student essays, error detection and correction and grade level text classification.
A subtask in student dialogue systems is Student Response Analysis (SRA) i.e. given a question and a reference answer, the system need to analyze student response and decide whether it is correct or else give a suitable feedback.
A key requirement to accomplish this is semantic inference, for example to detect whether the student answers say the same thing as the reference answer in different words or contradict it.
Proposal
Presentation
Poster
Final report
Code
Ashudeep Singh, 10162
Instructor: Dr. Amitabha Mukerjee
2013-14
Abstract
A major task in Educational NLP is to assess student responses to examination questions, homeworks and intelligent tutors.
Much of the related work has been done in evaluating student essays, error detection and correction and grade level text classification.
A subtask in student dialogue systems is Student Response Analysis (SRA) i.e. given a question and a reference answer, the system need to analyze student response and decide whether it is correct or else give a suitable feedback.
A key requirement to accomplish this is semantic inference, for example to detect whether the student answers say the same thing as the reference answer in different words or contradict it.
Proposal and Pre-Completion Project Presentation
Proposal
Presentation
Poster
Poster
Report
Final report
Code
Code
Contact