Name
Abstract | ||
|---|---|---|
This paper describes and evaluates DQGen, which automatically generates multiple choice cloze questions to test a child's comprehension while reading a given text. Unlike previous methods, it generates different types of distracters designed to diagnose different types of comprehension failure, and tests comprehension not only of an individual sentence but of the context that precedes it. We evaluate the quality of the overall questions and the individual distracters, according to 8 human judges blind to the correct answers and intended distracter types. The results, errors, and judges' comments reveal limitations and suggest how to address some of them. |
Year | Venue | Keywords |
|---|---|---|
2012 | BEA@NAACL-HLT | multiple choice cloze question,distracter type,overall question,human judge,tests comprehension,comprehension cloze question,generating diagnostic multiple choice,comprehension failure,individual sentence,different type,correct answer,individual distracters |
Field | DocType | Citations |
Computer science,Artificial intelligence,Natural language processing,Sentence,Comprehension,Multiple choice | Conference | 16 |
PageRank | References | Authors |
1.06 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jack Mostow | 1 | 1133 | 263.51 |
| Hyeju Jang | 2 | 49 | 6.87 |