Xiao et al., 2018 - Google Patents
Automatic generation of multiple-choice items for prepositions based on word2vecXiao et al., 2018
- Document ID
- 3170338317828331926
- Author
- Xiao W
- Wang M
- Zhang C
- Tan Y
- Chen Z
- Publication year
- Publication venue
- International conference of pioneering computer scientists, engineers and educators
External Links
Snippet
The automatic generation of multiple-choice item (MI) has attracted amounts of attention. However, only a limited number of existing research address automatic MI generation for prepositions, and even fewer consider learners' need in the generation process. In this …
- 238000000034 method 0 abstract description 10
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2705—Parsing
- G06F17/271—Syntactic parsing, e.g. based on context-free grammar [CFG], unification grammars
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
- G06F17/277—Lexical analysis, e.g. tokenisation, collocates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/28—Processing or translating of natural language
- G06F17/2809—Data driven translation
- G06F17/2827—Example based machine translation; Alignment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2785—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/274—Grammatical analysis; Style critique
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/28—Processing or translating of natural language
- G06F17/289—Use of machine translation, e.g. multi-lingual retrieval, server side translation for client devices, real-time translation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/28—Processing or translating of natural language
- G06F17/2872—Rule based translation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B7/00—Electrically-operated teaching apparatus or devices working with questions and answers
- G09B7/02—Electrically-operated teaching apparatus or devices working with questions and answers of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B19/00—Teaching not covered by other main groups of this subclass
- G09B19/06—Foreign languages
- G09B19/08—Printed or written appliances, e.g. text books, bilingual letter assemblies, charts
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Cavalcanti et al. | How good is my feedback? a content analysis of written feedback | |
Burstein et al. | The e-rater® automated essay scoring system | |
Correia et al. | Automatic generation of cloze question stems | |
Gamon et al. | Using statistical techniques and web search to correct ESL errors | |
Pong-Inwong et al. | Sentiment analysis in teaching evaluations using sentiment phrase pattern matching (SPPM) based on association mining | |
Liu et al. | Automatic question generation for literature review writing support | |
Villalón et al. | Glosser: Enhanced feedback for student writing tasks | |
CN114462389A (en) | Automatic test paper subjective question scoring method | |
Rüdian et al. | Challenges of using auto-correction tools for language learning | |
Nassiri et al. | Approaches, methods, and resources for assessing the readability of arabic texts | |
Bannò et al. | Back to grammar: Using grammatical error correction to automatically assess L2 speaking proficiency | |
Menini et al. | Automated Short Answer Grading: A Simple Solution for a Difficult Task. | |
Benedetto et al. | Abstractive video lecture summarization: applications and future prospects | |
Jiménez et al. | Sentiment Analysis of Student Surveys--A Case Study on Assessing the Impact of the COVID-19 Pandemic on Higher Education Teaching. | |
Sukkarieh et al. | Auto-marking 2: An update on the UCLES-Oxford University research into using computational linguistics to score short, free text responses | |
Arshad et al. | Comprehensive readability assessment of scientific learning resources | |
Han et al. | Beyond BLEU: Repurposing neural-based metrics to assess interlingual interpreting in tertiary-level language learning settings | |
Lee et al. | Building an automated English sentence evaluation system for students learning English as a second language | |
Xiao et al. | Automatic generation of multiple-choice items for prepositions based on word2vec | |
Qin et al. | Machine-assisted writing evaluation: exploring pre-trained language models in analyzing argumentative moves | |
Riza et al. | Natural language processing and levenshtein distance for generating error identification typed questions on TOEFL | |
Duan et al. | Automatically build corpora for chinese spelling check based on the input method | |
Ravikiran et al. | TEEMIL: Towards Educational MCQ Difficulty Estimation in Indic Languages | |
Shweta et al. | Comparative study of feature engineering for automated short answer grading | |
Tschichold et al. | Intelligent CALL and written language |