Assessing Students' Use of Evidence and Organization in Response-to-Text Writing: Using Natural Language Processing for Rubric-Based Automated Scoring.
Zahra RahimiDiane J. LitmanRichard CorrentiElaine WangLindsay Clare MatsumuraPublished in: Int. J. Artif. Intell. Educ. (2017)
Keyphrases
- natural language processing
- peer assessment
- free text
- text mining
- computational linguistics
- reading comprehension
- text processing
- textual data
- writing skills
- collaborative writing
- university courses
- information extraction
- assessment tool
- text summarization
- text understanding
- learning experience
- student learning
- student responses
- semester long
- learning environment
- linguistic analysis
- computer assisted
- feel comfortable
- learning outcomes
- information retrieval
- assessment process
- multiple choice
- collaborative learning
- text documents
- high school
- technology mediated
- artificial intelligence
- e learning
- college students
- undergraduate students
- intelligent tutoring systems
- learning activities
- distance learning
- machine learning
- knowledge representation
- text to speech
- question answering
- experimental design
- semantic relations
- text messaging
- student progress
- named entity recognition
- control group
- open ended
- keywords
- natural language
- higher education
- high school students
- english language
- learning styles
- university students
- learning process
- worked examples
- elementary school students
- text classification
- named entities
- communication tools
- statistical natural language processing
- formative assessment
- programming course
- english as a foreign language
- affective states