Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Computational Linguistics | 3 |
| Natural Language Processing | 3 |
| Problem Solving | 3 |
| Academic Achievement | 1 |
| Achievement Gains | 1 |
| Artificial Languages | 1 |
| College Students | 1 |
| Computer Assisted Instruction | 1 |
| Computer Assisted Testing | 1 |
| Computer Science Education | 1 |
| Computer Software | 1 |
| More ▼ | |
Author
| Chang, Chun-Yen | 1 |
| Dye, Melody | 1 |
| Li, Tsai-Yen | 1 |
| Reilly, Joseph M. | 1 |
| Schneider, Bertrand | 1 |
| Wang, Hao-Chuan | 1 |
Publication Type
| Reports - Research | 2 |
| Dissertations/Theses -… | 1 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Elementary Secondary Education | 1 |
| Higher Education | 1 |
| Postsecondary Education | 1 |
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Dye, Melody – ProQuest LLC, 2017
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a…
Descriptors: Computational Linguistics, Natural Language Processing, Artificial Languages, Computer Software
Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
Wang, Hao-Chuan; Chang, Chun-Yen; Li, Tsai-Yen – Computers & Education, 2008
The work aims to improve the assessment of creative problem-solving in science education by employing language technologies and computational-statistical machine learning methods to grade students' natural language responses automatically. To evaluate constructs like creative problem-solving with validity, open-ended questions that elicit…
Descriptors: Interrater Reliability, Earth Science, Problem Solving, Grading

Direct link
Peer reviewed
