Publication Date
| In 2026 | 0 |
| Since 2025 | 2 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 4 |
| Since 2007 (last 20 years) | 6 |
Descriptor
| Automation | 6 |
| Natural Language Processing | 6 |
| Program Effectiveness | 6 |
| Artificial Intelligence | 4 |
| Feedback (Response) | 4 |
| Online Courses | 4 |
| Foreign Countries | 3 |
| Scoring | 3 |
| Academic Achievement | 2 |
| Chinese | 2 |
| College Students | 2 |
| More ▼ | |
Source
| Annenberg Institute for… | 1 |
| International Educational… | 1 |
| International Journal of… | 1 |
| International Working Group… | 1 |
| Journal of Computer Assisted… | 1 |
| Turkish Online Journal of… | 1 |
Author
| Calders, Toon | 1 |
| Conati, Cristina | 1 |
| Demszky, Dorottya | 1 |
| Desmarais, Michel, Ed. | 1 |
| Detlef Urhahne | 1 |
| Elisabeth Bauer | 1 |
| Frank Fischer | 1 |
| Frank Niklas | 1 |
| Hill, Heather C. | 1 |
| Jan Kiesewetter | 1 |
| Jan M. Zottmann | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 4 |
| Journal Articles | 3 |
| Collected Works - Proceedings | 2 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 3 |
| Elementary Education | 2 |
| Postsecondary Education | 2 |
| Elementary Secondary Education | 1 |
| Grade 4 | 1 |
| Grade 6 | 1 |
| Grade 8 | 1 |
| High Schools | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Secondary Education | 1 |
| More ▼ | |
Audience
Location
| Brazil | 1 |
| Germany | 1 |
| Netherlands | 1 |
| Taiwan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| International English… | 1 |
What Works Clearinghouse Rating
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Xinming Chen; Ziqian Zhou; Malila Prado – International Journal of Assessment Tools in Education, 2025
This study explores the efficacy of ChatGPT-3.5, an AI chatbot, used as an Automatic Essay Scoring (AES) system and feedback provider for IELTS essay preparation. It investigates the alignment between scores given by ChatGPT-3.5 and those assigned by official IELTS examiners to establish its reliability as an AES. It also identifies the strategies…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Demszky, Dorottya; Liu, Jing; Hill, Heather C.; Jurafsky, Dan; Piech, Chris – Annenberg Institute for School Reform at Brown University, 2021
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource intensive in most educational contexts. We develop an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage teaching practice that…
Descriptors: Automation, Feedback (Response), Online Courses, Teaching Methods
Liao, Chen-Huei; Kuo, Bor-Chen; Pai, Kai-Chih – Turkish Online Journal of Educational Technology - TOJET, 2012
Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children's Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function…
Descriptors: Foreign Countries, Program Effectiveness, Scoring, Personality
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring

Peer reviewed
Direct link
