Publication Date
In 2025 | 0 |
Since 2024 | 5 |
Since 2021 (last 5 years) | 6 |
Since 2016 (last 10 years) | 6 |
Since 2006 (last 20 years) | 6 |
Descriptor
Source
Author
Abdullahi Yusuf | 1 |
Amira Hassouna | 1 |
Anna Koufakou | 1 |
Binh H. Vu | 1 |
Darius Postma | 1 |
Don Hickerson | 1 |
Emily Dux Speltz | 1 |
Evgeny Chukharev-Hudilainen | 1 |
Fawthrop, D. | 1 |
Gerrard, Lisa, Ed. | 1 |
Hua Zhang | 1 |
More ▼ |
Publication Type
Reports - Research | 11 |
Journal Articles | 9 |
Books | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Practitioners | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
Anna Koufakou – Education and Information Technologies, 2024
Student opinions for a course are important to educators and administrators, regardless of the type of the course or the institution. Reading and manually analyzing open-ended feedback becomes infeasible for massive volumes of comments at institution level or online forums. In this paper, we collected and pre-processed a large number of course…
Descriptors: Learning, Opinions, Student Attitudes, Natural Language Processing
Rianne Conijn; Emily Dux Speltz; Evgeny Chukharev-Hudilainen – Reading and Writing: An Interdisciplinary Journal, 2024
Revision plays an important role in writing, and as revisions break down the linearity of the writing process, they are crucial in describing writing process dynamics. Keystroke logging and analysis have been used to identify revisions made during writing. Previous approaches include the manual annotation of revisions, building nonlinear…
Descriptors: Automation, Revision (Written Composition), Word Processing, Computers
Mike Perkins; Jasper Roe; Binh H. Vu; Darius Postma; Don Hickerson; James McGaughran; Huy Q. Khuat – International Journal of Educational Technology in Higher Education, 2024
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity…
Descriptors: Artificial Intelligence, Inclusion, Computer Software, Word Processing
Abdullahi Yusuf; Nasrin Pervin; Marcos Román-González – International Journal of Educational Technology in Higher Education, 2024
In recent years, higher education (HE) globally has witnessed extensive adoption of technology, particularly in teaching and research. The emergence of generative Artificial Intelligence (GenAI) further accelerates this trend. However, the increasing sophistication of GenAI tools has raised concerns about their potential to automate teaching and…
Descriptors: Artificial Intelligence, Educational Trends, Futures (of Society), Higher Education
Kay M. Hammond; Patricia Lucas; Amira Hassouna; Stephen Brown – Journal of University Teaching and Learning Practice, 2023
Research on academic integrity used to focus more on student character and behaviour. Now this research includes wider viewing of this issue as a current teaching and learning challenge which requires pedagogical intervention. It is now the responsibility of staff and institutions to treat the creation of a learning environment supporting academic…
Descriptors: Criticism, Automation, Word Processing, Technology Uses in Education

Yannakoudakis, E. J.; Fawthrop, D. – Information Processing and Management, 1983
This paper describes an intelligent spelling error correction system for use in a word processing environment. The system employs a dictionary of 93,769 words and, provided the intended word is in the dictionary, it identifies 80 percent to 90 percent of spelling and typing errors. Nine references are cited. (Author/EJS)
Descriptors: Algorithms, Artificial Intelligence, Computer Programs, Dictionaries

Rushinek, Avi; Rushinek, Sara – Office Systems Research Journal, 1984
Describes results of a system rating study in which users responded to WPS (word processing software) questions. Study objectives were data collection and evaluation of variables; statistical quantification of WPS's contribution (along with other variables) to user satisfaction; design of an expert system to evaluate WPS; and database update and…
Descriptors: Artificial Intelligence, Computer Software, Evaluation Methods, Information Retrieval
Kieras, David E. – 1992
The Computerized Comprehensibility System (CCS) provides an automated copy editing function, generating a mark-up of a draft of a technical document by simulating the simpler comprehension processes of a human reader, and then criticizing the text when these simple processes cannot successfully comprehend the material. A key CCS function is…
Descriptors: Artificial Intelligence, Computer Software Development, Computer System Design, Databases
Gerrard, Lisa, Ed. – 1987
Most of the essays in this collection originated as presentations at the University of California, Los Angeles, Conference on Computers and Writing, held in May 1985. Issues addressed in the volume range from concrete, practical considerations (such as designing classroom exercises) to political and theoretical ones (such as the instructor's…
Descriptors: Artificial Intelligence, Audiences, Computer Assisted Instruction, Elementary Secondary Education
Rumery, Kenneth R. – Technological Horizons in Education, 1986
Discusses the results of a survey taken of postsecondary schools with regard to the use of computers in music education programs. Indicates that a significant number of institutions have, or plan to have, music computer facilities. Describes computer uses in instruction, research, and administration of music education programs. (TW)
Descriptors: Artificial Intelligence, College Instruction, Computer Assisted Instruction, Computer Literacy