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Showing 796 to 810 of 1,521 results Save | Export
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George Hanshaw; Joanna Vance; Craig Brewer – Open Praxis, 2024
This study examines the impact of AI course assistants on student learning experiences in online undergraduate courses at Los Angeles Pacific University. A controlled experiment involving 92 students across treatment and control groups was conducted to evaluate the effectiveness of AI assistants developed by Nectir. The treatment group had access…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Student Experience, Undergraduate Students
Mozer, Reagan; Miratrixy, Luke; Relyea, Jackie Eunjung; Kim, James S. – Annenberg Institute for School Reform at Brown University, 2021
In a randomized trial that collects text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by human raters. An impact analysis can then be conducted to compare treatment and control groups, using the hand-coded scores as a measured outcome. This…
Descriptors: Scoring, Automation, Data Analysis, Natural Language Processing
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Rybinski, Krzysztof – Quality Assurance in Education: An International Perspective, 2020
Purpose: This paper aims to analyse the relationship between two measures of university quality, the outcome and other characteristics of a mandatory accreditation and the university position in the national ranking. Design/methodology/approach: Natural language processing (NLP) models are used to calculate the sentiment indicators for 1,850…
Descriptors: Foreign Countries, Reputation, Accreditation (Institutions), Higher Education
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Terzopoulos, George; Satratzemi, Maya – Informatics in Education, 2020
In recent years, Artificial Intelligence (AI) has shown significant progress and its potential is growing. An application area of AI is Natural Language Processing (NLP). Voice assistants incorporate AI by using cloud computing and can communicate with the users in natural language. Voice assistants are easy to use and thus there are millions of…
Descriptors: Artificial Intelligence, Natural Language Processing, Assistive Technology, Technology Uses in Education
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Fonseca, Samuel C.; Pereira, Filipe Dwan; Oliveira, Elaine H. T.; Oliveira, David B. F.; Carvalho, Leandro S. G.; Cristea, Alexandra I. – International Educational Data Mining Society, 2020
As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as 'Online Judges'. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, this may cause difficulties to learners that do not have the typical intrinsic motivation for…
Descriptors: Programming, Introductory Courses, Computer Science Education, Automation
Kylie L. Anglin; Vivian C. Wong – Annenberg Institute for School Reform at Brown University, 2020
Researchers are rarely satisfied to learn only whether an intervention works, they also want to understand why and under what circumstances interventions produce their intended effects. These questions have led to increasing calls for implementation research to be included in high quality studies with strong causal claims. Of critical importance…
Descriptors: Intervention, Artificial Intelligence, Natural Language Processing, Semantics
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Salas-Pilco, Sdenka Zobeida; Yang, Yuqin – International Journal of Educational Technology in Higher Education, 2022
Over the last decade, there has been great research interest in the application of artificial intelligence (AI) in various fields, such as medicine, finance, and law. Recently, there has been a research focus on the application of AI in education, where it has great potential. Therefore, a systematic review of the literature on AI in education is…
Descriptors: Artificial Intelligence, Higher Education, Foreign Countries, Technology Uses in Education
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Zhang, Mo; Sinharay, Sandip – International Journal of Testing, 2022
This article demonstrates how recent advances in technology allow fine-grained analyses of candidate-produced essays, thus providing a deeper insight on writing performance. We examined how essay features, automatically extracted using natural language processing and keystroke logging techniques, can predict various performance measures using data…
Descriptors: At Risk Persons, Writing Achievement, Educational Technology, Writing Improvement
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Sullivan, Florence R.; Keith, P. Kevin – British Journal of Educational Technology, 2019
In this study, we explore the potential of a natural language processing (NLP) approach to support discourse analysis of in-situ, small group learning conversations. The theoretical basis of this work derives from Bakhtin's notion of speech genres as bounded by educational robotics activity. Our goal is to leverage computational linguistics…
Descriptors: Natural Language Processing, Discourse Analysis, Group Discussion, Middle School Students
Guerrero, Tricia A.; Wiley, Jennifer – Grantee Submission, 2019
Teachers may wish to use open-ended learning activities and tests, but they are burdensome to assess compared to forced-choice instruments. At the same time, forced-choice assessments suffer from issues of guessing (when used as tests) and may not encourage valuable behaviors of construction and generation of understanding (when used as learning…
Descriptors: Computer Assisted Testing, Student Evaluation, Introductory Courses, Psychology
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Xiaoling Bai; Nur Rasyidah Mohd Nordin – Eurasian Journal of Applied Linguistics, 2025
A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…
Descriptors: Artificial Intelligence, Feedback (Response), Evaluators, Writing Skills
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Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Crossley, Scott; Wan, Qian; Allen, Laura; McNamara, Danielle – Grantee Submission, 2021
Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…
Descriptors: Writing Skills, Cognitive Processes, Essays, Cues
Lynette Hazelton; Jessica Nastal; Norbert Elliot; Jill Burstein; Daniel F. McCaffrey – Grantee Submission, 2021
In writing studies research, automated writing evaluation technology is typically examined for a specific, often narrow purpose: to evaluate a particular writing improvement measure, to mine data for changes in writing performance, or to demonstrate the effectiveness of a single technology and accompanying validity arguments. This article adopts a…
Descriptors: Formative Evaluation, Writing Evaluation, Automation, Natural Language Processing
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Liu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
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