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Ruchi Doshi, Editor; Manish Dadhich, Editor; Sandeep Poddar, Editor; Kamal Kant Hiran, Editor – IGI Global, 2024
A new challenge has become present in the field of generative artificial intelligence (AI). The fundamental nature of education, a vital element for advancing the United Nations' Sustainable Development Goals (SDGs), now grapples with the transformative impact of AI technologies. As we stand at this intersection of progress and pedagogy, critical…
Descriptors: Artificial Intelligence, Sustainable Development, Technology Uses in Education, Educational Innovation
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Educational Data Mining Society, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
Bermudez-Gonzalez, Daniel; Miranda-Jiménez, Sabino; García-Moreno, Raúl-Ulises; Calderón-Nepamuceno, Dora – Research-publishing.net, 2016
Nowadays, machine learning techniques are being used in several Natural Language Processing (NLP) tasks such as Opinion Mining (OM). OM is used to analyse and determine the affective orientation of texts. Usually, OM approaches use affective dictionaries in order to conduct sentiment analysis. These lexicons are labeled manually with affective…
Descriptors: Dictionaries, Spanish, Natural Language Processing, Psychological Patterns
Cai, Zhiqiang; Gong, Yan; Qiu, Qizhi; Hu, Xiangen; Graesser, Art – Grantee Submission, 2016
AutoTutor uses conversational intelligent agents in learning environments. One of the major challenges in developing AutoTutor applications is to assess students' natural language answers to AutoTutor questions. We investigated an AutoTutor dataset with 3358 student answers to 49 AutoTutor questions. In comparisons with human ratings, we found…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Dialogs (Language), Programming
González-Castro, Nuria; Muñoz-Merino, Pedro J.; Alario-Hoyos, Carlos; Delgado Kloos, Carlos – Australasian Journal of Educational Technology, 2021
Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that…
Descriptors: Online Courses, Learning Modules, Computer Science Education, Programming
Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara; Philippe Dessus; Stefan Trausan-Matu – Grantee Submission, 2018
A critical task for tutors is to provide learners with suitable reading materials in terms of difficulty. The challenge of this endeavor is increased by students' individual variability and the multiple levels in which complexity can vary, thus arguing for the necessity of automated systems to support teachers. This chapter describes…
Descriptors: Reading Materials, Difficulty Level, Natural Language Processing, Artificial Intelligence
Haapanen, Lauri; Leppänen, Leo – AILA Review, 2020
The amount of available digital data is increasing at a tremendous rate. These data, however, are of limited use unless converted into a user-friendly form. We took on this task and built a natural language generation (NLG) driven system that generates journalistic news stories about elections without human intervention. In this paper, after…
Descriptors: News Reporting, Journalism, Elections, Computational Linguistics
Moon, Jewoong; Ke, Fengfeng; Sokolikj, Zlatko – British Journal of Educational Technology, 2020
Tracking students' learning states to provide tailored learner support is a critical element of an adaptive learning system. This study explores how an automatic assessment is capable of tracking learners' cognitive and emotional states during virtual reality (VR)-based representational-flexibility training. This VR-based training program aims to…
Descriptors: Adolescents, Autism, Pervasive Developmental Disorders, Learning Processes
Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe – Computer Assisted Language Learning, 2022
Often, second/foreign (L2) language learners receive little opportunity to interact orally in the target language. Interactive, conversation-based spoken dialog systems (SDSs) that use automated speech recognition and natural language processing have the potential to address this need by engaging learners in meaningful, goal-oriented speaking…
Descriptors: Second Language Learning, Second Language Instruction, Oral Language, Dialogs (Language)
Mahmoud M. S. Abdallah – Online Submission, 2025
This article offers a rigorous and forward-looking examination of contemporary research directions and transformative trends within the fields of TESOL (Teaching English to Speakers of Other Languages) and TEFL (Teaching English as a Foreign Language). Positioned at the intersection of rapidly evolving technologies, innovative pedagogies, and…
Descriptors: English (Second Language), Second Language Instruction, Second Language Learning, Language Teachers
Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
Michelle P. Banawan; Jinnie Shin; Tracy Arner; Renu Balyan; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…
Descriptors: Algebra, Discourse Analysis, Semantics, Syntax
Dominique J. Baker; Lauren Mena Shook; Jaime Ramirez-Mendoza; Christopher T. Bennett – Annenberg Institute for School Reform at Brown University, 2023
The media discourse on student loans plays a significant role in the way that policy actors conceptualize challenges and potential solutions related to student debt. This study examines the racialized language in student loan news articles published in eight major news outlets between 2006 and 2021. We found that 18% of articles use any racialized…
Descriptors: Race, Student Financial Aid, Loan Repayment, Loan Default

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