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Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee – Grantee Submission, 2021
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labor intensive and error-prone. To address this challenge, prior research proposed machine learning based solutions to auto-label educational content with limited success.…
Descriptors: Mathematics Education, Knowledge Level, Video Technology, Educational Technology
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
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
Liu, Ming; Rus, Vasile; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Question generation is an emerging research area of artificial intelligence in education. Question authoring tools are important in educational technologies, e.g., intelligent tutoring systems, as well as in dialogue systems. Approaches to generate factual questions, i.e., questions that have concrete answers, mainly make use of the syntactical…
Descriptors: Chinese, Questioning Techniques, Automation, Natural Language Processing
Cotos, Elena; Pendar, Nick – CALICO Journal, 2016
This paper reports on the development of an analysis engine for the Research Writing Tutor (RWT), an AWE program designed to provide genre and discipline-specific feedback on the functional units of research article discourse. Unlike traditional NLP-based applications that categorize complete documents, the analyzer categorizes every sentence in…
Descriptors: Discourse Analysis, Classification, Rhetoric, Writing Evaluation
Lama, Manuel; Vidal, Juan C.; Otero-Garcia, Estefania; Bugarin, Alberto; Barro, Senen – Educational Technology & Society, 2012
Large-sized repositories of learning objects (LOs) are difficult to create and also to maintain. In this paper we propose a way to reduce this drawback by improving the classification mechanisms of the LO repositories. Specifically, we present a solution to automate the LO classification of the Universia repository, a collection of more than 15…
Descriptors: Foreign Countries, Electronic Libraries, Metadata, Programming
Heiner, Cecily – ProQuest LLC, 2009
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This dissertation analyzes 411 questions from an introductory Java programming course by reducing the…
Descriptors: Programming, Information Needs, Online Courses, Teaching Assistants
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers