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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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
Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
Ouissem, Benmesbah; Lamia, Mahnane; Hafidi, Mohamed – International Journal of Web-Based Learning and Teaching Technologies, 2021
Context modeling is the keystone to enable the intelligent system to adapt its functionalities properly to different situations. As such, a representation mechanism that allows an adequate manipulation of this kind of information is required, and diverse approaches have been introduced; however, what takes more value and is being positioned as a…
Descriptors: Electronic Learning, Educational Technology, Models, Educational Methods
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
Geller, Shay A.; Gal, Kobi; Segal, Avi; Sripathi, Kamali; Kim, Hyunsoo G.; Facciotti, Marc T.; Igo, Michele; Hoernle, Nicholas; Karger, David – IEEE Transactions on Learning Technologies, 2021
This article provides computational and rule-based approaches for detecting confusion that is expressed in students' comments in couse forums. To obtain reliable, ground truth data about which posts exhibit student confusion, we designed a decision tree that facilitates the manual labeling of forum posts by experts. However, manual labeling is…
Descriptors: Identification, Misconceptions, Student Attitudes, Computer Mediated Communication
Ramazanoglu, Mehmet – European Journal of Educational Sciences, 2021
This paper focuses on revealing and modeling the cognitive constructs of pre-service teachers regarding the characteristics of a good IT academician. The research was carried out via the exploratory sequential design with the participation of 42 volunteer pre-service teachers enrolled in the Department of Computer and Instructional Technology. The…
Descriptors: Preservice Teachers, Student Attitudes, Information Technology, Cognitive Structures
Hersh, Marion – British Journal of Educational Technology, 2017
The paper presents the first systematic approach to the classification of inclusive information and communication technologies (ICT)-based learning technologies and ICT-based learning technologies for disabled people which covers both assistive and general learning technologies, is valid for all disabled people and considers the full range of…
Descriptors: Classification, Information Technology, Educational Technology, Assistive Technology
Steven Moore; John Stamper; Norman Bier; Mary Jean Blink – Grantee Submission, 2020
In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…
Descriptors: Learning Analytics, Educational Improvement, Classification, Learning Processes
Gerasimov, Kirill; Gerasimov, Boris – International Journal of Educational Management, 2017
Purpose: The purpose of this paper is to present the results of the research in the sphere of education and preparation of Russian executives in view of mentality and elements of national model of management. Design/methodology/approach: The research consisted in analysis of modern developments in the sphere of HR management in socio-economic…
Descriptors: Professionalism, Administrator Education, Foreign Countries, Human Relations
Adachi, Chie; Tai, Joanna; Dawson, Phillip – Higher Education Research and Development, 2018
The term 'peer assessment' may apply to a range of student activities. This imprecision may impact on the uptake of peer assessment pedagogies. To better describe peer assessment approaches, typologies of peer assessment diversity were previously derived from the education literature. However, these typologies have not yet been tested with…
Descriptors: Foreign Countries, Peer Evaluation, Classification, Models
Jancaríková, Katerina; Jancarík, Antonín – Electronic Journal of e-Learning, 2017
PISA study has defined several key areas to be paid attention to by teachers. One of these areas is work with models. The term model can be understood very broadly, it can refer to a drawing of a chemical reaction, a plastic model, a permanent mount (taxidermy) to advanced 3D projections. Teachers are no longer confined to teaching materials and…
Descriptors: Foreign Countries, Models, Electronic Learning, Science Education
Dempsey, John V.; Litchfield, Brenda C. – International Association for Development of the Information Society, 2013
Analysis of learning outcomes can be a complex and esoteric instructional design process that is often ignored by educators and e-learning designers. This paper describes a model of analysis that fosters the real-life application of learning outcomes and explains why the model may be needed. The Elemental Learning taxonomy is a hierarchical model…
Descriptors: Educational Technology, Technology Uses in Education, Electronic Learning, Models
Harsley, Rachel – International Association for Development of the Information Society, 2014
This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…
Descriptors: Intelligent Tutoring Systems, Classification, Instructional Effectiveness, Educational Technology
Eyal, Liat – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2015
This study attempts to present the variety of possible uses for iPads, in the learning process. The objective is to evaluate a unique implementation model that was tried out at a teacher training college in Israel. The methodology is based on a qualitative research paradigm. The findings show that students' use the iPads in various contexts: (a)…
Descriptors: Handheld Devices, Educational Technology, Technology Uses in Education, Qualitative Research