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Direct linkZhe Gao – ProQuest LLC, 2022
Mandarin Chinese verbs are composed of one to four characters that function together as a conceptual unit. However, in modern spoken Chinese, most of these verbs are two-character compounds. This dissertation is focused on adult second language (L2) learners' acquisition of these two-character verb compounds. Specifically, the acquisition of a…
Descriptors: Mandarin Chinese, Second Language Learning, Second Language Instruction, Verbs
Peer reviewedPaquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
Castro, Robin – Education and Information Technologies, 2019
Education is a complex system that requires multiple perspectives and levels of analysis to understand its contexts, dynamics, and actors' interactions, particularly concerning technological innovations. This paper aims to identify some of the most promising trends in blended learning implementations in higher education, the capabilities provided…
Descriptors: Blended Learning, Educational Technology, Technology Uses in Education, Higher Education
Rosé, Carolyn P.; McLaughlin, Elizabeth A.; Liu, Ran; Koedinger, Kenneth R. – British Journal of Educational Technology, 2019
Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…
Descriptors: Discovery Learning, Man Machine Systems, Artificial Intelligence, Models
Damacharla, Praveen; Dhakal, Parashar; Stumbo, Sebastian; Javaid, Ahmad Y.; Ganapathy, Subhashini; Malek, David A.; Hodge, Douglas C.; Devabhaktuni, Vijay – International Journal of Artificial Intelligence in Education, 2019
As part of a perennial project, our team is actively engaged in developing new synthetic assistant (SA) technologies to assist in training combat medics and medical first responders. It is critical that medical first responders are well trained to deal with emergencies more effectively. This would require real-time monitoring and feedback for each…
Descriptors: Emergency Medical Technicians, Intelligent Tutoring Systems, Instructional Effectiveness, Performance
Download full textChen, Guanliang; Ferreira, Rafael; Lang, David; Gasevic, Dragan – International Educational Data Mining Society, 2019
For the development of successful human-agent dialogue-based tutoring systems, it is essential to understand what makes a human-human tutorial dialogue successful. While there has been much research on dialogue-based intelligent tutoring systems, there have been comparatively fewer studies on analyzing large-scale datasets of human-human online…
Descriptors: Student Attitudes, Intelligent Tutoring Systems, Computer Software, Dialogs (Language)
Suijing Yang; Daniel Taylor-Griffiths; Fabienne van der Kleij; Pauline Taylor-Guy; Ralph Saubern – Australian Council for Educational Research, 2025
Many existing reviews of educational technologies focus on the affordances of specific types of technology rather than how different technologies can be designed and used to achieve specific teaching and learning objectives. Furthermore, there appears to be a widely held assumption that the use of educational technology will result in improved…
Descriptors: Teacher Empowerment, Educational Technology, Technology Uses in Education, Technology Integration
Graesser, Arthur C.; Hu, Xiangen; Nye, Benjamin D.; VanLehn, Kurt; Kumar, Rohit; Heffernan, Cristina; Heffernan, Neil; Woolf, Beverly; Olney, Andrew M.; Rus, Vasile; Andrasik, Frank; Pavlik, Philip; Cai, Zhiqiang; Wetzel, Jon; Morgan, Brent; Hampton, Andrew J.; Lippert, Anne M.; Wang, Lijia; Cheng, Qinyu; Vinson, Joseph E.; Kelly, Craig N.; McGlown, Cadarrius; Majmudar, Charvi A.; Morshed, Bashir; Baer, Whitney – International Journal of STEM Education, 2018
Background: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics,…
Descriptors: Intelligent Tutoring Systems, STEM Education, Electronics, Integrated Curriculum
Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2018
This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…
Descriptors: Artificial Intelligence, Models, Tutors, Learning Theories
He, Qingshun – English Language Teaching, 2018
The research of Systemic Functional Linguistics has been quite in-depth in both theory and practice. However, many linguists hold that Systemic Functional Linguistics has no hypothesis testing or experiments and its research is only qualitative. Analyses of the corpus, intelligent computing and language evolution on the ideological background of…
Descriptors: Language Research, Linguistics, Statistical Analysis, Intelligent Tutoring Systems
Gilbert, Stephen B.; Slavina, Anna; Dorneich, Michael C.; Sinatra, Anne M.; Bonner, Desmond; Johnston, Joan; Holub, Joseph; MacAllister, Anastacia; Winer, Eliot – International Journal of Artificial Intelligence in Education, 2018
With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of…
Descriptors: Tutors, Teamwork, Intelligent Tutoring Systems, Tutoring
Ma, Xueying; Ye, Lu – International Journal of Mobile and Blended Learning, 2018
This article describes how e-learning recommender systems nowadays have applied different kinds of techniques to recommend personalized learning content for users based on their preference, goals, interests and background information. However, the cold-start problem which exists in traditional recommendation algorithms are still left over in…
Descriptors: Electronic Learning, Individualized Instruction, Occupational Aspiration, Intelligent Tutoring Systems
Nguyen, Huy; Liew, Chun Wai – International Educational Data Mining Society, 2018
Recent works on Intelligent Tutoring Systems have focused on more complicated knowledge domains, which pose challenges in automated assessment of student performance. In particular, while the system can log every user action and keep track of the student's solution state, it is unable to determine the hidden intermediate steps leading to such…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Data Analysis, Error Patterns
Albacete, Patricia; Jordan, Pamela; Lusetich, Dennis; Katz, Sandra; Chounta, Irene-Angelica; McLaren, Bruce M. – Grantee Submission, 2018
This paper discusses how a dialogue-based tutoring system makes decisions to proactively scaffold students during conceptual discussions about physics. The tutor uses a student model to predict the likelihood that the student will answer the next question in a dialogue script correctly. Based on these predictions, the tutor will, step by step,…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Physics, Science Instruction
Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
