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Hartmann, Christian; Olsen, Jennifer K.; Brand, Charleen; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2017
Social interdependence is a key concept in CSCL research. However, investigations of students' positive and negative interdependence during collaborative activities have often relied on self-report, rather than dialogue analysis. Bringing together politeness and social interdependence theory, we assessed "dialogue indicators" of positive…
Descriptors: Elementary School Students, Computer Uses in Education, Cooperative Learning, Intelligent Tutoring Systems
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Hauk, Shandy; Matlen, Bryan; Thomas, Larry – Grantee Submission, 2017
A variety of computerized interactive learning platforms exist. Most include instructional supports in the form of problem sets. Feedback to users ranges from a single word like "Correct!" to offers of hints and partially- to fully-worked examples. Behind-the-scenes design of systems varies as well--from static dictionaries of problems…
Descriptors: Community Colleges, Algebra, Web Based Instruction, Randomized Controlled Trials
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Fang, Ying; Nye, Benjamin; Pavlik, Philip; Xu, Yonghong Jade; Graesser, Arthur; Hu, Xiangen – International Educational Data Mining Society, 2017
Student persistence in online learning environments has typically been studied at the macro-level (e.g., completion of an online course, number of academic terms completed, etc.). The current examines student persistence in an adaptive learning environment, ALEKS (Assessment and LEarning in Knowledge Spaces). Specifically, the study explores the…
Descriptors: Learning Processes, Academic Persistence, Correlation, Academic Achievement
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Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima – Turkish Online Journal of Distance Education, 2018
Learners' concentration is an essential factor for learning and acquisition. The duration of concentration varies from one individual to another. Some learners have a long duration of concentration; whereas, others have a short one. Leaving the learner in front of a screen for a random duration is a strategy that does not optimize online learning.…
Descriptors: Study Habits, Attention, Educational Technology, Technology Uses in Education
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DeFalco, Jeanine A.; Rowe, Jonathan P.; Paquette, Luc; Georgoulas-Sherry, Vasiliki; Brawner, Keith; Mott, Bradford W.; Baker, Ryan S.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2018
Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences. Creating successful affective responses requires considerable effort both to detect student affect and to design appropriate responses to affect. Recent work has suggested that affect detection is more effective when both physical…
Descriptors: Psychological Patterns, Stress Variables, Educational Games, Intelligent Tutoring Systems
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Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Horng, Shi-Jinn; Lim, Heuiseok – Innovations in Education and Teaching International, 2018
In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor's actions in implementing one-to-one adaptive and personalised teaching. Thus, in this…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Skill Development, Programming
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Weston-Sementelli, Jennifer L.; Allen, Laura K.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2018
Source-based essays are evaluated both on the quality of the writing and the content appropriate interpretation and use of source material. Hence, composing a high-quality source-based essay (an essay written based on source material) relies on skills related to both reading (the sources) and writing (the essay) skills. As such, source-based…
Descriptors: Reading Comprehension, Writing Strategies, Writing Instruction, Essays
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Likens, Aaron D.; McCarthy, Kathryn S.; Allen, Laura K.; McNamara, Danielle D. – Grantee Submission, 2018
Self-explanations are commonly used to assess on-line reading comprehension processes. However, traditional methods of analysis ignore important temporal variations in these explanations. This study investigated how dynamical systems theory could be used to reveal linguistic patterns that are predictive of self-explanation quality. High school…
Descriptors: Reading Comprehension, High School Students, Content Area Reading, Sciences
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Dincer, Ali – IAFOR Journal of Education, 2020
This study aims to understand the extent to which English as a foreign language learners use technology for their autonomous language learning beyond the classroom. With a cross-sectional survey design approach, the study focuses on learner characteristics. It first investigates the existing language learner profiles of 512 English major…
Descriptors: Informal Education, Information Technology, English (Second Language), Second Language Instruction
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Troussas, Christos; Espinosa, Kurt Junshean; Virvou, Maria – Informatics in Education, 2016
Social networks are progressively being considered as an intense thought for learning. Particularly in the research area of Intelligent Tutoring Systems, they can create intuitive, versatile and customized e-learning systems which can advance the learning process by revealing the capacities and shortcomings of every learner and by customizing the…
Descriptors: Social Media, Educational Technology, Technology Uses in Education, Computer Software
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Bull, Susan; Kay, Judy – International Journal of Artificial Intelligence in Education, 2016
The SMILI? (Student Models that Invite the Learner In) Open Learner Model Framework was created to provide a coherent picture of the many and diverse forms of Open Learner Models (OLMs). The aim was for SMILI? to provide researchers with a systematic way to describe, compare and critique OLMs. We expected it to highlight those areas where there…
Descriptors: Educational Research, Data Collection, Data Analysis, Intelligent Tutoring Systems
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Murray, Tom – International Journal of Artificial Intelligence in Education, 2016
Intelligent Tutoring Systems authoring tools are highly complex educational software applications used to produce highly complex software applications (i.e. ITSs). How should our assumptions about the target users (authors) impact the design of authoring tools? In this article I first reflect on the factors leading to my original 1999 article on…
Descriptors: Usability, Programming, Computer Software, Intelligent Tutoring Systems
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Allen, Laura K.; Jacovina, Matthew E.; Dascalu, Mihai; Roscoe, Rod D.; Kent, Kevin M.; Likens, Aaron D.; McNamara, Danielle S. – International Educational Data Mining Society, 2016
This study investigates how and whether information about students' writing can be recovered from basic behavioral data extracted during their sessions in an intelligent tutoring system for writing. We calculate basic and time-sensitive keystroke indices based on log files of keys pressed during students' writing sessions. A corpus of prompt-based…
Descriptors: Writing Processes, Intelligent Tutoring Systems, Natural Language Processing, Feedback (Response)
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Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – International Educational Data Mining Society, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Intelligent Tutoring Systems, Sequential Approach, Problem Solving, Learning Processes
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Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2013
This article begins with a summary of two dominant approaches to adaptive learning systems: Intelligent Tutoring Systems (ITS), which have been around since the late 1970s and relatively new learning systems based on Learning Analytics, deriving largely from technical advances in BIG DATA pioneered by Google. The article then describes a third…
Descriptors: Intelligent Tutoring Systems, Learning Analytics, Delivery Systems, Learning Theories
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