NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Location
Indiana1
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 9 results Save | Export
Olney, Andrew M.; Gilbert, Stephen B.; Rivers, Kelly – Grantee Submission, 2021
Cyberlearning technologies increasingly seek to offer personalized learning experiences via adaptive systems that customize pedagogy, content, feedback, pace, and tone according to the just-in-time needs of a learner. However, it is historically difficult to: (1) create these smart learning environments; (2) continuously improve them based on…
Descriptors: Educational Technology, Computer Assisted Instruction, Learning Analytics, Intelligent Tutoring Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Frick, Theodore W.; Myers, Rodney D.; Dagli, Cesur – Educational Technology Research and Development, 2022
In this naturalistic design-research study, we tracked 172,417 learning journeys of students who were interacting with an online resource, the Indiana University Plagiarism Tutorials and Tests (IPTAT) at https://plagiarism.iu.edu. IPTAT was designed using First Principles of Instruction (FPI; Merrill in Educ Technol Res Dev 50:43-59, 2002,…
Descriptors: Time, Educational Principles, Instructional Design, Instructional Effectiveness
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Conijn, Rianne; Martinez-Maldonado, Roberto; Knight, Simon; Buckingham Shum, Simon; Van Waes, Luuk; van Zaanen, Menno – Computer Assisted Language Learning, 2022
Current writing support tools tend to focus on assessing final or intermediate products, rather than the writing process. However, sensing technologies, such as keystroke logging, can enable provision of automated feedback during, and on aspects of, the writing process. Despite this potential, little is known about the critical indicators that can…
Descriptors: Automation, Feedback (Response), Writing Evaluation, Learning Analytics
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Rozo, Hugo; Real, Miguel – Journal of Technology and Science Education, 2019
The present article constitutes a systematic review of the literature with the objective of identifying the appropriate elements that must be considered when designing and creating adaptive digital educational resources. The methodological process was rigorous and systematic, employing an article search in which the texts related to the object of…
Descriptors: Instructional Design, Intelligent Tutoring Systems, Instructional Materials, Educational Technology
Shute, Valerie J.; Smith, Ginny; Kuba, Renata; Dai, Chih-Pu; Rahimi, Seyedahmad; Liu, Zhichun; Almond, Russell – Grantee Submission, 2020
In honor of Jim Greer, we share our recent work--a design and development study of various learning supports embedded within the game "Physics Playground." This 2-dimensional computer game is designed to help students learn Newtonian physics and uses stealth assessment to measure, in real-time, their physics understanding. The game…
Descriptors: Physics, Educational Games, Computer Games, Science Education
Peer reviewed Peer reviewed
Direct linkDirect link
Feng, Shihui; Law, Nancy – International Journal of Artificial Intelligence in Education, 2021
In this study, we review 1830 research articles on artificial intelligence in education (AIED), with the aim of providing a holistic picture of the knowledge evolution in this interdisciplinary research field from 2010 to 2019. A novel three-step approach in the analysis of the keyword co-occurrence networks (KCN) is proposed to identify the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Intelligent Tutoring Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2016
Intelligent Tutoring Systems (ITS) have a long history, almost as long as the Structural Learning Theory (initially in Scandura, 1971). Although well-funded for many years, neither ITS nor contemporary successors based on BIG DATA (e.g., Knewton) come close to modeling the processes used by good human tutors. AuthorIT & TutorIT rest on a…
Descriptors: Intelligent Tutoring Systems, Delivery Systems, Tutorial Programs, Instructional Design
Sungjin Nam – ProQuest LLC, 2020
This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…
Descriptors: Vocabulary Development, Intelligent Tutoring Systems, Student Evaluation, Learning Analytics