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Brenner, Daniel G.; Matlen, Bryan J.; Timms, Michael J.; Gochyyev, Perman; Grillo-Hill, Andrew; Luttgen, Kim; Varfolomeeva, Marina – Technology, Knowledge and Learning, 2017
This study investigated how the frequency and level of assistance provided to students interacted with prior knowledge to affect learning in the "Voyage to Galapagos" ("VTG") science inquiry-learning environment. "VTG" provides students with the opportunity to do simulated science field work in Galapagos as they…
Descriptors: Learning Processes, Prior Learning, Online Courses, Science Education
Jamet, Eric; Fernandez, Jonathan – Educational Technology Research and Development, 2016
The present study investigated whether learning how to use a web service with an interactive tutorial can be enhanced by cueing. We expected the attentional guidance provided by visual cues to facilitate the selection of information in static screen displays that corresponded to spoken explanations. Unlike most previous studies in this area, we…
Descriptors: Intelligent Tutoring Systems, Web Sites, Cues, Visual Stimuli
Rau, Martina A.; Aleven, Vincent; Rummel, Nikol – Instructional Science: An International Journal of the Learning Sciences, 2017
Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally explaining how…
Descriptors: Elementary School Students, Grade 3, Grade 4, Grade 5
Rau, Martina A.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2017
Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics (STEM) domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally…
Descriptors: Elementary School Students, Grade 3, Grade 4, Grade 5
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 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: Sequential Learning, Data Collection, Information Retrieval, Evaluation Methods
Hausmann, Robert G. M.; VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2010
Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to…
Descriptors: Instructional Design, Intelligent Tutoring Systems, College Students, Predictor Variables
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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