NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Ying Fang; Tong Li; Linh Huynh; Katerina Christhilf; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Literacy assessment is essential for effective literacy instruction and training. However, traditional paper-based literacy assessments are typically decontextualized and may cause stress and anxiety for test takers. In contrast, serious games and game environments allow for the assessment of literacy in more authentic and engaging ways, which has…
Descriptors: Literacy, Student Evaluation, Educational Games, Literacy Education
Ryan D. Kopatich; Joseph P. Magliano; Keith K. Millis; Christopher P. Parker; Melissa Ray – Grantee Submission, 2019
A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…
Descriptors: Inferences, Reading Comprehension, Models, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Ryan D. Kopatich; Joseph P. Magliano; Keith K. Millis; Christopher P. Parker; Melissa Ray – Discourse Processes: A Multidisciplinary Journal, 2019
A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediational Inference model of comprehension (DIME) assumes that general inference processes mediate the effects of reader resources on general comprehension…
Descriptors: Reading Tests, Intelligence Tests, Inferences, Reading Comprehension
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Varner, Laura K.; Jackson, G. Tanner; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2013
This study expands upon an existing model of students' reading comprehension ability within an intelligent tutoring system. The current system evaluates students' natural language input using a local student model. We examine the potential to expand this model by assessing the linguistic features of self-explanations aggregated across entire…
Descriptors: Reading Comprehension, Intelligent Tutoring Systems, Natural Language Processing, Reading Ability