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Strobl, Carola – ReCALL, 2015
This exploratory study sheds new light on students' perceptions of online feedback types for a complex writing task, summary writing from spoken input in a foreign language (L2), and investigates how these correlate with their actual learning to write. Students tend to favour clear-cut, instructivist rather than constructivist feedback, and guided…
Descriptors: Feedback (Response), Writing (Composition), Constructivism (Learning), Computer Mediated Communication
Asay, Loretta Johnson – ProQuest LLC, 2013
Analogies are ubiquitous during instruction in science classrooms, yet research about the effectiveness of using analogies has produced mixed results. An aspect seldom studied is a model of instruction when using analogies. The few existing models for instruction with analogies have not often been examined quantitatively. The Teaching With…
Descriptors: Science Education, Logical Thinking, Concept Mapping, Science Instruction
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Singer-Dudek, Jessica; Speckman, JeanneMarie; Nuzzolo, Robin – Behavior Analyst Today, 2010
The Comprehensive Application of Behavior Analysis to Schooling or CABAS[R] model is characterized by an organizational system of teacher training and mentoring by those with more expertise in the science of behavior analytic teaching. At the center of the system are the students, whose data drive the system. Decades of research support the…
Descriptors: Expertise, Learning Modules, Comparative Analysis, Teaching Methods
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Hambleton, Ronald K.; Jones, Russell W. – Educational Measurement: Issues and Practice, 1993
This National Council on Measurement in Education (NCME) instructional module compares classical test theory and item response theory and describes their applications in test development. Related concepts, models, and methods are explored; and advantages and disadvantages of each framework are reviewed. (SLD)
Descriptors: Comparative Analysis, Educational Assessment, Graphs, Item Response Theory
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Harris, Deborah – Educational Measurement: Issues and Practice, 1989
This instructional module discusses the one-, two-, and three-parameter logistic item response theory (IRT) models. Mathematical formulas are given for each model and they are compared, with figures illustrating the effects of changing parameters. A single data set is used to demonstrate the effects of changing parameter values. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Instructional Materials