Andrew Cuneo

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We describe the automated generation and use of 69,326 comprehension cloze questions and 5,668 vocabulary matching questions in the 2001-2002 version of Project LISTEN’s Reading Tutor used by 364 students in grades 1-9 at seven schools. To validate our methods, we used students’ performance on these multiple-choice questions to predict their scores on the(More)
A basic question in mining data from an intelligent tutoring system is, “What happened when...?” We identify requirements for a tool to help answer such questions by finding occurrences of specified phenomena and browsing them in human-understandable form. We describe an implemented tool and how it meets the requirements. The tool applies to MySQL databases(More)
A year-long study of 131 second and third graders in 12 classrooms compared three daily 20-minute treatments. (a) 58 students in 6 classrooms used the 1999-2000 version of Project LISTEN’s Reading Tutor, a computer program that uses automated speech recognition to listen to a child read aloud, and gives spoken and graphical assistance. Students took daily(More)
It is easier to record logs of multimodal human-computer tutorial dialogue than to make sense of them. In the 2000-2001 school year, we logged the interactions of approximately 400 students who used Project LISTEN's Reading Tutor and who read aloud over 2.4 million words. This paper discusses some difficulties we encountered converting the logs into a more(More)
A basic question in mining data from an intelligent tutoring system is, “What happened when...?” We identify requirements for a tool to help answer such questions by finding occurrences of specified phenomena and browsing them in human-understandable form. We describe an implemented tool and how it meets the requirements. The tool applies to MySQL databases(More)
Analyzing the time allocation of students’ activities in a schooldeployed mixed initiative tutor can be illuminating but surprisingly tricky. We discuss some complementary methods that we have used to understand how tutoring time is spent, such as analyzing sample videotaped sessions by hand, and querying a database generated from session logs. We identify(More)
We describe results on helping children learn vocabulary during computer-assisted oral reading. This paper focuses on one aspect – vocabulary learning – of a larger study comparing computerized oral reading tutoring to classroom instruction and one-on-one human tutoring. 144 students in second and third grade were assigned to one of three conditions: (a)(More)
A year-long study of 144 second and third graders compared outcomes (gains in test scores) and process variables (e.g. words read) for Project LISTEN’s Reading Tutor, human tutors, and a classroom control. Human tutors beat the Reading Tutor only in word attack. Both beat the control in grade 3 word comprehension. 1. Experimental Design Project LISTEN’s(More)
A basic question in mining data from an intelligent tutoring system is, “What happened when...?” A generic tool to answer such questions should let the user specify which phenomenon to explore; explore selected events and the context in which they occurred; and require minimal effort to adapt the tool to new versions, to new users, or to other tutors. We(More)
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