It is well-documented that most students do not have adequate proficiencies in inquiry and metacognition, particularly at deeper levels of comprehension that require explanatory reasoning. The proficiencies are not routinely provided by teachers and normal tutors so it is worthwhile to turn to computer-based learning environments. This article describes some of our recent computer systems that were designed to facilitate explanation-centered learning through strategies of inquiry and metacognition while students learn science and technology content. Point&Query augments hypertext, hypermedia, and other learning environments with question–answer facilities that are under the learner control. AutoTutor and iSTART use animated conversational agents to scaffold strategies of inquiry, metacognition, and explanation construction. AutoTutor coaches students in generating answers to questions that require explanations (e.g., why, what-if, how) by holding a mixed-initiative dialogue in natural language. iSTART models and coaches students in constructing self-explanations and in applying other metacomprehension strategies while reading text. These systems have shown promising results in tests of learning gains and learning strategies. Imagine an active, curious, self-regulated learner who asks

This study examined the impact of an automated reading strategy trainer called the Interactive Strategy Trainer for Active Reading and Thinking (iSTART) for improving students ’ reading comprehension of a science text. iSTART is an interactive trainer that utilizes animated agents to provide reading strategy instruction. The program contains both vicarious and interactive modules that provide adaptive feedback on the quality of students ’ self-explanations. Thirtyeight children from an east coast middle school were assessed in terms of their prior knowledge, reading ability, and reading strategy knowledge. Half of the participants were provided with iSTART training. Comprehension of a science passage was assessed with text-based and bridging-inference questions. The results indicated that children with less prior knowledge about reading strategies performed significantly better on text-based questions if they received iSTART training. Conversely for high-strategy knowledge students, iSTART improved comprehension over control students for bridging–inference questions. The results support the need for user-adaptive intelligent tutoring systems.

Users of educational hypertext are faced with the challenge of creating meaning both within and between texts. Cohesion is an important factor contributing to whether a reader is able to capture meaning and comprehend text. When readers are required to fill in conceptual gaps in text, comprehension can fail if they do not have sufficient knowledge. Cohesion helps low-knowledge readers to create a more coherent mental representation of the text. However, text that is too cohesive can inhibit active processing, and thus reduce coherence for more knowledgeable readers. Similar patterns have been found for hypertext, which requires readers to create coherence between multiple electronic texts. Domain novices are in greater need of explicit pointers to important links between documents and gain from having less control over system navigation. Domain experts are in less need of scaffolding within the system. We discuss the use of a multimedia reading strategy training program to help low-knowledge readers better understand less cohesive text. Finally, we discuss four principles to guide hypertext development geared toward improving coherence and metacognitive engagement.

It is well documented that most students do not have adequate proficiencies in inquiry and metacognition, particularly at deeper levels of comprehension that require explanatory reasoning. The proficiencies are not routinely provided by teachers and normal tutors so it is worthwhile to turn to computer-based learning environments. This article describes some of our recent computer systems that were designed to facilitate explanation-centered learning through strategies of inquiry and metacognition while students learn science and technology content. Point&Query augments hypertext, hypermedia, and other learning environments with question-answer facilities that are under the learner control. AutoTutor and iSTART use animated conversational agents to scaffold strategies of inquiry, metacognition, and explanation construction. AutoTutor coaches students in generating answers to questions that require explanations (e.g., why, what-if, how) by holding a mixed-initiative dialogue in natural language. iSTART models and coaches students in constructing self-explanations and in applying other metacomprehension strategies while reading text. These systems have shown promising results in tests of learning gains and learning strategies.

About the Alliance for Excellent Education The Alliance for Excellent Education is a national policy, advocacy, and research organization created to help middle and high school students receive an excellent education. The Alliance focuses on America’s six million most at-risk secondary school students–those in the lowest achievement quartile–who are likely to leave school without a diploma or to graduate unprepared for a productive future. Based in Washington, D.C., we work to make it possible for these students to achieve high standards and graduate prepared for college and success in life. Our audience includes parents, teachers, and students, as well as the federal, state, and local policy communities, education organizations, the media, and a concerned public. To inform the national debate about education policies and options, we produce reports and other materials, make presentations at meetings and conferences, brief policymakers and the press, and provide timely information to a wide audience via our biweekly newsletter and regularly updated Web site, www.all4ed.org.

This report describes the evolution of an innovative research project in which inservice special education teachers engaged in collaborative strategy instruction with small groups of severely reading-delayed adolescents (ages 12-16). The project stressed working with teachers to resolve problems of application; this report emphasizes how teachers ' contributions resulted in a unique approach to reading strategy instruction. The characteristics of the teacher education model are described and related to experimental findings from research carried out to test the effects of the model. Nine experimental and 7 control teachers and their students took part in the study. Experimental teachers received peer support from previously trained teachers and took part in self-evaluative workshops as they applied

This manuscript was prepared while the author was on sabbatical leave as a Visiting Scholar at the Center for the Study of Reading. The author would like to thank the Center for the help of its support staff and the use of its facilities. Phillips Inference Strategies- 1 This study identified the inference strategies used by grade six readers reading three short narratives. Differences in strategy use were studied with reading proficiency and background knowledge varied. Eighty students comprised the sample, 40 low proficiency and 40 high proficiency readers. Equal numbers of students were randomly assigned to read either three familiar or three unfamiliar passages and to verbally report their thinking as they constructed interpretations. Qualitative and quantitative analyses showed that young readers ' inference strategies appeared to be a decomposition of those used by adults as reported in the work of Collins, Brown, and Larkin (1980). Two observations were made from comparisons of young readers ' strategy use. The first has to do with the importance of reading proficiency and the second with the relative insignificance of background

The work upon which this publication is based was performed pursuant to