Scaffolding Problem Solving with Embedded Examples to Promote Deep Learning

This study compared the relative utility of an intelligent tutoring system that uses procedure-based hints to a version that uses worked-out examples. The system, Andes, taught college level physics. In order to test which strategy produced better gains in competence, two versions of Andes were used: one offered participants graded hints and the other offered annotated, worked-out examples in response to their help requests. We found that providing examples was at least as effective as the hintsequences and was more efficient in terms of the number of problems it took to obtain the same level of mastery

The Assistment Project: Comparing Learning through Hints and Worked Examples

There were three main goals for this project. The first was to develop content for the ASSISTment system based on the Connected Mathematics Project series of textbooks. The second goal was to convert this into a study to determine whether worked examples are more effective than hints for helping students learn in a computer tutoring environment. Data analysis suggests that worked examples were more beneficial for learning than hints. The third goal was to develop an ASSISTment support website

An Online Tutor for Astronomy: The GEAS Self-Review Library

We introduce an interactive online resource for use by students and college instructors in introductory astronomy courses. The General Education Astronomy Source (GEAS) online tutor guides students developing mastery of core astronomical concepts and mathematical applications of general astronomy material. It contains over 12,000 questions, with linked hints and solutions. Students who master the material quickly can advance through the topics, while under-prepared or hesitant students can focus on questions on a certain topic for as long as needed, with minimal repetition. Students receive individual accounts for study and course instructors are provided with overview tracking information, by time and by topic, for entire cohorts of students. Diagnostic tools support self-evaluation and close collaboration between instructor and student, even for distance learners. An initial usage study shows clear trends in performance which increase with study time, and indicates that distance learners using these materials perform as well as or better than a comparison cohort of on-campus astronomy students. We are actively seeking new collaborators to use this resource in astronomy courses and other educational venues.Comment: 15 pages, 9 figures; Vogt, N. P., and A. S. Muise. 2015. An online tutor for general astronomy: The GEAS self-review library. Cogent Education, 2 (1

The ASSISTment Project: Comparing Learning through Hints and Worked Examples

There were three main goals for this project. The first was to develop content for the ASSISTment system based on the Connected Mathematics Project series of textbooks. The second goal was to convert this into a study to determine whether worked examples are more effective than hints for helping students learn in a computer tutoring environment. Data analysis suggests that worked examples were more beneficial for learning than hints. The third goal was to develop an ASSISTment support website

The ASSISTment Project: Comparing Learning through Hints and Worked Examples

There were three main goals for this project. The first was to develop content for the ASSISTment system based on the Connected Mathematics Project series of textbooks. The second goal was to convert this into a study to determine whether worked examples are more effective than hints for helping students learn in a computer tutoring environment. Data analysis suggests that worked examples were more beneficial for learning than hints. The third goal was to develop an ASSISTment support website

The ASSISTment Project: Comparing Learning Through Hints and Worked Examples

There were three main goals for this project. The first was to develop content for the ASSISTment system based on the Connected Mathematics Project series of textbooks. The second goal was to convert this into a study to determine whether worked examples are more effective than hints for helping students learn in a computer tutoring environment. Data analysis suggests that worked examples were more beneficial for learning than hints. The third goal was to develop an ASSISTment support website

Investigating Learning in an Intelligent Tutoring System through Randomized Controlled Experiments

In the United States, many students are doing poorly on new high-stakes standards-based tests that are required by the No Child Left Behind Act of 2002. Teachers are expected to cover more material to address all of the topics covered in standardized tests, and instructional time is more precious than ever. Educators want to know that the interventions that they are using in their classrooms are effective for students of varying abilities. Many educational technologies rely on tutored problem solving, which requires students to work through problems step-by-step while the system provides hints and feedback, to improve student learning. Intelligent tutoring researchers, education scientists and cognitive scientists are interested in knowing whether tutored problem solving is effective and for whom. Intelligent tutoring systems have the ability to adapt to individual students but need to know what types of feedback to present to individual students for the best and most efficient learning results. This dissertation presents an evaluation of the ASSISTment System, an intelligent tutoring system for the domain of middle school mathematics. In general, students were found to learn when engaging in tutored problem solving in the ASSISTment System. Students using the ASSISTment System also learned more when compared to paper-and-pencil problem-solving. This dissertation puts together a series of randomized controlled studies to build a comprehensive theory about when different types of tutoring feedback are more appropriate in an intelligent tutoring system. Data from these studies were used to analyze whether interactive tutored problem solving in an intelligent tutoring system is more effective than less interactive methods of allowing students to solve problems. This dissertation is novel in that it presents a theory that designers of intelligent tutoring systems could use to better adapt their software to the needs of students. One of the interesting results showed is that the effectiveness of tutored problem solving in an intelligent tutoring system is dependent on the math proficiency of the students. Students with low math proficiency learned more when they engaged in interactive tutoring sessions where they worked on one step at a time, and students with high math proficiency learned more when they were given the whole solution at once. More interactive methods of tutoring take more time versus less interactive methods. The data showed that it is worth the extra time it takes for students with low math proficiency. The main contribution of this dissertation is the development of a comprehensive theory of when educational technologies should use tutored problem solving to help students learn compared to other feedback mechanisms such as hints on demand, worked out solutions, worked examples and educational web pages