Mastery-Oriented Shared Student/System Control Over Problem Selection in a Linear Equation Tutor

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9684)

Abstract

Making effective problem selection decisions is a challenging Self-Regulated Learning skill. Students need to learn effective problem-selection strategies but also develop the motivation to use them. A mastery-approach orientation is generally associated with positive problem selection behaviors such as willingness to work on new materials. We conducted a classroom experiment with 200 6th – 8th graders to investigate the effectiveness of shared control over problem selection with mastery-oriented features (i.e., features that aim at fostering a mastery-approach orientation that simulates effective problem-selection behaviors) on students’ domain-level learning outcomes, problem-selection skills, enjoyment, future learning and future problem selection. The results show that shared control over problem selection accompanied by mastery-oriented features leads to significantly better learning outcomes, as compared to fully system-controlled problem selection, as well as better declarative knowledge of a key problem-selection strategy. Nevertheless, there was no effect on future problem selection and future learning. Our experiment contributes to prior literature by demonstrating that with tutor features to foster a mastery-approach orientation, shared control over problem selection can lead to significantly better learning outcomes than full system control.

Keywords

Mastery-approach orientation Problem selection Self-Regulated Learning Learner control Classroom experiment Intelligent Tutoring System 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Learning Research and Development Center, University of PittsburghPittsburghUSA
  2. 2.Human-Computer Interaction Institute, Carnegie Mellon UniversityPittsburghUSA

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