Pennsylvania

The project team will conduct comparative, experimental research to investigate how MERs can best be used to cause robust student learning (i.e., the research will generate causal results). In three planned experiments, we will investigate three open issues related to learning with multiple representations, by comparing experimental conditions in which students learn with multiple versions of intelligent software tutors for fractions learning. We will develop these tutors with dedicated authoring tools (CTAT). The open issues relate to the frequency of switching between representations, the most effective activities for helping students make connections between different representations, and the relative amount of time that should be devoted to making connections between representations, compared to activities centered on a single representation. In each experiment, we will compare learning outcomes with different versions of the intelligent tutor that differ only by the feature at issue in the given experiment.

This project collects original data using assessments of learning and achievement tests and detailed logs of student-tutor interactions (records of online usage).

To assess learning outcomes, we will create a test instrument that assesses students’ reproduction and transfer of conceptual and procedural knowledge. The test will include standardized test items, gathered from various readily-available sources (primarily state tests), as well as items adapted from the fractions literature, and new items created with the help of a retired middle-school math teacher.

To analyze the data from the planned experiments, one-factorial MANCOVAs will be used to investigate the between subjects effects of the experimental variations at the post-test and delayed post-test, using data from the pre-test as a covariate. In addition, we will analyze log data of students’ interactions with the fraction tutors to study how different tutor versions may affect their learning behavior.