Successful online students must learn and maintain motivation to learn. The Self-regulation of Motivation (SRM) model (Sansone and Thoman 2005) suggests two kinds of motivation are essential: Goals-defined (i.e., value and expectancy of learning), and experience-defined (i.e., whether interesting). The Regulating Motivation and Performance Online (RMAPO) project examines implications using online HTML lessons. Initial project results suggested that adding usefulness information (enhancing goalsdefined motivation) predicted higher engagement levels (enhancing experience), which in turn predicted motivation (interest) and performance (HTML quiz) outcomes. The present paper examined whether individual interest in computers moderated these results. When provided the utility value information, students with higher (relative to lower) individual interest tended to display higher engagement levels, especially when usefulness was framed in terms of personal versus organizational applications. In contrast, higher engagement levels continued to positively predict outcomes regardless of individual interest. We discuss implications for designing optimal online learning environments.

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This paper presents a within-subject, randomized experiment to compare automated interventions for teaching vocabulary to young readers using Project LISTEN's Reading Tutor. The experiment compared three conditions: no explicit instruction, a quick definition, and a quick definition plus a poststory battery of extended instruction based on a published instructional sequence for human teachers. A month long study with elementary school children indicates that the quick instruction, which lasts about seven seconds, has immediate effects on learning gains that did not persist. Extended instruction which lasted about thirty seconds longer than the quick instruction had a persistent effect and produced gains on a posttest one week later.