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This study examined the direct and indirect effects of medical clerkship students' prior knowledge, self-regulation and motivation on learning performance in complex multimedia learning environments. The data from 386 medical clerkship students from six medical schools were analysed using structural equation modeling. The structural model revealed that medical students' prior knowledge directly positively affected their learning outcome, selfefficacy and performance approach goal orientation. The learners' self-regulation had a significant positive direct effect on learning outcome. The learners' mastery goal orientation directly affected their learning outcome. Interestingly, inconsistent with our hypothesis, the learners' performance approach goal orientation showed a significant negative direct effect on learning outcome, and performance avoidance goal orientation had a significant positive effect on learning outcome. These findings help develop a more comprehensive understanding of the role of individual characteristics on learning performance of complex tasks in multimedia learning environments. [ABSTRACT FROM AUTHOR]

Successful online students must learn and maintain motivation to learn. The Self-regulation of Motivation (SRM) model (Sansone and Thoman ) 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 goals-defined 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. [ABSTRACT FROM AUTHOR]