Research shows the students improve their reading comprehension with Intelligent Tutoring of the Structure Strategy (ITSS). One problem for ITSS is that some students are producing responses in the on-line instruction that are unrelated to learning and practicing the reading strategy. These types of disengaged responses can be referred to as system active off-task responses ("off-task"). In this study we characterize who produces off-task responses and why. Classification and Regression Trees (C&RT) and logistic regression analyses were used to answer the why question. Variables predicted to relate to gaming included reading strategy and skill variables, motivation, attitude, self-efficacy, and goal orientation variables, demographic variables, and type of computer feedback (simple versus elaborated). C&RT analysis could explain 66% of the variance in off-task responses. Students without off-task responses were higher in motivation to read and worked in ITSS to produce good main ideas. Students with higher off-task responses had low scores on work mastery goals. The highest producers of off-task responses in Grades 5 and 7 (averaging 24 off-task responses over 7 lessons) had low motivation to read and scored over 2 SD below average on recall tasks in ITSS. The logistic regression could explain 42% of the variance in off-task responses. Use of motivational scales prior to starting instruction as well as on-line performance measures could be used to flag students for early intervention to prevent system active off-task responses and increase on-line learning. The C&RT approach may be particularly helpful to designers in making software more appropriate for different types of students.
All Science Journal Classification (ASJC) codes
- Computer Science(all)