Individual Differences in Patterns of Spontaneous Online Tool Use

More than 400 individuals participated in an experiment involving two versions of a computer-based tutor teaching principles of electricity. We examined the relations among elective tool use, learning environment, outcome, and efficiency. We also tested the influence of both individual differences and learning environment on tool-usage behavior. The data showed no differences between the two learning environments (rule application vs. rule induction) with regard to outcome performance or learning efficiency. In addition, neither environment significantly influenced overall tool use. There was a main effect of tool use on learning outcome, but not on learning time. We categorized learners into four groups, based on tool-usage patterns and found that (a) people tended to show stable patterns across time and (b) that patterns differed significantly in terms of learning outcome—it was most effective to use the online tools earlier in the learning process rather than later. In terms of individual differences, we identified the characteristics of learners who evidenced different tool-usage patterns. They varied according to cognitive ability, domain-related interest, and gender. We propose a causal model that takes into account all of these data sources in predicting posttest performance. The article concludes with implications of these findings for those interested in maximizing instructional effectiveness, as well as suggestions for future research directions.