Practice schedule and cognitive style interaction in learning a maze task

In the present study the effects of contextual interference on the retention and transfer performance of reflectives and impulsives on a maze task were studied. Forty-seven subjects were randomly assigned to either a high contextual interference group or to a low contextual interference group. Within the two groups subjects were further classified according to their preferred modes of responding. Retention and transfer were measured immediately following practice and after a 4-week delay. The dependent variables were tracing time and errors. Reflectives made fewer errors and moved more quickly after practising under conditions of high contextual interference. Impulsives tended to have fewer errors after practising under conditions of high contextual interference but moved more slowly. Based on these results it was suggested that trainers consider individual differences in reflectivity-impulsivity before designing particular practice schedules

Instructional strategy effects on the retention and transfer of procedures of different difficulty level

In the present study, the effects of two instructional strategies on the retention and transfer of procedures of different difficulty level were investigated. Difficulty level was manipulated by providing a different number of cues during training. The instructional strategies differed with respect to the amount of contextual interference. Sixty-four subjects were randomly assigned to either a high interference group or a low interference group. Retention and transfer were measured immediately following training and after a three-week delay. The dependent variables were number of errors and decision time. Results showed no differences between the two training groups over the various difficulty levels. Results further showed that retention performance increased as fewer cues were available during practice. It is suggested that ‘delayed automatization’ can account for the observed increment in performance level. It is further suggested that contextual interference may produce delayed automatization of task performance but is only effective if relationships can be discovered in the learning material

Contextual interference:interactions with reflection-impulsivity

In the present study, interactions of contextual interference and the cognitive style reflection-impulsivity were examined for training and retention performance. 64 subjects were randomly assigned to either a random or blocked practice schedule in learning a cursor-movement task. Reflectivity indices were determined by means of our computerized version of the Matching Familiar Figures Test. Analysis showed that the generally positive effect of practicing under a random practice schedule decreased for more reflective subjects. Further, training under a random practice schedule forced impulsive subjects to behave more like reflective ones, which improved their performance at retention. It was concluded that reflection-impulsivity is an important factor to be incorporated into the design of effective training programs. </jats:p

Training for reflective expertise: a four-component instructional design model for complex cognitive skills

This article presents a four-component instructional design model for the training of complex cognitive skills. In the analysis phase, the skill is decomposed into a set of recurrent skills that remain consistent over problem situations and a set of nonrecurrent skills that require variable performance over situations. In the design phase, two components relate to the design of practice; they pertain to the conditions under which practice leads either to rule automation during the performance of recurrent skills or to schema acquisition during the performance of nonrecurrent skills. The other two components relate to the design of information presentation; they pertain to the presentation of information that supports the performance of either recurrent or nonrecurrent skills. The basic prediction of the model is that its application leads to “reflective expertise” and increased performance on transfer tasks. Applications of the model that support this prediction are briefly discussed for the training of fault management in process industry, computer programming, and statistical analysis

Training for reflective expertise: A four-component instructional design model for complex cognitive skills

This article presents a four-component instructional design model for the training of complex cognitive skills. In the analysis phase, the skill is decomposed into a set of recurrent skills that remain consistent over problem situations and a set of nonrecurrent skills that require variable performance over situations. In the design phase, two components relate to the design of practice; they pertain to the conditions under which practice leads either to rule automation during the performance of recurrent skills or to schema acquisition during the performance of nonrecurrent skills. The other two components relate to the design of information presentation; they pertain to the presentation of information that supports the performance of either recurrent or nonrecurrent skills. The basic prediction of the model is that its application leads to "reflective expertise" and increased performance on transfer tasks. Applications of the model that support this prediction are briefly discussed for the training of fault management in process industry, computer programming, and statistical analysis

The transfer paradox:Effects of contextual interference on retention and transfer performance of a complex cognitive skill

In an exploratory study, the effects oi contextual interference on retention and transfer performance were studied for learning A complex cognitive skd, namely, troubleshooting a computer-based simulation oC J chemical process plant. Support was found for the "transfer paradox": high contextual interference had negative effects on performance during practice and none on number of retention problems solved after the training but positive effects on number of new problems solved (transfer). Implications for the design of training are discussed