Graduate Thesis Or Dissertation
 

An examination of inverse sequential (serial) learning as a method of skill training in industry : a human factors engineering approach

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  • The necessity for the evaluation of training methods on a between methods basis is suggested. Current methods of training evaluations are considered, and found to be generally deficient for their lack of between technique comparisons. The necessity for an outline of planned comparative analysis of training methods is indicated and a method using Gagne's hierarchy of tasks is suggested. A comparison of chaining techniques, forward or inverse, for the learning of a non-verbal serial task is proposed and the superiority of the inverse chaining technique is hypothesized. A machine driven non-verbal maze tracing task is used to train subjects in forward and inverse directions of learning with each direction having the same three levels of pacing for task performance. The maze is presented as two separate spans of seven elements each with ten possible trace alternatives within each element. The two spans are then combined into one 14 element sequence as the final phase of training for whole task performance. Pacing levels impose decision speeds of 4, 5.7 and 7 seconds per element and all training phases require one error free performance prior to proceeding to the next training phase. Errors, time, and cycles required to achieve criterion are used as performance measures to allow statistical inference of the best performance method. Experimental findings do not support the original hypotheses as forward sequence learning is found to significantly decrease time required for learning at the fastest pacing level and some evidence of fewer cycle starts and errors is determined to be present. Other pacing effects do not achieve acceptable statistical significance levels but some evidence of pacing effects on cycle starts and time are found in the individual span phases of training.
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