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The Optimize Of Management Training Effect Evaluation System Based On The Kirkpatrick Model

Posted on:2012-10-17Degree:MasterType:Thesis
Country:ChinaCandidate:B LiFull Text:PDF
GTID:2219330368487059Subject:Business management
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In the era of knowledge economy, training as a practical management strategy has been widely used by large enterprises in the world. Recent years, more and more small and medium enterprises are also focusing investment on training. However, the question of how to evaluate the quality and effectiveness of training has been a big problem, which hasn't been solved well in the work of practice, it not only directly affect the scientific measurement and the control of the economy and the effectiveness in enterprises'training, but also influence the further development of the enterprise. Therefor, design a project can evaluate the training effect of the staff members, is one of the key success factor in enterprises which want to form their competitive advantage.On foreign and domestic training evaluation model, the Kirkpatrick model is the most representative evaluation model. This model was separated training effectiveness evaluation into four levels of layer, reactive layer, learning layer, behavior level and results level, and respectively summarized the basic method of each levers, it has great significance to the training effect's theoretical research and practical work, it is also the base of other model, but the two latter levels'indexes are slightly obscure of Kirkpatrick model, so the training don't have slightly accurate evaluation results. In order to remedy the defect, we can fix the model with Fuzzy Analytic Hierarchy Process (FAHP) to make the evaluation results quantified.According to the field of investigation and analysis, the evaluation of the management training existed problems, such as the training effect evaluation methods are simple, the indexes are difficult to quantify, the work-load and the evaluation results are fuzzy. The management training optimization design of evaluation project are based on Kirkpatrick model, marching with the implementation of training effect evaluation, the collection of all levels'index, the comprehensive evaluation of the implementation effect and feedback results. According to the experts'index advices, the management training companies'reactive layer of evaluation on project used questionnaire survey which includes evaluation of logistics, trainers, the trainees'basic situation, teaching management and training usefulness. And on the lever of learning used Bulge Test, evaluation and measurement the understanding and mastering of the content which includes the trainee's knowledge, skill and attitude. Because of the lag of time on the behavior level and results level, the Kirkpatrick model trends to fuzzification, in order to quantifying the results of training evaluation, we can fix the model with FAHP. Kirkpatrick model's two layers as big dimensions, and divided into several small layer, on this account, construct the sets of the factor evaluation, draw factors weights, and determine evaluation sets according with the fuzzy mathematics method, evalue the two levels under fuzzy comprehensive evaluation, draw quantitative evaluation results.The optimize designed training effect evaluation system was used by the XG enterprise which was serviced by the management companies, after priority analyses the data of the management training in human resources, obtained the training evaluation results. And match the training evaluation with satisfaction from the companies, so judge the effectiveness. For one thing, it can guide the training evaluation, for another thing, it can find the key difficulty of the appraisal process in implementing.Although we fix the latter layers with FAHP, combined qualitative analysis with quantitative analysis, it still exists many shortages, such as the index extraction method is subjective, evaluation methods targeted are not strong.
Keywords/Search Tags:Kirkpatrick model, training effect evaluation, evaluation indicators, optimize the evaluation system
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