During the operation of complex dynamic systems, the operator is exposed to unusual and abnormal situations, and has to be able to discriminate erroneous inputs, and promptly identify the source of the problem in order to define the corrective actions to be taken. In this work, the development and evaluation of an Intelligent Assistant for Operator?s Training (IAOT) is presented. It uses, as input, a recommended plan generated by a decision-theoretic planner, which establishes the sequence of actions that will allow a steam generator to reach its optimum operation. The system monitors the operator's actions and detects his/her discrepancies, compared to those recommended by the planner. On the basis of the above, follow-up advice is given on-line, and an evaluation of performance is given later. Results obtained from an experimental evaluation of IAOT show that the usage of the intelligent assistant can be helpful to increase operator performance.