There is an issue with erroneous assessment, which is a major concern when it comes to evaluating the success of foreign language teaching methods. The impact assessment challenge in evaluating the effect of foreign language education cannot be solved by the usual genetic algorithm, and the results are not sufficient. Consequently, this work analyses the design of a technique to evaluate the effectiveness of foreign language education and suggests a way based on reinforcement algorithms for doing so. First, the influencing elements are located using Markov’s decision theory. Then, the indicators are split according to the assessment method design criteria to eliminate interference factors. Subsequently, a design scheme for the reinforcement algorithm’s evaluation technique is derived from Markov decision theory, and the evaluation method’s design outcomes are thoroughly examined. In terms of evaluation method design influencing factor time and evaluation method design accuracy, the MATLAB simulation results reveal that the improved algorithm outperforms the conventional genetic algorithm under certain evaluation conditions.