Capability level evaluation method, device and equipment and storage medium
A technology of ability and level, applied in the direction of instruments, data processing applications, resources, etc., can solve the problems of large deviation between the estimated ability level and the actual level, inability to optimize adjustment, poor flexibility, etc., and achieve the effect of accurate ability level assessment
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Embodiment 1
[0030] figure 1 It is a flow chart of an ability level evaluation method provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation where the ability level of the object to be evaluated is evaluated based on two evaluation models. The method can be provided by the embodiment of the present invention The capability level assessment device or equipment can be implemented, and the device can be implemented in the form of hardware and / or software. The method specifically includes:
[0031] S101. Determine an evaluation topic for an object to be evaluated.
[0032] Wherein, the object to be evaluated may be a user who needs to assess the ability level, and the ability level assessment requirement may be the ability level to evaluate a certain skill of the user, for example, it may be the ability level to evaluate the user's English proficiency, or it may be to evaluate the ability level of a certain skill of the user. On the one hand, the ab...
Embodiment 2
[0046] figure 2 Embodiment 2 of the present invention provides a flow chart of a capability level evaluation method. The method is further optimized on the basis of the above embodiments, and specifically provides an introduction on how to construct the first evaluation model and the second evaluation model. Such as figure 2 As shown, the method includes:
[0047] S201, constructing a model where the input is capability parameters, the model parameters are attribute information of evaluation items, and the model output is a first evaluation model of correct answer probability of evaluation items.
[0048] Optionally, the model input of the first evaluation model constructed in the embodiment of the present invention is the ability parameter; the model parameter of the first evaluation model is the attribute information of the evaluation item, and the model output of the first evaluation model is the correct answer probability of the evaluation item. The first evaluation mo...
no. 3 example
[0063] image 3 Embodiment 3 of the present invention provides a flow chart of an ability level assessment method. This method is further optimized on the basis of the above-mentioned embodiments, and specifically gives how to perform the first assessment model and the second assessment according to the actual answering situation. An introduction to cross-iterative training of models. Such as image 3 As shown, the method includes:
[0064] S301. The input of the model construction is the ability parameter, the model parameter is the attribute information of the evaluation item, and the model output is the first evaluation model of the correct answer probability of the evaluation item.
[0065] S302, building a model whose input is the attribute information of the evaluation item, the model parameter is the ability parameter, and the model output is the second evaluation model of the correct answer probability of the evaluation item.
[0066] S303. Determine an evaluation t...
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