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The construction of a correct worldview, outlook on life, and values for students is linked to the development and breakthrough in the management of ideological as well as political education of students. At the same time, college students must be encouraged to follow well-rounded education and struggle to be well-prepared for the challenges of the new era. In order to raise students’ understanding of the critical role that political and ideological education plays in their academic success, it is authoritative that efforts to integrate these two spheres of learning be extended and new encounters made. That’s what prompted this study, which is focused on assessing college students’ level of ideological and political education administration, and it uses a mixture of big data technologies as well as artificial intelligence (AI) to do it. The accuracy of the traditional ideological as well as political education management quality assessment algorithm is not high, feature information extracted by the single-scale neural network (NN) is not rich enough, and the multiscale convolutional network (CN) fusion cannot consider the different values and importance for each scale. In this paper, the convolution kernel of the two-dimensional CN is changed to a one-dimensional convolution kernel, and the multiscale feature fusion CN model MCNN is first designed. The model is optimized and improved, the attention mechanism is integrated, and the MACNN model for the management evaluation of ideological as well as political education is proposed. Besides, this work organizes the network model in a wireless network environment that users can contact and operate at any time.

There are more than 14,000 square kilometers of mining subsidence areas in China, most of which have been reclaimed for the construction of new buildings. In the past, few special measures were required for the foundations of small buildings above old gob areas. But a plan was created to construct a large office building 100 m in length, 90 m in width, and 100 m in height, above old gob areas in the Huaibei subsidence area. However, the results of exploration borehole data and borehole TV observation indicated a broken bedrock stratum and developmental fractures above the old gob areas, and thus, the space stabilities of the building foundation were poor. Therefore, grouting reinforcement measure was adopted for the old gob and foundation areas. And the grouting effect was examined using borehole TV observation and the water injection test, where the detection results of boreholes TV observation showed that the filling ratio of the stratum fracture was over 85%, and the stability of the foundation was obviously enhanced. In addition, we monitored the settlement of the foundation continuously for 930 days. The results show that the maximum cumulative subsidence was 15.3 mm and the maximum slope was 0.05 mm/m, which verifies that grouting reinforcement is feasible in terms of the safety of large buildings constructed over old gob areas using bedrock stratum grouting in the Huaibei subsidence area.