In job market, there's an increased demand for application-oriented talents. Computer Supported Collaborative Learning (CSCL) is an important model of practice teaching for the training of the application-oriented talents. The status of practice teaching is studied based on the characteristics of the Information Management and Information System (IMIS). Computer Supported Collaborative Learning is introduced to break the shackles of the traditional practice teaching. An effective open practice teaching method is stated. The method has more communication and cooperation.

The existing privacy big data encryption algorithm cannot achieve real-time update of big data and repeat more big data, resulting in low attack resistance and more malicious attack data. An updating encryption algorithm for privacy big data based on consortium blockchain technology is proposed in this paper. The redundancy of privacy big data is obtained, the deduplication technology is designed on this basis, and the big data preprocessing is completed. The source coding sequence of privacy big data is obtained, the security of network route query and identity is verified, and the update and extraction of user data access authority are realized. The data structure of encrypted block is generated by using consortium blockchain technology and updating homomorphic encryption technology to realize the updating encryption algorithm of privacy big data. Experimental results show that the proposed algorithm improves the ability of resisting attacks and the amount of malicious data intercepted. The encryption complexity is lower, the time consumption is shorter, and the error of privacy large data encryption is smaller.

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Aiming to solve the problems of low fault tolerance, low throughput, and high delay in traditional methods, an improved method of the blockchain cross-chain consensus algorithm based on weighted PBFT is proposed. This article constructs a blockchain cross-chain exchange model based on cluster centers and divides the nodes in the blockchain system into consensus service nodes, cross-chain exchange nodes, and application nodes to improve the performance of consensus computing services. On this basis, according to the weighted PBFT consensus mechanism, the blockchain consensus environment is set up, and the distribution of nodes in the consensus domain and the blockchain signature scheme are obtained. Therefore, the blockchain cross-chain consensus optimization algorithm is designed to reduce throughput and delay and optimize the consensus effect. The experimental results show that the proposed method can effectively improve the shortcomings of traditional methods, with high throughput and low latency, and strong security. It shows that it is a low resource consumption and secure consensus method.