The development of big data concepts and technology can not only effectively improve management efficiency but also promote the realization of personalized management. Based on the concept of big data and the management concepts advocated by scientific management theory, goal management theory, and human-oriented management theory, the survey materials were analyzed and organized to understand the current situation of student management in higher education institutions in terms of study management, internship management, merit management, life management, mental health management, and employment management. Combined with the background of big data, we found that there are problems in student management in higher education institutions, such as incomplete information collection, subjective decision-making, low efficiency of resource utilization, delayed management feedback, and lack of personalized management. Therefore, using the concept of big data to promote the optimization of student management in higher education institutions will be the future development trend.

Big data improves opportunities for enhancing and improving university students’ IPE. In order to improve the accessibility of IPE for university students, this study integrates big-data techniques into the IPE (Ideological and Political Education) model of university students and builds the IPE platform. This study presents the idea of user rating sparsity and employs a two-step training strategy to address the issues of user cold start and sparse data in light of the drawbacks of conventional methods. This algorithm produces a very small data structure, which saves a lot of storage space. This study also uses hybrid recommendation technology, which effectively enables platform users to select customized update resources based on their interest information. According to test results, this method’s suggestion accuracy can reach 95.69%, and it has a high user rating. This demonstrates that the method is reliable and accomplishes the desired result. This paper fully utilizes mega data to improve the accessibility of IPE for university students.

Nanoparticle Ru:TiO 2 films were prepared by a sol-gel process using RuCl 3 , Ti(OBu) 4 as raw material, the as-prepared film samples were also characterized by TG-DTA, SEM, and SPS testing techniques. TiO 2 nanoparticles experienced two processes of phase transition, i.e. amorphous to anatase and anatase to rutile at the calcining temperature range from 400 to 800 ºC. TiO 2 nanoparticles calcined at 700 ºC had similar composition, structure, morphology and particle size with the internationally commercial P-25 TiO 2 particles. Thus, the conclusion that 700 ºC might be the most appropriate calcining temperature during the preparation process of nanoparticle Ru:TiO 2 /ITO film photocatalysts could be made by considering the main factors such as the properties of TiO 2 nanoparticles, the adhesion of nanoparticle Ru:TiO 2 film to glass substrate, and the surface characteristics and morphology of nanoparticle Ru:TiO 2 /ITO film for the practice view. The SPS demonstrates that the effects of the quantum size on optical property were greater than that of the Coulomb and surface polarization. In addition, during the experimental process of the photocatalytic degradation phenol, the photocatalytic activity of nanoparticle Ru:TiO 2 /ITO film with five layers calcined at 700 ºC is the highest.