In order to solve the problems of uneven local educational resources, imperfect comprehensive practice systems, and insufficient teachers in rural schools, this paper proposes a research activity based on mobile information system. The research activities proposed in this paper take STEAM (the acronym of Science, Technology, Engineering, Art, and Mathematics) as the educational concept, carry out local research-based learning (research-based learning, hereinafter referred to as “research-based learning”), and create STEAM research activities suitable for local teaching in combination with the requirements of national education reform to improve students’ scientific literacy such as innovation, scientific, and technological level, and independent practice and exploration. The results are as follows: 92% of the students in the experimental group think that STEAM research and learning activities are very interesting and recognize the research and learning process; STEAM research activities have a strong role in promoting the cultivation of students’ three abilities and the training of core skills, and the scores are increased by about 50%; the excellent, good, qualified, and unqualified students in the experimental group accounted for 15%, 73%, 12%, and 0%, respectively, while the control group accounted for 6%, 55%, 32%, and 7%, respectively. Through the participation of STEAM research activities, the students’ learning attitude has been greatly improved. The practice of STEAM research activities proposed in this paper in the research and implementation institute has achieved remarkable results, which provides experience for Western schools in the follow-up stage of compulsory education to carry out STEAM research activities.
In order to solve the problem of quality education reform in research activities, a multiobjective optimization model for the optimal performance distribution of college teachers is proposed. We mainly use the multiobjective optimization method to study the allocation of optimal performance. On the basis of considering individual differences, a multiobjective optimization model is established with the goal of maximizing the total satisfaction of all assessment objects and balancing the satisfaction as much as possible by introducing the score conversion function and the satisfaction function. The results show that the variation trends of the weak Pareto fronts at five different confidence levels are basically the same; that is, different confidence levels have little effect on the results. Conclusion. The use of a multiobjective optimization model can improve the optimal performance distribution of college teachers, so as to effectively promote the reform of quality education in research activities.
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