The Construction and Optimization of an AI Education Evaluation Indicator Based on Intelligent Algorithms

The Construction and Optimization of an AI Education Evaluation Indicator Based on Intelligent Algorithms

Yu Zeng, Xing Xu
DOI: 10.4018/IJCINI.315275
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Abstract

The basic tool in the analytic hierarchy process (AHP) is the complete judgment matrix. To address the weakness of the AHP in determining weight in the comprehensive evaluation system, the particle swarm optimization (PSO)-AHP model proposed in this paper is based on the PSO in the meta-heuristic algorithm. The model was used to solve the indicator weights in the evaluation system of AI education in primary and secondary schools in Fujian Province and was compared with the genetic algorithm and war strategy optimization algorithm. From the comparison results, the PSO-AHP optimization is more effective among the three algorithms, and the indicator consistency can be improved by about 30%. They are both effective in solving the problem that once the judgment matrix is given in the AHP, the weights and indicator consistency cannot be improved. Finally, the results were tested by Friedman statistics to prove the viability of the proposed algorithm.
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Introduction

Research Background

Since the concept of artificial intelligence (AI) was proposed in the 1950s, after years of development and the integration of technologies such as the Internet, big data, and cloud computing in today’s society, a number of disruptive technologies have been produced. These technologies have had a great impact on the production and life of human society (Zhang, Lu, 2021). In July 2021, the Central Committee of the Communist Party of China and the State Council issued the “Opinions on Further Reducing the Burden of Students’ Homework and Off-Campus Training in Compulsory Education” (hereafter referred to as “double reduction”). With the promulgation of the double reduction policy, students’ learning pressure in the compulsory education stage has been greatly reduced, and more emphasis has been placed on the all-round development of students’ morality, intelligence, physique, beauty, and labor. In addition to education courses such as arts, music, and physical education, the AI education has gradually opened under the general trend of society (Fang, Huang, 2020; Kangasharju, Ilomäki, et al., 2022; Ng, Luo, et al., 2022). Some scholars have also paid attention to the development and prosperity of AI education (Tedre, Toivonen, et al., 2021; Chiu, Chai, 2020; Lin, Chai, et al., 2021; Wang, Cheng, 2021). In response to the development of the situation and policy requirements, (T. S. C. of China, 2017; M. of Education of the People’s Republic of China, 2018) some cities in China have begun to conduct the practical exploration of AI education in primary and secondary schools. These explorations are roughly divided into two categories:

  • The school-based curriculum that combines the practical theories developed by schools and their teachers within primary and secondary schools.

  • The practical teaching courses supported by external forces outside primary and secondary schools, such as universities and scientific research institutes.

With the issuance of the “New Batch of Artificial Intelligence Pilot Schools in Primary and Secondary Schools in Fujian Province” by the Education Department of Fujian Provincial (T. E. D. of Fujian Province, 2021), AI education in Fujian Province has received much attention, but the development of AI education still remains in the early stage of exploration, and a complete education evaluation system is still needed to measure the weight of each indicator. For example, Zhang et al. (2021) have proposed an evaluation indicators system for low-carbon industry development and energy conservation, Ren et al. (2018) have proposed an evaluation indicators system for ecological civilization education in Chinese universities, and Zhou et al. (2022) have proposed a quality evaluation system for college students’ innovation and entrepreneurship education. Prior to these proposals, Education Informatization 1.0 in China had already accomplished its goals; namely, introducing a variety of multimedia smart devices to schools to enhance learning and teaching. AI technology is being introduced to schools as part of the Education Information Technology 2.0 Action Plan (M. of Education of the People’s Republic of China, 2018) that is currently being presented. To encourage students’ creative thinking and practical skills to proactively adapt to the new opportunities and difficulties presented by the new wave of technology, the plan places a strong emphasis on the development of smart education. As of now, however, no evaluation standards are available to assess how effectively AI instruction is delivered on schools. A reasonable indicator evaluation system can not only make the management of AI education in schools more scientific but also enrich the existing theories and combine them with the actual practice, thus giving the research significant practical importance. The results of this work can be completely implemented to practice, serve as a foundation for developing relevant national standards and policies, and offer recommendations for the long-term advancement of intellectual education.

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