The effect of the use of an educational software based on the strategy of artificial intelligence on students’ achievement and their attitudes towards it

Alomari, Mohammed A.; Jabr, Manar Omar

doi:10.5267/j.msl.2020.5.030

Cited by 5 publications

(1 citation statement)

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“…Massive amounts of data are generated every second in the big data environment. Arti cial intelligence can greatly improve the speed and quality of data processing and be used to process large amounts of complex data to improve data security [2]. With the development of arti cial intelligence and the arrival of the 5G communication era, in order to realize the e ective management of massive network information, advanced arti cial intelligence technology can be adopted, many scienti c and reasonable solutions can be compiled, and an expert knowledge sharing system can be established to gradually improve the data analysis and processing e ect.…”

Section: Introductionmentioning

confidence: 99%

Student Education Management Strategy Based on Artificial Intelligence Information Model under the Support of 5G Wireless Network

Guan

2022

Computational Intelligence and Neuroscience

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With the popularity of the Internet and the advancement of information technology, more and more people are accepting the teaching and sharing of knowledge through the digitalization of information. The widespread adoption of 5G technology has pushed online learning even further into the mainstream. However, because online teaching does not have the drawback of being intuitive like classroom teaching, teachers’ assessments of students’ learning situations are less accurate. As a result, how to effectively evaluate students’ academic performance in the context of 5G wireless network technology is a pressing issue that must be investigated. By processing these heterogeneous large-scale learning records and integrating multiple perspectives to analyze this learning record information to identify students’ learning behaviors, this study proposes an integrated analysis algorithm based on artificial intelligence information technology. The possible learning outcomes of students are predicted based on their current learning situation, so teachers can provide auxiliary teaching strategies to students who may have learning difficulties based on the predicted information. The method proposed in this article uses information technology to predict students’ grades, and the analysis shows that the method is very effective. In this article, different grades of classification methods are used to analyze and predict the whole students. All grade classification methods are effective in describing decision rules. No matter what grades classification method is used, the error rate of students’ grades distribution is predicted to be below 40%.

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Section: Introductionmentioning

confidence: 99%