Matches in SemOpenAlex for { <https://semopenalex.org/work/W4295874844> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W4295874844 endingPage "10" @default.
- W4295874844 startingPage "1" @default.
- W4295874844 abstract "In recent years, many colleges and universities have been experimenting and exploring the evaluation of education and teaching system and have achieved certain results. In order to understand the quality of education and teaching system in colleges and universities, to improve the school conditions, and to promote the reform of teaching management, methods and means of evaluating the quality of education and teaching system in general higher education institutions are needed. Modern university education and teaching system should realize the combination of classroom teaching and practice teaching, and education and teaching system adopts the mode of the combination of on-campus practice and off-campus practice, so the design of teaching system is the key to the quality of teaching. Aiming at the current problem that talents cultivated by colleges and universities can hardly meet social demands in terms of engineering practice ability, innovation ability, and international competitiveness, this paper proposes the evaluation and adjustment of college education and teaching system driven by algorithms based on artificial intelligence (AI). By designing the teaching system of talent cultivation, and then establishing a quantitative and controllable quality assurance system for practical teaching, a new mechanism for the design of university education system is further explored. Specifically, the framework of the instructional system is built with the aid of an actor-critic algorithm in reinforcement learning, which assists in the design of the university education system, allowing students to truly understand, master and flex their knowledge, and strengthening the correct understanding of the students' internal learning mechanisms. The practical teaching effect shows that the AI-driven instructional designs are more popular with contemporary students and have higher evaluation scores. The numerical experiment results also show the stability of the instructional design, overcoming the drawbacks of traditional manual subjectivity in the design. AI-driven college education and teaching system is conducive to cultivating students' solid technical theoretical foundation. Therefore, through the AI-driven teaching system to strengthen the training of practical ability, so as to comprehensively improve students' comprehensive quality and innovation ability." @default.
- W4295874844 created "2022-09-15" @default.
- W4295874844 creator A5034062577 @default.
- W4295874844 date "2022-09-10" @default.
- W4295874844 modified "2023-09-26" @default.
- W4295874844 title "Design and Application of Artificial Intelligence Technology-Driven Education and Teaching System in Universities" @default.
- W4295874844 cites W2072812723 @default.
- W4295874844 cites W2109154290 @default.
- W4295874844 cites W2162078145 @default.
- W4295874844 cites W2317987987 @default.
- W4295874844 cites W2618369548 @default.
- W4295874844 cites W2803937896 @default.
- W4295874844 cites W2908402086 @default.
- W4295874844 cites W3024269187 @default.
- W4295874844 cites W3087405997 @default.
- W4295874844 cites W3090363550 @default.
- W4295874844 cites W3099231346 @default.
- W4295874844 cites W3100789280 @default.
- W4295874844 cites W3120892219 @default.
- W4295874844 cites W3132709382 @default.
- W4295874844 cites W3134445832 @default.
- W4295874844 cites W3169924685 @default.
- W4295874844 cites W3177669185 @default.
- W4295874844 cites W3188473925 @default.
- W4295874844 cites W3188987586 @default.
- W4295874844 cites W3199814407 @default.
- W4295874844 cites W3203076355 @default.
- W4295874844 cites W3204760719 @default.
- W4295874844 cites W4205160884 @default.
- W4295874844 cites W4205346763 @default.
- W4295874844 cites W4213377513 @default.
- W4295874844 cites W4214737092 @default.
- W4295874844 cites W4220737776 @default.
- W4295874844 cites W4220758675 @default.
- W4295874844 cites W4220786059 @default.
- W4295874844 cites W4226049981 @default.
- W4295874844 cites W4285246637 @default.
- W4295874844 cites W4285278949 @default.
- W4295874844 cites W4293079885 @default.
- W4295874844 doi "https://doi.org/10.1155/2022/8503239" @default.
- W4295874844 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36124170" @default.
- W4295874844 hasPublicationYear "2022" @default.
- W4295874844 type Work @default.
- W4295874844 citedByCount "2" @default.
- W4295874844 countsByYear W42958748442023 @default.
- W4295874844 crossrefType "journal-article" @default.
- W4295874844 hasAuthorship W4295874844A5034062577 @default.
- W4295874844 hasBestOaLocation W42958748441 @default.
- W4295874844 hasConcept C110354214 @default.
- W4295874844 hasConcept C111472728 @default.
- W4295874844 hasConcept C120912362 @default.
- W4295874844 hasConcept C127413603 @default.
- W4295874844 hasConcept C138885662 @default.
- W4295874844 hasConcept C145420912 @default.
- W4295874844 hasConcept C151416629 @default.
- W4295874844 hasConcept C15744967 @default.
- W4295874844 hasConcept C17744445 @default.
- W4295874844 hasConcept C199539241 @default.
- W4295874844 hasConcept C2777632682 @default.
- W4295874844 hasConcept C2779530757 @default.
- W4295874844 hasConcept C41008148 @default.
- W4295874844 hasConcept C88610354 @default.
- W4295874844 hasConceptScore W4295874844C110354214 @default.
- W4295874844 hasConceptScore W4295874844C111472728 @default.
- W4295874844 hasConceptScore W4295874844C120912362 @default.
- W4295874844 hasConceptScore W4295874844C127413603 @default.
- W4295874844 hasConceptScore W4295874844C138885662 @default.
- W4295874844 hasConceptScore W4295874844C145420912 @default.
- W4295874844 hasConceptScore W4295874844C151416629 @default.
- W4295874844 hasConceptScore W4295874844C15744967 @default.
- W4295874844 hasConceptScore W4295874844C17744445 @default.
- W4295874844 hasConceptScore W4295874844C199539241 @default.
- W4295874844 hasConceptScore W4295874844C2777632682 @default.
- W4295874844 hasConceptScore W4295874844C2779530757 @default.
- W4295874844 hasConceptScore W4295874844C41008148 @default.
- W4295874844 hasConceptScore W4295874844C88610354 @default.
- W4295874844 hasLocation W42958748441 @default.
- W4295874844 hasLocation W42958748442 @default.
- W4295874844 hasLocation W42958748443 @default.
- W4295874844 hasOpenAccess W4295874844 @default.
- W4295874844 hasPrimaryLocation W42958748441 @default.
- W4295874844 hasRelatedWork W2347871761 @default.
- W4295874844 hasRelatedWork W2355210071 @default.
- W4295874844 hasRelatedWork W2357815886 @default.
- W4295874844 hasRelatedWork W2358195025 @default.
- W4295874844 hasRelatedWork W2380677004 @default.
- W4295874844 hasRelatedWork W2391394668 @default.
- W4295874844 hasRelatedWork W2748952813 @default.
- W4295874844 hasRelatedWork W2885143447 @default.
- W4295874844 hasRelatedWork W2899084033 @default.
- W4295874844 hasRelatedWork W4285734253 @default.
- W4295874844 hasVolume "2022" @default.
- W4295874844 isParatext "false" @default.
- W4295874844 isRetracted "false" @default.
- W4295874844 workType "article" @default.