Guide Teaching System Based on Artificial Intelligence

被引:15
作者
Luo, Dali [1 ]
机构
[1] Financial Inst Trade, Chongqing Vocat Inst Engn, Chongqing, Peoples R China
关键词
intelligence; SSH; intelligence learning; !text type='Java']Java[!/text]EE;
D O I
10.3991/ijet.v13i08.9058
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
To improve the development and deployment efficiency of the system, this paper combined the software system with Java and AI language Prolog to achieve the guide teaching system based on artificial intelligence (AI). The system creatively adopted the theory of artificial intelligence expert system, at the same time, built a Struts+Spring+Hibernate lightweight JavaEE framework. The coupling degree of each module in the system was greatly reduced to facilitate the expansion of future functions. Based on the development principle of the artificial intelligence expert system, the system diagnosed the learner's mastery of each point of knowledge. It classified students' learning effect and evaluated the knowledge points. Making full use of the learning state of students and combining it with artificial intelligence expert system theory, the system developed a suitable learning strategy to help students improve their learning with less efforts. In addition, the system took the forgetting rule of human brain into account, which periodically presented trainees' knowledge points assessment and avoided students wasting time. The purpose was to help students improve their learning effect. Finally, the system was tested. The test results showed that the system is applicable and useful. It is concluded that the artificial intelligence system provides an example for the same method and has certain reference significance.
引用
收藏
页码:90 / 102
页数:13
相关论文
共 10 条
[1]   Machine Learning for First-Order Theorem Proving Learning to Select a Good Heuristic [J].
Bridge, James P. ;
Holden, Sean B. ;
Paulson, Lawrence C. .
JOURNAL OF AUTOMATED REASONING, 2014, 53 (02) :141-172
[2]  
HENDRAWAN Y, 2014, 19 IFAC TRIENN WORLD, P8122
[3]  
Hilles M.M., 2017, EUROPEAN ACAD RES, V4, P8783
[4]   A flowchart-based intelligent tutoring system for improving problem-solving skills of novice programmers [J].
Hooshyar, D. ;
Ahmad, R. B. ;
Yousefi, M. ;
Yusop, F. D. ;
Horng, S. -J. .
JOURNAL OF COMPUTER ASSISTED LEARNING, 2015, 31 (04) :345-361
[5]  
Melo F. V. S., 2013, Revista Brasileira de Pesquisa em Turismo, V7, P281
[6]   Intelligent Interface for Textual Attitude Analysis [J].
Neviarouskaya, Alena ;
Aono, Masaki ;
Prendinger, Helmut ;
Ishizuka, Mitsuru .
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2014, 5 (03)
[7]  
Pantic M., IEEE T ED, V48, P382
[8]   Improving students' help-seeking skills using metacognitive feedback in an intelligent tutoring system [J].
Roll, Ido ;
Aleven, Vincent ;
McLaren, Bruce M. ;
Koedinger, Kenneth R. .
LEARNING AND INSTRUCTION, 2011, 21 (02) :267-280
[9]  
Sanjika H., 2016, NAT LANG ENG, V22, P549, DOI [10.1017/S1351324916000139, DOI 10.1017/S1351324916000139]
[10]   Exploring the effectiveness of a novel feedback mechanism within an intelligent tutoring system [J].
Sullins, Jeremiah ;
Craig, Scotty D. ;
Hu, Xiangen .
INTERNATIONAL JOURNAL OF LEARNING TECHNOLOGY, 2015, 10 (03) :220-236