A New Reciprocal Teaching Approach for Information Literacy Education under the Background of Big Data

Liu, Fei; Zhang, Qian

doi:10.3991/ijet.v16i03.20459

Cited by 15 publications

(10 citation statements)

References 9 publications

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“…The decision-making scene of education is more complex and changeable, and higher decision-making requirements are put forward. Data analysis suggests that IPE should apply the data-driven decision-making theory [ 23 ]. More targeted data need to be mined to establish a data screening, collection, analysis, and output model and rationally use data sources from different channels [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

Immersive Learning Method of Ideological and Political Education under Big Data and Artificial Intelligence

2022

Computational Intelligence and Neuroscience

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The study aims to explore the influence of big data on college students’ learning methods of ideological and political education (IPE) under artificial intelligence. First, the characteristics of big data are analyzed. Second, big data is introduced into IPE’s classroom teaching, and its influence on students’ learning methods is discussed. Finally, the questionnaire is designed to investigate students’ learning attitudes and teachers’ effectiveness. The results show that the scores of the students are poor, and the traditional teaching method should be updated to improve the teaching quality of IPE. Motivating students’ enthusiasm and updating the teaching content are the main tasks to improve students’ learning effect on IPE. College students who receive IPE based on big data have better academic performance and a positive learning attitude, and each factor is more significant than 0.05. It is concluded that big data has a considerable impact on IPE. It can promote students’ mastery of the knowledge and improve their learning efficiency.

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Section: Methodsmentioning

confidence: 99%

Immersive Learning Method of Ideological and Political Education under Big Data and Artificial Intelligence

2022

Computational Intelligence and Neuroscience

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“…e literature [4] referred to "electronic video" as "new media," from which the concept of new media was born. Nowadays, with the continuous development of digital media in the information age, there are more and more books on new media.…”

Section: Related Workmentioning

confidence: 99%

The Teaching Effect Evaluation Model of University Ideological and Political Theory under the Background of New Media and Big Data

Liu¹,

Madina

2022

Security and Communication Networks

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This study uses new media technology and big data technology to build a teaching impact assessment model of university ideological and political theory based on new media and big data in order to enhance the effect of ideological and political teaching in colleges and universities. Furthermore, by specifying the instance distribution interval, this work explains the probable probability distribution of all instances of the tuple, ensuring the integrity of the data information of the clustering object and therefore boosting the algorithm’s clustering accuracy. Furthermore, this research constructs an intelligent system frame structure by combining the real teaching requirements of ideology and politics. Finally, from the viewpoints of new media teaching efficiency and teaching impact assessment, this research develops experiments to validate system functionalities. The experimental research results show that the teaching effect evaluation model of university ideological and political theory constructed in this study based on new media and big data has a good teaching effect, and the effect of ideological and political teaching evaluation also meets the actual teaching needs.

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“…They have worked hard and actively pushed the development of educational and instructional systems, with some degree of success. The seamless blending of theory and practice is still not adequately accomplished [ 6 , 7 ]. The flawed design of the educational system is to blame.…”

Section: Introductionmentioning

confidence: 99%

Design and Application of Artificial Intelligence Technology-Driven Education and Teaching System in Universities

Zhang

2022

Computational and Mathematical Methods in Medicine

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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.

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A New Reciprocal Teaching Approach for Information Literacy Education under the Background of Big Data

Cited by 15 publications

References 9 publications

Immersive Learning Method of Ideological and Political Education under Big Data and Artificial Intelligence

Immersive Learning Method of Ideological and Political Education under Big Data and Artificial Intelligence

The Teaching Effect Evaluation Model of University Ideological and Political Theory under the Background of New Media and Big Data

Design and Application of Artificial Intelligence Technology-Driven Education and Teaching System in Universities

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