Author(s)

Dan Li^*, Jinping Sun, Zilong Li

Affiliation(s)

School of Information Engineering(School of Big Data), Xuzhou University of Technology, Xuzhou, Jiangsu, China.

Corresponding Author

Dan Li, email: lidanonline@xzit.edu.cn

ABSTRACT

Based on the analysis of learners' cognitive state, learning style and other data, big data uses the analysis model to build an interpretation framework that describes learners' characteristics and learners' group characteristics, so as to achieve a better understanding of learners before the implementation of instructional design, as well as the integration and integration of learning resources in the process of instructional design. By interpreting the data, finding the difficulty of learning content, mining and presenting the rules of learners' learning result data, we can better determine the effectiveness of the teaching process, predict the future learning trend, and promote the continuous adjustment and improvement of teaching content.

KEYWORDS

Big data, group characteristics, higher education, teaching design and evaluation.

CITE THIS PAPER

Li Dan, Sun Jinping, Li Zilong. Research on the influence of higher education teaching design and evaluation under the framework of interpreting learners' group characteristics. Eurasia Journal of Science and Technology. 2022, 4(2): 1-5.

REFERENCES

[1]Taele, P. , and  T. Hammond . "BopoNoto: An Intelligent Sketch Education Application for Learning Zhuyin Phonetic Script. " The 21st International Conference on Distributed Multimedia Systems 2015.

[2]Liu, W. . "Exploration and Practice in the Classroom Teaching of Higher Vocational Education in the Intelligent Mobile Phone and "Internet Plus"." Education Teaching Forum (2017).

[3]Zhu, and Biao. "Design and Implementation of Intelligent Remote Multimedia Physical Education Teaching System." International Conference on Intelligent Transportation IEEE Computer Society, 2016:421-423.

[4]Leng,J.,L.U. Xiaoxu, and Z. Xiao . "Key Scientific Problems and Applied Research Driven by Educational Big Data in Education." Journal of Open Learning (2019).

[5]Zeng, W. , et al. "Research on the application of big data in the reform of college education mode—taking sports as an example." CIPAE 2021: 2021 2nd International Conference on Computers, Information Processing and Advanced Education 2021.

[6]Fischer, C. , et al. "Mining Big Data in Education: Affordances and Challenges." Review of Research in Education 44.1(2020).

[7]Othman, Oziah ,  Z. H. Iksan , and  R. M. Yasin . "Teachers' Views towards Changes in Curriculum and the Use of Real-Time Big Data in Statistics Education." Creative Education 12.10(2021):17.

[8]Wang, C. , and  Y. Wang . "Opportunities for Digital Culture and Innovation under Cultural Construction in the Big Data Era -- Take Digital Cultural Innovation in Jiangxi Universities as an Example." International Journal of Social Science and Education Research 2.11(2020):38-43.

[9]Bonami, Beatrice|Piazentini, Luiz|Dala-Possa, André. "Education, Big Data and Artificial Intelligence: Mixed Methods in Digital Platforms. " Comunicar: Media Education Research Journal 28(2020).

[10]Bouache, M. . "How Can Big Data Improve Higher Education Through Deep Learning? Equity and access to education." ICBDE2021 International Conference Proceedings by ACM ACM, 2021.

[11]Bourekkache, S. , and  O. Kazar . "Mobile and Adaptive Learning Application for English Language Learning." International journal of information and communication technology education: an official publication of the Information Resources Management Association 16.2(2020):36-46.

[12]Troussas, C. , A. Krouska , and  C. Sgouropoulou . "A Novel Teaching Strategy Through Adaptive Learning Activities for Computer Programming." IEEE Transactions on Education PP.99(2020):1-7.