Author(s)

Jie Huang^1,2

Affiliation(s)

¹Hunan Provincial Engineering Research Center for Missile Maintenance, Changsha 410024, Hunan, China.

²Department of Aviation Electronic Equipment Maintenance, Changsha Aeronautical Vocational and Technical College, Changsha 410024, Hunan, China.

Corresponding Author

Jie Huang

ABSTRACT

In the new era, artificial intelligence (AI) technology is effectively empowering the development of higher vocational education. Within this context, smart classrooms, evolved from the iteration and upgrading of multimedia classrooms, have become an essential and routine teaching environment in higher vocational institutions. Utilizing smart classrooms to promote deep learning among vocational students has emerged as a crucial approach for enhancing talent development quality in the future. This paper constructs a new model for smart classroom teaching in higher vocational education, which effectively standardizes the implementation of smart classroom teaching activities. Furthermore, the implementation requirements of this model are elaborated. This model demonstrates significant potential in effectively promoting deep learning among students.

KEYWORDS

Smart classroom; Deep learning; Teaching strategy

CITE THIS PAPER

Jie Huang. Promoting deep learning: smart classroom teaching strategies. World Journal of Educational Studies. 2025, 3(2): 69-72. DOI: https://doi.org/10.61784/wjes3047.

REFERENCES

[1] P-Dec V N. A Time for Deeper Learning Preparing Students for a Changing World. Education Digest Essential Readings Condensed for Quick Review, 2011, 77: 43-49.

[2] Y H Wang. Could a mobile-assisted learning system support flipped classrooms for classical Chinese learning?. Journal of Computer Assisted Learning, 2016, 1-25.

[3] Loyens S M M, Gijbels D, Coertjens L, et al. Students’ approaches to learning in problem-based learning: Taking into account professional behavior in the tutorial groups, self-study time, and different assessment aspects. Studies In Educational Evaluation, 2013, 39(1): 23-32.

[4] María, Consuelo Sáiz-Manzanares, César Ignacio García Osorio, José Francisco Díez-Pastor, et al. Will personalized e-Learning increase deep learning in higher education?. Information Discovery & Delivery, 2019, 1(47): 53-63.

[5] Schaufeli W B, Martinez I M, Pinto A M, et al. Burnout and Engagement in University Students: A Cross-National Study. Journal of Cross-Cultural Psychology, 2002, 33(5): 464-481.

[6] Clark K R. The Effects of the Flipped Model of Instruction on Student Engagement and Performance in the Secondary Mathematics Classroom. Journal of Educators Online, 2015, 12(1): 91-115.

[7] CHIH-YANG CHAO. Computer Aided Design Curriculum: A Study in High School Engineering Education. Computer Applications in Engineering Education, 2015, 514-526.

[8] Kaushal Kumar Bhagat. The Impact of the Flipped Classroom on Mathematics Concept Learning in High School. Educational Technology & Society, 2016, 19(3): 134-142.

[9] Snyder Catherine. Cast from the Past: Using Screen casting in the Social Studies Classroom. 2014, 105(6): 310-314.

[10] Shi Y, Ma Y, Macleod J, et al. College students' cognitive learning outcomes in flipped classroom instruction: a meta-analysis of the empirical literature. Journal of Computers In Education, 2019, 1-25.