Practical evaluation of human-computer interaction and artificial intelligence deep learning algorithm in innovation and entrepreneurship teaching evaluation
Abstract
The rise of knowledge economy has drawn much attention to Innovation and Entrepreneurship Education (IEE). IEE is conducive to helping graduates relieve employment pressure, and also to cultivating students’ innovation ability and entrepreneurial willingness, which is also of great significance for promoting high-quality quantitative and sustainable development of social economy. However, the current IEE still has some limitations, such as the students’ insufficient entrepreneurial willingness, low innovation practice ability, and unreasonable evaluation methods of innovation and entrepreneurship teaching, which hinder the further development of IEE. Therefore, for the purpose of further promoting the development of IEE, this article studied the evaluation of innovation and entrepreneurship teaching, and proposed an innovation and entrepreneurship teaching evaluation system combining Human–Computer Interaction (HCI) and Deep Learning (DL). The evaluation system was used to evaluate the innovation and entrepreneurship teaching of Class A and Class B. The evaluation result showed that Class A’s innovation and entrepreneurship teaching evaluation score was 7; Class B’s innovation and entrepreneurship teaching evaluation score was 7.1. The evaluation of innovation and entrepreneurship teaching in Class A and Class B was still not high enough, and the teaching quality and effect still needed to be improved; the innovation and entrepreneurship teaching evaluation system combined wi…
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Wang et al. (2025) combined human-computer interaction and deep learning algorithm to design an intelligent evaluation system for innovation and entrepreneurship.
“Wang et al. (2025) combined human-computer interaction and deep learning algorithm to design an intelligent evaluation system for innovation and entrepreneurship.”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Wang et al. (2025)
AI is found to accurately assess students' learning process and outcomes, and further determine teaching effect.
“AI is found to accurately assess students' learning process and outcomes, and further determine teaching effect (Novais et al., 2023;Saad and Tounkara, 2023;Wang et al., 2025;Zhu et al., 2023).”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Wang et al., 2025
AI benefits assessments by generating personalized assignments, effectively assessing and predicting students' academic achievement and non-cognitive outcomes, identifying disadvantaged students, and assessing teaching effectiveness.
“Additionally, AI seems to benefit assessments by generating personalized assignments (Pereira et al., 2023), effectively assessing and predicting students' academic achievement (Wang et al., 2025) and non-cognitive outcomes (e.g., soft skills, Novais et al., 2023), identifying disadvantaged students (Saad and Tounkara, 2023), and assessing teaching effectiveness (Wang et al., 2025).”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Wang et al., 2025
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Liang, J., Stephens, J. M., & Brown, G. T. L. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1522841 · Cited by 112 · see citing works
- Authors
- Wang, D., Han, L., Cong, L., Zhu, H., & Liu, Y.
- Affiliations
- College of Science and Technology, Hebei Agricultural University
- College of Economics and Management, Hebei Agricultural University
- College of Humanities and Social Science, Hebei Agricultural University
- College of Financial Technology, Hebei Finance University
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2023-04-20
- Volume
- 41
- Issue
- 3
- Pages
- 1742-1750
- ISSN
- 1044-7318
- 1532-7590
- Cited by
- 20
- References
- 0
- Language
- en
- Funders
- Research of Higher Education Reform (2021GJJG594, 2022GJJG096)
- Research on the Construction of “Liberal Arts” + “Agriculture” Major in Agricultural Colleges (2022GJJG597)
- Hebei Educational Science “Fourteenth Five-Year Plan” (2205408, KY2021074)
- Hebei Agricultural University (2021xwk01)
- Ministry of Education (220600523243020)
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