Abstract
Building an innovative country and promoting employment through entrepreneurship is China’s major development strategy for the future. Building an innovative country needs to vigorously cultivate Bi-innovation talents. Based on the analysis of the quality structure of Bi-innovation talents, this paper puts forward reasonable ideas on the quality evaluation system of Bi-innovation talents from four aspects: evaluation principles, evaluation objectives, evaluation indicators and evaluation methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Men, Y., Cai, H.: Design of online training system for innovative and entrepreneurial talents based on interdisciplinary integration. In: Fu, W., Liu, S., Dai, J. (eds.) eLEOT 2021. LNICST, vol. 390, pp. 39–49. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-84386-1_4
Xu, C., Zhang, Z.: The effect of law students in entrepreneurial psychology under the artificial intelligence technology. Front. Psychol. 12, 731713 (2021)
Jin, C., Luo, Y., Cao, R., et al.: Research and practice on the training mode of innovative and entrepreneurial talents in colleges and universities: a case study of academic association of “federation of life science research and innovation.” Asian Agric. Res. 013(002), 55–57 (2021)
Cetindamar, D., Lammers, T., Zhang, Y.: Exploring the knowledge spillovers of a technology in an entrepreneurial ecosystem—the case of artificial intelligence in Sydney. Thunderbird Int. Bus. Rev. 62(5), 457–474 (2020)
Hu, W., Hu, Y., Lyu, Y., et al.: Research on integrated innovation design education for cultivating the innovative and entrepreneurial ability of industrial design professionals. Front. Psychol. 12, 693216 (2021)
Jiao, G., Li, L., Deng, H., et al.: Exploration on cultivation of practical ability of artificial intelligence talents in universities in the context of innovation and entrepreneurship education. In: 2020 IEEE 2nd International Conference on Computer Science and Educational Informatization (CSEI). IEEE (2020)
Wang, S.: Innovative thinking and practice of mobile interaction design teaching in artificial intelligence era. In: IC4E 2021: 2021 12th International Conference on E-Education, E-Business, E-Management, and E-Learning (2021)
Khadse, C., Chaudhari, B.S., Patharkar, A.A.: Electromagnetic field and artificial intelligence based fault detection and classification system for the transmission lines in smart grid. Energy Sources Part A Recovery Utilization Environ. Eff. 24, 1–16 (2021)
Gao, Y., Suo, X., Zheng, F.: The teacher evaluation and management system innovation based on the artificial intelligence algorithms. In: Abawajy, J.H., Choo, K.-K., Islam, R., Xu, Z., Atiquzzaman, M. (eds.) ATCI 2019. AISC, vol. 1017, pp. 1144–1149. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-25128-4_144
Barik, L., Barukab, O., Ahmed, A.A.: Employing artificial intelligence techniques for student performance evaluation and teaching strategy enrichment: an innovative approach. Int. J. Adv. Appl. Sci. 7(11), 10–24 (2020)
Eliiyi, U.: Artificial intelligence for smart cities: locational planning and dynamic routing of emergency vehicles. In: Bozkuş Kahyaoğlu, S. (ed.) The Impact of Artificial Intelligence on Governance Economics and Finance, Volume 2. AFSGFTA. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-8997-0_3
Chiang, L.H., Wang, Z., Braun, B., et al.: Towards artificial intelligence at scale in the chemical industry. AIChE J. 68(6), 1145–1157 (2022)
Vilone, G., Longo, L.: A novel human-centred evaluation approach and an argument-based method for explainable artificial intelligence. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds.) AIAI 2022. IFIPAICT, vol. 646, pp. 447–460. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-08333-4_36
Khan, S.U., Eusufzai, F., Azharuddin Redwan, M., Ahmed, M., Sabuj, S.R.: Artificial intelligence for cyber security: performance analysis of network intrusion detection. In: Ahmed, M., Islam, S.R., Anwar, A., Moustafa, N., Pathan, A.S.K. (eds.) Explainable Artificial Intelligence for Cyber Security. SCI, vol. 1025, pp. 113–139. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-96630-0_6
Weigang, L., et al.: New directions for artificial intelligence: human, machine, biological, and quantum intelligence. Front. Inform. Technol. Electron. Eng. 23(6), 984–990 (2022). https://doi.org/10.1631/FITEE.2100227
Acknowledgements
2021 Jilin higher education scientific research project “Research on the Quality Evaluation System of Entrepreneurial Talent Training in Private University Based on Improved Fuzzy Comprehensive Evaluation Method” (JGJX2021D657).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Zhang, J., Zhang, D. (2023). Construction of Quality Evaluation System for Innovative and Entrepreneurial Talent Training Under Artificial Intelligence System. In: Jan, M.A., Khan, F. (eds) Application of Big Data, Blockchain, and Internet of Things for Education Informatization. BigIoT-EDU 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 467. Springer, Cham. https://doi.org/10.1007/978-3-031-23944-1_36
Download citation
DOI: https://doi.org/10.1007/978-3-031-23944-1_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-23943-4
Online ISBN: 978-3-031-23944-1
eBook Packages: Computer ScienceComputer Science (R0)