Abstract
To keep up with the technology reform, “absorbing, transferring and re-innovating” is a feasible and effective approach to technology improvement for late developing countries. However, it remains unclear about the mechanism and influencing factors in knowledge transfer of individual engineer, leading to the incapability in tackling the low-quality and low-efficiency transfer in this process. To solve this problem, this paper proposes an eye-tracking experiment to concentrate on the transfer of empirical engineering knowledge under technological paradigm shift, based on the transfer of learning theory and “Concept-Knowledge” theory. An experiment conducts in the conceptual design of new type accelerator, and measures the performance of engineers in the process of knowledge transfer. The result shows that the quality of transfer is positively affected by the creativity facet in self-direct learning, accuracy of mastering an original technological paradigm, and important noun concepts in accessing a new technological paradigm; while the efficiency of transfer is negatively affected by the integrity of mastering an original technological paradigm, and unrelated noun concepts and engineering plots in accessing a new technological paradigm. The output of this paper is supportive for constructing the transfer mechanism of empirical engineering knowledge under technological paradigm shift, and improving the performance of knowledge transfer in knowledge management aspect.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Blume, B.D., Ford, J.K., Baldwin, T.T., Huang, J.L.: Transfer of training: a meta-analytic review. J. Manag. 36(4), 1065–1105 (2010)
Schunk, D.: Learning Theories: An Educational Perspective, 4th edn, p. 220. Pearson, Upper Saddle River (2004)
Ausubel, D.P.: Educational Psychology: A Cognitive View. Am. J. Psychol. 83(2), 303 (1988)
Mayer, R.E.: Cognitive, metacognitive, and motivational aspects of problem solving. Instr. Sci. 26(1), 49–63 (1998)
Hatchuel, A., Weil, B.: CK design theory: an advanced formulation. Res. Eng. Des. 19(4), 181 (2009)
Hatchuel, A., Weil, B., Le Masson, P.: Towards an ontology of design: lessons from C-K design theory and forcing. Res. Eng. Des. 24(2), 147–163 (2013)
Poelmans, J., Dedene, G., Snoeck, M., Viaene, S.: An iterative requirements engineering framework based on formal concept analysis and C-K theory. Expert Syst. Appl. 39(9), 8115–8135 (2012)
Kroll, E., Le Masson, P., Weil, B.: Steepest-first exploration with learning-based path evaluation: uncovering the design strategy of parameter analysis with C-K theory. Res. Eng. Des. 25(4), 351–373 (2014)
Siddiq, F., Scherer, R.: Revealing the processes of students’ interaction with a novel collaborative problem solving task: an in-depth analysis of think-aloud protocols. Comput. Hum. Behav. 76, 509–525 (2017)
Just, M.A., Carpenter, P.A.: A theory of reading: from eye fixations to comprehension. Psychol. Rev. 87(4), 329 (1980)
Lai, M.L., Tsai, M.J., Yang, F.Y., Hsu, C.Y., Liu, T.C., Lee, S.W.Y., et al.: A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educ. Res. Rev. 10, 90–115 (2013)
Bi, Y., Reid, T.: Evaluating students’ understanding of statics concepts using eye gaze data. Int. J. Eng. Educ. 33(1), 225–235 (2017)
Deng, Y.: Adult Learning and Self-direct Learning. Wunan Book, Taiwan (2004). (in Chinese) 邓运林. 成人教学与自导学习[M]. 台湾:五南图书出版公司 (2004)
Li, J.: Negative language transfer in college English writing by Chinese students: problems and strategies. CELEA J. 2, 88–103 (2007)
Chou, J.S., Yang, J.G.: Project management knowledge and effects on construction project outcomes: an empirical study. Proj. Manag. J. 43(5), 47–67 (2012)
Acknowledgment
This research was supported by National Natural Science Foundation of China (Nos. 70971085, 71271133, 71671113, 71601113), Shanghai Science and Technology Commission (No. 13111104500), and Shanghai Municipal Education Commission (13ZZ012). The authors would like to express great gratitude to all the editors and reviewers for their fair, encouraging and constructive advice.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Li, X., Jiang, Z., Guan, Y., Li, G. (2019). Transfer of Empirical Engineering Knowledge Under Technological Paradigm Shift. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 857. Springer, Cham. https://doi.org/10.1007/978-3-030-01177-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-01177-2_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01176-5
Online ISBN: 978-3-030-01177-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)