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Designing Training Programs to Introduce Emerging Technologies to Future Workers—A Pilot Study Based on the Example of Artificial Intelligence Enhanced Robotics

Author

Listed:
  • Janika Leoste

    (School of Educational Sciences, Tallinn University, 10120 Tallinn, Estonia)

  • Tiia Õun

    (School of Educational Sciences, Tallinn University, 10120 Tallinn, Estonia)

  • Krista Loogma

    (School of Educational Sciences, Tallinn University, 10120 Tallinn, Estonia)

  • José San Martín López

    (School of Computer Science & Engineering, Universidad Rey Juan Carlos, Calle Tulipán, s/n, 28933 Móstoles, Madrid, Spain)

Abstract

Implementing an Emerging Technology (ET) is a difficult task due to people lacking ET-related knowledge and skills or having skeptical and negative attitudes towards the ET. As learners construct their understanding about an ET and develop related skills by actually passing through the ET Innovation Process (IP) stages (Awareness, Acceptance and Adoption), it could be useful to provide them with training that imitates certain IP stages. Using Artificial Intelligence Enhanced Robotics (AIER) as the example ET, we designed a two-day workshop to lead learners ( n = 16) through the AIER IP Awareness stage, and a six-week training course with eight contact days to simulate the AIER IP Acceptance stage to learners ( n = 10). Using online surveys and quantitative content analysis methods we confirmed that the workshop format increased the AIER-related self-confidence and general knowledge in 78% of participants, while the training course helped more than half of the participants to construct usable knowledge about a specific AIER and to see its possibilities in their specific work-place contexts. This paper is the pilot of using the Technology-Enhanced Learning Innovation Process (TELIP) model, first tested on a STEAM innovation, outside the educational context, for developing appropriate training approaches for specific ET IP stages.

Suggested Citation

  • Janika Leoste & Tiia Õun & Krista Loogma & José San Martín López, 2021. "Designing Training Programs to Introduce Emerging Technologies to Future Workers—A Pilot Study Based on the Example of Artificial Intelligence Enhanced Robotics," Mathematics, MDPI, vol. 9(22), pages 1-19, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2876-:d:677514
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    References listed on IDEAS

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    1. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    2. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    3. Kevin Zhu & Kenneth L. Kraemer & Sean Xu, 2006. "The Process of Innovation Assimilation by Firms in Different Countries: A Technology Diffusion Perspective on E-Business," Management Science, INFORMS, vol. 52(10), pages 1557-1576, October.
    4. Ko, Eunju & Kim, Sook Hyun & Kim, Myungsoo & Woo, Ji Young, 2008. "Organizational characteristics and the CRM adoption process," Journal of Business Research, Elsevier, vol. 61(1), pages 65-74, January.
    5. Goodarzi, Shadi & Masini, Andrea & Aflaki, Sam & Fahimnia, Behnam, 2021. "Right information at the right time: Reevaluating the attitude–behavior gap in environmental technology adoption," International Journal of Production Economics, Elsevier, vol. 242(C).
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