Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Computer Graphics and Games pp 1–10Cite as

Design Framework for Learning to Support Industry 4.0

  • Living reference work entry
  • First Online:

Synonyms

Education model; Education pedagogy; Fourth Industrial Revolution; Industry 4.0; Learning analytics; Learning framework

Definition

Learning analytics is defined as the measurement, gathering, analysis, and reporting of data about learners and their environments, for the aim of understanding and improving learning process and the contexts in which learning occurs (Siemens and Baker 2012).

Introduction

The technology era has been growing very quickly, and it leads to the new industrial revolution which is also known as Industry 4.0. The inventions of new technologies like virtual reality, 3D printer, and the Internet have greatly influenced different sectors of the world economy. The digital technology sector in the UK has grown tremendously despite the economic crisis in 2008. Based on the Tech Nation Report in 2018, the UK digital tech sector is worth nearly £184bn to the economy, a rise from £170bn in 2016 (Cahill et al. 2018). However, Job Market Report 2017 has shown that...

This is a preview of subscription content, log in via an institution.

References

  • Bacigalupo, M., Kampylis, P., Punie, Y., Van den Brande, G.: EntreComp: The Entrepreneurship Competence Framework. Publication Office of the European Union, Luxembourg (2016)

    Google Scholar 

  • Balula, A.: The use of DigComp in teaching and learning strategies: a roadmap towards inclusion. In: Proceedings of the 7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-Exclusion, Vila Real, Portugal pp. 275–282. ACM (2016)

    Google Scholar 

  • Bandura, H.: Human agency in social cognitive theory. Am. Psychol. 44(9), 1175 (1989)

    Article  Google Scholar 

  • Bandura, A.: Self-Efficacy: The Exercise of Control. Freeman, New York (1997)

    Google Scholar 

  • Cahill, F., Windsor, G., Sorotos, H.E., Cousins, L., Boga, S., Mohamed, S.B.: Connection and collaboration: powering UK tech and driving the economy. Tech Nation. https://technation.io/wp-content/uploads/2018/05/Tech-Nation-Report-2018-WEB-180514.pdf (2018). Accessed 25 July 2018

  • Cai, S., Chiang, F.K., Sun, Y., Lin, C., Lee, J.J.: Applications of augmented reality-based natural interactive learning in magnetic field instruction. Interact. Learn. Environ. 25(6), 1–14 (2017)

    Article  Google Scholar 

  • Campbell, J.P., DeBlois, P.B., Oblinger, D.G.: Academic analytics: a new tool for a new era. EDUCAUSE Rev. 42(4), 40 (2007)

    Google Scholar 

  • Chatti, M.A., Dyckhoff, A.L., Schroeder, U., Thüs, H.: A reference model for learning analytics. Int. J. Technol. Enhanc. Learn. 4(5–6), 318–331 (2012)

    Article  Google Scholar 

  • Daniel, B.: Big data and analytics in higher education: opportunities and challenges. Br. J. Educ. Technol. 46(5), 904–920 (2015)

    Article  Google Scholar 

  • Dice: Job Market Report 2017. Dice Publishing. http://assets.theitjobboard.com/JE/uk/Dice_Job_Market_Report_2017.pdf (2017). Accessed 25 July 2018

  • Evangelinos, G., Holley, D.: Investigating the digital literacy needs of healthcare students when using mobile tablet devices. EAI Endorsed Trans. e-Learn. 160, 60–67 (2016)

    Google Scholar 

  • Ferguson, R.: Learning analytics: drivers, developments and challenges. Int. J. Technol. Enhanc. Learn. 4(5–6), 304–317 (2012)

    Article  Google Scholar 

  • Ferrari, A.: DIGCOMP: A Framework for Developing and Understanding Digital Competence in Europe. JRC83167 Scientific and Policy Report. Publications Office of the European Union, Seville, Spain (2013)

    Google Scholar 

  • Gerstein, J.: Moving from Education 1.0 through Education 2.0 towards Education 3.0. In: Blaschke, L.M., Kenyon, C., Hase, S. (eds.) Experiences in Self-Determined Learning, pp. 83–98. Createspace Independent Publishing Platform, California (2014)

    Google Scholar 

  • Greenwood, J.: The Third Industrial Revolution: Technology, Productivity, and Income Inequality (No. 435). American Enterprise Institute, Washington, DC (1997)

    Google Scholar 

  • Greller, W., Drachsler, H.: Translating learning into numbers: a generic framework for learning analytics. J. Educ. Technol. Soc. 15(3), 42 (2012)

    Google Scholar 

  • Hatlevik, O.E., Guðmundsdóttir, G.B., Loi, M.: Examining factors predicting students’ digital competence. J. Inf. Technol. Educ. Res. 14, 123–137 (2015)

    Google Scholar 

  • Hughes, T.P.: Networks of Power: Electrification in Western Society, pp. 1880–1930. JHU Press, Baltimore (1993)

    Google Scholar 

  • Khalil, M., Ebner, M.: What is learning analytics about? A survey of different methods used in 2013–2015. In: The Smart Learning Conference, Dubai, UAE, 294–304. Dubai: HBMSU Publishing House (2016)

    Google Scholar 

  • Khan, R.N.: The Third Industrial Revolution: An Economic Overview. Impact of Science on Society, vol. 146, pp. 115–122. Taylor and Francis/UNESCO, London (1987)

    Google Scholar 

  • Larusson, J.A., White, B.: Learning Analytics: From Research to Practice, vol. 13. Springer, Heidelberg (2014)

    Google Scholar 

  • Leadbeater, C.: What’s Next? 21 Ideas for 21st Century Learning, Innovation Unit, London (2008)

    Google Scholar 

  • Lepper, M.R., Corpus, J.H., Iyengar, S.S.: Intrinsic and extrinsic motivational orientations in the classroom: age differences and academic correlates. J. Educ. Psychol. 97(2), 184 (2005)

    Article  Google Scholar 

  • Liñán, L.C., Pérez, Á.A.J.: Educational data mining and learning analytics: differences, similarities, and time evolution. Int. J. Educ. Technol. High. Educ. 12(3), 98–112 (2015)

    Google Scholar 

  • Lortie, D.: Schoolteacher: A Sociological Study. University of Chicago Press, Chicago (2002)

    Google Scholar 

  • Manpower Group: Talent Shortage Survey 2018- Solving the Talent Shortage: Build, Buy, Borrow and Bridge. Manpower Group Publishing. https://go.manpowergroup.com/hubfs/TalentShortage%202018%20(Global)%20Assets/PDFs/MG_TalentShortage2018_lo%206_25_18_FINAL.pdf (2018). Accessed 20 Sept 2018

  • Mavroudi, A., Giannakos, M., Krogstie, J.: Supporting adaptive learning pathways through the use of learning analytics: developments, challenges and future opportunities. Interact. Learn. Environ. 26(2), 206–220 (2018)

    Article  Google Scholar 

  • McWilliam, E.: Teaching for creativity: from sage to guide to meddler. Asia Pac. J. Educ. 29(3), 281–293 (2009)

    Article  Google Scholar 

  • Meyer, B., Haywood, N., Sachdev, D., Faraday, S.: Independent Learning: Literature Review. Research Report No. DCSF-RR051. Department for Children, Schools and Families, Nottingham (2010). www.gov.uk/government/uploads/system/uploads/attachment_data/file/222277/DCSF-RR051.pdf. Last accessed 8 Apr 2018

    Google Scholar 

  • Pérez-López, D., Contero, M.: Delivering educational multimedia contents through an augmented reality application: a case study on its impact on knowledge acquisition and retention. Turk. Online J. Educ. Technol. 12(4), 19–28 (2013)

    Google Scholar 

  • Petrina, S.: Multidisciplinary technology education. Int. J. Technol. Des. Educ. 8, 103–138 (1998)

    Article  Google Scholar 

  • Robinson, K.: Out of Our Minds: Learning to Be Creative. Wiley, West Sussex (2011)

    Google Scholar 

  • Romero, C., Ventura, S., Pechenizkiy, M., Baker, R.S.: Handbook of Educational Data Mining. CRC Press, London (2010)

    Google Scholar 

  • Ryan, R.M., Deci, E.L.: Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp. Educ. Psychol. 25(1), 54–67 (2000)

    Article  Google Scholar 

  • Saveedra, A., Opfer, V.: Teaching and Learning 21st Century Skills: Lessons from the Learning Sciences. A Global Cities Education Network Report. Asia Society, New York (2012). http://asiasociety.org/files/rand-0512report.pdf. Accessed 8 Apr 2018

    Google Scholar 

  • Siemens, G., d Baker, R.S.: Learning analytics and educational data mining: towards communication and collaboration. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, pp. 252–254. ACM, Vancouver, British Columbia, Canada (2012)

    Google Scholar 

  • Tang, M., Werner, C.H. (eds.): Handbook of the Management of Creativity and Innovation: Theory and Practice, pp. 225–229. World Scientific, London (2017)

    Google Scholar 

  • Van den Bogaard, M.E.D., De Vries, P.: Learning analytics is about learning, not about analytics. A reflection on the current state of affairs. In: 45th Annual SEFI Conference, Terceira Portugal, Lisbon (2017)

    Google Scholar 

  • Vuorikari, R., Punie, Y., Carretero Gomez, S., Van den Brande, G.: DigComp 2.0: The Digital Competence Framework for Citizens. Update Phase 1: The Conceptual Reference Model. JRC27948 Scientific and Policy Report. Office of the European Union, Luxembourg (2016)

    Google Scholar 

  • Wallner, T.: The return of the human. In: Jeschke, S., Hees, F., Richert, A., Trantow, S. (eds.) Prethinking Work – Insights on the Future of Work, pp. 19–20. Lit-Verlag, Hamburg (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Liverpool John Moores University, Liverpool, UK

    Sin Ying Tan, Dhiya Al-Jumeily, Abir Hussain & Yuanyuan Shen

  2. Kazan Federal University, Kazan, Russia

    Jamila Mustafina

Authors
  1. Sin Ying Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dhiya Al-Jumeily
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jamila Mustafina
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abir Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuanyuan Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sin Ying Tan .

Editor information

Editors and Affiliations

  1. Inst. for Ed., Research, a. Scholarships, Los Angeles, CA, USA

    Newton Lee

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Tan, S.Y., Al-Jumeily, D., Mustafina, J., Hussain, A., Shen, Y. (2020). Design Framework for Learning to Support Industry 4.0. In: Lee, N. (eds) Encyclopedia of Computer Graphics and Games. Springer, Cham. https://doi.org/10.1007/978-3-319-08234-9_382-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08234-9_382-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08234-9

  • Online ISBN: 978-3-319-08234-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation