Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Student Personality, Motivation and Sustainability of Technology Enhanced Learning: A SEM-Based Approach

  • Conference paper
  • First Online:
Advances in Computing and Data Sciences (ICACDS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1848))

Included in the following conference series:

  • 364 Accesses

Abstract

Technology enhanced learning (TEL) has come into prominence and become more relevant after the onset of COVID-19 pandemic. However, it is not known that whether TEL will be socially sustainable, and what factors can affect its sustainability. Therefore, in this work we propose a new research model based on UTAUT2 and the Big 5 Personality Framework that considers several motivational factors together with the different personality traits of the students. Data is collected from two Asian countries and analyzed using a Covariance-based SEM method. Results suggest that motivational factors of performance expectancy, hedonic motivation, social influence, price value and habit significantly affect the social sustainability of TEL. Likewise, the personality traits of agreeableness and neuroticism are also relevant. Suitable theoretical and practical implications are discussed based on the results.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Almpanis, T., Joseph-Richard, P.: Lecturing from home: exploring academics’ experiences of remote teaching during a pandemic. Int. J. Educ. Res. Open. 3, 100133 (2022). https://doi.org/10.1016/j.ijedro.2022.100133

    Article  Google Scholar 

  2. Rohan, R., Pal, D., Funilkul, S.: Gamifying MOOC’s a step in the right direction? In: Proceedings of the 11th International Conference on Advances in Information Technology, pp. 1–10. ACM, New York, NY, USA (2020). https://doi.org/10.1145/3406601.3406607

  3. Nayak, B., Bhattacharyya, S.S., Goswami, S., Thakre, S.: Adoption of online education channel during the COVID-19 pandemic and associated economic lockdown: an empirical study from push–pull-mooring framework. J. Comput. Educ. 9, 1–23 (2021). https://doi.org/10.1007/s40692-021-00193-w

    Article  Google Scholar 

  4. Pal, D., Vanijja, V., Patra, S.: Online learning during COVID-19. In: Proceedings of the 11th International Conference on Advances in Information Technology, pp. 1–6. ACM, New York, NY, USA (2020). https://doi.org/10.1145/3406601.3406632

  5. Mushtaha, E., Abu Dabous, S., Alsyouf, I., Ahmed, A., Raafat Abdraboh, N.: The challenges and opportunities of online learning and teaching at engineering and theoretical colleges during the pandemic. Ain Shams Eng. J. 13, 101770 (2022). https://doi.org/10.1016/j.asej.2022.101770

    Article  Google Scholar 

  6. Martin, F., Xie, K., Bolliger, D.U.: Engaging learners in the emergency transition to online learning during the COVID-19 pandemic. J. Res. Technol. Educ. 54, S1–S13 (2022). https://doi.org/10.1080/15391523.2021.1991703

    Article  Google Scholar 

  7. Rohan, R., Dutsinma, F.L.I., Pal, D., Funilkul, S.: Applying the stimulus organism response framework to explain student’s academic self-concept in online learning during the COVID-19 Pandemic. In: Tiwari, S., Trivedi, M.C., Kolhe, M.L., Singh, B.K. (eds.) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol. 522, pp. 373–384 Springer, Singapore (2023).https://doi.org/10.1007/978-981-19-5292-0_35

  8. Perera, R.H.A.T., Abeysekera, N.: Factors affecting learners’ perception of e-learning during the COVID-19 pandemic. Asian Assoc. Open Univ. J. 17, 84–100 (2022). https://doi.org/10.1108/AAOUJ-10-2021-0124

    Article  Google Scholar 

  9. Visvizi, A., Daniela, L.: Technology-Enhanced learning and the pursuit of sustainability. Sustainability 11, 4022 (2019). https://doi.org/10.3390/su11154022

    Article  Google Scholar 

  10. Dutsinma, F.L.I., Pal, D., Roy, P., Thapliyal, H.: Personality is to a conversational agent what perfume is to a flower. IEEE Consum. Electron. Mag. 1–1 (2022). https://doi.org/10.1109/MCE.2022.3180183

  11. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425 (2003). https://doi.org/10.2307/30036540

  12. Venkatesh, T.: Xu: consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q. 36, 157 (2012). https://doi.org/10.2307/41410412

    Article  Google Scholar 

  13. Tamilmani, K., Rana, N.P., Wamba, S.F., Dwivedi, R.: The extended unified theory of acceptance and use of technology (UTAUT2): a systematic literature review and theory evaluation. Int. J. Inf. Manage. 57, 102269 (2021). https://doi.org/10.1016/j.ijinfomgt.2020.102269

    Article  Google Scholar 

  14. Pal, D., Arpnikanondt, C., Razzaque, M.A., Funilkul, S.: To trust or not-trust: privacy issues with voice assistants. IT Prof. 22, 46–53 (2020). https://doi.org/10.1109/MITP.2019.2958914

    Article  Google Scholar 

  15. Pal, D., Arpnikanondt, C.: An integrated TAM/ISS model based PLS-SEM approach for evaluating the continuous usage of voice enabled IoT systems. Wirel. Pers. Commun. 119(2), 1065–1092 (2021). https://doi.org/10.1007/s11277-021-08251-3

    Article  Google Scholar 

  16. Al-Azawei, A., Alowayr, A.: Predicting the intention to use and hedonic motivation for mobile learning: a comparative study in two Middle Eastern countries. Technol. Soc. 62, 101325 (2020). https://doi.org/10.1016/j.techsoc.2020.101325

    Article  Google Scholar 

  17. Sewandono, R.E., Thoyib, A., Hadiwidjojo, D., Rofiq, A.: Performance expectancy of E-learning on higher institutions of education under uncertain conditions: Indonesia context. Educ. Inf. Technol. 28, 4041–4068 (2022). https://doi.org/10.1007/s10639-022-11074-9

    Article  Google Scholar 

  18. Al-Emran, M., AlQudah, A.A., Abbasi, G.A., Al-Sharafi, M.A., Iranmanesh, M.: Determinants of using AI-based chatbots for knowledge sharing: evidence from PLS-SEM and fuzzy sets (fsQCA). IEEE Trans. Eng. Manag. 1–15 (2023). https://doi.org/10.1109/TEM.2023.3237789

  19. Bouzguenda, I., Alalouch, C., Fava, N.: Towards smart sustainable cities: a review of the role digital citizen participation could play in advancing social sustainability. Sustain. Cities Soc. 50, 101627 (2019). https://doi.org/10.1016/j.scs.2019.101627

  20. Pal, D., Arpnikanondt, C., Razzaque, M.A.: Personal information disclosure via voice assistants: the personalization–privacy paradox. SN Comput. Sci. 1(5), 1–17 (2020). https://doi.org/10.1007/s42979-020-00287-9

    Article  Google Scholar 

  21. Fang, H., Li, X., Zhang, J.: Integrating social influence modeling and user modeling for trust prediction in signed networks. Artif. Intell. 302, 103628 (2022). https://doi.org/10.1016/j.artint.2021.103628

    Article  MathSciNet  MATH  Google Scholar 

  22. Yoo, D.K., Cho, S.: Role of habit and value perceptions on m-learning outcomes. J. Comput. Inf. Syst. 60, 530–540 (2020). https://doi.org/10.1080/08874417.2018.1550731

    Article  Google Scholar 

  23. Nazir, S., Khadim, S., Ali Asadullah, M., Syed, N.: Exploring the influence of artificial intelligence technology on consumer repurchase intention: the mediation and moderation approach. Technol. Soc. 72, 102190 (2023). https://doi.org/10.1016/j.techsoc.2022.102190

    Article  Google Scholar 

  24. John, O.P., Srivastava, S.: The Big-Five trait taxonomy: history, measurement, and theoretical perspectives (1999)

    Google Scholar 

  25. Kim, K.-J., Liu, S., Bonk, C.J.: Online MBA students’ perceptions of online learning: benefits, challenges, and suggestions. Internet High. Educ. 8, 335–344 (2005). https://doi.org/10.1016/j.iheduc.2005.09.005

    Article  Google Scholar 

  26. Wallace, M.P.: Individual differences in second language listening: examining the role of knowledge, metacognitive awareness, memory, and attention. Lang. Learn. 72, 5–44 (2022). https://doi.org/10.1111/lang.12424

    Article  Google Scholar 

  27. Osei, H.V., Kwateng, K.O., Boateng, K.A.: Integration of personality trait, motivation and UTAUT 2 to understand e-learning adoption in the era of COVID-19 pandemic. Educ. Inf. Technol. 27, 10705–10730 (2022). https://doi.org/10.1007/s10639-022-11047-y

    Article  Google Scholar 

  28. Watjatrakul, B.: Online learning adoption: effects of neuroticism, openness to experience, and perceived values. Interact. Technol. Smart Educ. 13, 229–243 (2016). https://doi.org/10.1108/ITSE-06-2016-0017

    Article  Google Scholar 

  29. Waldeyer, J., et al.: A moderated mediation analysis of conscientiousness, time management strategies, effort regulation strategies, and university students’ performance. Learn. Individ. Differ. 100, 102228 (2022). https://doi.org/10.1016/j.lindif.2022.102228

    Article  Google Scholar 

  30. Lv, M., Sun, Y., Shi, B.: Impact of introversion-extraversion personality traits on knowledge-sharing intention in online health communities: a multi-group analysis. Sustainability. 15, 417 (2022). https://doi.org/10.3390/su15010417

    Article  Google Scholar 

  31. Tavitiyaman, P., Ren, L., Guan, J., Chung, K.-H.M.: How personality affects flow experience and performance in online classes: a cross-regional comparison among hospitality and tourism students. J. Hosp. Tour. Educ. 1–16 (2022). https://doi.org/10.1080/10963758.2022.2109479

  32. Pelletier, L.G., Legault, L.R., Tuson, K.M.: The environmental satisfaction scale. Environ. Behav. 28, 5–26 (1996). https://doi.org/10.1177/0013916596281001

    Article  Google Scholar 

Download references

Acknowledgement

This work has been partially supported by the Thailand Science Research and Innovation (TSRI) Basic Research Fund under grant no FRB650048/0164.

Author information

Authors and Affiliations

  1. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Rohani Rohan, Suree Funilkul & Debajyoti Pal

  2. Department of Operations Management, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India

    Subhodeep Mukherjee

  3. Department of Computer Science and Engineering, Camellia Institute of Technology, Kolkata, West Bengal, India

    Syamal Patra

Authors
  1. Rohani Rohan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Subhodeep Mukherjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Syamal Patra
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Suree Funilkul
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Debajyoti Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Debajyoti Pal .

Editor information

Editors and Affiliations

  1. Consilio Research Lab, Tallinn, Estonia

    Mayank Singh

  2. Jaypee University of Engineering and Technology, Guna, India

    Vipin Tyagi

  3. Jaypee University of Information Technology, Waknaghat, India

    P.K. Gupta

  4. Institute of Information Theory and Automation, Prague, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, ON, Canada

    Tuncer Ören

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Rohan, R., Mukherjee, S., Patra, S., Funilkul, S., Pal, D. (2023). Student Personality, Motivation and Sustainability of Technology Enhanced Learning: A SEM-Based Approach. In: Singh, M., Tyagi, V., Gupta, P., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2023. Communications in Computer and Information Science, vol 1848. Springer, Cham. https://doi.org/10.1007/978-3-031-37940-6_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-37940-6_42

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-37939-0

  • Online ISBN: 978-3-031-37940-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation