Skip to main content
SpringerLink
Log in

Latin American Smart University: Key Factors for a User-Centered Smart Technology Adoption Model

  • Chapter
  • First Online:
Sustainable Intelligent Systems

Part of the book series: Advances in Sustainability Science and Technology ((ASST))

Abstract

The quality of administrative, academic, and extension processes is influenced by the management of technology in universities. Smart technologies such as artificial intelligence (AI), cloud computing, the Internet of things (IoT), and big data continue to emerge with great prominence. Universities must use tools that connect learning with the use of new technologies, bridging gaps with the outside world. Smart education is provided by an educational environment supported by smart technologies and devices. A smart university is primarily based on the integration of smart technologies into the educational process. The emergence of this concept allows the application of a large number of components that involve the adaptation of the traditional educational model using these technologies. Many of the ideas of adoption in Latin American universities generate demotivation toward change and do not imply the expected impact in their processes. One way to prevent this situation is to monitor the adoption process itself. The generation of tools that can measure the level of adoption by universities is a necessity as smart technologies are incorporated and become more powerful. Focusing on the users of the processes is an objective of adoption measurement. A User-Centered Smart University Model is the goal of this transformation process, established on factors such as an individual’s perception, safety and risks, and organizational support.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover 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. A. Abushakra, D. Nikbin, Extending the UTAUT2 Model to Understand the Entrepreneur Acceptance and Adopting Internet of Things (IoT) (Springer International Publishing, 2019). https://doi.org/10.1007/978-3-030-21451-7

  2. A. Adamkó et al., Intelligent and Adaptive Services for a Smart Campus. in 5th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2014–Proceedings (2014), pp. 505–509. https://doi.org/10.1109/CogInfoCom.2014.7020509

  3. A.M. Al-momani et al., A review of factors influencing customer acceptance of internet of things services. 11(1), 54–67 (2019). https://doi.org/10.4018/IJISSS.2019010104

  4. A.M. Al-momani et al., Factors that influence the acceptance of internet of things services by customers of telecommunication companies in Jordan. 30(4), 51–63 (2018). https://doi.org/10.4018/JOEUC.2018100104

  5. M. Al-ruithe et al, Sciencedirect procedia science direct current state of cloud computing adoption—an empirical study in major public sector organizations current state of cloud computing adoption—of Saudi Arabia (KSA) An empirical study in major public S Procedia Comput. Sci. 110, 378–385 (2017). https://doi.org/10.1016/j.procs.2017.06.080

  6. A. Alamri, Harnessing the power of big data analytics in the cloud to support learning analytics in mobile learning environment Comput. Human Behav (2018) https://doi.org/10.1016/j.chb.2018.07.002

  7. S. Alqassemi. et al., Maturity Level of Cloud Computing at HCT. in ITT 2017—Information Technology Trends Exploring Current Trends Information Technology Conference Proceedings 2018-January Itt, 5–8 (2018). https://doi.org/10.1109/CTIT.2017.8259558

  8. I. Arpaci, Antecedents and consequences of cloud computing adoption in education to achieve knowledge management. Comput. Human Behav. (2017). https://doi.org/10.1016/j.chb.2017.01.024

    Article  Google Scholar 

  9. Y. Atif et al., Building a smart campus to support ubiquitous learning. J. Ambient Intell. Humaniz. Comput. 6(2), 223–238 (2015). https://doi.org/10.1007/s12652-014-0226-y

    Article  Google Scholar 

  10. F. Authors, Adoption of internet of things ( IOT ) based wearables for elderly healthcare—a behavioural reasoning theory (BRT) approach (2018). https://doi.org/10.1108/JET-12-2017-0048

  11. F. Authors, An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management—a mixed research approach (2016)

    Google Scholar 

  12. P Brous et al., The dual effects of the Internet of Things (IoT): A systematic review of the benefits and risks of IoT adoption by organizations. Int. J. Inf. Manage (2019). https://doi.org/10.1016/j.ijinfomgt.2019.05.008

  13. F.H. Cerdeira Ferreira, R. Mendes de Araujo, Campus Inteligentes: Conceitos, aplicações, tecnologias e desafios. Relatórios Técnicos do DIA/UNIRIO. 11(1), 4–19 (2018)

    Google Scholar 

  14. R.A. Choix et al, Factores determinantes en la adopción de tecnologías de información (TI) en las pymes. VinculaTégica EFAN (2015)

    Google Scholar 

  15. M. Coccoli et al., Smarter universities: A vision for the fast changing digital era. J. Vis. Lang. Comput. 25(6), 1003–1011 (2014). https://doi.org/10.1016/j.jvlc.2014.09.007

    Article  Google Scholar 

  16. S. Das, The early bird catches the worm—first mover advantage through IoT adoption for Indian Public sector retail oil outlets. The early bird catches the worm—first mover advantage. J. Glob. Inf. Technol. Manag. 00(00), 1–29 (2019). https://doi.org/10.1080/1097198X.2019.1679588

    Article  Google Scholar 

  17. Z.Y. Dong et al., Smart campus: definition, framework, technologies, and services. IET Smart Cities. 2(1), 43–54 (2020). https://doi.org/10.1049/iet-smc.2019.0072

    Article  Google Scholar 

  18. T. Dybå et al., Applying Systematic Reviews to Diverse Study Types: An Experience Report. in Proceedings—1st International Symposium on Empirical Software Engineering and Measurement, ESEM 2007 (2007). https://doi.org/10.1109/ESEM.2007.21

  19. E.E. Grandón et al., Internet de las Cosas : Factores que influyen su adopción en Pymes chilenas Internet of Things : Factors that influence its adoption among Chilean SMEs (2020)

    Google Scholar 

  20. T. Granollers i Saltiveri, MPIu+a. Una metodología que integra la Ingeniería del Software, la Interacción Persona-Ordenador y la Accesibilidad en el contexto de equipos de desarrollo multidisciplinares (2004).

    Google Scholar 

  21. C.D. Guerrero et al., IoT: Una aproximación desde ciudad inteligente a universidad inteligente. Rev. Ingenio UFPSO. 13(1), 1–12 (2017)

    Google Scholar 

  22. S. Jose et al., Disruptive architectural technology in engineering education. Procedia Comput. Sci. 172, 641–648 (2020). https://doi.org/10.1016/j.procs.2020.05.083

    Article  Google Scholar 

  23. S. Jose et al., Nurturing engineering skills and talents, a disruptive methodology in engineering education. Procedia Comput. Sci. 172, 568–572 (2020). https://doi.org/10.1016/j.procs.2020.05.069

    Article  Google Scholar 

  24. Y. Kao et al., An exploration and confirmation of the factors influencing adoption of IoT-based wearable fitness trackers (2019)

    Google Scholar 

  25. Y. Khamayseh et al., Integration of Wireless Technologies in Smart University Campus Environment: Framework Architecture (2015) https://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=psyc11&NEWS=N&AN=2015-00124-004, https://doi.org/10.4018/ijicte.2015010104

  26. U. Lleida, de: Departament de Llenguatges i Sistemes Informàtics Universitat de Lleida Lleida, julio 2004. Screen (2004)

    Google Scholar 

  27. M.V. López Cabrera et al., Factors that enable the adoption of educational technology in medical schools. Educ. Medica. 20(xx), 3–9 (2019). https://doi.org/10.1016/j.edumed.2017.07.006

  28. J. Lorés, T. Granollers, Ingeniería de la Usabilidad y de la Accesibilidad aplicada al diseño y desarrollo de sitios web (2004)

    Google Scholar 

  29. G. Maestre-Góngora, Revisión de literatura sobre ciudades inteligentes: una perspectiva centrada en las TIC. Ingeniare. 19(19), 137–149 (2016)

    Article  Google Scholar 

  30. G. Maestre-Gongora, R.F. Colmenares-Quintero, Systematic mapping study to identify trends in the application of smart technologies. Iber. Conf. Inf. Syst. Technol. Cist. 1–6 (2018). https://doi.org/10.23919/CISTI.2018.8398638

  31. E.M. Malatji, The Development of a Smart Campus—African Universities Point of View. In: 2017 8th International Renewable Energy Congress, IREC 2017 (2017). https://doi.org/10.1109/IREC.2017.7926010

  32. J. Mariano, G. Romano, Introducción a la IPO (Metro, 2008)

    Google Scholar 

  33. A.V. Martín García et al., Factores determinantes de adopción de blended learning en educación superior. Adapta ción del modelo UTAUT. Educ. XX1 (2014). https://doi.org/10.5944/educxx1.17.2.11489

  34. M. Mital et al., Technological forecasting & social change adoption of internet of things in India : A test of competing models using a structured equation modeling approach. Technol. Forecast. Soc. Chang. 1–8 (2017). https://doi.org/10.1016/j.techfore.2017.03.001

  35. A. Mukherjee, N. Dey, Smart Computing with Open Source Platforms. (2019). https://doi.org/10.1201/9781351120340

    Article  Google Scholar 

  36. L Muñoz López et al., El Estudio y Guía Metodológica sobre Ciudades Inteligentes ha sido dirigido y coordinado por el equipo del ONTSI Deloitte (2012). https://doi.org/10.1017/CBO9781107415324.004

  37. U. Nasir, Cloud computing adoption assessment model (CAAM). 44(0), 34–37 (2011)

    Google Scholar 

  38. D. Nikbin, A. Abushakra, Internet of Things Adoption: Empirical Evidence From An Emerging Country. in Communications in Computer and Information Science. (2019). https://doi.org/10.1007/978-3-030-21451-7_30

  39. F. Nikolopoulos, Using UTAUT2 for Cloud Computing Technology Acceptance Modeling (2017)

    Google Scholar 

  40. K. Njenga et al., Telematics and Informatics The cloud computing adoption in higher learning institutions in Kenya : Hindering factors and recommendations for the way forward. Telemat. Inf. (2018). https://doi.org/10.1016/j.tele.2018.10.007

  41. P. Palos-Sanchez et al., Models of adoption of information technology and cloud computing in organizations. Inf. Tecnol. 30(3), 3–12 (2019). https://doi.org/10.4067/S0718-07642019000300003

    Article  Google Scholar 

  42. G. Perboli et al., A new taxonomy of smart city projects. Transp. Res. Procedia. 3, 470–478 (2014). https://doi.org/10.1016/j.trpro.2014.10.028

    Article  Google Scholar 

  43. F.M. Pérez et al., Smart university: hacia una universidad más abierta, https://dialnet.unirioja.es/servlet/libro?codigo=676751, (2016)

  44. K. Petersen et al., Systematic Mapping Studies in Software Engineering. in 12th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008 (2008). https://doi.org/10.14236/ewic/ease2008.8

  45. P. Pinheiro, C. Costa, Adoption of Cloud Computing Systems. 127–131 (2014)

    Google Scholar 

  46. P. Pornphol, T. Tongkeo, Transformation From a Traditional University into A Smart University (2008). https://dl.acm.org/citation.cfm?id=3178167, https://doi.org/10.1145/3178158.3178167

  47. P. Priyadarshinee et al., Understanding and predicting the determinants of cloud computing adoption: A two staged hybrid SEM—neural networks approach. Comput. Human Behav. (2017). https://doi.org/10.1016/j.chb.2017.07.027

    Article  Google Scholar 

  48. R.D. Raut et al., Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach. Technol. Forecast. Soc. Change. (2018). https://doi.org/10.1016/j.techfore.2018.05.020

    Article  Google Scholar 

  49. O. Revelo Sanchez et al., Gamification as a didactic strategy for teaching/learning programming: a systematic mapping of the literature. Rev. Digit. LAMPSAKOS. (2018). https://doi.org/10.21501/21454086.2347

  50. D Rico-Bautista et al., Analysis of the potential value of technology: Case of universidad Francisco de paula santander Ocaña. RISTI—Rev. Iber. Sist. e Tecnol. Inf. E17, 756–774 (2019)

    Google Scholar 

  51. D. Rico-Bautista et al., Caracterización de la situación actual de las tecnologías inteligentes para una Universidad inteligente en Colombia/Latinoamérica. RISTI—Rev. Iber. Sist. e Tecnol. Inf. E27, 484–501 (2020)

    Google Scholar 

  52. D. Rico-Bautista, Conceptual framework for smart university J. Phys. Conf. Ser. (2019)

    Google Scholar 

  53. D. Rico-Bautista et al., Smart University: A Review from the Educational and Technological View of Internet of Things. In Advances in Intelligent Systems and Computing (2019), pp. 427–440

    Google Scholar 

  54. D. Rico-Bautista et al., Smart University: Key Factors for An Artificial Intelligence Adoption Model. in Advances in Intelligent Systems and Computing (2020)

    Google Scholar 

  55. D. Rico-Bautista et al., Smart University: Strategic map since the adoption of technology. RISTI—Rev. Iber. Sist. e Tecnol. Inf. 2020, E28, 711–724 (2020)

    Google Scholar 

  56. D. Rico-Bautista et al., Smart University: Big Data Adoption Model. in 2020 9th International Conference on Software Process Improvement, CIMPS 2020 - Applications in Software Engineering (2020)

    Google Scholar 

  57. D. Rico-Bautista et al., Smart University: IoT Adoption Model. in Proceedings of the Fourth World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2020 (2020)

    Google Scholar 

  58. D.W. Rico-Bautista, Conceptual framework for smart university. J. Phys. Conf. Ser. 1409, 012009 (2019). https://doi.org/10.1088/1742-6596/1409/1/012009

    Article  Google Scholar 

  59. Rjab, A. Ben, S. Mellouli, Smart cities in the era of artificial intelligence and internet of things. 1, 1–10 (2018). https://doi.org/10.1145/3209281.3209380

  60. M. Rohs, J. Bohn, Entry points into a smart campus environment-overview of the ETHOC system. Distrib. Comput. Syst. Work. 1–7 (2003)

    Google Scholar 

  61. H.M. Sabi et al., Conceptualizing a model for adoption of cloud computing in education. Int. J. Inf. Manage. 36(2), 183–191 (2016). https://doi.org/10.1016/j.ijinfomgt.2015.11.010

    Article  Google Scholar 

  62. B. Sánchez-Torres et al., Smart Campus: Trends in cybersecurity and future development. Rev. Fac. Ing. 27, 47, (2018). https://doi.org/10.19053/01211129.v27.n47.2018.7807

  63. F.P. Sejahtera et al., Information & Management Factors influencing effective use of big data : A research framework. Inf. Manag. 103146 (2019). https://doi.org/10.1016/j.im.2019.02.001

  64. H. Shaikh et al., A Conceptual Framework for Determining Acceptance of Internet of Things (IoT) in Higher Education Institutions of Pakistan. in 2019 International Conference on Information Science Communication Technology (2019), 1–5

    Google Scholar 

  65. C. Shaoyong et al., UNITA : A Reference Model of University IT Architecture. in ICCIS ‘16 Proc. 2016 International Conference on Information System (2016), 73–77. https://doi.org/10.1145/3023924.3023949

  66. B. Sivathanu, Adoption of internet of things (IOT) based wearables for healthcare of older adults—a behavioural reasoning theory (BRT) approach. J. Enabling Technol. (2018). https://doi.org/10.1108/JET-12-2017-0048

    Article  Google Scholar 

  67. H. Vasudavan, User Perceptions in Adopting Cloud Computing in Autonomous Vehicle (2018), 151–156

    Google Scholar 

  68. M.C. Vega-Hernández et al., Multivariate characterization of university students using the ICT for learning. Comput. Educ. 121, 124–130 (2018). https://doi.org/10.1016/j.compedu.2018.03.004

    Article  Google Scholar 

  69. M.S. Viñán-Ludeña et al., Smart University: An Architecture Proposal for Information Management Using Open Data for Research Projects. Advances in Intelligent Systems and Computing, 1137 AISC, March, 172–178 (2020). https://doi.org/10.1007/978-3-030-40690-5_17

  70. J. Vuorio et al., Enhancing User Value of Educational Technology by Three Layer Assessment (2017),220–226. https://doi.org/10.1145/3131085.3131105

  71. M. Zapata-ros, La universidad inteligente La transición de los LMS a los Sistemas Inteligentes de Aprendizaje en Educación Superior The smart university. 57, 10, 1–43 (2018)\

    Google Scholar 

  72. Applied Machine Learning for Smart Data Analysis. (2019). https://doi.org/10.1201/9780429440953

Download references

Author information

Authors and Affiliations

  1. Universidad Francisco de Paula Santander Ocaña, Sede el Algodonal Vía Acolsure, 546552, Ocaña, Colombia

    Dewar Rico-Bautista & Yurley Medina-Cárdenas

  2. Universidad del Cauca, Calle 5 No. 4–70, 190003, Popayán, Colombia

    César A. Collazos

  3. Universidad Autónoma de Bucaramanga, Avenida 42 No. 48–11, 680003, Bucaramanga, Colombia

    César D. Guerrero

  4. Universidad Cooperativa de Colombia, Calle 50 No. 40–74 Bloque A piso 6, 050016, Medellín, Colombia

    Gina Maestre-Gongora

Authors
  1. Dewar Rico-Bautista
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. César A. Collazos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. César D. Guerrero
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gina Maestre-Gongora
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yurley Medina-Cárdenas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dewar Rico-Bautista .

Editor information

Editors and Affiliations

  1. Global Knowledge Research Foundation, Ahmedabad, Gujarat, India

    Amit Joshi

  2. School of Mathematics, Computer Science and Engineering, Liverpool Hope University, Liverpool, UK

    Atulya K. Nagar

  3. University of Costa Rica, San José, Costa Rica

    Gabriela Marín-Raventós

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rico-Bautista, D., Collazos, C.A., Guerrero, C.D., Maestre-Gongora, G., Medina-Cárdenas, Y. (2021). Latin American Smart University: Key Factors for a User-Centered Smart Technology Adoption Model. In: Joshi, A., Nagar, A.K., Marín-Raventós, G. (eds) Sustainable Intelligent Systems. Advances in Sustainability Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-33-4901-8_10

Download citation

Publish with us

Policies and ethics

Search

Navigation