Emerging technologies. Analysis and current perspectives

Miriam Agreda Montoro, Ana Mª Ortiz Colón, Javier Rodríguez Moreno, Karl Steffens

Abstract


The convergence in the use of technology in classrooms and the development of new methodologies have involved a redefinition of the different educational agents’ performance, for the upcoming Horizon reports to generate a radiography of the emerging technological trends that will have an impact in the upcoming years. As a consequence, we will focus on adaptative learning technologies based on the perspectives of profound learning, where the achievement of objectives will be reflected through generated learning analytics, whose association may produce consistent verifiable blockchains. For that matter, this work proposes a meta-analysis of 62 research studies indexed in the WOS and Scopus databases during 2013 and 2018, in the area of Social Sciences, taking as descriptors the technologies mentioned in those reports. A search strategy based on four different criteria has been used: public (target), topic, methodological design and main conclusions.


Keywords


Emerging Technologies; Literature Review, Deep Learning, Collaborative Learning, Adaptative Learning, Learning Analytics, e-learning.

Full Text:

PDF

References


Adams Becker, S., Cummins, M., Freeman, A., Giesenger Hall, C., & Yuhnke, B. (2016). NMC Horizon Report: 2016 K-12 Edition. (pp. 1-49). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2016-nmc-cosn-horizon-report-k12-EN.pdf

Adams Becker, S., Cummins, M., Freeman, A., Giesinger Hall, C., & Ananthanarayanan, V. (2017). NMC Horizon Report: Higher Education Edition (pp. 1-56). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2017-nmc-horizon-report-he-EN.pdf

Adner, R., & Levinthal, D. A. (2002). The emergence of emerging technologies. California Management Review, 45(1), 50–66. Recuperado de https://journals.sagepub.com/doi/pdf/10.2307/41166153?casa_token=QhkZSixBAjkAAAAA%3A_IE5RZWxuI7hGbzBa3o7m5TO-t2DwhUNobkRgoIrTudYtCICL_6zgp16XWidPoOo3qB_Egu4Y3XAkg

Aguaded, I., Vázquez-Cano, E. & López-Meneses, E. (2016). El impacto bibliométrico del movimiento MOOC en la Comunidad Científica Española. Educación XX1, 19(2), 77-104, doi: 10.5944/educXX1. 13217

Akhtar, S., Warburton, S., & Xu, W. (2017). The use of an online learning and teaching system for monitoring computer aided design student participation and predicting student success. International Journal of Technology and Design Education, 27(2), 251-270. https://doi.org/10.1007/s10798-015-9346-8

Avila-Robinson, A., & Miyazaki, K. (2011). Conceptualization and operationalization of emerging technologies: A complementing approach. En 2011 Proceedings of PICMET ’11: Technology Management in the Energy Smart World (PICMET) (pp. 1-12).

Baker, R. S., & Inventado, P. S. (2014). Educational Data Mining and Learning Analytics. En J. A. Larusson & B. White (Eds.), Learning Analytics: From Research to Practice (pp. 61-75). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4614-3305-7_4

Baytiyeh, H., & Naja, M. K. (2017). Students’ perceptions of the flipped classroom model in an engineering course: a case study. European Journal of Engineering Education, 42(6), 1048-1061. https://doi.org/10.1080/03043797.2016.1252905

Berners‐Lee, T., Cailliau, R., Pollermann, B., & Groff, J. (1992). World‐Wide Web: The Information Universe. Internet Research, 2(1), 52-58. https://doi.org/10.1108/eb047254

Bettencourt, L., Kaiser, D., Kaur, J., Castillo-Chávez, C., & Wojick, D. (2008). Population modeling of the emergence and development of scientific fields. Scientometrics, 75(3), 495-518. https://doi.org/10.1007/s11192-007-1888-4

Biggs, J., & Tang, C. (2007). Setting the stage for effective teaching. Teaching for quality learning at university, 31–59.

Boyack, K. W., Small, H., & Klavans, R. (2013). Improving the accuracy of co-citation clustering using full text. Journal of the American Society for Information Science and Technology, 64(9), 1759-1767. https://doi.org/10.1002/asi.22896

Brooks, C., Greer, J., & Gutwin, C. (2014). The Data-Assisted Approach to Building Intelligent Technology-Enhanced Learning Environments. En J. A. Larusson & B. White (Eds.), Learning Analytics: From Research to Practice (pp. 123-156). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4614-3305-7_7

Castellon-Fuentes, J. D., Morente-Molinera, J. A., Herrera-Viedma, E., & Lopez-Herrera, A. G. (2013). A New Moodle Module for Interactive Video-Lessons: An Adaptative Way to Follow a Course. En L. G. Chova, A. L. Martinez, & I. C. Torres (Eds.), 7th International Technology, Education and Development Conference (inted2013). Valenica: Iated-Int Assoc Technology Education a& Development.

Choi, G. W., Land, S. M., & Zimmerman, H. T. (2018). Investigating children’s deep learning of the tree life cycle using mobile technologies. Computers in Human Behavior, 87, 470-479. https://doi.org/10.1016/j.chb.2018.04.020

Clarivate Analytics. (2018). WOS-basic search. Recuperado 26 de noviembre de 2018, de https://apps.webofknowledge.com/WOS_GeneralSearch_input.do?product=WOS&search_mode=GeneralSearch&SID=D2ajRUcJRO4QoSbDj1O&preferencesSaved=

Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, 18(6), 683-695. https://doi.org/10.1080/13562517.2013.827653

Day, G. S., Schoemaker, P. J. H., & Gunther, R. E. (2004). A perfect game. En Wharton on Managing Emerging Technologies (pp. 1-23). New Jersey: John Wiley & Sons.

De Backer, L., Van Keer, H., Moerkerke, B., & Valcke, M. (2016). Examining evolutions in the adoption of metacognitive regulation in reciprocal peer tutoring groups. Metacognition and Learning, 11(2), 187-213. https://doi.org/10.1007/s11409-015-9141-7

De Corte, E. (2015). Constructive, self-regulatory, situated and collaborative learning: an approach to the acquisition of the adaptative competency in mathematics. Paginas De Educacion, 8(2).

Dietz-Uhler, B., & Hurn, J. E. (2013). Using learning analytics to predict (and improve) student success: A faculty perspective. Journal of Interactive Online Learning, 12(1), 17–26.

European Comission. (2018). Digital Education Action Plan (Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions). Brussels: European Union. Recuperado de https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0022&from=EN

Freeman, A., Adams Becker, S., Cummins, M., Davis, A., & Giesinger Hall, C. (2017). NMC Horizon Report: 2017 K-12 Edition. (pp. 1-55). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2016-nmc-cosn-horizon-report-k12-EN.pdf

Garcia-Ros, R., & Perez-Gonzalez, F. (2011). Assessment preferences of preservice teachers: analysis according to academic level and relationship with learning styles and motivational orientation. Teaching in Higher Education, 16(6), 719-731. https://doi.org/10.1080/13562517.2011.570434

Geels, F. W. (2005). Processes and patterns in transitions and system innovations: Refining the co-evolutionary multi-level perspective. Technological Forecasting and Social Change, 72(6), 681-696. https://doi.org/10.1016/j.techfore.2004.08.014

Giardina, M. (1998). A distributed interaction model for the development of intelligent networked learning diagnostic system. (T. W. Chan, A. Collins, & J. X. Lin, Eds.). Beijing: China Higher Education Press Beijing.

Glänzel, W., & Thijs, B. (2011). Using ‘core documents’ for detecting and labelling new emerging topics. Scientometrics, 91(2), 399-416. https://doi.org/10.1007/s11192-011-0591-7

Halaweh, M. (2013). Emerging Technology: What is it? Journal of Technology Management & Innovation, 8(3), 108-115. https://doi.org/10.4067/S0718-27242013000400010

Hernández-Lara, A. B., Perera-Lluna, A., & Serradell-López, E. (2018). Applying learning analytics to students’ interaction in business simulation games. The usefulness of learning analytics to know what students really learn. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2018.03.001

Houghton, W. (2004). Deep and surface approaches to learning. Engineering Subject Centre Guide: Learning and Teaching Theory for Engineering Academics, W. Houghton, ed. Loughborough, UK: HEA Engineering Subject Centre.

Howard, C., Di Eugenio, B., Jordan, P., & Katz, S. (2017). Exploring Initiative as a Signal of Knowledge Co-Construction During Collaborative Problem Solving. Cognitive Science, 41(6), 1422-1449. https://doi.org/10.1111/cogs.12415

Jiménez-Fanjul, N. (2016). Producción científica internacional en Educación Matemática. Estudio bibliométrico (1983-2012). Tesis doctoral. Universidad de Córdoba. Córdoba. http://hdl.handle.net/10396/13759

Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., & Freeman, A. (2014). NMC Horizon Report: 2014 K-12 Edition. (pp. 1-48). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2014-nmc-horizon-report-k12-EN.pdf

Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013a). NMC Horizon Report: 2013 K-12 Edition. (pp. 1-40). Austin, Texas: The New Media Consortium. Recuperado de https://www.nmc.org/pdf/2013-horizon-report-k12.pdf

Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013b). NMC Horizon Report: Higher Education Edition. (UNIR, Trad.) (pp. 1-46). Austin, Texas: The New Media Consortium. Recuperado de https://www.nmc.org/pdf/2013-Horizon-Report-HE-ES.pdf

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). NMC Horizon Report: Higher Education Edition (pp. 1-48). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2014-nmc-horizon-report-he-EN-SC.pdf

Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). NMC Horizon Report: Higher Education Edition (pp. 1-49). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2015-nmc-horizon-report-HE-EN.pdf

Johnson, L., Adams Becker, S., Estrada, V., Freeman, A., & Giesinger Hall, C. (2016). NMC Horizon Report: Higher Education Edition (pp. 1-49). Austin, Texas: The New Media Consortium. Recuperado de http://cdn.nmc.org/media/2016-nmc-horizon-report-he-EN.pdf

Kacfah Emani, C., Cullot, N., & Nicolle, C. (2015). Understandable Big Data: A survey. Computer Science Review, 17, 70-81. https://doi.org/10.1016/j.cosrev.2015.05.002

Kirkwood, A., & Price, L. (2013). Examining some assumptions and limitations of research on the effects of emerging technologies for teaching and learning in higher education. British Journal of Educational Technology, 44(4), 536-543. https://doi.org/10.1111/bjet.12049

Leu, D. J., Kinzer, C. K., Coiro, J. L., & Cammack, D. W. (2004). Toward a theory of new literacies emerging from the Internet and other information and communication technologies. En Theoretical models and processes of reading (5th ed., pp. 1570–1613). Recuperado de https://s3.amazonaws.com/academia.edu.documents/39882371/Toward_a_Theory_of_New_Literacies_Emergi20151110-27533-1mpueq6.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1543232526&Signature=%2BesAiKLgtqjNkXa6%2BEdtHuVGxi0%3D&response-content-disposition=inline%3B%20filename%3DToward_a_theory_of_new_literacies_emergi.pdf

Manca, S. (2018). ResearchGate and Academia.edu as networked socio-technical systems for scholarly communication: a literature review. Research in Learning Technology, 26. https://dx.doi.org/10.25304/rlt.v26.2008

Manjarres, A. V., Sandoval, L. G. M., & Suárez, M. J. S. (2018a). Data mining techniques applied in educational environments: Literature Review. Digital Education Review, 0(33), 235-266. Recuperado de http://revistes.ub.edu/index.php/der/article/view/18067

Manjarres, A. V., Sandoval, L. G. M., & Suárez, M. J. S. (2018b). Data mining techniques applied in educational environments: Literature Review. Digital Education Review, 0(33), 235-266. Recuperado de http://revistes.ub.edu/index.php/der/article/view/18067

Markard, J., Raven, R., & Truffer, B. (2012). Sustainability transitions: An emerging field of research and its prospects. Research Policy, 41(6), 955-967. https://doi.org/10.1016/j.respol.2012.02.013

Martin, B. R. (1995). Foresight in science and technology. Technology Analysis & Strategic Management, 7(2), 139-168. https://doi.org/10.1080/09537329508524202

Martin, B. R. (2010). The origins of the concept of ‘foresight’ in science and technology: An insider’s perspective. Technological Forecasting and Social Change, 77(9), 1438-1447. https://doi.org/10.1016/j.techfore.2010.06.009

McLean, S., Attardi, S. M., Faden, L., & Goldszmidt, M. (2016). Flipped classrooms and student learning: not just surface gains. Advances in Physiology Education, 40(1), 47-55. https://doi.org/10.1152/advan.00098.2015

Nguyen, A., Gardner, L. A., & Sheridan, D. (2018). A framework for applying learning analytics in serious games for people with intellectual disabilities. British Journal of Educational Technology, 49(4), 673-689. https://doi.org/http:/doi.org/10.1111/bjet.12625

O’Brien, J. (2018). NMC Horizon Report 2018 Higher Education | #EnlightED. Madrid: La Nave. Recuperado de https://www.youtube.com/watch?v=_F0fvxZzZL8

Nupur, C. (2014). World Wide Web and its jpurney from web 1.0 to web 4.0. International Journal of Computer Science and Information Technologies, 5(6), 8096-8100. Recuperado de http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.666.6445&rep=rep1&type=pdf

Pegrum, M., Bartle, E., & Longnecker, N. (2015). Can creative podcasting promote deep learning? The use of podcasting for learning content in an undergraduate science unit. British Journal of Educational Technology, 46(1), 142-152. https://doi.org/10.1111/bjet.12133

Philip Chen, C. L., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347. https://doi.org/10.1016/j.ins.2014.01.015

Pina, A. R. B., Torlà, C. B., Quintero, L. C., & Segura, J. A. (2017). Blockchain en Educación: introducción y crítica al estado de la cuestión. Edutec. Revista Electrónica de Tecnología Educativa, 0(61), 363. https://doi.org/10.21556/edutec.2017.61.915

Porter, A. L. (2004). Technology futures analysis: Toward integration of the field and new methods. Technological Forecasting and Social Change, 71(3), 287-303. https://doi.org/10.1016/j.techfore.2003.11.004

Porter, A. L., & Detampel, M. J. (1995). Technology opportunities analysis. Technological Forecasting and Social Change, 49(3), 237-255. https://doi.org/10.1016/0040-1625(95)00022-3

Prendes, M. P. (2018). La Tecnología Educativa en la Pedagogía del siglo XXI: una visión en 3D. Revista Interuniversitaria de Investigación en Tecnología Educativa, (4), 6-16. http://dx.doi.org/10.6018/riite/2018/335131

Rodriguez Triana, M. J., Martínez-Monés, A., & Villagrá-Sobrino, S. (2015). Applying Learning Analytics to a Primary School Classroom: Benefits and Barriers. Recuperado de https://infoscience.epfl.ch/record/210524

Rogers, P. L. (2000). Barriers to Adopting Emerging Technologies in Education. Journal of Educational Computing Research, 22(4), 455-472. https://doi.org/10.2190/4UJE-B6VW-A30N-MCE5

Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827-1843. https://doi.org/10.1016/j.respol.2015.06.006

Sampieri, R., Collado, C., & Lucio, P. (2014). Metodología de la investigación. Nueva York: Editorial McGraw-Hill.

San Pedro, M. O. Z., Baker, R. S., & Heffernan, N. T. (2017). An Integrated Look at Middle School Engagement and Learning in Digital Environments as Precursors to College Attendance. Technology Knowledge and Learning, 22(3), 243-270. https://doi.org/10.1007/s10758-017-9318-z

Shen, Y.C., Chang, S.H., Lin, G.T.R., & Yu, H.C. (2010). A hybrid selection model for emerging technology. Technological Forecasting and Social Change, 77(1), 151-166. https://doi.org/10.1016/j.techfore.2009.05.001

Small, H. (2006). Tracking and predicting growth areas in science. Scientometrics, 68(3), 595-610. https://doi.org/10.1007/s11192-006-0132-y

Small, H., Boyack, K. W., & Klavans, R. (2014). Identifying emerging topics in science and technology. Research Policy, 43(8), 1450-1467. https://doi.org/10.1016/j.respol.2014.02.005

Smith, K. (2018). Perceptions of Preservice Teachers about Adaptive Learning Programs in K-8 Mathematics Education. Contemporary Educational Technology, 9(2), 111-130. https://doi.org/10.30935/cet.414780

Srinivasan, R. (2008). Sources, characteristics and effects of emerging technologies: Research opportunities in innovation. Industrial Marketing Management, 37(6), 633-640. https://doi.org/10.1016/j.indmarman.2007.12.003

Stahl, B. C. (2011). What Does the Future Hold? A Critical View of Emerging Information and Communication Technologies and Their Social Consequences. En M. Chiasson, O. Henfridsson, H. Karsten, & J. I. DeGross (Eds.), Researching the Future in Information Systems (Vol. 356, pp. 59-76). Berlin: Springer. https://doi.org/10.1007/978-3-642-21364-9_5

Suárez-Manzano, S., Ruiz-Ariza, A., De La Torre-Cruz, M., & Martínez-López, E. J. (2018). Acute and chronic effect of physical activity on cognition and behaviour in young people with ADHD: A systematic review of intervention studies. Research in developmental disabilities, 77, 12-23. https://doi.org/10.1016/j.ridd.2018.03.015

Subramanyam, K. (1983). Bibliometric studies of research collaboration: A review. Journal os Information Science, 6, 33-38.

The Business Dictionary. (2018). What are emerging technologies? definition and meaning. Recuperado 26 de noviembre de 2018, de http://www.businessdictionary.com/definition/emerging-technologies.html

Torres-Toukoumidis, Romero-Rodríguez & Pérez-Rodríguez (2018). Ludificación y sus posibilidades en el entorno de blended learning: revisión documental, RIED. Revista Iberoamericana de Educación a Distancia, 21(1), 95-111. DOI: http://dx.doi.org/10.5944/ried.21.1.18792

UNESCO. (2015). Qingdao Declaration (Seize digital opportunities, lead education transformation) (pp. 1-54). Qindgao, China: UNESCO. Recuperado de http://unesdoc.unesco.org/images/0023/002333/233352m.pdf

Viberg, O., Hatakka, M., Balter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98-110. https://doi.org/10.1016/j.chb.2018.07.027

Wise, A. F. (2014). Designing Pedagogical Interventions to Support Student Use of Learning Analytics. En Proceedings of the Fourth International Conference on Learning Analytics And Knowledge (pp. 203–211). New York, NY, USA: ACM. https://doi.org/10.1145/2567574.2567588

Wollscheid, S., Sjaastad, J., & Tømte, C. (2016). The impact of digital devices vs. Pen (cil) and paper on primary school students’ writing skills–A research review. Computers & Education, 95, 19-35. DOI: https://doi.org/10.1016/j.compedu.2015.12.001

Xing, W., Guo, R., Petakovic, E., & Goggins, S. (2015). Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining and theory. Computers in Human Behavior, 47, 168-181. https://doi.org/10.1016/j.chb.2014.09.034

Zilvinskis, J., Willis, J., & Borden, V. M. H. (2017). An Overview of Learning Analytics. New Directions for Higher Education, 2017(179), 9-17. https://doi.org/10.1002/he.20239

Zniber, N. (2011). Pops: A Service-Oriented Approach for Composing Personalized Courses. In L. G. Chova, I. C. Torres, & A. L. Martinez (Eds.), INTED2011 Proceedings (pp.2951-2961). Valencia: Iated-Int Assoc Technology Education & Development.




DOI: https://doi.org/10.1344/der.2019.35.186-201

Refbacks

  • There are currently no refbacks.


Licencia Creative Commons

ISSN 2013-9144

 

RCUB revistesub@ub.edu Avís Legal RCUB Universitat de Barcelona