Journal of Research in Science, Mathematics and Technology Education

Real and ideal perception of the intelligent classroom environment of future teachers

Carlos Hervás-Gómez 1 * ,
Purificación Toledo-Morales 1
1 University of Seville* Corresponding Author
Download PDF
Journal of Research in Science, Mathematics and Technology Education, Volume 1, Issue 1, January 2018, pp. 91-111
OPEN ACCESS VIEWS: 451 DOWNLOADS: 222 Publication date: 15 Jan 2018
ABSTRACT
The proliferation of information and communication technology tools in the last years has led many teachers to review the way they teach and structure their learning environments. The growth of technological applications in teaching and the training of future teachers is not only gaining momentum; it is also becoming an important part of the current educational scene. The objectives of this study were to adapt and validate the Real and Ideal Intelligent Classroom Questionnaires (REQSC) and (IEQSC), and to determine if there were significant differences in the perception that future teachers had of the real and ideal environment of intelligent classrooms. A quantitative methodology was used, applying the statistical software SPSS 23 for the factor analysis. The results indicated that both questionnaires showed a valid and reliable internal consistency. The real and ideal perceptions of the use of technology as a learning tool and access to information make it clear that it is currently being used correctly. It is important that future teachers acquire adequate skills for their use and research in different topics.
KEYWORDS
Classroom Environment, Information and Communication Technology, Technological Education, Technological Innovations, Higher Education.
CITATION (APA)
Hervás-Gómez, C., & Toledo-Morales, P. (2018). Real and ideal perception of the intelligent classroom environment of future teachers. Journal of Research in Science, Mathematics and Technology Education, 1(1), 91-111. https://doi.org/10.31756/jrsmte.115
REFERENCES
  1. Aldridge, J. M., Dorman, J. P., & Fraser, B. J. (2004). Use of multitrait-multimethod modelling to validate actual and preferred forms of the Technology-Rich Outcomes-Focused Learning Environment Inventory (Troflei). Australian Journal of Educational and Developmental Psychology, 4, 110–125.
  2. Baoping, L., Siu Cheung, K., & Guang, C.(2015). Development and validation of the smart classroom inventory. Smart Learning Environments, 2(3). http://doi.org/10.1186/s40561-015-0012-0
  3. Bhagat, K. K., Wu, L. Y., & Chang, C. (2016). Development and validation of the perception of students towards online learning. Journal of Education Technology & Society, 19(1), 350–359.
  4. Dogan, B., & Camurcu, A.Y. (2008). Association Rule Mining from an Intelligent Tutor. Journal of Educational Technology Systems, 36(4), 433-447. http://doi.org/10.2190/ET.36.4.f
  5. Giannakos, M. N., Sampson, D. G., & Kidziński, Ł. (2016). Introduction to smart learning analytics: foundations and developments in video-based learning. Smart Learning Environments, 3(1), 1-9. http://doi.org/10.1186/s40561-016-0034-2
  6. Hall, M., Ramsay, A., & Raven, J. (2004). Changing the learning environment to promote deep learning approaches in first-year accounting students. Accounting Education, 13(4), 489-505. http://doi.org/10.1080/0963928042000306837
  7. Hedberg, J. G. (2014). Extending the Pedagogy of Mobility. Educational Media International, 51(3), 237-253. http://doi.org/10.1080/09523987.2014.96844
  8. Hwang, G. H., Chu, H. C., Chen, B., & Cheng, Z. S. (2014). Development and evaluation of a web 2.0-Based ubiquitous learning platform for schoolyard plant identification. International Journal of Distance Education Technologies (IJDET), 12(2), 83-103. http://doi.org/10.4018/ijdet.2014040105
  9. Kemp, N., & Grieve, R. (2014). Face-to-face or face-to-screen? Undergraduates' opinions and test performance in classroom vs. online learning. Frontiers in Psychology, 5 (1278), 1-11. http://doi.org/10.3389/fpsyg.2014.01278
  10. Kumara, G. W., Wattanachote, K., Battulga, B., Shih, T. K., & Hwang, W.-Y. (2015). A Kinect-Based Assessment System for Smart Classroom. International Journal of Distance Education Technologies, 13(2), 34-53. http://doi.org/10.4018/IJDET.2015040103
  11. Lathama, A., Crocketta, K., McLeana, D., & Edmondsb, B. (2012). A conversational intelligent tutoring system to automatically predict learning styles. Computers & Education, 59 (1), 95–109. http://doi.org/10.1016/j.compedu.2011.11.001
  12. Lee, J., Lee, H., & Park, Y. (2013). The Smart Classroom: Combining Smart Technologies with Advanced Pedagogies. Educational Technology, 53(3), 3-12. http://eric.ed.gov/?id=EJ1014084
  13. Lee, J., Zo, H., & Lee, H. (2014). Smart Learning Adoption in Employees and HRD Managers. British Journal of Educational Technology, 45(6), 1082-1096. http://doi.org/10.1111/bjet.12210
  14. Li, B.P., & Kong, S.C. (2014). Technology intelligence of the smart learning environment: a content analysis of publications in the past decade. Paper presented at The 18th Global Chinese Conference on Computers in Education, East China Normal University, China.
  15. Li, B.P., Kong, S.C., & Chen, K.G. (2015). Development and validation of the smart classroom inventory. Smart Learning Environments, 2 (3), 3-18. http://doi.org/10.1186/s40561-015-0012-0
  16. Lin, Y. T., Huang, Y. M., & Cheng, S. C. (2010). An automatic group composition system for composing collaborative learning groups using enhanced particle swarm optimization. Computers & Education, 55(4), 1483-1493. http://doi.org/10.1016/j.compedu.2010.06.014
  17. Lizzio, A., Wilson, K., & Simons, R. (2002). University students' perceptions of the learning environment and academic outcomes: implications for theory and practice. Studies in Higher Education, 27 (1), 27-52. http://dx.doi.org/1010.1080/03075070120099359
  18. Moos, R.H. (1974). The Social Climate Scales: an overview. Palo Alto, CA: Consulting Psychologists Press.
  19. Noh, K.S., Ju, S.H., & Jung, J.T. (2011). An exploratory study on concept and realization conditions of smart learning. Korean Journal of Digital Policy & Management, 9(2), 79-88. http://www.koreascience.or.kr/article/ArticleFullRecord.jsp?cn=DJTJBT_2011_v9n2_79&ordernum=7
  20. Oliver, R., Herrington, J., & Mcloughlin, C. (2014). Exploring the Development of Students’ Generic Skills Development in Higher Education Using A Web-based Learning Environment. Education, (May 2014).
  21. Özyurt, Ö., Özyurt, H., Baki, A., & Güven, B. (2013). Integration into mathematics classrooms of an adaptive and intelligent individualized e-learning environment: implementation and evaluation of UZWEBMAT. Computers in Human Behavior, 29 (3), 726–738. http://doi.org/10.1016/j.chb.2012.11.013
  22. Ramamuruthy, V., & Rao, S. (2015). Smartphones Promote Autonomous Learning in ESL Classrooms. Malaysian Online Journal of Educational Technology, 3(4), 23-35. http://files.eric.ed.gov/fulltext/EJ1085930.pdf
  23. Specht, M., Ternier, S., & Greller, W. (2011). Dimensions of Mobile Augmented Reality for Learning: A First Inventory. Journal of the Research Center for Educational Technology, 7(1), 117-127. http://hdl.handle.net/1820/4008
  24. Sykes, E.R. (2014). New Methods of Mobile Computing: From Smartphones to Smart Education. TechTrends: Linking Research and Practice to Improve Learning, 58(3), 26-37. http://search.proquest.com/docview/1651858928?accountid=14744
  25. Wojciechowski, R., & Cellary, W. (2013). Evaluation of learners’ attitude toward learning in ARIES augmented reality environments. Computers and Education, 68, 570-585. http://doi.org/10.1016/j.compedu.2013.02.014
  26. Yang, Y., Leung, H., & Yue, L. (2013). Generating a two-phase lesson for guiding beginners to learn basic dance movements. Computer & Education, 61(1), 1–20. http://doi.org/10.1016/j.compedu.2012.09.006
  27. Zhao, J.T. (2008). Research university faculty perceptions of smart classroom technologies (Intellectual Property Publishing House, Beijing, pp. 3-15. http://search.proquest.com/docview/305356528
LICENSE
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.