BibTex RIS Cite
Year 2018, Volume: 3 Issue: 2, 12 - 21, 01.06.2018

Abstract

References

  • Agarwal, J., & Malhotra, N. K. (2005). An integrated model of attitude and affect: Theoretical foundation and an empirical investigation. Journal of Business research, 58(4), 483-493.
  • Akkağıt, Ş. F., & Tekin, A. (2012). Simülasyon Tabanlı Öğrenmenin Ortaöğretim Öğrencilerinin Temel Elektronik ve Ölçme Dersindeki Başarılarına Etkisi. Ege Eğitim Dergisi, 13(2).
  • Alnoukari, M., Shafaamry, M. & Aytouni, K. (2013). Simulation for Computer Sciences Education. Communications of the ACS, 6(1), 1-19.
  • Anderson, L.W. (1994). Attitude measures. In T. Husen (ed.). The International Encyclopedia of Education. (2nd ed.), 1.Oxford: Pergamon.
  • Baumgartner, F., Braun, T., Kurt, E., & Weyland, A. (2003). Virtual routers: a tool for networking research and education. ACM SIGCOMM Computer Communication Review, 33(3), 127-135.
  • De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179-201.
  • Demir, D. (2002). The Effects of Student Awareness of Goals on Success in and Attitudes Towards a Reading Course at Gaziosmanpaşa University (Doctoral dissertation, Institute of Economics and Social Sciences, Bilkent Univ.).
  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
  • Eagly, A. H., & Chaiken, S. (1998). Attitude structure and function. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 269-322). New York, NY, US: McGraw-Hill.
  • Garard, D. L., Lippert, L., Hunt, S. K., & Paynton, S. T. (1998). Alternatives to traditional instruction: Using games and simulations to increase student learning and motivation. Communication Research Reports, 15(1), 36-44.
  • Gottfried, A. E. (1985). Academic intrinsic motivation in elementary and junior high school students. Journal of Educational Psychology, 77(6), 631-645.
  • Graven, O., Hansen, H., & MacKinnon, L. (2009). A computer game modelling routing in computer networks as abstract learning material in a blended learning environment. International Journal of Emerging Technologies in Learning (iJET),4(2009), 18-22.
  • Hendricks, A.B. (1997). Predicting student success with the Learning and Study Strategies Inventory (LASSI). Unpublished Master’s thesis. Iowa State University, Ames, IA.
  • Jeschke, S., Richter, T., & Zorn, E. (2010). Virtual labs in mathematics and natural sciences. International Conference on Technology Supported Learning & Training: Online Educa Berlin.
  • Keller, J. M., & Kopp, T. W. (1987). An application of the ARCS model of motivational design. In C.M. Reigeluth (Ed.), Instructional theories in actions: Lessons illustrating selected theories and models (pp. 289-320). Hillsdale, NJ: Lawrence Erlbaum.
  • Keller, J. M. (1983). Motivational design of instruction. Instructional design theories and models: An overview of their current status, 1, 383-434.
  • Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. Cambridge, MA: MIT Press.
  • Kranjc, T. (2011). Simulations as a complement and a motivation element in the teaching of physics. Metodički obzori, 6(12), 175-187.
  • Kumar, A., Pakala, R., Ragade, R. K., & Wong, J. P. (1998, November). The virtual learning environment system. In Frontiers in Education Conference, 1998. FIE'98. 28th Annual (Vol. 2, pp. 711-716). IEEE.
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. biometrics, 33, 159-174.
  • Lepper, M. R., Corpus, J. H., & Iyengar, S. S. (2005). Intrinsic and extrinsic motivational orientations in the classroom: age differences and academic correlates. Journal of educational psychology, 97(2), 184-196.
  • Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic inquiry. Thousand Oaks, Calif.: Sage.
  • Mack, N., Woodsong, C., MacQueen, K. M., Guest, G., & Namey, E. (2005). Qualitative research methods: a data collectors field guide.
  • Merriam, S. (2009). Qualitative research: A guide to design and implamentation. San Francisco, CA: Jossey-Bass.
  • Petranek, C.F.,Corey, S.,& Black,R.(1992).Three levels of learning in simulations: Participating, debriefing, and journals writing. Simulation & Gaming, 23(2),174-185.
  • Potemans, J., Theunis, J., Rodiers, B., Van den Broeck, B., Leys, P., Van Lil, E., & Van de Capelle, A. (2002). Simulation of a Campus Backbone Network, a case-study. education, 5(6), 7.
  • Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill.
  • Ruiz-Martinez, A., Pereniguez-Garcia, F., Marin-Lopez, R., Ruiz-Martinez, P. M., & Skarmeta-Gomez, A. F. (2013). Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool. Learning Technologies, IEEE Transactions on, 6(1), 85-96.
  • Shin, D., Yoon, E.S., Park, S.J., & Lee, E.S. (2000). Web-based interactive virtual laboratory system for unit operations and process systems engineering education. Computers and Chemical Engineering, 24(2), 1381–1385.
  • Stipek, D. (1993). Motivation to learn: From theory to practice. Needham Heights, MA: Allyn & Bacon.
  • Urhahne, D., Harms, M. G. (2006). Instruktionale Unterstützung beim Lernen mit Computersimulationen. Unterrichtswissenschaft, 34(4), 358–377.
  • Woodfield, B. (2005). Virtual chemlab getting started. Pearson Education website. Retrieved May, 25, 2005.
  • Zheng, D. (2015) Future Communication, Information and Computer Science. CRC Press.
  • Zimmerman, B.J., Bandura, A. & Martinez-Pons, M. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663-676.

The Effect of Computer Network Simulators on Students’ Motivation and Learning

Year 2018, Volume: 3 Issue: 2, 12 - 21, 01.06.2018

Abstract

The purpose of this study was to explore students’ attitude, motivation and learning in introductory networking courses where a simulator was utilized for doing practice on the content. Basic qualitative research method was utilized to seek answers to the research question. Data was collected by individual interviews, conducted to 12 undergraduate and 5 graduate students. The interview data was transcribed and analyzed trough content analysis to find out the themes and categories. Analysis of data culminated five main themes with categories. Two of the five themes were related to student attitudes; 1 goal setting theme with information age qualities, professional development and problem solving skills categories, 2 learner internal factors, with curiosity and interest categories. Other two themes were related to student motivation; 3 Self-confidence, with visuality and manuals categories and 4 locus of control, with chance to practice and trial and error categories. The last theme was related to learning; 5 deep understanding with providing concreteness, learning by applying and visuality categories.

References

  • Agarwal, J., & Malhotra, N. K. (2005). An integrated model of attitude and affect: Theoretical foundation and an empirical investigation. Journal of Business research, 58(4), 483-493.
  • Akkağıt, Ş. F., & Tekin, A. (2012). Simülasyon Tabanlı Öğrenmenin Ortaöğretim Öğrencilerinin Temel Elektronik ve Ölçme Dersindeki Başarılarına Etkisi. Ege Eğitim Dergisi, 13(2).
  • Alnoukari, M., Shafaamry, M. & Aytouni, K. (2013). Simulation for Computer Sciences Education. Communications of the ACS, 6(1), 1-19.
  • Anderson, L.W. (1994). Attitude measures. In T. Husen (ed.). The International Encyclopedia of Education. (2nd ed.), 1.Oxford: Pergamon.
  • Baumgartner, F., Braun, T., Kurt, E., & Weyland, A. (2003). Virtual routers: a tool for networking research and education. ACM SIGCOMM Computer Communication Review, 33(3), 127-135.
  • De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179-201.
  • Demir, D. (2002). The Effects of Student Awareness of Goals on Success in and Attitudes Towards a Reading Course at Gaziosmanpaşa University (Doctoral dissertation, Institute of Economics and Social Sciences, Bilkent Univ.).
  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.
  • Eagly, A. H., & Chaiken, S. (1998). Attitude structure and function. In D. T. Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 269-322). New York, NY, US: McGraw-Hill.
  • Garard, D. L., Lippert, L., Hunt, S. K., & Paynton, S. T. (1998). Alternatives to traditional instruction: Using games and simulations to increase student learning and motivation. Communication Research Reports, 15(1), 36-44.
  • Gottfried, A. E. (1985). Academic intrinsic motivation in elementary and junior high school students. Journal of Educational Psychology, 77(6), 631-645.
  • Graven, O., Hansen, H., & MacKinnon, L. (2009). A computer game modelling routing in computer networks as abstract learning material in a blended learning environment. International Journal of Emerging Technologies in Learning (iJET),4(2009), 18-22.
  • Hendricks, A.B. (1997). Predicting student success with the Learning and Study Strategies Inventory (LASSI). Unpublished Master’s thesis. Iowa State University, Ames, IA.
  • Jeschke, S., Richter, T., & Zorn, E. (2010). Virtual labs in mathematics and natural sciences. International Conference on Technology Supported Learning & Training: Online Educa Berlin.
  • Keller, J. M., & Kopp, T. W. (1987). An application of the ARCS model of motivational design. In C.M. Reigeluth (Ed.), Instructional theories in actions: Lessons illustrating selected theories and models (pp. 289-320). Hillsdale, NJ: Lawrence Erlbaum.
  • Keller, J. M. (1983). Motivational design of instruction. Instructional design theories and models: An overview of their current status, 1, 383-434.
  • Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. Cambridge, MA: MIT Press.
  • Kranjc, T. (2011). Simulations as a complement and a motivation element in the teaching of physics. Metodički obzori, 6(12), 175-187.
  • Kumar, A., Pakala, R., Ragade, R. K., & Wong, J. P. (1998, November). The virtual learning environment system. In Frontiers in Education Conference, 1998. FIE'98. 28th Annual (Vol. 2, pp. 711-716). IEEE.
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. biometrics, 33, 159-174.
  • Lepper, M. R., Corpus, J. H., & Iyengar, S. S. (2005). Intrinsic and extrinsic motivational orientations in the classroom: age differences and academic correlates. Journal of educational psychology, 97(2), 184-196.
  • Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic inquiry. Thousand Oaks, Calif.: Sage.
  • Mack, N., Woodsong, C., MacQueen, K. M., Guest, G., & Namey, E. (2005). Qualitative research methods: a data collectors field guide.
  • Merriam, S. (2009). Qualitative research: A guide to design and implamentation. San Francisco, CA: Jossey-Bass.
  • Petranek, C.F.,Corey, S.,& Black,R.(1992).Three levels of learning in simulations: Participating, debriefing, and journals writing. Simulation & Gaming, 23(2),174-185.
  • Potemans, J., Theunis, J., Rodiers, B., Van den Broeck, B., Leys, P., Van Lil, E., & Van de Capelle, A. (2002). Simulation of a Campus Backbone Network, a case-study. education, 5(6), 7.
  • Prensky, M. (2001). Digital game-based learning. New York: McGraw Hill.
  • Ruiz-Martinez, A., Pereniguez-Garcia, F., Marin-Lopez, R., Ruiz-Martinez, P. M., & Skarmeta-Gomez, A. F. (2013). Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool. Learning Technologies, IEEE Transactions on, 6(1), 85-96.
  • Shin, D., Yoon, E.S., Park, S.J., & Lee, E.S. (2000). Web-based interactive virtual laboratory system for unit operations and process systems engineering education. Computers and Chemical Engineering, 24(2), 1381–1385.
  • Stipek, D. (1993). Motivation to learn: From theory to practice. Needham Heights, MA: Allyn & Bacon.
  • Urhahne, D., Harms, M. G. (2006). Instruktionale Unterstützung beim Lernen mit Computersimulationen. Unterrichtswissenschaft, 34(4), 358–377.
  • Woodfield, B. (2005). Virtual chemlab getting started. Pearson Education website. Retrieved May, 25, 2005.
  • Zheng, D. (2015) Future Communication, Information and Computer Science. CRC Press.
  • Zimmerman, B.J., Bandura, A. & Martinez-Pons, M. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663-676.
There are 34 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

Halil GULLU This is me

Omer DELİALİOGLU

Publication Date June 1, 2018
Published in Issue Year 2018 Volume: 3 Issue: 2

Cite

APA GULLU, H., & DELİALİOGLU, O. (2018). The Effect of Computer Network Simulators on Students’ Motivation and Learning. Journal of Learning and Teaching in Digital Age, 3(2), 12-21.

Journal of Learning and Teaching in Digital Age 2023. © 2023. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. 19195

Journal of Learning and Teaching in Digital Age. All rights reserved, 2023. ISSN:2458-8350