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Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration

Year 2010, Volume: 1 Issue: 4, 335 - 347, 01.12.2010

Abstract

This study was designed to investigate the relative and combined contributions of cognition and emotion on Nigerian undergraduate students’ level of computer frustration in online environments. A total of 1972 (Male=987, Female=985) students randomly selected from the two state-owned universities in Ogun State of Nigeria participated in the study. The data for the study were collected through the use of Students’ Cognition Scale (SCS), Students’ Emotion Scale (SES) and Students’ Computer Frustration Scale (SCFS). Data analysis involved the use of mean and standard deviation as descriptive statistics as well as Pearson Product Moment Correlation and regression analysis as inferential statistics. The research findings revealed that students encountered various frustrating experiences during e-registration, when a combination of the predictor variables (cognition and emotion) significantly accounted for 2.5% to the variance of the students’ level of frustration during e-registration. Meanwhile, cognition was found as the potent contributor of students’ frustration during e-registration. The results of this study further indicated that there was a statistically significant difference in the level of computer frustration among students of different universities. Recommendations were made according to the findings of the study.

References

  • Baylor, A. L. & Rosenberg-Kima, (2006, June). Interface agents to alleviate online frustration. Paper presented at the 7th International Conference on Learning Sciences. Bloomington, Indiana.
  • Baylor, A. L., Warren, D., Park, S., Shen, E., & Perez, R. (2005, July). The impact of frustration- mitigating messages delivered by an interface agent. Paper presented at the 12th International Conference on Artificial Intelligence in Education. Amsterdam, The Netherlands.
  • Bessiere, K., Newhagen, J.E., Robinson, J.P. & Shneiderman, B. (2006). A model for computer frustration: The role of instructional and dispositional tutors on incident, session and post-session frustration and mood. Computers in Human Behavior, 22, 941–961
  • Creed, C. & B’eale, R. (2005). Using emotion simulation to influence user attitudes and behavior. Retrieved March 23, 2009 from http://citeseerx.ist.psu.edu/viewdoc/ download?doi=10.1.1.132.1622&rep=rep1&type=pdf.
  • Cristescu, I. (2008). Emotion in human-computer interaction: The role of non-verbal behavior in interactive systems. Revista Informatica Economică nr, 2(46), 110-116. Retrieved February 20, 2010 from http://revistaie.ase.ro/content/46/S%20-%20Irina%20Cristescu. pdf
  • Dalgleish, T. & Power, M.J. (1999). Cognition and emotion: Future directions. In T. Dalgleish & M. Power (Eds.), Handbook of Cognition and Emotion. Chichester, England: Wiley.
  • D’Mello, S., Jackson, T., Craig, S, Morgan, B., Chip-man, P., White, H., Person, N., Kort, B., Kaliouby, R., Picard, R., & Graesser, A. (2007). AutoTutor detects and responds to learners affective and cognitive states. Retrieved October 17, 2010 from http://www. emotion.autotutor.org/files/dmello-affectwkshp-its08.pdf
  • Dror, I. & Harnad, S. (2009). Offloading cognition onto cognitive technology. In I. Dror & S. Harnad (Eds.), Cognition distributed: How cognitive technology extends our minds. Amsterdam, the Netherland: John Benjamins.
  • Ekman, P. (1993). Facial expression and emotion. American Psychologist, 48(4), 638–652. Retrieved March 23, 2009 from http://www.ncbi.nlm.nih.gov/pubmed/8512154
  • Freese, J., Rivas, S., & Hargittai, E. (2006). Cognitive ability and Internet use among older adults. Poetics, 34(4/5), 236-249.
  • Glazer, C. (2008). Emotions and students role in an online course. E-Learning and Digital Media, 5(1), 51-63. Retrieved February 20, 2010 from http://www.wwwords.co.uk/ rss/abstract.asp?j=elea&aid=3271
  • Gottfredson, L. S. (2002). g: Highly general and highly practical. In R.J. Sternberg & E.L. Grigorenko (Eds.), The general factor of intelligence: How general is it? Mahwah, NJ: Lawrence Erlbaum.
  • Graesser, A., Chipman, P., King, B., McDaniel, B., & D’Mello, S. (2007, July). Emotions and learning with auto tutor. Paper presented at the 13th International Conference on Artificial Intelligence in Education. Los Angeles, CA.
  • Hazlett, R. L. (2003, April). Measurement of user frustration: A biologic approach. Paper presented at the Conference on Human Factors in Computing Systems. Lauderdale, FL.
  • Hemby, H. (1998). Self-directedness in nontraditional college students: A behavioral factor in computer anxiety? Computers in Human Behavior, 14(2), 303-319. Retrieved February 20, 2010 from http://www.sciencedirect.com/science?
  • Hess, B. (1999). Graduate student cognition during information retrieval using the World Wide Web: A pilot study. Computers & Education, 33(1), 1-13. Retrieved February 20, 2010 from http://portal.acm.org/citation.cfm?id=331340
  • Hone, K. (2006). Emphatic agents to reduce user frustration: the affects of varying agent characteristics. Interacting with Computers, 18(2), 227-245. Retrieved February 20, 2010 from http://bura.brunel.ac.uk/handle/2438/3107
  • Lazar, J., Jones, A., Bessiere, K., Ceaparu, I., & Shneiderman, B. (2004). User frustration with technology in the workplace. AMCIS 2003 Proceedings. Retrieved March 23, 2009 from http://aisel.aisnet.org/amcis2003/283/
  • Lazar, J., Jones, A., Bessiere, K., Hackley, M., & Shneiderman, B. (2006). Severity and impact of computer user frustration: A comparison of students and workplace user. Interacting with Computers, 18(2), 187-207. Retrieved February 20, 2010 from http://portal.acm. org/citation.cfm?id=1220955.1221011
  • Lazar, J., Jones, A., & Hackley, M. (2004). Severity and Impact of Computer User Frustration: A Comparison of Student and Workplace Users. Interacting with Computers, 18(2), 187- 207.
  • Lim,D.H. (2004, March). Cross cultural differences in online learning motivation. Paper presented at the Academy of Human Resource Development International Conference (AHRD). Austin, TX.
  • Mandernach, B.J., Donelli, E., & Dailey-Hebert, A. (2006). Learners attribute research juxtaposed with online instructor experience: Predictor of success in the accelerated, online classroom. The Journal of Educators Online, 3(2), 1-17. Retrieved March 23, 2009 from http://www.thejeo.com/Volume3Number2/MandernachFinal.pdf
  • Miltiadou, M. & Savenye, W.C. (2003). Applying social cognitive constructs of motivation to enhance students’ success in online distance education. AACE Journal, 11(1), 78-95. Retrieved March 23, 2009 from http://www.aace.org/pubs/etr/issue4/miltiadou2.pdf
  • Nummenmaa, M. (2007). Emotions in a web-based learning environment (Unpublished master’s thesis). University of Turku, Finland.
  • Ojerinde, D. Kolo, T.N. (2009, August). Cyber crime in e-registration. Paper presented at the 27th Annual conference of the Association for Education Assessment in Africa (AEAA). Yaoundé, Cameroon.
  • Onochie, M. (2010, February 10). Endless hurdles of online JAMB registration. Daily Trust. Retrieved February 10, 2010, from www.news.dailytrust.com/index.php?...endless- hurdles-of-online-jamb-registration
  • O’Regan, K. (2003). Emotion and e-learning. Journal of Asynchronous Learning Networks, 7(3), 78-92. Retrieved March 23, 2009, from http://www.sloan-c.org/publications/jaln/ v7n3/v7n3_oregan.asp
  • Pew Internet and American Life Project. (2003). The ever-shifting Internet population: A new look at Internet access and the digital divide. Retrieved March 23, 2009 from http://www.pewinternet.org/Reports/2003/The-EverShifting-Internet-Population-A- new-look-at-Internet-access-and-the-digital-divide.aspx
  • Picard, R.W. 1998. Toward agents that recognize emotion. Actes Proceedings IMAGINA (pp.153-165). Monaco. Retrieved March 20, 2010 from http://vismod.media.mit.edu/ tech-reports/TR-515.pdf
  • Preece, J., Rogers, Y., & Sharp, H. (2002). Interaction design: Beyond the human-computer interaction. New York: John Wiley & Sons.
  • Roseman, I. J. & Smith C.A. (2001). Appraisal theory: Overview, assumptions, varieties, controversies. In K.R. Scherer, A. Schorr & T. Johnstone (Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 3–19). Oxford/New York: Oxford University Press.
  • Rozell, E. J. & Gardner, W. L. (2000). Cognitive, motivation and affective processes associated with computer-related performance: A path analysis. Computers in Human Behavior, 16(2), 199-222. Retrieved March 23, 2009 from http://www.sciencedirect.com/science?
  • Tatum, S. & Morote, E. (2006). Teachers’ motivations and frustration when using instructional technology. Paper presented at the International Conference for Society for Information Technology & Teacher Education. Chesapeake, VA: AACE.
  • Tu, C. & McIsaac, M. (2002). The relationship of social presence and interaction in online classes. American Journal of Distance Education, 16(3), 131-150. Retrieved March 20, 2010 from http://www.informaworld.com/smpp/839354790-6278033/content~db=all~ content=a783721577
  • Yildirim, S., Lee, C.M., Potamianos, A., & Narayanan, S. (2005, September). Detecting politeness and frustration state of a child in a conversational computer game. Paper presented at the 9th biennial conference of the International Speech Communication Association. Lisbon, Portugal.
  • Zhu, E. (2006). Interaction and cognitive engagement: An Analysis of four asynchronous online discussions. Instructional Science, 34(6), 451-480.
  • Correspondence: Alaba O Agbatogun, Moray House School of Education, University of
  • Edinburgh, EH8 8AQ, United Kingdom.
Year 2010, Volume: 1 Issue: 4, 335 - 347, 01.12.2010

Abstract

References

  • Baylor, A. L. & Rosenberg-Kima, (2006, June). Interface agents to alleviate online frustration. Paper presented at the 7th International Conference on Learning Sciences. Bloomington, Indiana.
  • Baylor, A. L., Warren, D., Park, S., Shen, E., & Perez, R. (2005, July). The impact of frustration- mitigating messages delivered by an interface agent. Paper presented at the 12th International Conference on Artificial Intelligence in Education. Amsterdam, The Netherlands.
  • Bessiere, K., Newhagen, J.E., Robinson, J.P. & Shneiderman, B. (2006). A model for computer frustration: The role of instructional and dispositional tutors on incident, session and post-session frustration and mood. Computers in Human Behavior, 22, 941–961
  • Creed, C. & B’eale, R. (2005). Using emotion simulation to influence user attitudes and behavior. Retrieved March 23, 2009 from http://citeseerx.ist.psu.edu/viewdoc/ download?doi=10.1.1.132.1622&rep=rep1&type=pdf.
  • Cristescu, I. (2008). Emotion in human-computer interaction: The role of non-verbal behavior in interactive systems. Revista Informatica Economică nr, 2(46), 110-116. Retrieved February 20, 2010 from http://revistaie.ase.ro/content/46/S%20-%20Irina%20Cristescu. pdf
  • Dalgleish, T. & Power, M.J. (1999). Cognition and emotion: Future directions. In T. Dalgleish & M. Power (Eds.), Handbook of Cognition and Emotion. Chichester, England: Wiley.
  • D’Mello, S., Jackson, T., Craig, S, Morgan, B., Chip-man, P., White, H., Person, N., Kort, B., Kaliouby, R., Picard, R., & Graesser, A. (2007). AutoTutor detects and responds to learners affective and cognitive states. Retrieved October 17, 2010 from http://www. emotion.autotutor.org/files/dmello-affectwkshp-its08.pdf
  • Dror, I. & Harnad, S. (2009). Offloading cognition onto cognitive technology. In I. Dror & S. Harnad (Eds.), Cognition distributed: How cognitive technology extends our minds. Amsterdam, the Netherland: John Benjamins.
  • Ekman, P. (1993). Facial expression and emotion. American Psychologist, 48(4), 638–652. Retrieved March 23, 2009 from http://www.ncbi.nlm.nih.gov/pubmed/8512154
  • Freese, J., Rivas, S., & Hargittai, E. (2006). Cognitive ability and Internet use among older adults. Poetics, 34(4/5), 236-249.
  • Glazer, C. (2008). Emotions and students role in an online course. E-Learning and Digital Media, 5(1), 51-63. Retrieved February 20, 2010 from http://www.wwwords.co.uk/ rss/abstract.asp?j=elea&aid=3271
  • Gottfredson, L. S. (2002). g: Highly general and highly practical. In R.J. Sternberg & E.L. Grigorenko (Eds.), The general factor of intelligence: How general is it? Mahwah, NJ: Lawrence Erlbaum.
  • Graesser, A., Chipman, P., King, B., McDaniel, B., & D’Mello, S. (2007, July). Emotions and learning with auto tutor. Paper presented at the 13th International Conference on Artificial Intelligence in Education. Los Angeles, CA.
  • Hazlett, R. L. (2003, April). Measurement of user frustration: A biologic approach. Paper presented at the Conference on Human Factors in Computing Systems. Lauderdale, FL.
  • Hemby, H. (1998). Self-directedness in nontraditional college students: A behavioral factor in computer anxiety? Computers in Human Behavior, 14(2), 303-319. Retrieved February 20, 2010 from http://www.sciencedirect.com/science?
  • Hess, B. (1999). Graduate student cognition during information retrieval using the World Wide Web: A pilot study. Computers & Education, 33(1), 1-13. Retrieved February 20, 2010 from http://portal.acm.org/citation.cfm?id=331340
  • Hone, K. (2006). Emphatic agents to reduce user frustration: the affects of varying agent characteristics. Interacting with Computers, 18(2), 227-245. Retrieved February 20, 2010 from http://bura.brunel.ac.uk/handle/2438/3107
  • Lazar, J., Jones, A., Bessiere, K., Ceaparu, I., & Shneiderman, B. (2004). User frustration with technology in the workplace. AMCIS 2003 Proceedings. Retrieved March 23, 2009 from http://aisel.aisnet.org/amcis2003/283/
  • Lazar, J., Jones, A., Bessiere, K., Hackley, M., & Shneiderman, B. (2006). Severity and impact of computer user frustration: A comparison of students and workplace user. Interacting with Computers, 18(2), 187-207. Retrieved February 20, 2010 from http://portal.acm. org/citation.cfm?id=1220955.1221011
  • Lazar, J., Jones, A., & Hackley, M. (2004). Severity and Impact of Computer User Frustration: A Comparison of Student and Workplace Users. Interacting with Computers, 18(2), 187- 207.
  • Lim,D.H. (2004, March). Cross cultural differences in online learning motivation. Paper presented at the Academy of Human Resource Development International Conference (AHRD). Austin, TX.
  • Mandernach, B.J., Donelli, E., & Dailey-Hebert, A. (2006). Learners attribute research juxtaposed with online instructor experience: Predictor of success in the accelerated, online classroom. The Journal of Educators Online, 3(2), 1-17. Retrieved March 23, 2009 from http://www.thejeo.com/Volume3Number2/MandernachFinal.pdf
  • Miltiadou, M. & Savenye, W.C. (2003). Applying social cognitive constructs of motivation to enhance students’ success in online distance education. AACE Journal, 11(1), 78-95. Retrieved March 23, 2009 from http://www.aace.org/pubs/etr/issue4/miltiadou2.pdf
  • Nummenmaa, M. (2007). Emotions in a web-based learning environment (Unpublished master’s thesis). University of Turku, Finland.
  • Ojerinde, D. Kolo, T.N. (2009, August). Cyber crime in e-registration. Paper presented at the 27th Annual conference of the Association for Education Assessment in Africa (AEAA). Yaoundé, Cameroon.
  • Onochie, M. (2010, February 10). Endless hurdles of online JAMB registration. Daily Trust. Retrieved February 10, 2010, from www.news.dailytrust.com/index.php?...endless- hurdles-of-online-jamb-registration
  • O’Regan, K. (2003). Emotion and e-learning. Journal of Asynchronous Learning Networks, 7(3), 78-92. Retrieved March 23, 2009, from http://www.sloan-c.org/publications/jaln/ v7n3/v7n3_oregan.asp
  • Pew Internet and American Life Project. (2003). The ever-shifting Internet population: A new look at Internet access and the digital divide. Retrieved March 23, 2009 from http://www.pewinternet.org/Reports/2003/The-EverShifting-Internet-Population-A- new-look-at-Internet-access-and-the-digital-divide.aspx
  • Picard, R.W. 1998. Toward agents that recognize emotion. Actes Proceedings IMAGINA (pp.153-165). Monaco. Retrieved March 20, 2010 from http://vismod.media.mit.edu/ tech-reports/TR-515.pdf
  • Preece, J., Rogers, Y., & Sharp, H. (2002). Interaction design: Beyond the human-computer interaction. New York: John Wiley & Sons.
  • Roseman, I. J. & Smith C.A. (2001). Appraisal theory: Overview, assumptions, varieties, controversies. In K.R. Scherer, A. Schorr & T. Johnstone (Eds.), Appraisal processes in emotion: Theory, methods, research (pp. 3–19). Oxford/New York: Oxford University Press.
  • Rozell, E. J. & Gardner, W. L. (2000). Cognitive, motivation and affective processes associated with computer-related performance: A path analysis. Computers in Human Behavior, 16(2), 199-222. Retrieved March 23, 2009 from http://www.sciencedirect.com/science?
  • Tatum, S. & Morote, E. (2006). Teachers’ motivations and frustration when using instructional technology. Paper presented at the International Conference for Society for Information Technology & Teacher Education. Chesapeake, VA: AACE.
  • Tu, C. & McIsaac, M. (2002). The relationship of social presence and interaction in online classes. American Journal of Distance Education, 16(3), 131-150. Retrieved March 20, 2010 from http://www.informaworld.com/smpp/839354790-6278033/content~db=all~ content=a783721577
  • Yildirim, S., Lee, C.M., Potamianos, A., & Narayanan, S. (2005, September). Detecting politeness and frustration state of a child in a conversational computer game. Paper presented at the 9th biennial conference of the International Speech Communication Association. Lisbon, Portugal.
  • Zhu, E. (2006). Interaction and cognitive engagement: An Analysis of four asynchronous online discussions. Instructional Science, 34(6), 451-480.
  • Correspondence: Alaba O Agbatogun, Moray House School of Education, University of
  • Edinburgh, EH8 8AQ, United Kingdom.
There are 38 citations in total.

Details

Other ID JA78GG83FT
Journal Section Articles
Authors

Alaba O. Agbatogun This is me

Peter A. Ajelabi This is me

Lawunmi M. Oyewusi This is me

Publication Date December 1, 2010
Published in Issue Year 2010 Volume: 1 Issue: 4

Cite

APA Agbatogun, A. O., Ajelabi, P. A., & Oyewusi, L. M. (2010). Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration. Contemporary Educational Technology, 1(4), 335-347.
AMA Agbatogun AO, Ajelabi PA, Oyewusi LM. Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration. Contemporary Educational Technology. December 2010;1(4):335-347.
Chicago Agbatogun, Alaba O., Peter A. Ajelabi, and Lawunmi M. Oyewusi. “Cognition and Emotions in Nigerian Undergraduates’ Frustration During E-Registration”. Contemporary Educational Technology 1, no. 4 (December 2010): 335-47.
EndNote Agbatogun AO, Ajelabi PA, Oyewusi LM (December 1, 2010) Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration. Contemporary Educational Technology 1 4 335–347.
IEEE A. O. Agbatogun, P. A. Ajelabi, and L. M. Oyewusi, “Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration”, Contemporary Educational Technology, vol. 1, no. 4, pp. 335–347, 2010.
ISNAD Agbatogun, Alaba O. et al. “Cognition and Emotions in Nigerian Undergraduates’ Frustration During E-Registration”. Contemporary Educational Technology 1/4 (December 2010), 335-347.
JAMA Agbatogun AO, Ajelabi PA, Oyewusi LM. Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration. Contemporary Educational Technology. 2010;1:335–347.
MLA Agbatogun, Alaba O. et al. “Cognition and Emotions in Nigerian Undergraduates’ Frustration During E-Registration”. Contemporary Educational Technology, vol. 1, no. 4, 2010, pp. 335-47.
Vancouver Agbatogun AO, Ajelabi PA, Oyewusi LM. Cognition and Emotions in Nigerian Undergraduates’ Frustration during e-Registration. Contemporary Educational Technology. 2010;1(4):335-47.