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IDENTIFYING FACTORS THAT AFFECT THE ACCEPTANCE AND USE OF E-ASSESSMENT BY ACADEMICS IN SAUDI UNIVERSITIES

Year 2016, , 132 - 140, 22.04.2016

Nuha Alruwais , Gary Wills Mike Wald

https://doi.org/10.18768/ijaedu.20012
Cited By: 1

Abstract

As assessment is one of the important pillars of the learning process, and E-assessment has become an essential part of education systems. E-assessment has developed to address some of the limitations and problems of a paper-test. In last the10 years, E-assessment has improved in developed countries such as the UK. In contrast, in Saudi Arabia, one of the developing countries, less attention has been paid to the usage of E-assessment and research which discusses E-assessment issues in Saudi Arabia is limited. Consequently, we investigate the factors that impact on academic’s use of E-assessment in Saudi universities. In order to examine these factors, the Decomposed Theory of Planned Behavior model (DTPB) is adopted with slight modification. Age and gender are added to the proposed model as moderating factors that affect attitude, subjective norms and perceived behavioral control. IT support is also added as a sub-factor under perceived behavioral control and technology facilitating conditions are included under resources facilitating conditions. 

Keywords: E-assessment, E-exam, electronic exam, online exam, online assessment.

Keywords

E-assessment E-exam electronic exam online exam online assessment

References

  • Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In Action Control (1st ed., pp. 11–39). Berlin Heidelberg: Springer.
  • Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50, 179–211.
  • Ajzen, I. (2005). Attitudes, Personality, and Behavior. McGraw-Hill International. Retrieved from http://books.google.co.uk/books?hl=en&lr=&id=ZbDlAAAAQBAJ&oi=fnd&pg=PP1&dq=Attitudes,+Personality,+and+Behavior&ots=hr_b4vcnbH&sig=gDd4yFNRh4KIgJlJxoEFqnqGQog#v=onepage&q=Attitudes%2C Personality%2C and Behavior&f=true
  • Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Prentice-Hall.
  • Alebaikan, R., & Troudi, S. (2010). Blended learning in Saudi universities: challenges and perspectives. Alt-J, 18(1), 49–59.
  • Al-fahad, F. N. (2009). Students’ Attitudes and Perceptions Towards The Effectiveness of Mobile Learning in King Saud University, Saudi Arabia. The Turkish Online Journal of Educational Technology- TOJET, 8(2).
  • Alkhalaf, S., Drew, S., & Alhussain, T. (2012). Assessing the Impact of e-Learning Systems on Learners: A Survey Study in the KSA. Procedia - Social and Behavioral Sciences, 47, 98–104.
  • Alkhalifa, H. (2010). E-learning and ICT Integration in Colleges and Universities in Saudi Arabia. Retrieved February 25, 2015, from http://elearnmag.acm.org/featured.cfm?aid=1735849
  • Almegran, A., Al-Yafei, A., & Ahmad, H. (2007). Pilot nationwide e-learning provision in the Kingdom of Saudi Arabia: Issues and challenges. In 21st Asian Association of Open Universities’ Annual Conference. Kuala Lumpur, Malaysia. Retrieved from http://eprints.oum.edu.my/13/
  • Al-Shehri, A. M. (2010). E-learning in Saudi Arabia: “To E or not to E, that is the question.” Journal of Family and Community Medicine, 17(3), 147–150.
  • Anandarajan, M., Igbaria, M., & Anakwe, U. P. (2002). IT acceptance in a less-developed country: A motivational factor perspective. International Journal of Information Management, 22, 47–65.
  • Audette, B. (2005). Beyond curriculum alignment: How one high school is using student assessment data to drive curriculum and instruction decision making, (2001). Retrieved from https://castl.duq.edu/Conferences/Library03/PDF/Dat_Driv_Dec/Audette_B.pdf
  • Chien, S. P., Wu, H. K., & Hsu, Y. S. (2014). An investigation of teachers’ beliefs and their use of technology-based assessments. Computers in Human Behavior, 31, 198–210.
  • Compeau, D., A. Higgins, C., & Huff, S. (1999). Social Cognitive Theory and Individual Reactions To Computing Technology: a Longitudinal Study. MIS Quarterly, 23(2), 145–158.
  • Crews, T. B., & Curtis, D. F. (2010). Online Course Evaluations : Faculty Perspective and Strategies for Improved Response Rates. In Assessment & Evalution in Higher Education (Vol. 36, pp. 965–878). Routledge.
  • Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Massachusetts Institute of Technology).
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS quarterly, 13(3), 319–340.
  • Donovan, J., Mader, C., & Shinsky, J. (2007). Online vs. traditional course evaluation formats: Student perceptions. Journal of Interactive Online Learning, 6, 158–180. Retrieved from http://www.ncolr.org/jiol/issues/pdf/6.3.2.pdf
  • Ejaz, A. (2014). Analysis of motivational factors influencing acceptance of technologically-enhanced personal , academic and professional development portifilos. (Doctoral dissertation, University of Huddersfield Repository).
  • Eljinini, M., & Alsamarai, S. (2012). The Impact of E-assessments system on the success of the implementation process. Modern Education and Computer Science, 4(11), 76–84.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : an introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gazette. (2008). Business: Kingdom’s e-learning industry to reach $ 125 milion this year. Retrieved March 1, 2015, from: http://www.saudigazette.com.sa/index.cfm?method=home.regcon&contentID=200804244097
  • Ghorab, K. E. (1997). The impact of technology acceptance considerations on system usage, and adopted level of technological sophistication: An empirical investigation. International Journal of Information Management, 17(4), 249–259.
  • Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57(4), 2333–2351.
  • Gilbert, L., Whitelock, D., & Gale, V. (2011). Synthesis Report on Assessment and Feedback with Technology Enhancement. University of Southampton.
  • Hakami, Y., Razak, A., Husin, C., & Tam, S. (2014). A CBT Framework For Secondary Schools of Saudi. Sci.Int. (1), 853–864.
  • IMS, G. L. Consortium. (2008). IMS Question & test Interoperability specification. Retrieved February 10, 2015, from http://www.imsglobal.org/question/
  • Llamas-Nistal, M., Fernández-Iglesias, M. J., González-Tato, J., & Mikic-Fonte, F. A. (2013). Blended e-assessment: Migrating classical exams to the digital world. Computers & Education, 62, 72–87.
  • Malek, A., & Karim, A. (2010). An Empirical Investigation into The Role of Enjoyment , Computer Anxiety , Computer Self-Efficacy and Internet Experience in Influencing the Students’ Intention to Use E-learning : A Case Study from Saudi Arabian Governmental Universities. Turkish Online Journal of Educational Technology-TOJET, 9(4), 22–34.
  • Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. Database for Advances in Information Systems, 32(3), 86–112.
  • McGill, L. (2006). Overview of JISC assessment activities. In 10th CAA International Computer Assissted Assessment Conference: Proceedings of the Conference 4th and 5th July 2006 at Loughborough University (pp. 309–312). Loughborough: Loughborough University. Retrieved from http://caaconference.co.uk/pastConferences/2006/proceedings/McGill_L_p1.pdf
  • Minton, H. L., & W. Schneider, F. (1980). Differential psychology. Waveland PressInc.
  • Mirza, A. (2007). Is e-learning finally gaining legitimacy in Saudi Arabia. Saudi Computer Journal, 6(2).
  • Moore, G., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research.
  • Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions : Implications for a changing work force. Personnel Psychology, 53(2), 375–403.
  • M: Ministry of Education and Planning, (Saudi Arabia) (2007). Population and Housing Characteristics in the Kingdom of Saudi Arabia: Demographic Survey 1428H.
  • Ridgway, J., McCusker, S., & Pead, D. (2004). Literature review of e-assessment. (Vol. 44). UNSPECIFIED. Futurelab, Bristol. Retrieved from http://dro.dur.ac.uk/1929/
  • Sadaf, A., Newby, T. J., & Ertmer, P. a. (2012). Exploring pre-service teachers’ beliefs about using Web 2.0 technologies in K-12 classroom. Computers and Education, 59(3), 937–945.
  • Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14(3), 213–223.
  • Sitthisak, O., Gilbert, L., & Davis, H. C. (2008). An evaluation of pedagogically informed parameterised questions for self‐assessment. Learning, Media and Technology, 33(3), 235–248.
  • Sitthiworachart, J., Joy, M., & Sutinen, E. (2008). Success Factors for E-assessment in Computer science Education. Advancement of Computing in Education, 4, 2287–2293.
  • Skinner, B. F. (1958). Teaching Machines. Science, 128(3330), 969–977.
  • Sorensen, E. (2013). Implementation and student perceptions of e-assessment in a Chemical Engineering module. European Journal of Engineering Education, 38(2), 172–185.
  • Taylor, S., & Todd, P. (1995a). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12, 137–155.
  • Taylor, S., & Todd, P. A. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research. MIS quarterly. 6(2), 144-176.
  • Todd, P., & Model, T. A. (1995). Assessing IT Usage : The Role of Prior Experience The Influence of Prior Experience, 19(4), 561–570.
  • Venkatesh, V., Davis, F. D., & College, S. M. W. (2000). Theoretical Acceptance Extension Model : Field Four Studies of the Technology Longitudinal. Management Science, 46(2), 186–204.
  • Venkatesh, V., & Morris, G. M. (2000). Why don’t men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115–139.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Towards a Unified View1. Management Information System Research Center, University of Minnesota, 27(3), 425–478.
  • Way, A. (2012). The Use of E-assessments in The Nigerian Higher Education System. Turkish Online Journal of Distance Education, 13(1), 140–152.
  • Williams, J. B., & Wong, A. (2009). The efficacy of final examinations: A comparative study of closed-book, invigilated exams and open-book, open-web exams. British Journal of Educational Technology, 40(2), 227–236.
  • Yushau, B. (2006). The Effects of Blended E-Learning on Mathematics and Computer Attitudes in Pre-Calculus Algebra. TMME, 3(2), 176–183.

Year 2016, , 132 - 140, 22.04.2016

Nuha Alruwais , Gary Wills Mike Wald

https://doi.org/10.18768/ijaedu.20012
Cited By: 1

Abstract

References

  • Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In Action Control (1st ed., pp. 11–39). Berlin Heidelberg: Springer.
  • Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50, 179–211.
  • Ajzen, I. (2005). Attitudes, Personality, and Behavior. McGraw-Hill International. Retrieved from http://books.google.co.uk/books?hl=en&lr=&id=ZbDlAAAAQBAJ&oi=fnd&pg=PP1&dq=Attitudes,+Personality,+and+Behavior&ots=hr_b4vcnbH&sig=gDd4yFNRh4KIgJlJxoEFqnqGQog#v=onepage&q=Attitudes%2C Personality%2C and Behavior&f=true
  • Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Prentice-Hall.
  • Alebaikan, R., & Troudi, S. (2010). Blended learning in Saudi universities: challenges and perspectives. Alt-J, 18(1), 49–59.
  • Al-fahad, F. N. (2009). Students’ Attitudes and Perceptions Towards The Effectiveness of Mobile Learning in King Saud University, Saudi Arabia. The Turkish Online Journal of Educational Technology- TOJET, 8(2).
  • Alkhalaf, S., Drew, S., & Alhussain, T. (2012). Assessing the Impact of e-Learning Systems on Learners: A Survey Study in the KSA. Procedia - Social and Behavioral Sciences, 47, 98–104.
  • Alkhalifa, H. (2010). E-learning and ICT Integration in Colleges and Universities in Saudi Arabia. Retrieved February 25, 2015, from http://elearnmag.acm.org/featured.cfm?aid=1735849
  • Almegran, A., Al-Yafei, A., & Ahmad, H. (2007). Pilot nationwide e-learning provision in the Kingdom of Saudi Arabia: Issues and challenges. In 21st Asian Association of Open Universities’ Annual Conference. Kuala Lumpur, Malaysia. Retrieved from http://eprints.oum.edu.my/13/
  • Al-Shehri, A. M. (2010). E-learning in Saudi Arabia: “To E or not to E, that is the question.” Journal of Family and Community Medicine, 17(3), 147–150.
  • Anandarajan, M., Igbaria, M., & Anakwe, U. P. (2002). IT acceptance in a less-developed country: A motivational factor perspective. International Journal of Information Management, 22, 47–65.
  • Audette, B. (2005). Beyond curriculum alignment: How one high school is using student assessment data to drive curriculum and instruction decision making, (2001). Retrieved from https://castl.duq.edu/Conferences/Library03/PDF/Dat_Driv_Dec/Audette_B.pdf
  • Chien, S. P., Wu, H. K., & Hsu, Y. S. (2014). An investigation of teachers’ beliefs and their use of technology-based assessments. Computers in Human Behavior, 31, 198–210.
  • Compeau, D., A. Higgins, C., & Huff, S. (1999). Social Cognitive Theory and Individual Reactions To Computing Technology: a Longitudinal Study. MIS Quarterly, 23(2), 145–158.
  • Crews, T. B., & Curtis, D. F. (2010). Online Course Evaluations : Faculty Perspective and Strategies for Improved Response Rates. In Assessment & Evalution in Higher Education (Vol. 36, pp. 965–878). Routledge.
  • Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Massachusetts Institute of Technology).
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS quarterly, 13(3), 319–340.
  • Donovan, J., Mader, C., & Shinsky, J. (2007). Online vs. traditional course evaluation formats: Student perceptions. Journal of Interactive Online Learning, 6, 158–180. Retrieved from http://www.ncolr.org/jiol/issues/pdf/6.3.2.pdf
  • Ejaz, A. (2014). Analysis of motivational factors influencing acceptance of technologically-enhanced personal , academic and professional development portifilos. (Doctoral dissertation, University of Huddersfield Repository).
  • Eljinini, M., & Alsamarai, S. (2012). The Impact of E-assessments system on the success of the implementation process. Modern Education and Computer Science, 4(11), 76–84.
  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : an introduction to theory and research. Reading, MA: Addison-Wesley.
  • Gazette. (2008). Business: Kingdom’s e-learning industry to reach $ 125 milion this year. Retrieved March 1, 2015, from: http://www.saudigazette.com.sa/index.cfm?method=home.regcon&contentID=200804244097
  • Ghorab, K. E. (1997). The impact of technology acceptance considerations on system usage, and adopted level of technological sophistication: An empirical investigation. International Journal of Information Management, 17(4), 249–259.
  • Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57(4), 2333–2351.
  • Gilbert, L., Whitelock, D., & Gale, V. (2011). Synthesis Report on Assessment and Feedback with Technology Enhancement. University of Southampton.
  • Hakami, Y., Razak, A., Husin, C., & Tam, S. (2014). A CBT Framework For Secondary Schools of Saudi. Sci.Int. (1), 853–864.
  • IMS, G. L. Consortium. (2008). IMS Question & test Interoperability specification. Retrieved February 10, 2015, from http://www.imsglobal.org/question/
  • Llamas-Nistal, M., Fernández-Iglesias, M. J., González-Tato, J., & Mikic-Fonte, F. A. (2013). Blended e-assessment: Migrating classical exams to the digital world. Computers & Education, 62, 72–87.
  • Malek, A., & Karim, A. (2010). An Empirical Investigation into The Role of Enjoyment , Computer Anxiety , Computer Self-Efficacy and Internet Experience in Influencing the Students’ Intention to Use E-learning : A Case Study from Saudi Arabian Governmental Universities. Turkish Online Journal of Educational Technology-TOJET, 9(4), 22–34.
  • Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. Database for Advances in Information Systems, 32(3), 86–112.
  • McGill, L. (2006). Overview of JISC assessment activities. In 10th CAA International Computer Assissted Assessment Conference: Proceedings of the Conference 4th and 5th July 2006 at Loughborough University (pp. 309–312). Loughborough: Loughborough University. Retrieved from http://caaconference.co.uk/pastConferences/2006/proceedings/McGill_L_p1.pdf
  • Minton, H. L., & W. Schneider, F. (1980). Differential psychology. Waveland PressInc.
  • Mirza, A. (2007). Is e-learning finally gaining legitimacy in Saudi Arabia. Saudi Computer Journal, 6(2).
  • Moore, G., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research.
  • Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions : Implications for a changing work force. Personnel Psychology, 53(2), 375–403.
  • M: Ministry of Education and Planning, (Saudi Arabia) (2007). Population and Housing Characteristics in the Kingdom of Saudi Arabia: Demographic Survey 1428H.
  • Ridgway, J., McCusker, S., & Pead, D. (2004). Literature review of e-assessment. (Vol. 44). UNSPECIFIED. Futurelab, Bristol. Retrieved from http://dro.dur.ac.uk/1929/
  • Sadaf, A., Newby, T. J., & Ertmer, P. a. (2012). Exploring pre-service teachers’ beliefs about using Web 2.0 technologies in K-12 classroom. Computers and Education, 59(3), 937–945.
  • Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14(3), 213–223.
  • Sitthisak, O., Gilbert, L., & Davis, H. C. (2008). An evaluation of pedagogically informed parameterised questions for self‐assessment. Learning, Media and Technology, 33(3), 235–248.
  • Sitthiworachart, J., Joy, M., & Sutinen, E. (2008). Success Factors for E-assessment in Computer science Education. Advancement of Computing in Education, 4, 2287–2293.
  • Skinner, B. F. (1958). Teaching Machines. Science, 128(3330), 969–977.
  • Sorensen, E. (2013). Implementation and student perceptions of e-assessment in a Chemical Engineering module. European Journal of Engineering Education, 38(2), 172–185.
  • Taylor, S., & Todd, P. (1995a). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12, 137–155.
  • Taylor, S., & Todd, P. A. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research. MIS quarterly. 6(2), 144-176.
  • Todd, P., & Model, T. A. (1995). Assessing IT Usage : The Role of Prior Experience The Influence of Prior Experience, 19(4), 561–570.
  • Venkatesh, V., Davis, F. D., & College, S. M. W. (2000). Theoretical Acceptance Extension Model : Field Four Studies of the Technology Longitudinal. Management Science, 46(2), 186–204.
  • Venkatesh, V., & Morris, G. M. (2000). Why don’t men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115–139.
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Towards a Unified View1. Management Information System Research Center, University of Minnesota, 27(3), 425–478.
  • Way, A. (2012). The Use of E-assessments in The Nigerian Higher Education System. Turkish Online Journal of Distance Education, 13(1), 140–152.
  • Williams, J. B., & Wong, A. (2009). The efficacy of final examinations: A comparative study of closed-book, invigilated exams and open-book, open-web exams. British Journal of Educational Technology, 40(2), 227–236.
  • Yushau, B. (2006). The Effects of Blended E-Learning on Mathematics and Computer Attitudes in Pre-Calculus Algebra. TMME, 3(2), 176–183.
There are 52 citations in total.

Details

Journal Section Articles
Authors

Nuha Alruwais

Gary Wills

Mike Wald

Publication Date April 22, 2016
Submission Date April 20, 2016
Published in Issue Year 2016

Cite

EndNote Alruwais N, Wills G, Wald M (April 1, 2016) IDENTIFYING FACTORS THAT AFFECT THE ACCEPTANCE AND USE OF E-ASSESSMENT BY ACADEMICS IN SAUDI UNIVERSITIES. IJAEDU- International E-Journal of Advances in Education 2 4 132–140.

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