Computer Self-Efficacy in the Academic Library

May 28, 2008

I’ve been meaning to post a link the research paper on computer self-efficacy that I wrote this past semester. I admit that I have been deliberately staying away from computers after work – and as such, blogging has been a very low priority. Anyway, for those who were interested, the paper (Computer Self-Efficacy and the Academic Library Employee: An Examination of Their Relationship) can be found here.


Computer Self-Efficacy Data

April 23, 2008

I learned something interesting this week. If you copy and paste tables from Excel 2007 into WordPress, Google Reader will not display the post. Additionally, WordPress doesn’t really care for this either. It gets slow and sluggish – although it does eventually save and publish the tables. I plan to leave the original post alone, but probably won’t copy any more tables into any blog posts.

Anyway, I wrote a post earlier this week with some of the results from my computer self-efficacy survey of academic librarians. While I saw the post in Bloglines, it appears as if Google Reader plans to simply ignore it. Many people were curious about the results, so here they are. I do plan to do some posts with narrative about my conclusions etc. This will most likely be after I have officially turned my paper in and completed the rest of the work for my class.

Some CSE Survey Results

April 20, 2008

I am currently finishing up final edits on my research paper on computer self-efficacy in academic library workers. It is now titled – Computer Self-Efficacy and the Academic Library Employee: An Examination of Their Relationship (and yes, titles are not my forte). Several people have asked about reading the paper and getting the results. I’m not quite ready to share the paper (but will share with those who asked to see it after the semester is over – and possibly after grades are in). However, I do want to publicly share the findings from the survey.

The following tables give the mean computer self-efficacy levels for those demographic variables that turned out to be major determinants. Some notes: SD stands for standard deviation; Total # is the total population for that category and # is the total percentage of the entire population (which is 167).

Computer Self-Efficacy Levels by Technical Support Model
Category Mean SD High Low Total # %
Entire Population 153.29 16.06 179 81 167 100
Library Systems Support 151.3 16.93 179 111 81 48.5
Combined Library/IT Support 155.08 11.51 172 126 24 14.37
IT Support 154.9 16.03 178 81 41 24.55
Vendor Support 147 n/a 147 147 1 0.6
No Formal Support 135.67 34.15 173 106 3 1.8
Other Means of Tech Support 157.75 6.02 163 150 4 2.4
Multiple Means of Support 160.23 10.65 177 142 13 7.78


Compute Self-Efficacy Levels by Age

Age Mean SD High Low Total # %
20-29 Years of Age 156.92 10.05 171 134 50 29.94
30-39 Years of Age 153.74 15.18 179 111 68 40.72
40-49 Years of Age 155.51 16.54 175 115 29 17.37
50-59 Years of Age 140.07 28.37 179 81 15 8.98
>60 Years of Age 137.8 16.81 167 126 5 2.99


Computer Self-Efficacy Levels by Sex

Sex Mean S.D. High Low Total # %
Female 154.03 15.52 179 81 137 82.04
Male 149.93 18.27 171 123 30 17.96


Computer Self-Efficacy Levels by Educational Attainment

Degree Mean S.D. High Low Total # %
High School Degree 156 16.44 174 126 7 4.19
Bachelors Degree 156.6 11.93 177 141 25 14.97
Masters Degree 152.57 16.85 179 81 129 77.25
Doctorate 152 14.64 175 135 6 3.59


Computer Self-Efficacy Level by MLS or Equivalent

MLS or Equivalent Mean S.D. High Low Total # %
Library School 155.48 10.09 171 135 16 9.58
No MLS 155.57 14.06 177 126 21 12.57
MLS or Equivalent 152.66 16.96 179 81 130 77.84


Computer Self-Efficacy Levels by Length of Career

Length of Career Mean S.D. High Low Total # %
<10 Years 154.18 15.64 179 81 108 64.67
10-19 Years 154.63 14.48 178 125 41 24.55
20-29 Years 148 18.7 176 123 12 7.19
30-39 Years 139 25.88 167 106 5 2.99
>40 Years 137 0 137 137 1 0.6


Computer Self-Efficacy Levels by Job Classification

Job Classification Mean S.D. High Low Total # %
Library Assistant 152.71 15.23 177 126 38 22.75
Other 156.83 9.5 168 147 6 3.59
Professional Librarian 153.3 16.63 179 81 123 73.65

 Computer Self-Efficacy Levels by Job Satisfaction

Job Satisfaction Mean S.D. High Low Total # %
Extremely Satisified 160.44 11.27 179 125 36 26.28
Mostly Satisfied 152.9 15.98 179 81 98 58.68
Neither Satisf. Nor Unsatisf. 137.33 19.86 171 106 9 5.38
Somewhat Unsatisfied 151.32 16.53 175 111 22 13.17
Unsatisfied 137.5 0.71 138 137 2 1.2


Computer Self-Efficacy Levels by Computer Experience

Computer Experience Mean S.D. High Low Total # %
Extremely Experienced 162.7 11.08 179 131 50 29.94
Much Experience 152.42 14.03 177 115 96 57.49
Some Experience 134.9 18.07 163 81 21 12.57
Little Experience 0 0 0 0 0 0
No Experience 0 0 0 0 0 0


Computer Self-Efficacy Levels by Computer Training

Computer Training Mean S.D. High Low Total # %
No Training 154.81 16.71 179 106 36 21.56
Training 152.88 15.92 179 81 131 78.44

Computer Self-Efficacy: A Bibliography

January 28, 2008

My preliminary bibliography for my ILS680 special project:


Agarwal, R., & V. Sambamurthy and Ralph M. Stair. (2000). Research report: The evolving relationship between general and specific computer self-efficacy – an empirical assessment. Information Systems Research, 11(4), 418-430.

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Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, New Jersey: Prentice-Hall, Inc.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman and Company.

Bandura, A., & Walters, R. H. (1963). Social learning and personality development. New York: Holt, Rinehart and Winston, Inc.

Barbeite, F. G., & Weiss, E. (2004). Computer self-efficacy and anxiety scales for an internet sample: Testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20, 1-15.

Beas, M. I., & Salanova, M. (2006). Self-efficacy beliefs, computer training and psychological well-being among information and communication technology workers. Computers in Human Behavior, 22, 1043-1058.

Beckers, J. J., & Schmidt, H. G. (2001). The structure of computer anxiety: A six-factor model. Computers in Human Behavior, 17, 35-49.

Busch, T. (1995). Gender differences in self-efficacy and attitudes toward computers. Journal of Educational Computing Research, 12, 147-158.

Cassidy, S., & Eachus, P. (2002). Developing the computer user self-efficacy (CUSE) scale: Investigating the relationship between computer self-efficacy, gender and experience with computers. Journal of Educational Computing Research, 26(2), 133-153.

Cleyle, S. (2003). Introduction. Library Hi Tech, 21(3), 270-272.

Coffin, R. J., & MacIntrye, P. D. (1999). Motivational influences on computer-related affective states. Computers in Human Behavior, 15, 549-569.

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.

Compeau, D. R., Higgins, C. A., & Huff, S. L. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.

Czaja, S. J., Neil Charness, Arthur D. Fisk, Christopher Herzog, Sankaran N. Nair, Wendy A. Rogers, et al. (2006). Factors predicting the use of technology: Findings from the center for research and education on aging and technology enhancement (CREATE). Psychology and Aging, 21(2), 333-352.

Decker, C. A. (1999). Technical education transfer: Perceptions of employee computer technology self-efficacy. Computers in Human Behavior, 15, 161-172.

Decker, C. A. (1998). Training transfer: Perception of computer use self-efficacy among university employees. Journal of Vocational and Technical Education, 14(2)

Deng, X. 1., Doll, W. 2., & Truong, D. 3. (2004). Computer self-efficacy in an ongoing use context. Behaviour & Information Technology, 23(6), 395-412.

Downey, J. (2006). Measuring general computer self-efficacy: The surprising comparison of three instruments in predicting performance, attitudes, and usage. Proceedings of the 39th Hawaii International Conference on Systems Sciences,

Downey, J. (2006). Refining the scope in computer self-efficacy relationships: An empirical comparison of three instruments in predicting competence and attitudes.

Downey, J. P., & McMurtrey, M. (2007). Introducing task-based general computer self-efficacy: An empirical comparison of three general self-efficacy instruments. Interacting with Computers, 19, 382-396.

Ellen, P. S., Bearden, W. O., & Sharma, S. (1991). Resistance to technological innovations: An examination of the role of self-efficacy and performance satisfaction. Journal of the Academy of Marketing Science, 19(4), 297-307.

Garnes, D. M. B. (2005). Hope and self-efficacy as motivational influences in technology adoption.

Goh, D., Ogan, C., Ahuja, M., Herring, S. C., & Robinson, J. C. (2007). Being the same isn’t enough: Impact of male and female mentors on computer self-efficacy of college students in IT-related fields. Journal of Educational Computing Research, 37(1), 19-40.

Hasan, B. (2006). Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance. Information & Management, 43, 565-571.

Hasan, B. 1. (2003). The influence of specific computer experiences on computer self-efficacy beliefs. Computers in Human Behavior, 19(4), 443.

Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307-313.

Hsu, W. K., & Huang, S. S. (2006). Determinants of computer self-efficacy – an examination of learning motivations and learning environments. Journal of Educational Computing Research, 35(3), 245-265.

Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega: International Journal of Management Science, 23(6), 587-605.

Imhof, M., Vollmeyer, R. 1., & Beierlein, C. 1. (2007). Computer use and the gender gap: The issue of access, use, motivation, and performance. Computers in Human Behavior, 23(6), 2823-2837.

Jawahar, L. M., & Elango, B. (2001). The effect of attitudes, goal setting and self-efficacy on end user performance. Journal of End User Computing, 13(2), 40-45.

Johnson, R. D. (2005). An empirical investigation of sources of application-specific computer self-efficacy and mediators of the efficacy-performance relationship. International Journal of Human-Computer Studies, 62, 737-758.

Jones, D. E. (1999). Ten years later: Support staff perceptions and opinions on technology in the workplace. Library Trends, 47(4), 711-745.

Korukonda, A. R. 1. (2007). Differences that do matter: A dialectic analysis of individual characteristics and personality dimensions contributing to computer anxiety. Computers in Human Behavior, 23(4), 1921-1942.

Kupersmith, J. (1992). Technostress and the reference librarian. Reference Services Review, 20, 7-14, 50.

Lam, T., & Vincent Cho, and Hailin Qu. (2007). A study of hotel employee behavioral intentions towards adoption of information technology. International Journal of Hospitality Management, 26, 49-65.

Leach, D. J. 1., Wall, T. D. 1., & Jackson, P. R. 2. (2003). The effect of empowerment on job knowledge: An empirical test involving operators of complex technology. Journal of Occupational & Organizational Psychology, 76(1), 27.

Liaw, S. 1. (2007). Computers and the internet as a job assisted tool: Based on the three-tier use model approach. Computers in Human Behavior, 23(1), 399-414.

Lin, H. (2007). Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions. Journal of Information Science, 33(135), 135-149.

Llorens, S., Schaufeli, W., Bakker, A., & Salanova, M. (2007). Does a positive gain spiral of resourcs, efficacy beliefs and engagement exist? Computers in Human Behavior, 23, 825-841.

Marakas, G. M., Johnson, R. D., & Clay, P. F. (2007). The evolving nature of the computer self-efficacy construct: An empirical investigation of measurement construction, validity, reliability and stability over time. Journal of the Association for Information Systems, 8(1), 15-46.

Marcolin, B. L., Compeau, D. R., Munro, M. C., & Huff, S. L. (2000). Assessing user competence: Conceptualization and measurement. Information Systems Research, 11(1), 37-60.

Marquié, J. C. 1., Jourdan-Boddaert, L. 1., & Huet, N. 1. (2002). Do older adults underestimate their actual computer knowledge? Behaviour & Information Technology, 21(4), 273-280.

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Potosky, D. (2002). A field study of computer efficacy beliefs as an outcome of training: The role of computer playfulness, computer knowledge, and performance during training. Computers in Human Behavior, 18, 241-255.

Raghuram, S., Wiesenfeld, B., & Garud, R. (2003). Technology enabled work: The role of self-efficacy in determining telecommuter adjustment and structuring behavior. Journal of Vocational Behavior, 63, 180-198.

Roberts, P., & Henderson, R. (2000). Information technology acceptance in a sample of government employees: A test of the technology acceptance model. Interacting with Computers, 12, 427-443.

Rosen, L. D., & Weil, M. M. (1995). Computer availability, computer experience and technophobia among public school teachers. Computers in Human Behavior, 11(1), 9-31.

Salanova, M., Grau, R. M., Llorens, S., & Cifre, E. (2000). Computer training, frequency of usage and burnout: The moderating role of computer self-efficacy. Computers in Human Behavior, 16, 575-590.

Salanova, M. 1., & Schaufeli, W. B. 2. (2000). Exposure to information technology and its relation to burnout. Behaviour & Information Technology, 19(5), 385-392.

Schaufeli, W. B., & Salanova, M. (2007). Efficacy or inefficacy, that’s the question: Burnout and work engagement, and their relationships with efficacy beliefs. Anxiety, Stress, and Coping, 20(2), 177-196.

Sheng, Y. P., Pearson, J. M., & Crosby, L. (2003). Organizational culture and employees’ computer self-efficacy: An emperical study. Information Resources Management Journal, 16(3), 42.

Shih, H. 1. (2006). Assessing the effects of self-efficacy and competence on individual satisfaction with computer use: An IT student perspective. Computers in Human Behavior, 22(6), 1012-1026.

Sievert, M. E. (1988). Investigating computer anxiety in an academic library. Information Technology and Libraries, 7(3), 243-252.

Sinha, S. P., Talwar, T., & Rajpal, R. (2002). Correlational study of organzational commitment, self-efficacy and psychological barriers to technology change. Psychologia, 45, 176-183.

Tella, A., Tella, A., & Adekunle, P. O. (2007). An assessment of librarian social competence and information technology self-efficacy: Implications for library practice in the digital era. PNLA Quarterly, 71(4), 12-16.

Thatcher, J. B., Gundlach, M. J., McKnight, D. H., & Srite, M. (2007). Individual and human-assisted computer self-efficacy: An empirical examination., 841-858. Available at

Topper, E. F. (2007). What’s new in libraries: Stress in the library workplace. New Library World, 108(11/12), 561-564.

Torkzadeh, G., Koufteros, X., & Pfughoeft, K. (2003). Confirmatory analysis of computer self-efficacy. Structural Equation Modeling, 10(2), 263-275.

Torkzadeh, R., Pfughoeft, K., & Hall, L. (1999). Computer self-efficacy, training effectiveness and user attitudes; am empirical study. Behaviour & Information Technology, 18(4), 299-309.

Weil, M. M., Rosen, L. D., & Wugalter, S. E. (1990). The etiology of computerphobia. Computers in Human Behavior, 6, 361-379.

Whitley, Bernard W. Jr. (1997). Gender differences in computer-related attitudes and behavior: A meta-analysis. Computers in Human Behavior, 13(1), 1-22.

Wilfong, J. D. (2006). Computer anxiety and anger: The impact of computer use, computer experience, and self-efficacy beliefs. Computers in Human Behavior, 22, 1001-1011.


My Research Topic

January 25, 2008

This semester is just about 4 days old. My class this semester, ILS680-Evaluation & Research, is built around a research project. I’ve been thinking about this since the end of last semester, doing some preliminary literature searches on issues relating to technology in libraries and/or technical support issues in libraries. Since Tuesday, I’ve been immersed in literature about computer self-efficacy – a fascinating field with a great deal of literature devoted to it. Of course, there isn’t much in the way of evaluating levels of perceived computer self-efficacy among library staff. I have to thank my professor for mentioning self-efficacy which was the missing piece to my jumbled research ideas.

So, my research question, which I’m sure will undergo future revisions, should be something along the lines of “Do different models of technical support in academic libraries impact computer self-efficacy levels of library staff?” Some of the questions that I’m hoping to be able to get answers to: Do different models of technical support affect computer self-efficacy? Do combined IT/library departments engender greater computer self-efficacy? Less? I also want to compare computer self-efficacy across demographic groups. Is there a difference depending upon educational attainment? Age? etc.

I’m pretty excited about my topic – which is good considering how much time I will be spending with it over the next several months. Computer self-efficacy is a key issue – once which I think must have a huge impact on library staff’s ability to make the most of technology in the workplace. I am definitely looking forward to getting started. Of course, in the near future, I need to refine my research question, do a literature review, and fill out an IRB (Institutional Research Board) application. There is lots and lots of work to be done, but I think this might just be the best ending to my graduate school experience.

How’s that for some positive thinking?