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.
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.
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).
|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|
|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
|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
Computer Self-Efficacy Levels by Educational Attainment
|High School Degree||156||16.44||174||126||7||4.19|
Computer Self-Efficacy Level by MLS or Equivalent
|MLS or Equivalent||Mean||S.D.||High||Low||Total #||%|
|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 #||%|
Computer Self-Efficacy Levels by Job Classification
|Job Classification||Mean||S.D.||High||Low||Total #||%|
Computer Self-Efficacy Levels by Job Satisfaction
|Job Satisfaction||Mean||S.D.||High||Low||Total #||%|
|Neither Satisf. Nor Unsatisf.||137.33||19.86||171||106||9||5.38|
Computer Self-Efficacy Levels by Computer Experience
|Computer Experience||Mean||S.D.||High||Low||Total #||%|
Computer Self-Efficacy Levels by Computer Training
|Computer Training||Mean||S.D.||High||Low||Total #||%|
My preliminary bibliography for my ILS680 special project:
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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.
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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.
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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.
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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 http://www.aifb.uni-karlsruhe.de/Forschungsgruppen/BIK/wi2007/papers/wi-2007-1-051.pdf.
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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?