Technological self-efficacy (TSE) is “ the belief in one ’ s ability to successfully perform a technologically sophisticated new task ” .McDonald, T., & Siegall, M. (1992). The effects of technological self-efficacy and job focus on job performance, attitudes, and withdrawal behaviors. The Journal of Psychology, 126, 465-475. This is a specific application of the broader and more general construct of self-efficacy, which is defined as the belief in one ’ s ability to engage in specific actions that result in desired outcomes.Bandura, A. (1997). Self efficacy: The exercise of control. New York: Freeman. Self efficacy does not focus on the skills one has, but rather the judgments of what one can do with his or her skills. Traditionally, a distinguishing feature of self efficacy is its domain-specificity. In other words, judgments are limited to certain types of performances as compared to an overall evaluation of his or her potential. Importance Today’s modern society is completely embedded within a technological context, which makes the understanding and evaluation of technological self efficacy critical. Indeed, nearly half of Americans own smartphones and this trend towards technology use is not limited to the United States; instead cell phone, computer, and internet use is becoming increasingly common around the world. Technology is particularly prevalent in the workplace and learning environments. At work, 62\% of employed Americans use the internet and email, but interestingly workplace internet users either use the internet everyday (60\%) or not at all (28\%).Madden, M., & Jones, S. (2008, September 24). Networked workers. (PDF) Internet and email use is obviously influenced by work duties, but 96\% of employed Americans use some sort of new communication technology on the job. Successful investment in technology is associated with enhanced productivity; however, full realization of technological potential commonly plagues organizations.Johansen, R., Swigart, R. (1996). Upsizing the Individual in the Downsized Organization: Managing in the Wake of Reengineering, Globalization and Overwhelming Technological Change. Addison-Wesley, Reading, MA. In learning environments, college courses are more frequently being offered online. This is commonly referred to as distance education and implementation ranges from courses being supported by the web (teaching occurs predominantly through face-to-face instructor interactions with supplemental materials being offered on the web) to blended learning (significantly less face-to-face instructor interactions and more online instruction) to fully online (all instruction is conducted virtually with no face-to-face instructor interactions). A number of advantages are associated with distance learning such as increased flexibility and convenience, which allows individuals the opportunity to enroll in classes that would otherwise be off-limits due to geographical or personal reasons.Phipps, R., & Merisotis, J. (1999). What ’ s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington, DC: Institute for Higher Education Policy. Another commonly cited advantage is that instruction is self paced, which allows for personalized tailoring based on individual needs.Vrasidas, C., & McIsaac, M. S. (2000). Principles of pedagogy and evaluation for web-based learning. Educational Media International, 37, 105-112. However, these advantages are not likely to be realized if the individual is anxious about the method of instructional delivery and/or his or her expectation of success is low due to its technological component. Taken together, these two critical arenas discussed above (workplace and learning) reinforce the extent to which technology has impacted modern activities and consequently the importance of perceived beliefs in one ’ s ability to master new technology. Success in everyday life often hinges on the utilization of technology and by definition, new technology will always be new. Therefore, this construct warrants review. Differentiation from Other Forms of Self-efficacy Since TSE stems from the same theory as general self-efficacy and other task-specific self-efficacy, the differentiation of this construct from these other forms of self-efficacy is crucial. Unfortunately, previous studies focusing in on TSE have not shown the uniqueness of TSE measures. Despite the dearth of differentiating research on TSE, the uniqueness of this construct can be shown by considering closely related and technology specific self-efficacies (i.e. computer self-efficacy), which has been established as a unique construct. When compared to general self-efficacy, computer self-efficacy has been shown to be unique based on two measures of general self-efficacy.Chen, G., Gully, S. M., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4, 62-83. In this same study, the authors showed computer self-efficacy was not related to many types of specific self-efficacy including art, persuasion, and science self-efficacy. One of the most related types of specific self-efficacy was mechanical. This makes sense given both types of specific self-efficacies are related to using tools albeit one being technology the other being more physical in nature. Computer self-efficacy has a domain has also been shown to be related, but distinct, to self-efficacy about computer programs.Agarwal, R., Sambamurthey, V., & Stair, R. M. (2000). Research Report: The evolving relationship between general and specific computer self-efficacy-An empirical assessment. Information Systems Research, 4, 418-430 Measurement Following the definition set forth by Bandura, self-efficacy is an individual ’ s belief and confidence in him or herself. This property has important implications for the measurement of any type of self-efficacy. Specifically, measures of self-efficacy must be self-report because the only person who can accurately portray beliefs in one ’ s ability is the target of investigation. In other words, self-report measures of self-efficacy have definitional truth. While a number of problems exist with self-report inventories, in the case of self-efficacy (and other constructs that are defined as internal beliefs and cognitions) this measurement approach is unavoidable. Another difference between TSE measures concerns the issue of generality. This consideration is similar to the previous differentiation between-TSE as a broader concept and technology specific self-efficacy. Measurement attempts of the broader concept of technological self-efficacy will be considered first. McDonald and Siegall developed a five-item likert scale of technological self-efficacy based on the consideration of previous theoretical studies. This scale was scored using the strength approach to self-efficacy scales. Items in this scale were not referring to specific technologies, but instead focused on technology as a general concept. Using a development process, Holcomb, King and Brown, also proposed a scale to measure TSE Holcomb, L. B., King, F. B., & Brown, S. W. (2004). Student traits and attributes contributing to the success in online courses: Evaluation of university online courses. The Journal of Interactive Online Learning, 2, 1-17. Factor analysis revealed three distinct factors containing 19 likert type items, which also was scored according to the strength scoring system. In contrast to the McDonald and Siegall scale, the items in this scale referenced certain technologies (specifically computers and software packages). The two studies mentioned above represent of attempts to measure TSE as a broader concept. In addition to the attempts to measure TSE more broadly, a number of studies have developed measures of technology specific self-efficacy. One of the most cited measures of computer self-efficacy comes from Compeau and Higgins. These authors reviewed previous attempts to measure computer self-efficacy and theoretically derived a 10 item scale. Unlike previously mentioned scales, this study employed a “composite” scoring approach. For each item, participants were first asked whether they could complete a specific task related to computers using a dichotomous yes/no scale. Following this answer, participants were then asked to rate their confidence about completing the task from 1 ( ‘’ not at all confident ’’ ) to 10 ( ‘’totally confident’’ ). The final score was calculated by counting the number of “yes” answers (reflecting self-efficacy magnitude) and the average of the confidence ratings (representing self-efficacy strength). The authors then validated this measure in a nomological network of related constructs. A second example of technology specific self-efficacy is internet self-efficacy. Similar to previous measurement approaches, internet self-efficacy was developed using a theoretical approach that considered previous measures of related topics and developed novel items to address the missing construct space. This scale showed a high level of reliability and validity. Prior experience Prior experience with technology is repeatedly found to be influential on technology related self efficacy beliefs.Compeau, D. R., Higgins, C. A. (1995b). Application of social cognitive theory to training for computer skills. Information Systems Research, 6, 118-143.Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case for computers. Journal of Applied Psychology, 72, 307–313.Jorde-Bloom, P., & Ford, M. (1988). Factors influencing early childhood administrators ’ decisions regarding the adoption of computer technology. Journal Educational Computing, 4, 31–47.Murphy, C. A., Coover, D., & Owen, S. V. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49, 893–899. If an individual has had the opportunity to interact with new technologies and, more importantly, has had success with mastering new technologies then individuals are more likely to hold more positive beliefs for future performance. Modeling or participation in technological training Modeling or participation in technological training are also found to be significant predictors of technological self efficacy.Brinkerhoff, J. (2006). Effects of long-duration, professional development academy on technology skills, computer self efficacy, and technology integration beliefs and practices. '' Journal of Research on Technology in Education, 39, ’’ 22-43.Gist. M. E., Schwoerer, C. E., & Rosen, B. (1989). Effects of alternative training methods on self-efficacy and performance in computer software training. Journal of Applied Psychology, 74, 884-891.Torkzadeh, G. & Van Dyke, T. P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers and Human Behavior, 18, 479-494.Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement, 54, 813–821. Although different types of training interventions have been associated with different gains;Smith, J. M. (1994). The effects of education on computer self-efficacy. Journal of Industrial Teacher Education, 31, 51–65. in general, research supports that seeing other individuals successfully perform the task at hand (for example, the instructor) and then providing the learner with some opportunity for reinforcement and demonstration (for example, trying to successfully utilize the technology without aid) increases technology related self efficacy beliefs. Social persuasions Social persuasions such as encouragement by others and organizational supportHenry, J. W., & Stone, R. W. (1994). A structural equation model of end-user satisfaction with a computer-based medical information system. Information Resources Management Journal, 7(3), 21–33.Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. are also important contributors to technology related self efficacy beliefs. The actions and statements of others can significantly alter perceptions of their likelihood for success. Organizational support typically includes management ’ s encouragement and assistance. If management does not appear to enthusiastically support employees ’ attempts to utilize technology then employees are unlikely to accept technology. Age Age is also significantly related, such that younger individuals tend to have higher levels of technology related self efficacy beliefs than older individuals.Reed, K. Doty, & May, (2005). The impact of aging on self-efficacy and computer skill acquisition. Journal of Managerial Issues, 17, 212-228.Suls, J. & Mullen, C. (1982). From the cradle to the grave: Comparison and self-evaluation across the life-span. In J. Suls (Ed.), Psychological Perspectives on the Self, Vol. 1, Erlbaum, Hillsdale, NJ, 97–125. This finding is not surprising given the widespread stereotype of older adults' inability to learn new material, especially when the material is technology related.Posthuma, R. A. & Campion, M. A. (2009). Age stereotypes in the workplace: Common stereotypes, moderators, and future research directions. Journal of Management, 35,158-188. However, older adults ’ low technological self efficacy beliefs suggest that older adults may internalize the ‘ old dogs can ’ t learn new tricks ’ stereotype, which consequently affects expectations about future performance in technology related domains. Task Performance Task performance is negatively affected, such that lower technology related self efficacy beliefs are related to poorer performance This is extremely important, because these findings suggest that positive perceptions of individuals ’ technological capabilities may need to be present before successful performance can be achieved. Anxiety Anxiety is negatively related, such that lower technology related self efficacy beliefs are associated with higher level of anxiety.Russell, G., & Bradley, G. (1997). Teachers' computer anxiety: Implications for professional development. Education and Information Technologies, 2, 1-14.
Technological self-efficacy (TSE) is " the belief in one ' s ability to successfully perform a technologically sophisticated new task " .McDonald, T., & Siegall, M. (1992). The effects of technological self-efficacy and job focus on job performance, attitudes, and withdrawal behaviors. The Journal of Psychology, 126, 465-475. This is a specific application of the broader and more general construct of self-efficacy, which is defined as the belief in one ' s ability to engage in specific actions that result in desired outcomes.Bandura, A. (1997). Self efficacy: The exercise of control. New York: Freeman. Self efficacy does not focus on the skills one has, but rather the judgments of what one can do with his or her skills. Traditionally, a distinguishing feature of self efficacy is its domain-specificity. In other words, judgments are limited to certain types of performances as compared to an overall evaluation of his or her potential. Importance 21st-century society is completely embedded within a technological context, which makes the understanding and evaluation of technological self efficacy critical. Indeed, nearly half of Americans own smartphones and this trend towards technology use is not limited to the United States; instead cell phone, computer, and internet use is becoming increasingly common around the world. Technology is particularly prevalent in the workplace and learning environments. At work, 62\% of employed Americans use the internet and email, but interestingly workplace internet users either use the internet everyday (60\%) or not at all (28\%).Madden, M., & Jones, S. (2008, September 24). Networked workers. (PDF) Internet and email use is obviously influenced by work duties, but 96\% of employed Americans use some sort of new communication technology on the job. Successful investment in technology is associated with enhanced productivity; however, full realization of technological potential commonly plagues organizations.Johansen, R., Swigart, R. (1996). Upsizing the Individual in the Downsized Organization: Managing in the Wake of Reengineering, Globalization and Overwhelming Technological Change. Addison-Wesley, Reading, MA. In learning environments, college courses are more frequently being offered online. This is commonly referred to as distance education and implementation ranges from courses being supported by the web (teaching occurs predominantly through face-to-face instructor interactions with supplemental materials being offered on the web) to blended learning (significantly less face-to-face instructor interactions and more online instruction) to fully online (all instruction is conducted virtually with no face-to-face instructor interactions). A number of advantages are associated with distance learning such as increased flexibility and convenience, which allows individuals the opportunity to enroll in classes that would otherwise be off-limits due to geographical or personal reasons.Phipps, R., & Merisotis, J. (1999). What ' s the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington, DC: Institute for Higher Education Policy. Another commonly cited advantage is that instruction is self paced, which allows for personalized tailoring based on individual needs.Vrasidas, C., & McIsaac, M. S. (2000). Principles of pedagogy and evaluation for web-based learning. Educational Media International, 37, 105-112. However, these advantages are not likely to be realized if the individual is anxious about the method of instructional delivery and/or his or her expectation of success is low due to its technological component. Taken together, these two critical arenas discussed above (workplace and learning) reinforce the extent to which technology has impacted modern activities and consequently the importance of perceived beliefs in one ' s ability to master new technology. Success in everyday life often hinges on the utilization of technology and by definition, new technology will always be new. Therefore, this construct warrants review. Differentiation from other forms of self-efficacy Since TSE stems from the same theory as general self-efficacy and other task-specific self-efficacy, the differentiation of this construct from these other forms of self-efficacy is crucial. Unfortunately, previous studies focusing in on TSE have not shown the uniqueness of TSE measures. Despite the dearth of differentiating research on TSE, the uniqueness of this construct can be shown by considering closely related and technology specific self-efficacies (i.e. computer self-efficacy), which has been established as a unique construct. When compared to general self-efficacy, computer self-efficacy has been shown to be unique based on two measures of general self-efficacy.Chen, G., Gully, S. M., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4, 62-83. In this same study, the authors showed computer self-efficacy was not related to many types of specific self-efficacy including art, persuasion, and science self-efficacy. One of the most related types of specific self-efficacy was mechanical. This makes sense given both types of specific self-efficacies are related to using tools albeit one being technology the other being more physical in nature. Computer self-efficacy has a domain has also been shown to be related, but distinct, to self-efficacy about computer programs.Agarwal, R., Sambamurthey, V., & Stair, R. M. (2000). Research Report: The evolving relationship between general and specific computer self-efficacy-An empirical assessment. Information Systems Research, 4, 418-430 Measurement Following the definition set forth by Bandura, self-efficacy is an individual ' s belief and confidence in him or herself. This property has important implications for the measurement of any type of self-efficacy. Specifically, measures of self-efficacy must be self-report because the only person who can accurately portray beliefs in one ' s ability is the target of investigation. In other words, self-report measures of self-efficacy have definitional truth. While a number of problems exist with self-report inventories, in the case of self-efficacy (and other constructs that are defined as internal beliefs and cognitions) this measurement approach is unavoidable. Another difference between TSE measures concerns the issue of generality. This consideration is similar to the previous differentiation between-TSE as a broader concept and technology specific self-efficacy. Measurement attempts of the broader concept of technological self-efficacy will be considered first. McDonald and Siegall developed a five-item likert scale of technological self-efficacy based on the consideration of previous theoretical studies. This scale was scored using the strength approach to self-efficacy scales. Items in this scale were not referring to specific technologies, but instead focused on technology as a general concept. Using a development process, Holcomb, King and Brown, also proposed a scale to measure TSE Holcomb, L. B., King, F. B., & Brown, S. W. (2004). Student traits and attributes contributing to the success in online courses: Evaluation of university online courses. The Journal of Interactive Online Learning, 2, 1-17. Factor analysis revealed three distinct factors containing 19 likert-type items, which also was scored according to the strength scoring system. In contrast to the McDonald and Siegall scale, the items in this scale referenced certain technologies (specifically computers and software packages). The two studies mentioned above represent of attempts to measure TSE as a broader concept. In addition to the attempts to measure TSE more broadly, a number of studies have developed measures of technology specific self-efficacy. One of the most cited measures of computer self-efficacy comes from Compeau and Higgins. These authors reviewed previous attempts to measure computer self-efficacy and theoretically derived a 10-item scale. Unlike previously mentioned scales, this study employed a "composite" scoring approach. For each item, participants were first asked whether they could complete a specific task related to computers using a dichotomous yes/no scale. Following this answer, participants were then asked to rate their confidence about completing the task from 1 ( not at all confident ) to 10 ( totally confident ). The final score was calculated by counting the number of "yes" answers (reflecting self-efficacy magnitude) and the average of the confidence ratings (representing self-efficacy strength). The authors then validated this measure in a nomological network of related constructs. A second example of technology specific self-efficacy is internet self-efficacy. Similar to previous measurement approaches, internet self-efficacy was developed using a theoretical approach that considered previous measures of related topics and developed novel items to address the missing construct space. This scale showed a high level of reliability and validity. Prior experience Prior experience with technology is repeatedly found to be influential on technology related self efficacy beliefs.Compeau, D. R., Higgins, C. A. (1995b). Application of social cognitive theory to training for computer skills. Information Systems Research, 6, 118-143.Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case for computers. Journal of Applied Psychology, 72, 307–313.Jorde-Bloom, P., & Ford, M. (1988). Factors influencing early childhood administrators ' decisions regarding the adoption of computer technology. Journal Educational Computing, 4, 31–47.Murphy, C. A., Coover, D., & Owen, S. V. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49, 893–899. If an individual has had the opportunity to interact with new technologies and, more importantly, has had success with mastering new technologies then individuals are more likely to hold more positive beliefs for future performance. Modeling or participation in technological training Modeling or participation in technological training are also found to be significant predictors of technological self efficacy.Brinkerhoff, J. (2006). Effects of long-duration, professional development academy on technology skills, computer self efficacy, and technology integration beliefs and practices. Journal of Research on Technology in Education, 39, 22-43.Gist. M. E., Schwoerer, C. E., & Rosen, B. (1989). Effects of alternative training methods on self-efficacy and performance in computer software training. Journal of Applied Psychology, 74, 884-891.Torkzadeh, G. & Van Dyke, T. P. (2002). Effects of training on Internet self-efficacy and computer user attitudes. Computers and Human Behavior, 18, 479-494.Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement, 54, 813–821. Although different types of training interventions have been associated with different gains;Smith, J. M. (1994). The effects of education on computer self-efficacy. Journal of Industrial Teacher Education, 31, 51–65. in general, research supports that seeing other individuals successfully perform the task at hand (for example, the instructor) and then providing the learner with some opportunity for reinforcement and demonstration (for example, trying to successfully utilize the technology without aid) increases technology related self efficacy beliefs. Social persuasions Social persuasions such as encouragement by others and organizational supportHenry, J. W., & Stone, R. W. (1994). A structural equation model of end-user satisfaction with a computer-based medical information system. Information Resources Management Journal, 7(3), 21–33.Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587-605. are also important contributors to technology related self efficacy beliefs. The actions and statements of others can significantly alter perceptions of their likelihood for success. Organizational support typically includes management ' s encouragement and assistance. If management does not appear to enthusiastically support employees ' attempts to utilize technology then employees are unlikely to accept technology. Age Age is also significantly related, such that younger individuals tend to have higher levels of technology related self efficacy beliefs than older individuals.Reed, K. Doty, & May, (2005). The impact of aging on self-efficacy and computer skill acquisition. Journal of Managerial Issues, 17, 212-228.Suls, J. & Mullen, C. (1982). From the cradle to the grave: Comparison and self-evaluation across the life-span. In J. Suls (Ed.), Psychological Perspectives on the Self, Vol. 1, Erlbaum, Hillsdale, NJ, 97–125. This finding is not surprising given the widespread stereotype of older adults' inability to learn new material, especially when the material is technology related.Posthuma, R. A. & Campion, M. A. (2009). Age stereotypes in the workplace: Common stereotypes, moderators, and future research directions. Journal of Management, 35,158-188. However, older adults ' low technological self efficacy beliefs suggest that older adults may internalize the ' old dogs can ' t learn new tricks ' stereotype, which consequently affects expectations about future performance in technology related domains. Task performance Task performance is negatively affected, such that lower technology related self efficacy beliefs are related to poorer performance This is extremely important, because these findings suggest that positive perceptions of individuals ' technological capabilities may need to be present before successful performance can be achieved. Anxiety Anxiety is negatively related, such that lower technology related self-efficacy beliefs are associated with higher level of anxiety.Russell, G., & Bradley, G. (1997). Teachers' computer anxiety: Implications for professional development. Education and Information Technologies, 2, 1-14.
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