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Conceptions of Self and the Use of Digital Technologies in a Learning Environment

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Title: Conceptions of Self and the Use of Digital Technologies in a Learning Environment
Language: English
Authors: Benson, D. E., Mekolichick, Jeanne
Source: Education. Sum 2007 127(4):498-510.
Availability: Project Innovation, Inc. P.O. Box 8508 Spring Hill Station, Mobile, AL 36689-0508. Tel: 251-343-1878; Fax: 251-343-1878; Web site: http://www.projectinnovation.biz/education.html
Peer Reviewed: Y
Physical Description: PDF
Page Count: 13
Publication Date: 2007
Document Type: Journal Articles
Reports - Evaluative
Education Level: Higher Education
Descriptors: Undergraduate Students, Educational Technology, Educational Environment, Hypothesis Testing, Technology Uses in Education, Technology Integration, Use Studies, Self Concept, Self Efficacy, Psychological Patterns, Questionnaires, Sociology, Student Attitudes, Self Concept Measures, Likert Scales
ISSN: 0013-1172
Abstract: While research has identified various personality and demographic characteristics that appear to be associated with a variety of activities related to the use of digital technologies (e.g., Biner, Dean & Mellinger, 1994; Biner, Summers, Dean, Bink, Anderson & Gelder, 1996; Black, 1992; Clark, 1993; Figueroa, 1992), little is known about how conceptions of self might influence the use of digital technologies in a learning environment. (Benson, Haney, Ore, Persell, Schulte, Steele & Winfield, 2001). This paper is the first empirical attempt to understand this relationship. Using a sample of undergraduate students (N = 447) and faculty (N= 203) from two public universities in the United States, we examine how students' and faculty's conceptions of self affect the desire to use and success in using digital technologies in a university environment. Using Identity theory (e.g., Burke & Reitzes, 1991; Stryker, 1980), to test 4 hypotheses, regression analyses indicate that conceptions of self are correlated with the desire to use and the success in using digital technologies. These findings may help to inform policies concerning the use of digital technologies in learning environments as well as suggest new hypotheses for further exploration of this relationship. (Contains 6 tables.)
Abstractor: Author
Number of References: 32
Entry Date: 2008
Access URL: https://www.projectinnovation.biz/education.html
Accession Number: EJ790130
Database: ERIC
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  Value: <anid>AN0025607625;edu01jun.07;2007Jul13.10:29;v2.2.460</anid> <title id="AN0025607625-1">CONCEPTIONS OF SELF AND THE USE OF DIGITAL TECHNOLOGIES IN A LEARNING ENVIRONMENT </title> <p>While research has identified various personality and demographic characteristics that appear to be associated with a variety of activities related to the use of digital technologies (e.g., Biner, Dean & Mellinger, 1994; Biner, Summers, Dean, Bink, Anderson & Gelder, 1996; Black, 1992; Clark, 1993; Figueroa, 1992), little is known about how conceptions of self might influence the use of digital technologies in a learning environment. (Benson, Haney, Ore, Persell, Schulte, Steele & Winfield, 2001). This paper is the first empirical attempt to understand this relationship. Using a sample of undergraduate students (N = 447) and faculty (N= 203) from two public universities in the United States, we examine how students' and faculty's conceptions of self affect the desire to use and success in using digital technologies in a university environment. Using Identity theory (e.g., Burke & Reitzes, 1991; Stryker, 1980), to test 4 hypotheses, regression analyses indicate that conceptions of self are correlated with the desire to use and the success in using digital technologies. These findings may help to inform policies concerning the use of digital technologies in learning environments as well as suggest new hypotheses for further exploration of this relationship.</p> <p>The use of digital technology devices in American higher education is so extensive as to be almost ubiquitous (Green 2000). Virtually all faculty members and students in such settings use these tools in both varied and extensive ways. From highly interactive, web based pedagogical activities to "instant messaging," the use of such capabilities is now "second nature" to most faculty members and students.</p> <p>Within these larger patterns, however, often camouflaged micro and meso patterns exist that are significant for the way in which humans interact with and use these devices. Many of these patterns are important in helping to understand how best to utilize these capabilities for maximal educational impact for the largest number of users. For example, a number of studies have found that both faculty members and students vary widely in their desire and ability to use such tools (Blum, 1999; Brent, 1999; Clark, 1993; Daugherty & Funke, 1998).</p> <p>A number of studies have examined some of the psychological correlates of digital technology use including the use of the WWW in teaching and learning. (e.g., Biner, Bink, Huffman, & Dean, 1995; Biner, Dean & Mellinger, 1994; Biner, Summers, Dean, Bink, Anderson & Gelder, 1996; Black, 1992; Clark, 1993; Figueroa, 1992). These studies have contributed much to our understanding of the many dimensions of the "person-technology" nexus.</p> <p>What has not been examined are the many facets of the relationship between how people view themselves (their self concepts) and their desire to use, support for, and comfort with digital technologies (Benson et. al., 2003). As Jaffee (1998) notes, core identities are often invoked and defended in teacher-student interactions and the use of digital technologies may disrupt, threaten or enhance those identities. This is a particularly interesting and important question to pursue in view of the extensive use of digital technologies in colleges and universities. For example, for students, this association may influence the extent to which such use is related to performance on academic tests, papers and projects. For faculty, this relationship may help to explain who is more likely to adopt appropriate digital technological capabilities in their teaching which, in turn, may indirectly influence such factors as student evaluation scores and their professorial "reputation."</p> <p>Equally significant is the examination of these patterns for both faculty members and students because, given the highly interactive nature of education, the patterns extant in one group will have substantial consequences for the other. While many studies have examined selected personality characteristics of students (e.g., Biner et. al., 1994; Biner et. a1.,1995; Gibson, 1996) and others have focused on faculty members (e.g., Clark, 1993), very little attention has been paid to the examination of both groups within the same study. A notable exception to this observation is the work of Daugherty and Funke (1998) who examined perceptions of web-based instruction with a sample of 55 students and 76 faculty members. Unlike the present work, their research did not focus on the testing of hypotheses and it was limited to the topic of web-based instruction. Finally, many extant studies use small samples (e.g., Gibson, 1996) and/or focus on a specific aspect of the use of digital technology such as web-based instruction (see above).</p> <p>The present effort, 1) uses a large, representative sample of both undergraduate students and faculty members from two large state universities, 2) uses the same questionnaire (modified for group-specific wording) with the same hypotheses applied to both groups and is, 3) anchored in symbolic interaction theory (Mead, 1938; Stryker, 1980) one of the major micro level theories in sociology. With this theoretical anchoring and the use of a good, representative sample, the study provides a measure of confidence that the findings can be interpreted in the context of larger questions about how students and faculty use and manipulate their symbolic environment relative to digital technology and may be applicable to a wide range of institutions. To the extent there are differences between the two groups, this methodology will help to uncover the extent to which there is conflict and discomfort between students and faculty over the use of digital technologies in a learning environment with attendant consequences and implications.</p> <p>This study, therefore, will investigate the relationship between aspects of self conception and the degree of comfort with the use of digital technology in a large sample of students and faculty members using a widely known theory in sociology.</p> <cn>SYMBOLIC INTERACTION THEORY</cn> <p>Symbolic interaction theory provides the theoretical foundations for the present investigation of the relationship between a persons view of self as it interfaces with digital technology use. Symbolic Interactionism is one of the main theoretical traditions in the discipline of sociology. Based on the writings of G. H. Mead (1934), C. H. Cooley, (1902), and, more contemporaneously, in the work of H. Blumer (1969), P. Burke (1980, 1991), E. Goffman (1959, 1961, 1963), G. J. McCall (1978), and S. Stryker (1980), it specifically focuses on the extent to and the manner in which the individual is connected to the social structure through the use of symbols--especially spoken languages. As people become proficient in the use of languages they assemble a collection of those symbols which they regard as representative of "who they are;" in other words, their sense of "self." As Carrothers and Benson (2003) note: "Humans are both actors and reactors; shaped and shapers; definers of social reality and, in turn, defined by that reality. Thus, the human sense of "self" is product and process, as the self is both shaped by the larger society and, at the same time, helping to shape that same entity…" (p. 163).</p> <p>Within the tradition of symbolic interactionism, a group of contemporary sociological social psychologists (e.g., Benson & Trew, 1995; Burke & Reitzes, 1981; Burke, 1991; Callero, 1985; McCall & Simmons, 1978; Stryker, 1980, 2000) pay special attention to how humans are linked to roles and groups, and, by extension, the larger society. The tighter this linkage, the more likely one's view of self will be influenced by definitions and meanings attached to those roles and groups. The collections of meanings that are more closely bound to important roles that people play form the basis of an important identity for that person. The more important or salient an identity, the more likely a person is to behave and define reality in ways that are consonant with that identity. This "variation" of symbolic interaction theory is termed "identity theory."</p> <p>Closely connecting roles and self, identity theory argues that how we perceive our role identities influences our behavior. If the role identity of "mother" is very important (salient) for a person then identity theory would predict that this person will try to enact that identity as much as possible; will feel very comfortable enacting that role identity; will try to avoid situations where people may denigrate that role identity; and will welcome new characteristics and skills that are perceived to be consistent with that identity.</p> <p>Using a symbolic interactionist orientation, this study will examine the extent to which students and faculty members have incorporated the use of digital technology into the identities of "student" and "faculty member" together with some of the consequences of these outcomes.</p> <cn>HYPOTHESES</cn> <p>Based on the above discussion:</p> <olist> <item> The more the use of digital technologies is compatible with a role identity, the higher the use of such technologies.</item> <item> The more the use of digital technologies is compatible with a role identity, the higher the degree of computer self-efficacy.</item> <item> The more the use of digital technologies is compatible with a role identity, the more comfortable the person is using these technologies.</item> <item> The more the use of digital technologies is compatible with a role identity, the greater the desire to use these technologies.</item> <cn>METHODS</cn> </olist> <p>SAMPLE</p> <p>A non-probability sample of undergraduate students taking sociology classes at two public universities in the United States and the full-time faculty at both of these universities participated in this study. Questionnaires were distributed to students at the beginning of class and collected after they were completed. Four hundred seventy five students chose to participate in the study. Eight students reported that they did not use a personal computer and were therefore eliminated from the sample. Another 20 students were eliminated from the sample because of their age (the consent statement indicated the study was for students 18 years of age or older). Thus, the total usable student sample is 447. For the faculty, questionnaires were distributed to faculty mailboxes with an on-campus return address. Two hundred and three (<reflink idref="bib203" id="ref1">203</reflink>) instruments were returned from both institutions, bringing the combined sample of students and faculty members to a total of 650.</p> <p>MEASURES</p> <p>The data gathered for this research used an instrument devised by the authors and was drawn from the work of Burke and Reitzes (1991) and Cassidy and Eachus (2001) using standardized scales to measure some of the concepts employed. In the questionnaire, the respondents were prompted to think about themselves as students or faculty members engaged in academic work, and then asked to complete a number of questions.</p> <p>Integration of digital technology with the self was measured using a 4-item Likert scale created by the authors. Respondents were presented with 4 statements: 1) Digital technologies and I just don't get along; 2) Using digital technologies is important to the way I see myself as a student/faculty member; 3) I often feel that using digital technologies is not really "me;" 4) Using digital technologies does not make me feel uncomfortable. Possible response categories for each item ranged from strongly disagree to strongly agree, coded 1 to 5. The first and third items were reverse coded. High numbers indicate a high degree of digital technology integration with the self. The mean for this scale is 14.74, standard deviation 3.31, on a scale ranging from 4 to 20. Alpha reliability for this scale = .70. With an N=650, the sample easily exceeds minimum standards for performing exploratory factor analysis (a sample size of at least five times the number of variables, Bryant & Yarnold 1995). A factor analysis of the scale produced only one factor with respectable to good factor loadings on the items.</p> <p>Use of digital technology.</p> <p>Respondents were presented with a list of 8 digital technologies (such as word processing capabilities, e-mail, chat room participation, etc.). Responses were coded as either "use" or "don't use." High numbers indicate higher usage of digital technologies. Results indicate modal categories for: "use a computer," "use e-mail," and "use internet." On a scale ranging from 0 to 8, the mean is 4.58 with a standard deviation of 1.47.</p> <p>Level of comfort in using digital technologies. Respondents were presented with the same list of 8 digital technologies as above, and were asked to indicate their comfort level using each technology on a Likert scale ranging from "I have to put up with it" (<reflink idref="bib1" id="ref2">1</reflink>), to "I really enjoy it" (<reflink idref="bib5" id="ref3">5</reflink>). A response category of "do not use" was also provided, coded 0. As such, a high score indicates a high degree of comfort in using these technologies. Mirroring the above results, mean levels of comfort in using digital technologies are relatively high for "use a computer" x = 4.17 "use e-mail" x = 4.06 and "use the internet" x = 4.19. All the other digital technologies had means of 1.70 and below. For all technologies, the standard deviation is relatively small; all are 1.87 or smaller. Alpha reliability score for this scale = .73.</p> <p>Cognitive Commitment to Academic Identity was measured using an adapted version of the Burke and Reitzes (1991) scale. The scale consists of 5 Likert scaled items with high scores indicating high cognitive commitment to the identity. The mean for this scale is 16.83 with a standard deviation of 4.06 on a scale ranging from 5 to 25. Alpha reliability for this scale = .77. A factor analysis of the scale produced only one factor with respectable to good factor loadings on the items.</p> <p>Desire to use digital technologies was measured by a 3-item scale constructed by the authors with 5 Likert scaled response possibilities where higher scores indicate greater desire to use. The questions are: "I try to use digital technologies as little as possible" (reverse coded); "Being in the forefront in the use of digital technologies is important to me;" and "I want to use digital technologies in my academic work." On a scale ranging from 3 to 15, the mean for this sample is 10.74 with a standard deviation of 2.84. The alpha reliability for this scale = .76. A factor analysis produced one factor with good factor loadings.</p> <p>Computer self-efficacy was measured by 6 items adapted from Cassidy and Eachus Computer Self-Efficacy Scale (2001). The Likert scaled items range from "strongly agree" to "strongly disagree" with high scores indicating high computer self-efficacy. On a scale ranging from 5 to 25, the mean for this sample is 18.57 with a standard deviation of 4.47. The alpha reliability score for this scale = .85. A factor analysis produced one factor with good factor loadings.</p> <cn>RESULTS</cn> <p>SAMPLE CHARACTERISTICS</p> <p>The total number of respondents for this sample is 650. Students (n = 447) in this sample are overwhelmingly white (88%) women (72%) in their 20s (x = 20, s.d. = 3.6). Sixty seven percent of the sample are underclassmen (45 % freshman and 22% sophomores), with 15% of the sample reporting junior status and 17% reporting senior status.</p> <p>The faculty (n = 203) in this sample are also largely white (95%), with a mean age of 48 1/2 years (s.d. = 9.8). The sex division is roughly equal (50.2% female, 49.8% male). The total number of years teaching ranges from 0-43 with a mean of 17 and a standard deviation of 10.9 years.</p> <p>TESTS OF HYPOTHESES</p> <p>Both zero-order correlations and multiple regression analyses were conducted to test all 4 hypotheses. Table 1 presents the results of the zero-order correlations. As can be seen in Table 1, the data indicate many significant relationships and preliminary support for all 4 hypotheses. Level of integration of digital technologies is positively and significantly correlated with one's level of use, computer self-efficacy, comfort level in using digital technologies and desire to use digital technologies. In addition, following identity theory, one's cognitive commitment to the academic role identity is also positively and significantly correlated with all study variables.</p> <p>To test the hypotheses more stringently, multiple regression analyses were conducted for each hypothesis taking into account sex, age, and cognitive commitment to the academic identity. As indicated in Table 2, the data support hypothesis 1 suggesting that as the use of digital technologies is more integrated into the academic role identity, respondents reported higher levels of use of those digital technologies. Table 3 reports the results of hypothesis 2. Again, the data support the hypothesis. As integration of digital technologies with the academic identity increases, one's sense of computer self-efficacy also increases. Reported in Table 4 are the results of hypothesis 3. Again, the data are supportive of identity theory indicating the more the use of digital technologies is compatible with the academic identity, the more comfortable respondents are with using these technologies. Finally, the results reported in Table 5 are supportive of hypothesis 4. The more the use of digital technologies is compatible with the academic identity, the greater the desire to use these technologies. Overall, the data are supportive of the hypotheses as generated from symbolic interaction theory in general and identity theory in particular.</p> <cn>DIFFERENCES BETWEEN FACULTY MEMBERS AND STUDENTS</cn> <p>Finally, we examine the degree to which students and faculty members are different with respect to the major variables in the above hypotheses. These results are shown in Table 6. As can be seen from these data there were no significant differences between students and faculty on the variables of computer self-efficacy, cognitive commitment, and the desire to use digital technology. That is, the level of computer self-efficacy for students and faculty members is relatively high and about the same for both groups; while not statistically significant, the level of commitment to the academic identity is slightly higher and the extent of variation greater for faculty members as opposed to students; and finally, the desire to use digital technology is about the same for both groups with more variation among faculty members.</p> <p>The results for the other three primary variables in the study however, reveal significant differences between students and faculty members. Faculty members are more comfortable using digital technology, use it more than students and have integrated the use of such technology into their sense of self to a greater degree than have students. Standard deviation scores show similar patterns of variation on these three dimensions for the two groups.</p> <cn>DISCUSSION AND IMPLICATIONS</cn> <p>The purpose of this paper was to test several hypotheses from symbolic interaction theory using the academic role identity of college students and faculty relative to various dimensions of digital technology use. Using a large sample of students and faculty members from two different universities, the data from this study are supportive of the hypotheses and the tenets proposed in that theory. The more the use of digital technologies is compatible with one's academic role identity, the greater use of those technologies, the higher degree of computer self-efficacy, the more comfortable one is using these technologies, and the greater the desire to use these technologies. Further, as suggested by identity theory, one's cognitive commitment to the academic identity mediates the relationship between one's level of integration of digital technologies into the academic role identity and one's level of use, comfort in using, and desire to use digital technologies, but not one's computer self-efficacy.</p> <p>Age was also included in these analyses based on the findings from previous research (e.g., Biner et al., 1995; Biner et al., 1996). In all 4 hypotheses, age was an important predictor. In hypotheses 2 and 4, age negatively and significantly influences computer self-efficacy and the desire to use digital technologies. These findings are not surprising given that the students in the sample are likely to have grown up with many of the digital technologies examined, while many faculty members have had to learn to use these digital technologies during the course of their academic career. As such, the findings could suggest a loss of interest in maintaining "up to date" technological knowledge as one grows older, or, perhaps reflecting a cohort effect, that the sense of mastery of the computer and their desire to continue to learn new digital technologies among students is simply higher than among faculty members. In hypotheses 1 and 3, age is positively and significantly predictive of level of use and comfort in using digital technologies. The demands of the academic role necessitate the use of various digital technologies. Therefore, if one uses digital technologies with regularity, one is likely to become more comfortable with using them--and the older one is (perhaps up to the level of some threshold) the longer the requirements of the academic role identity have necessitated the use of these technologies with accompanying integration with a sense of self. The data in Table 6 are also interpretable with this same rationale. That is, the use and integration of, and comfort with such technology tend to be mutually reinforcing. While they cannot be examined with these data, it remains to be seen whether period and/or cohort effects may be operative in some of these relationships.</p> <p>This study has illuminated the strong role played by an important aspect of self--academic role identity--on how much students and faculty use digital technology and how comfortable they feel using such tools. Controlling for age, students with a stronger student identity and faculty members with a stronger faculty identity will use digital technology more, be more comfortable using it, desire to use more of it and have integrated the use of digital technology into their sense of self. These findings (especially the data in Table 2) suggest that some level of digital technology use has become one of the elements in the behavioral descriptions of the role of student and the role of faculty members. The implications of these findings are both important and extensive and while space does not permit a lengthy discussion of these we can mention a few for purposes of illustration.</p> <p>The adoption of web-based, web-enhanced and "hybrid" instructional modalities has greatly accelerated over the past decade (e.g., Green, 2000). The evidence presented herein suggests that while the majority of both students and faculty members can adjust and have adjusted to the expanded role of digital technologies in higher education, there are many that are uncomfortable with its use, do not feel it is "who they are", and do not feel a sense of self-efficacy when using such tools. This may help to explain why some students enroll in web-based instruction and others do not; why some students may avoid classes known to require the use of digital technology (beyond word processing and e-mail); why some students "hang around" with other students who also have this pattern; why some students are wary of discussing academic matters with faculty members who are known to be "heavy" users of digital technology. In short, students with the above pattern may be making academic decisions that have rather negative consequences for their academic life.</p> <p>Extant research suggests that males are more predisposed to digital technology than females (e.g., Blum, 1999; Galpin et. al., 2004; Jackson et. al., 2001; Littleton, 1996) but the present evidence suggests that such patterns may be the result of variables other than gender. Consistent with that literature, in the present work, there were gender differences for level of "computer self-efficacy" (Table 3). Equally as significant, however, is that no gender differences were found for the level of use, desire to use and comfort in using computer technology. There are many possible explanations for such findings including cohort effects but the present data cannot examine such questions. The present findings, however, are consistent with the hypothesis that level of commitment to the academic role may be a stronger predictor of variables related to the use of digital technology than sex role demands or psychological characteristics--at least for students and faculty members in higher education. The findings reported here are consistent with the observation, at least in higher education, that women use computer technology at the same level as men but they don't feel as efficacious about doing so. Clearly, much more work is needed to uncover what combinations of psychological and demographic characteristics represent those who tend to avoid or gravitate toward the use of digital technology with what consequences.</p> <p>Similarly, faculty members with this pattern, especially as related to age, may well make decisions that negatively affect their careers. Faculty members who don't use digital technology may be seen as "outdated" by students with the accompanying student evaluation outcomes. They may be more likely to be perceived as "over the hill" by other faculty producing a variety of unpleasant outcomes. They may demure from teaching important departmental courses that involve substantial use of digital technology thereby removing themselves from potential academic rewards. A key question for future research is whether or not these consequences are due to period or cohort effects.</p> <p>What is apparent from the data presented in this work is that those with a stronger commitment to the academic role (student or faculty member) are more likely to use and be comfortable with digital technology. This observation would follow to the extent that the use of digital technology has become a part of the description of the student role and the role of a faculty member in higher education settings. It follows, therefore, that whatever forces increase the level of commitment to the academic role will also be efficacious for the use of digital technology. These developments should be carefully monitored by all those concerned with how people are making the transition to the new paradigm involving the use of digital technology in educational settings.</p> <hd id="AN0025607625-2">Table 1. Intercorrelations for All Study Variables</hd> <ct id="AN0025607625-3"> Legend for Chart: A - Variable B - 1 C - 2 D - 3 E - 4 F - 5 G - 6 A B C D E F G 1. Integration of DT .659(*) .719(**) .576(**) .452(**) .356(**) 2. Computer Self-Efficacy .556(**) .413(**) .436(**) .285(**) 3. Desire to use DT .593(**) .440(**) .331(**) 4. Cognitive Commitment .423(**) .351(**) 5. Comfort in using DT .712(**) 6. Level of DT use (*) p < .05 (**) p < .01</ct> <hd id="AN0025607625-4">Table 2: Regression Analysis Summary Predicting Level of Digital Technology Use</hd> <ct id="AN0025607625-5"> Variable B SEB B Age .023 .004 .220(***) Cognitive Commitment .083 .016 .229(***) Sex -.095 .115 -.031 Integration of DT .093 .020 .208(***) Note. R² = .21 (***) p < .001</ct> <hd id="AN0025607625-6">Table 3: Regression Analysis Summary Predicting Computer Self Efficacy</hd> <ct id="AN0025607625-7"> Variable B SEB B Age -.043 .010 -.136(***) Cognitive Commitment .050 .041 .046 Sex .788 .290 .085(**) Integration of DT .844 .051 .629(***) Note. R² = .44 (**) p < .01 (***) p < .001</ct> <hd id="AN0025607625-8">Table 4: Regression Analysis Summary Predicting Comfort in Using Digital Technologies</hd> <ct id="AN0025607625-9"> Variable B SEB B Age .068 .019 .133(***) Cognitive Commitment .460 .076 .260(***) Sex -.736 .544 -.049 Integration of DT .623 .095 .285(***) Note. R² = .26 (***) p < .001</ct> <hd id="AN0025607625-10">Table 5: Regression Analysis Summary Predicting Desire to Use Digital Technologies</hd> <ct id="AN0025607625-11"> Variable B SEB B Age -.016 .006 -.080(**) Cognitive Commitment .185 .023 .268(***) Sex .281 .165 .048 Integration of DT .479 .029 .560(***) Note. R² = .56 (**) p < .01 (***) p < .001</ct> <hd id="AN0025607625-12">Table 6: Group Differences for Study Variables</hd> <ct id="AN0025607625-13"> Variables Students Faculty M SD M SD t Comp. Self-Eff. 18.56 4.18 18.54 4.52 .06 Cog. Commit. 16.62 3.86 17.33 4.49 -1.86 Desire to use DT 10.73 2.73 10.79 3.10 -.23 Comfort using DT 18.87 7.09 22.46 7.22 -5.91(***) Use of DT 4.25 1.40 5.31 1.37 -8.93(***) Integration of DT 14.48 3.19 15.34 3.50 -3.06(**) (**) p < .01. (***) p < .001</ct> <ref id="AN0025607625-14"> <title> BIBLIOGRAPY </title> <blist> <bibl id="bib1" idref="ref2" type="bt"></bibl> <bibtext>Benson, D.E., & Trew, K. (1995). Facets of Self in Northern Ireland: Explorations and Further Questions. In R. Wicklund, & A. Oosterwegel (Eds.), The Self in European and North American Culture: Development and Processes (pp. 291-307). Amsterdam: Kluwer Academic Publishing.</bibtext> </blist> <blist> <bibl id="bib2" type="bt"></bibl> <bibtext>Benson, D.E., Haney, W., Ore, T. E., Persell, C. H., Schulte, A., Steele, J., & Winfield, I. (2002). Digital Technologies and the Scholarship of Teaching and Learning in Sociology. Teaching Sociology, 30, 140-157.</bibtext> </blist> <blist> <bibl id="bib3" type="bt"></bibl> <bibtext>Biner, P. M., Bink, M.L., Huffman, M.L., & Dean, R.S. (1995). Personality Characteristics Differentiating and Predicting the Achievement of Televised-Course Students and Traditional-Course Students. American Journal of Distance Education, 9, 46-60.</bibtext> </blist> <blist> <bibl id="bib4" type="bt"></bibl> <bibtext>Biner, P. M., Dean, R.S., & Mellinger, A.E. (1994). Factors Underlying Distance Learner Satisfaction with Televised College-level Courses. American Journal of Distance Education, 8, 60-71.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref3" type="bt"></bibl> <bibtext>Biner, P. M., Summers, M., Dean, R.S., Bink, M.L., Anderson, J.L., & Gelder, B.C. (1996). Student Satisfaction with Interactive Telecourses as a Function of Demographic Variables and Prior Telecourse Experience. Distance Education, 17, 33-43.</bibtext> </blist> <blist> <bibl id="bib6" type="bt"></bibl> <bibtext>Black, J. E. (1992). Faculty Support for University Distance Education. Journal of Distance Education, 7, 5-29.</bibtext> </blist> <blist> <bibl id="bib7" type="bt"></bibl> <bibtext>Blum, K. D. (1999). Gender Differences in Asynchronous Learning in Higher Education: Learning Styles, Participation Barriers and Communication Patterns. Journal of Asynchronous Learning Networks, 3(1), 46-66.</bibtext> </blist> <blist> <bibl id="bib8" type="bt"></bibl> <bibtext>Blumer, H. (1969). Symbolic Interactionism: Perspective and Method. Englewood Cliffs, N.J.: Prentice Hall.</bibtext> </blist> <blist> <bibl id="bib9" type="bt"></bibl> <bibtext>Brent, E. (1999). Computers in the Undergraduate Classroom. Social Sciences Computer Review, 17, 162-75.</bibtext> </blist> <blist> <bibl id="bib10" type="bt"></bibl> <bibtext>Bryant, F. B., & Yarnold, P.R. (1995). Principle-components analysis and exploratory and confirmatory factor analysis. In L.G. Grimm and P.R. Yarnold (Eds.), Reading and Understanding Multivariate Statistics (pp. 99-136). Washington, D.C.: American Psychological Association.</bibtext> </blist> <blist> <bibl id="bib11" type="bt"></bibl> <bibtext>Burke, P. J. (1980). The Self: Measurement Implications from a Symbolic Interactionist Perspective. Social Psychology Quarterly, 43, 18-29.</bibtext> </blist> <blist> <bibl id="bib12" type="bt"></bibl> <bibtext>― (1991). Identity Processes and Social Stress. American Sociological Review, 56, 836- 49.</bibtext> </blist> <blist> <bibl id="bib13" type="bt"></bibl> <bibtext>Burke, P. J., & Reitzes, D. (1981). The Link between Identity and Role Performance. Social Psychology Quarterly; 44, 83-92.</bibtext> </blist> <blist> <bibl id="bib14" type="bt"></bibl> <bibtext>Callero, P. L. (1985). Role-Identity Salience. Social Psychology Quarterly, 48, 203-15.</bibtext> </blist> <blist> <bibl id="bib15" type="bt"></bibl> <bibtext>Carrothers, R. & Benson, D. (2003). Symbolic Interactionism in Introductory Textbooks: Coverage and Pedagogical Implications. Teaching Sociology, 31, 162-81.</bibtext> </blist> <blist> <bibl id="bib16" type="bt"></bibl> <bibtext>Cassidy, S. and P. Eachus. 2002. Developing the Computer Self-Efficacy (CSE) Scale: Investigating the Relationship between CSE, Gender, and Experience with Computers. Journal of Educational Computing Research, 26: 169-189.</bibtext> </blist> <blist> <bibl id="bib17" type="bt"></bibl> <bibtext>Clark, T. (1993). Attitudes Of Higher Education Faculty Towards Distance Education: A National Survey. The American Journal of Distance Education, 7, 19-33.</bibtext> </blist> <blist> <bibl id="bib18" type="bt"></bibl> <bibtext>Cooley, C. H. (1902). Human Nature and the Social Order. New York: Scribner.</bibtext> </blist> <blist> <bibl id="bib19" type="bt"></bibl> <bibtext>Daugherty, M. & Funke, B.L. (1998). University Faculty and Student Perceptions of Web-Based Instruction. Journal of Distance Education, 13, 21-39.</bibtext> </blist> <blist> <bibl id="bib20" type="bt"></bibl> <bibtext>Figueroa, M. L. (1992). Understanding Students' Approaches To Learning In University Traditional And Distance Education Courses. Journal of Distance Education, 7, 15-26.</bibtext> </blist> <blist> <bibl id="bib21" type="bt"></bibl> <bibtext>Galpin, V., Sanders, I., Turner, H., & Venter, B. (2004) Computer Self-Efficacy, Gender, and Educational Background in South Africa. Retrieved December 22, 2004 <ulink href="http://www.jncc.com/∼techsoc/galpin.html">http://www.jncc.com/∼techsoc/galpin.html</ulink>.</bibtext> </blist> <blist> <bibl id="bib22" type="bt"></bibl> <bibtext>Gibson, C. (1996). Toward An Understanding Of Academic Self-Concept In Distance Education. American Journal of Distance Education, 10, 23-36.</bibtext> </blist> <blist> <bibl id="bib23" type="bt"></bibl> <bibtext>Goffman, E. (1959). The Presentation of Self in Everyday Life. New York: Doubleday.</bibtext> </blist> <blist> <bibl id="bib24" type="bt"></bibl> <bibtext>―. (1961). Asylums: Essays on the Social Situation of Mental Patients and other Inmates. Chicago: Aldine Press.</bibtext> </blist> <blist> <bibl id="bib25" type="bt"></bibl> <bibtext>―. (1963). Stigma: Notes on the Management of a Spoiled Identity. Englewood Cliffs, NJ: Prentice Hall.</bibtext> </blist> <blist> <bibl id="bib26" type="bt"></bibl> <bibtext>Green, K. C. (2000). The 2000 National Survey of Information Technology in U.S. Higher Education. Online: http/<ulink href="http://www.campuscomputing.net/summaries/2000/index.html">www.campuscomputing.net/summaries/2000/index.html</ulink></bibtext> </blist> <blist> <bibl id="bib27" type="bt"></bibl> <bibtext>Jaffee, D. (1998). Institutionalized Resistance to Asynchronous Learning Networks. Journal of Asynchronous Learning Networks 2(2). Retrieved November 11, 2004 <ulink href="http://www.aln.org/alnweb/journal/vol2_issue2/jaffe.htm">http://www.aln.org/alnweb/journal/vol2_issue2/jaffe.htm</ulink>.</bibtext> </blist> <blist> <bibl id="bib28" type="bt"></bibl> <bibtext>Littleton, K. (1996). "Girls and Information Technology" in P. Murphy and C.V. Gipps (Eds.) Equity in the Classroom: Towards Effective Pedagogy for Girls and Boys. (pp. 81-96) London: Falmer Press.</bibtext> </blist> <blist> <bibl id="bib29" type="bt"></bibl> <bibtext>McCall, G. J., & Simmons, J.L. (1978). Identities and Interactions. New York: The Free Press.</bibtext> </blist> <blist> <bibl id="bib30" type="bt"></bibl> <bibtext>Mead, G. H. (1934). Mind, Self and Society. Chicago: University of Chicago Press.</bibtext> </blist> <blist> <bibl id="bib31" type="bt"></bibl> <bibtext>Stryker, S. 1980. Symbolic Interactionism: A Social Structural Version. Menlo Park, CA: Benjamin Cummings.</bibtext> </blist> <blist> <bibl id="bib32" type="bt"></bibl> <bibtext>― (2000). Identity Competition, Key to Differential Social Movement Involvement. In S. Stryker, T. Owens, & R. White (Eds), Identity, Self and Social Movements (pp. 21-40). Minneapolis, MN: University of Minnesota Press.</bibtext> </blist> </ref> <aug> <p>By D. E. Benson, Kent State University and Jeanne Mekolichick, Radford University</p> </aug> <nolink nlid="nl1" bibid="bib203" firstref="ref1"></nolink>
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  Data: Conceptions of Self and the Use of Digital Technologies in a Learning Environment
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  Data: <searchLink fieldCode="SO" term="%22Education%22"><i>Education</i></searchLink>. Sum 2007 127(4):498-510.
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  Data: Project Innovation, Inc. P.O. Box 8508 Spring Hill Station, Mobile, AL 36689-0508. Tel: 251-343-1878; Fax: 251-343-1878; Web site: http://www.projectinnovation.biz/education.html
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  Data: While research has identified various personality and demographic characteristics that appear to be associated with a variety of activities related to the use of digital technologies (e.g., Biner, Dean & Mellinger, 1994; Biner, Summers, Dean, Bink, Anderson & Gelder, 1996; Black, 1992; Clark, 1993; Figueroa, 1992), little is known about how conceptions of self might influence the use of digital technologies in a learning environment. (Benson, Haney, Ore, Persell, Schulte, Steele & Winfield, 2001). This paper is the first empirical attempt to understand this relationship. Using a sample of undergraduate students (N = 447) and faculty (N= 203) from two public universities in the United States, we examine how students' and faculty's conceptions of self affect the desire to use and success in using digital technologies in a university environment. Using Identity theory (e.g., Burke & Reitzes, 1991; Stryker, 1980), to test 4 hypotheses, regression analyses indicate that conceptions of self are correlated with the desire to use and the success in using digital technologies. These findings may help to inform policies concerning the use of digital technologies in learning environments as well as suggest new hypotheses for further exploration of this relationship. (Contains 6 tables.)
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        PageCount: 13
        StartPage: 498
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