Analyzing the Technology Affecting on the Social Integration of Students at University
The aim of this paper is to examine the technology access and use on the affecting social integration of local students at university. This aim is achieved by designing a structural equation modeling (SEM) in terms of integration with peers, integration with faculty, faculty support and on the other hand, examining the socio demographic impact on the technology access and use. The collected data were analyzed using the WarpPLS 5.0 software. This study was survey based and it was conducted at a public university in Canada. The results of the study indicated that technology has a strong impact on integration with faculty, faculty support, but technology does not have an impact on integration with peers. However, the social demographic has also an impact on the technology access and use.
[1] K. E. Wohlwend, “A is for avatar: young children in literacy 2.0 worlds and literacy 1.0 schools”, Language Arts, vol. 88, no. 2, 2010, pp. 144–152.
[2] G. Hinchliff, “Toddling toward technology: computer use by very young children”, Children and Libraries, 4, 2008, pp. 47–49.
[3] V. Tinto, “Dropout from higher education: a theoretical Synthesis of Recent Research”, Review of Educational Research, vol.45, no1, 1975, pp. 89-125.
[4] V. Tinto, (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.), 1993, Chicago: University of Chicago Press.
[5] C. A. Amenkhienan, and L. Kogan, “Engineering students’ perceptions of academic activities and support services: factors that influence their academic performance”, College Student Journal, 2004.
[6] R. L. Myers, “Persistence of technical degree seekers”, Unpublished doctoral dissertation, University of Memphis, TN, 2001.
[7] J. M. Billson, and B. T. Terry, “In search of the silken purse: Factors in attrition among first generation students”, College and University, vol. 58, 1982, pp. 57-75.
[8] S. A. Elkins, J. M. Braxton, and G. W. James, “Tinto’s separation stage and its influence on first semester college student persistence”, Research in Higher Education, vol. 41, 2000, pp. 251-268.
[9] J. B. Hertel, “College student generational status: similarities, differences, and factors in college adjustment”, Psychological Record, vol. 52, 2002, pp. 3-18.
[10] C. Jones, J. Turner, and B. Street, Students Writing in the University: Cultural and Epistemological Issues, 1999, Amsterdam: John Benjamins Publishing Company.
[11] V. Tinto, Leaving College: Rethinking the Causes and Cures of Student Attrition, 1987, University of Chicago Press, Chicago.
[12] V. Tinto, “Colleges as communities: taking research on student persistence seriously”, The Review of Higher Education, vol. 21, no. 2, 1998, pp. 167-177.
[13] J. Horrigan, The Mobile Difference: Wireless Connectivity Has Drawn Many Users More Deeply into Digital Life, 2009, Washington, DC: Pew Internet & American Life Project.
[14] Bai and Pan (2009) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[15] Townsend and Wilson (2008) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[16] N. J. M. Ashmore, “The relationship between computer engagement and estimate of gains for students of a two-year college”, Doctoral Dissertation, 2000, University of Memphis, Dissertation Abstracts International, A61/11, ISBN: 0-493-02011-7.
[17] L. B. Gatz, and J. B. Hirt, “Academic and social integration in cyberspace: students and e-mail,” The Review of Higher Education, vol. 23, no. 3, 2000, pp. 299-318.
[18] V. Tinto, P. Russo, and S. Kadel, “Constructing educational communities: increasing retention in challenging circumstances”, AACC Journal, 1994, pp. 26-29.
[19] A. R. Napoli, and P. M. Wortman, “A meta-analysis of the impact of academic and social integration of persistence of community college students”, Journal of Applied Research in the Community College, vol. 4, no. 1, 1996, pp. 5-21.
[20] C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[21] A. G. Liversidge, “Academic and social integration of deaf and hard-of-hearing students in a Carnegie Research-I University”, PhD Thesis, 2003, Univesity of Maryland, College Park.
[22] J. P. Bean, Nine Themes of College Student Retention, In A. Seidman (Ed.), College Student Retention, 2005, pp. 215-243, Westport: praeger Publishers.
[23] H. Gerdes, and B. Mallinckrodt, “Emotional, social, and academic adjustment of college students: a longitudinal study of retention”, Journal of Counseling and Development, vol. 72, 1994, pp. 281-288.
[24] A. W. Chickering, and L. Reisser, Education and identity (2nd ed.), 1993, San Francisco, CA: Jossey-Bass.
[25] G. D. Kuh, and P. G. Love, A Cultural Perspective on Student Departure, In J. M. Braxton (Ed.), Reworking the student departure puzzle (pp. 196-212), 2000, Nashville, TN: Venderbilt University Press.
[26] A. W. Astin, What Mattes in College: Four Critical Years Revised, Jossy-Bass, Inc., 1993, San Francisco.
[27] A. W. Astin, “Student involvement: a developmental theory for higher education”, Journal of College Student Development, vol. 40, no. 5, 1999, pp. 518-529.
[28] J. M. Braxton, A. S. Sullivan, and R. M. Johnson, Appraising Tinto’s Theory of College Student Departure, In I. C. Smart (Ed.), Higher education: Handbook of theory and research, vol. 12, 1997, pp. 107-164, New York, NY: Agathon.
[29] S. B. Robbins, K. Lauver, H. Le, D. Davis, R. Langley, and A. Carlstrom, “Do psychosocial and study skill factors predict college outcomes? A meta-analysis”, Psychological Bulletin, vol. 130, no. 2, 2004, pp. 261-288, doi: 10.1037/003-2909.130.261
[30] G. L. Peltier, R. Laden, M. Matranga, “Student persistence in college: a review of research”, Journal of College Student Retention, vol. 1, no. 4, 1999, pp. 357-275.
[31] K. C. Sorey, and M. H. Duggan, “Differential predictors of persistence between community college adult and traditional-aged students”, Community College Journal of Research and practice, vol. 32, no. 2, 2008, pp. 75-100.
[32] N. J. Evans, D. S. Forney, F. M. Guido, L. D. Patton, and K. A. Renn, Student development in college: Theory, research, and practice, 2009, San Francisco: Jossey-Bass.
[33] A. D. Rayle, S. E. R. Kurpius, and P. Arredondo, “Relationship of self-beliefs, social support, and university comfort with the academic success of freshman college women”, Journal of College Student Retention, vol. 8, no. 3, 2006, pp. 325-343.
[34] Thomas (2000) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[35] J. F. Hair, C. B. William, J. B. Barry, and E. A. Rolph, Multivariate Data Analysis, Englewood Cliffs, 2010, NJ: Prentice Hall.
[36] N. Kock, “Using WarpPLS in e-collaboration studies: an overview of five main analysis steps”, International Journal of e-Collaboration, vol. 6, no. 4, 2010, pp. 1-11.
[37] R. Rosenthal, and R. L. Rosenow, Essentials of behavioural research: methods and data analysis, McGraw-Hill Humanities Social, 1991.
[38] J. Henseler, C. M. Ringle, and R. R. Sinkovics, “The use of partial least square path modelling in international marketing,” Advances in International Marketing, vol. 20, 2009, pp. 277-319.
[39] L. Cronbach, “Coefficient alpha and the internal structure of tests,” Psychometrika, vol. 16, no. 3, 1951, pp. 297-334.
[40] WarpPLS 2.0 User Manual.
[1] K. E. Wohlwend, “A is for avatar: young children in literacy 2.0 worlds and literacy 1.0 schools”, Language Arts, vol. 88, no. 2, 2010, pp. 144–152.
[2] G. Hinchliff, “Toddling toward technology: computer use by very young children”, Children and Libraries, 4, 2008, pp. 47–49.
[3] V. Tinto, “Dropout from higher education: a theoretical Synthesis of Recent Research”, Review of Educational Research, vol.45, no1, 1975, pp. 89-125.
[4] V. Tinto, (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.), 1993, Chicago: University of Chicago Press.
[5] C. A. Amenkhienan, and L. Kogan, “Engineering students’ perceptions of academic activities and support services: factors that influence their academic performance”, College Student Journal, 2004.
[6] R. L. Myers, “Persistence of technical degree seekers”, Unpublished doctoral dissertation, University of Memphis, TN, 2001.
[7] J. M. Billson, and B. T. Terry, “In search of the silken purse: Factors in attrition among first generation students”, College and University, vol. 58, 1982, pp. 57-75.
[8] S. A. Elkins, J. M. Braxton, and G. W. James, “Tinto’s separation stage and its influence on first semester college student persistence”, Research in Higher Education, vol. 41, 2000, pp. 251-268.
[9] J. B. Hertel, “College student generational status: similarities, differences, and factors in college adjustment”, Psychological Record, vol. 52, 2002, pp. 3-18.
[10] C. Jones, J. Turner, and B. Street, Students Writing in the University: Cultural and Epistemological Issues, 1999, Amsterdam: John Benjamins Publishing Company.
[11] V. Tinto, Leaving College: Rethinking the Causes and Cures of Student Attrition, 1987, University of Chicago Press, Chicago.
[12] V. Tinto, “Colleges as communities: taking research on student persistence seriously”, The Review of Higher Education, vol. 21, no. 2, 1998, pp. 167-177.
[13] J. Horrigan, The Mobile Difference: Wireless Connectivity Has Drawn Many Users More Deeply into Digital Life, 2009, Washington, DC: Pew Internet & American Life Project.
[14] Bai and Pan (2009) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[15] Townsend and Wilson (2008) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[16] N. J. M. Ashmore, “The relationship between computer engagement and estimate of gains for students of a two-year college”, Doctoral Dissertation, 2000, University of Memphis, Dissertation Abstracts International, A61/11, ISBN: 0-493-02011-7.
[17] L. B. Gatz, and J. B. Hirt, “Academic and social integration in cyberspace: students and e-mail,” The Review of Higher Education, vol. 23, no. 3, 2000, pp. 299-318.
[18] V. Tinto, P. Russo, and S. Kadel, “Constructing educational communities: increasing retention in challenging circumstances”, AACC Journal, 1994, pp. 26-29.
[19] A. R. Napoli, and P. M. Wortman, “A meta-analysis of the impact of academic and social integration of persistence of community college students”, Journal of Applied Research in the Community College, vol. 4, no. 1, 1996, pp. 5-21.
[20] C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[21] A. G. Liversidge, “Academic and social integration of deaf and hard-of-hearing students in a Carnegie Research-I University”, PhD Thesis, 2003, Univesity of Maryland, College Park.
[22] J. P. Bean, Nine Themes of College Student Retention, In A. Seidman (Ed.), College Student Retention, 2005, pp. 215-243, Westport: praeger Publishers.
[23] H. Gerdes, and B. Mallinckrodt, “Emotional, social, and academic adjustment of college students: a longitudinal study of retention”, Journal of Counseling and Development, vol. 72, 1994, pp. 281-288.
[24] A. W. Chickering, and L. Reisser, Education and identity (2nd ed.), 1993, San Francisco, CA: Jossey-Bass.
[25] G. D. Kuh, and P. G. Love, A Cultural Perspective on Student Departure, In J. M. Braxton (Ed.), Reworking the student departure puzzle (pp. 196-212), 2000, Nashville, TN: Venderbilt University Press.
[26] A. W. Astin, What Mattes in College: Four Critical Years Revised, Jossy-Bass, Inc., 1993, San Francisco.
[27] A. W. Astin, “Student involvement: a developmental theory for higher education”, Journal of College Student Development, vol. 40, no. 5, 1999, pp. 518-529.
[28] J. M. Braxton, A. S. Sullivan, and R. M. Johnson, Appraising Tinto’s Theory of College Student Departure, In I. C. Smart (Ed.), Higher education: Handbook of theory and research, vol. 12, 1997, pp. 107-164, New York, NY: Agathon.
[29] S. B. Robbins, K. Lauver, H. Le, D. Davis, R. Langley, and A. Carlstrom, “Do psychosocial and study skill factors predict college outcomes? A meta-analysis”, Psychological Bulletin, vol. 130, no. 2, 2004, pp. 261-288, doi: 10.1037/003-2909.130.261
[30] G. L. Peltier, R. Laden, M. Matranga, “Student persistence in college: a review of research”, Journal of College Student Retention, vol. 1, no. 4, 1999, pp. 357-275.
[31] K. C. Sorey, and M. H. Duggan, “Differential predictors of persistence between community college adult and traditional-aged students”, Community College Journal of Research and practice, vol. 32, no. 2, 2008, pp. 75-100.
[32] N. J. Evans, D. S. Forney, F. M. Guido, L. D. Patton, and K. A. Renn, Student development in college: Theory, research, and practice, 2009, San Francisco: Jossey-Bass.
[33] A. D. Rayle, S. E. R. Kurpius, and P. Arredondo, “Relationship of self-beliefs, social support, and university comfort with the academic success of freshman college women”, Journal of College Student Retention, vol. 8, no. 3, 2006, pp. 325-343.
[34] Thomas (2000) as cited in C. M. Ruud, “College student social networking and its relationship to perceived social support”, PhD Dissertation, 2013, University of Illinois at Urbana-Champaign.
[35] J. F. Hair, C. B. William, J. B. Barry, and E. A. Rolph, Multivariate Data Analysis, Englewood Cliffs, 2010, NJ: Prentice Hall.
[36] N. Kock, “Using WarpPLS in e-collaboration studies: an overview of five main analysis steps”, International Journal of e-Collaboration, vol. 6, no. 4, 2010, pp. 1-11.
[37] R. Rosenthal, and R. L. Rosenow, Essentials of behavioural research: methods and data analysis, McGraw-Hill Humanities Social, 1991.
[38] J. Henseler, C. M. Ringle, and R. R. Sinkovics, “The use of partial least square path modelling in international marketing,” Advances in International Marketing, vol. 20, 2009, pp. 277-319.
[39] L. Cronbach, “Coefficient alpha and the internal structure of tests,” Psychometrika, vol. 16, no. 3, 1951, pp. 297-334.
[40] WarpPLS 2.0 User Manual.
@article{"International Journal of Business, Human and Social Sciences:72873", author = "Sujit K. Basak and Simon Collin", title = "Analyzing the Technology Affecting on the Social Integration of Students at University", abstract = "The aim of this paper is to examine the technology access and use on the affecting social integration of local students at university. This aim is achieved by designing a structural equation modeling (SEM) in terms of integration with peers, integration with faculty, faculty support and on the other hand, examining the socio demographic impact on the technology access and use. The collected data were analyzed using the WarpPLS 5.0 software. This study was survey based and it was conducted at a public university in Canada. The results of the study indicated that technology has a strong impact on integration with faculty, faculty support, but technology does not have an impact on integration with peers. However, the social demographic has also an impact on the technology access and use.
", keywords = "Faculty, integration, peer, technology access and use. ", volume = "10", number = "5", pages = "1509-9", }
