Determining IT Student Profile Using Data Mining and Social Network Analysis
Keywords:
data mining, social network analysis, personas, IT graduates’ skills, job profile, personas, jobs' profile, social network analysis, IT graduates' skillsAbstract
To become higher competitive a university needs to develop a viable students’ absorption strategy on the labor market. A key to the successful development of such a strategy rests to synchronize jobs descriptions with profiles and behavior of IT students. In order to generate this synchronization, it is essential to identify a way to improve university curricula, learning and teaching process based on the students’ profile and on the labor market needs. In this manner, universities could offer IT companies information about their IT students’ profile and behavior. Our paper proposes a data mining and social network analysis to examine IT students’ skills and behavior in order to generate their actual profile. The results contribute to the development of knowledge concerning the IT graduates’ profile and based on this, a solution that might match the university curricula with the labor market requirements. Finally, the results attempt to provide IT companies with information with the aim of better understanding the IT students’ profile and to create a realistic description of the job in the recruitment software on the digital market.
References
[2] Alreck, P.; Settle, R. (2004). The Survey Research Handbook. 3rd ed., McGraw-Hill Education, 2004.
[3] Bahner C.A., Clark C.B. (2020). Sixteen Personality Factor Questionnaire (16PF), In Zeigler- Hill V., Shackelford T.K. (eds.) Encyclopedia of Personality and Individual Differences, Springer 2020. https://doi.org/10.1007/978-3-319-24612-3_86
[4] Bapna, R.; Langer, N.; Mehra, A.; Gopal, R.; Gupta, A. (2013). Human capital investments and employee performance: An analysis of IT services industry, Management Science, 59(3), 641-658, 2013. https://doi.org/10.1287/mnsc.1120.1586
[5] Benta, D.; Bologa, G.; Dzitac, I. (2014). E-learning Platforms in Higher Education. Case Study, Procedia Computer Science, 31, 1170-1176, 2014. https://doi.org/10.1016/j.procs.2014.05.373
[6] Benta, D.; Bologa, G.; Dzitac, S.; Dzitac, I. (2015). University level learning and teaching via e-learning platforms, Procedia Computer Science, 55, 1366-1373, 2015. https://doi.org/10.1016/j.procs.2015.07.123
[7] Borden, J.; Pearson, S. (2015). Education 3.0: Embracing Technology to 'Jump the Curve', Wired Magazine, 2015.
[8] Borgatti, S.P. (2005). Centrality and network flow, Social Networks, 27(1), 55-71, 2005. https://doi.org/10.1016/j.socnet.2004.11.008
[9] Capretz, L.F.(2002). Implications of MBTI in Software Engineering Education, ACM SIGCSE Bulletin, 34(4), 134-137, 2002. https://doi.org/10.1145/820127.820185
[10] Carrington, P.J.; Scott, J.; Wasserman, S. (2005). Models and Methods in Social Network Analysis, Cambridge University Press, 2005. https://doi.org/10.1017/CBO9780511811395
[11] Cattell, H; Mead, A. D. (2008). The Sixteen Personality Factor Questionnaire (16PF), The Sage handbook of personality theory and assessment, SAGE Publications Ltd., 135-159, 2008. https://doi.org/10.4135/9781849200479.n7
[12] Cattell, R. B.; Eber, H. W.; Tatsuoka, M.M. (1970). Handbook for the Sixteen Personality Factor Questionnaire (16PF)s, Institute for Personality and Ability Testing, 1970.
[13] Chaoqun Ni; Sugimoto, C.R.; Jiang, J. (2011). Degree, Closeness, and Betweenness: Application of group centrality measurements to explore macro-disciplinary evolution diachronically, Proceedings of ISSI, 2011.
[14] Charlton, J.P.; Birkett, P.E. (1999), An integrative model of factors related to computing course performance, Journal of Educational Computing Research, 20(3), 237-257, 1999. https://doi.org/10.2190/BTG0-7VQK-6XD3-G4C4
[15] Cheryan, S.; Plaut, V.C.; Handron, C.; Hudson, L. (2013), The stereotypical computer scientist: Gendered media representations as a barrier to inclusion for women, Sex Roles, 69, 58-71, 2013. https://doi.org/10.1007/s11199-013-0296-x
[16] Chopra, S.; Golab, L.; Pretti, T.J.; Toulis, A. (2018). Using data mining methods for research in co-operative education, Asia-pacific journal of cooperative education, 19(3), 297-310, 2018.
[17] Conroy, R. (2016). The RCSI Sample size handbook. A rough guide, 2016. Available: http://www.rcsi.ie/files/research/docs/20160811111051_Sample%20size%202016.pdf, Accesed on 10 May 2020.
[18] Cristea, D. (2001). Tratat de psihologie sociala, ProTransilvania Bucuresti, 2001.
[19] Culic, I.(2004). Metode avansate in cercetarea sociala. Analiza multivariata de interdependenta, Editura Polirom, 230-245, 2004.
[20] Dan C. (2013), Analiza Componentelor Principale pentru date Categoriale (CATPCA), Psihologia Resurselor Umane Journal, 103-117, 2013.
[21] DeYoung, C. G. (2011). Intelligence and personality, In JR. J. Sternberg & S. B. Kaufman(Eds.), The Cambridge handbook of intelligence, Cambridge University Press, 711-737, 2011. https://doi.org/10.1017/CBO9780511977244.036
[22] Dhillon I.; Modha D.(2001). Concept Decomposition for Large Sparse Text Data Using Clustering, Machine Learning, 42, 143-175, 2001. https://doi.org/10.1023/A:1007612920971
[23] Enachescu, D. (2009). Data mining, Metode si aplicatii, Editura Academiei Romane, 2009.
[24] Everett M.; Borgatti, S.P. (2005). Extending centrality, Models and Methods in Social Network Analysis, Cambridge University Press, 57-76, 2005. https://doi.org/10.1017/CBO9780511811395.004
[25] Feldman, R.S.; Fienman, J.A. (1992). Who You Are, Venture Books New York, 1992.
[26] Fisher, D.; Frey, N. (2013). Better Learning Through Structured Teaching: A Framework for the Gradual Release of Responsibility (2nd ed.), Association for Supervision and Curriculum Development, 2013. https://doi.org/10.1598/e-ssentials.8037
[27] Fortunato, S. (2010), Community detection in graphs, Physics Reports, 486(3), 75-174, 2010. https://doi.org/10.1016/j.physrep.2009.11.002
[28] Fowler, S.B.; Lapp, V. (2019). Sample Size in Quantitative Research: Sample Size Will Affect the Significance of Your Research, American Nurse Today, 14(5), 2019.
[29] Freeman, L.C. (1979), Centrality in social networks conceptual clarification, Social Networks, 1(3), 215-239, 1979. https://doi.org/10.1016/0378-8733(78)90021-7
[30] Gie Yong A.; Pearce S. (2013). A beginner's guide to factor analysis: Focusing on exploratory factor analysis, Tutor Quant Methods Psychol, 9, 79-94, 2013. https://doi.org/10.20982/tqmp.09.2.p079
[31] Girvan, M.; Newman, M.N. (2002). Community structure in social and biological networks, Proceedings of the National Academy of Sciences, 99(12), 7821-7826, 2002. https://doi.org/10.1073/pnas.122653799
[32] Goldberg L.R.; Johnson, J.A.; Eber, H.W.; Hogan, R.; Ashton M.C.; Cloninger, C.R.; Gough, H.G.(2006). The International Personality Item Pool and The Future of Public-Domain Personality Measures, Journal of Research in Personality, 40, 84-96, 2006. https://doi.org/10.1016/j.jrp.2005.08.007
[33] Goldberg L.R. (1990). An alternative "description of personality": The Big-Five factor structure, Journal of Personality and Social Psychology, 59, 1216-1229, 1990. https://doi.org/10.1037/0022-3514.59.6.1216
[34] Goldberg L.R.; Sweeney, D.; Merenda, P.F.; Hughes Jr, J.E. (1996). The Big Five Factor Structure as an Integrative Framework: An analysis of Clarke's AVA Model, Journal of Personality Assessment, 66(3), 441-71., 1996. https://doi.org/10.1207/s15327752jpa6603_1
[35] Goldberg L.R.; Sweeney, D.; Merenda, P.F.; Hughes Jr, J.E. (1999). A Broad-Bandwidth, Public- Domain, Personality Inventory Measuring the Lower-Level Facets of Several Five-Factor Model, Personality Psychology in Europe, 7, 2-28, 1999.
[36] Goodwin, K. (2008). Perfecting your personas, The Cooper Journal, 2008.
[37] Halasz, G.; Michel, A. (2011). Key Competencies in Europe: interpretation, policy formulation and implementation, European Journal of Education, 46, 289-306, 2011. https://doi.org/10.1111/j.1465-3435.2011.01491.x
[38] Halpern D.F. (2000). Creating cooperative learning environments, APS Observer, 2000.
[39] Hambleton, R.K.; Swaminathan, H.; Rogers, H.J. (1991). Fundamentals of Item Response Theory, Sage Press, 1991.
[40] Han-Haas, G.H.; Peng G. (2018). Big Data Analytics in Human Resource Management and Its Impact: Theoretical Development and Empirical Results, Twenty-fourth Americas Conference on Information Systems, New Orleans, 2018.
[41] Horn, M. (2014). KAIST Does not Wait For Change In Korea, Pioneers 'Education 3.0, Forbes Magazine, 2014.
[42] Ivanovic, M.; Mitrovic, D.; Budimac, Z.; Jerinic, L.; Badica, C. (2015). HAPA: Harvester and pedagogical agents in e-learning environments, International Journal of Computers Communications & Control, 10(2), 200-210, 2015. https://doi.org/10.15837/ijccc.2015.2.1753
[43] Johnson L.; Becker A. S.; Cummins, M.; Freeman, A.; Ifenthaler, D.; Vardaxis N. (2013). FTechnology Outlook for Australian Tertiary Education 2013-2018: An NMC Horizon Project Regional Analysis, New Media Consortium, 2013.
[44] Karimi, Z.; Baraani-Dastjerdi, A.; Ghasem-Aghaee, N.; Wagner, S. (2016). Links between the personalities, styles and performance in computer programming, Journal of Systems and Software, 111, 228-24, 2013. https://doi.org/10.1016/j.jss.2015.09.011
[45] Kim, E B.; Schniederjans, M. J.(2004). The Role of Personality in Web-Based Distance Education Courses, Communications of the ACM, 47(3), 95-98, 2004. https://doi.org/10.1145/971617.971622
[46] Krause, L. (2000). How We Learn and Why We Don't, Thomson Learning, 2000.
[47] Kuncel, N.R.; Hezlett, S.A. (2010). Fact and fiction in cognitive ability testing for admissions and hiring decisions, Current Directions in Psychological Science, 19, 339-345, 2010. https://doi.org/10.1177/0963721410389459
[48] Kurekova, L.M.; Beblavy, M.; Haita C.; Thum A.E. (2016). Employers' skill preferences across Europe: between cognitive and non-cognitive skills, Journal of Education and Work, 29(6), 662- 687, 2016. https://doi.org/10.1080/13639080.2015.1024641
[49] Ledward, B. C.; Hirata D. (2011). An Overview of 21st Century Skills. Summary of 21st Century Skills for Students and Teachers, Pacific Policy Research Center, Honolulu: Kamehameha Schools-Research & Evaluation, 2011.
[50] Lindsey, W. H. (2011). The Relationship Between Personality Type and Software Usability Using the Myers-Briggs Type Indicator(MBTI R) and the Software Usability Measurement Inventory (SUMI), Doctoral dissertation, Nova Southeastern University, 2011.
[51] McConnell, S. (1999). After the Gold Rush: Creating a True Profession of Software Engineering, Microsoft Press, 1999.
[52] McCrae, R. R.; Greenberg, D. M. (2014). Openness to experience, In D. K. Simonton (Ed.), The Wiley Handbook of Genius Chisester, Wiley, 222-243, 2014. https://doi.org/10.1002/9781118367377.ch12
[53] Michel W.; Shoda Y.; Smith R. E. (2004). Introduction to Personality: Towards an Integration, John Wiley, 2004.
[54] Moisil, I.; Pitic, A.; Dzitac, S.; Popper, L. (2010). Adaptive Web Applications for Citizens' Education. Case Study: Teaching Children the Value of Electrical Energy, International Journal of Computers Communications & Control, 5(5), 819-824, 2010. https://doi.org/10.15837/ijccc.2010.5.2242
[55] Myers, I. B.; McCaulley M. H. (1992). Manual: A guide to the development and use of the Myers-Briggs type indicator, Consulting Psychologists Press, 1992.
[56] Oram, A., Wilson, G. (2010). Making software: What really works, and why we believe it, O'Reilly Media, Inc., 2010.
[57] Pitic, A. E.; Moisil, I.; Dzitac, S. (2013). Raising energy saving awareness through educational software, International Journal of Computers Communications & Control, 8(2), 255-262, 2013. https://doi.org/10.15837/ijccc.2013.2.306
[58] Popa, M. (2008). Statistica pentru psihologi. Teorie si aplicatii SPSS, Colectia Collegium, Psihologie, 2008.
[59] Rubens, N.; Kaplan, D.; Okamoto, T. (2012). E-Learning 3.0: anyone, anywhere, anytime, and AI, In Chiu D.K.W., Wang M., Popescu E., Li Q., Lau R. (Eds.) New Horizons in Web Based Learning. ICWL 2012. LNCS, Springer, 171-180, 2012. https://doi.org/10.1007/978-3-662-43454-3_18
[60] Shaffer, D.W. (2004). Epistemic frames and islands of expertise: Learning from infusion experiences, In Y. Kafai, W.A. Sandoval, N. Enyedy, A.S. Nixon, F. Herrera (Eds.) Proceedings of the Sixth International Conference of the Learning Sciences, 473-480, 2004.
[61] Soto, C.J.; Kronauer, A.; Liang, J.K. (2015). Five-Factor Model of Personality, In S.K. Whitbourne (Ed.) The Encyclopedia of Adulthood and Aging, 2015. https://doi.org/10.1002/9781118521373.wbeaa014
[62] Tieger, P. D.; Barron-Tieger B. (2001). Do What You Are, Little, Brown and Company, 2001.
[63] Trilling, B.; Fadel, C. (2009). 21st Century Skills: Learning for Life in Our Times, John Wiley & Sons, 2009.
[64] Verma, V. (1991). Sampling Methods. Training Handbook, Statistical Institute for Asia and the Pacific, World Bank, 1991.
[65] Waksberg, J. (1978). Sampling Methods for Random Digit Dialing, The Journal of the American Statistical Association, 73, 40-46, 1978. https://doi.org/10.1080/01621459.1978.10479995
[66] Wall, L. (2000). DProgramming Perl, 3rd Edition, O'Reilly, 2000.
[67] Wasserman, S.; Faust, K. (1994). Social network analysis: Methods and applications, Cambridge University Press, 1994. https://doi.org/10.1017/CBO9780511815478
[68] Weinberg, G.M. (1998). The psychology of computer programming. 2nd ed., Van Nostrand Reinhold. xv. 288, 1998.
[69] Williams, B.; Onsman, A.; Brown, T. (1996). Exploratory factor analysis: A five-step guide for novices, J Emerg Prim Health Care, 19, 42-50, 1996.
[70] Woszczynski; A. B., Guthrie; T. C.; Shade, S. (2005). Personality and programming, Journal of Information Systems Education, 16(3), 293-299, 2005.
[71] World Bank, (1999). Core Welfare Indicators Questionnaire (CWIQ) Handbook, Chapter 4: Preparing the CWIQ Sample Design, World Bank, 1999.
[72] Yorke, M; Knight, P.T. (2004). Embedding employability into the curriculum, Learning & Employability, 3, 1-28, 2004.
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