Examination of Relation Between Personality Types and Demographic Properties of Academic Staff

Main Article Content

Abstract

Abstract

Universities are top institutions among education organizations. The personality types of academicians employed in these organizations are very important in terms of their own development and development of students they educate. The aim of this study is to examine the relation between personality types of academic staff and gender, mother education level and father education level variables. The research model is relational scanning. While determining the research group, teleological sampling method was selected among non-random sampling methods. The research was conducted through data obtained from 67 academic staff employed in different universities of Turkey in 2011-2012 academic year. As data collection tool, “Holland vocational preference inventory†and “personal information form†were used. Chi square (x2)  test was performed in order to determine whether personality types of academic staff vary according to gender, mother education level and father education level.It was observed that the personality types of academic staff do not demonstrate significant difference according to gender. (x2= 1.01 and p>0.05) It was observed that personality types of academic staff have significant relation with mother education level (x2 = 9.29 and p<0.05) and father education level. (x2 = 9.79 ve p<0.05) In line with the research findings it was observed that academic staff has social personality type containing helpfulness, socially cooperative, sincerity, patient, etc. properties. The relation of academic staff personality types with mother and father education levels emphasize the importance of parent education in determination of preferences and interests.  Related with determination of academic staff personality types, their relation with variables such as attitude towards profession, academic success, etc. can also be checked.

Keywords: Holland vocational preference inventory, academic staff, demographic properties 

Abstract

Universities are top institutions among education organizations. The personality types of academicians employed in these organizations are very important in terms of their own development and development of students they educate. The aim of this study is to examine the relation between personality types of academic staff and gender, mother education level and father education level variables. The research model is relational scanning. While determining the research group, teleological sampling method was selected among non-random sampling methods. The research was conducted through data obtained from 67 academic staff employed in different universities of Turkey in 2011-2012 academic year. As data collection tool, “Holland vocational preference inventory†and “personal information form†were used. Chi square (x2)  test was performed in order to determine whether personality types of academic staff vary according to gender, mother education level and father education level.It was observed that the personality types of academic staff do not demonstrate significant difference according to gender. (x2= 1.01 and p>0.05) It was observed that personality types of academic staff have significant relation with mother education level (x2 = 9.29 and p<0.05) and father education level. (x2 = 9.79 ve p<0.05) In line with the research findings it was observed that academic staff has social personality type containing helpfulness, socially cooperative, sincerity, patient, etc. properties. The relation of academic staff personality types with mother and father education levels emphasize the importance of parent education in determination of preferences and interests.  Related with determination of academic staff personality types, their relation with variables such as attitude towards profession, academic success, etc. can also be checked.

Keywords: Holland vocational preference inventory, academic staff, demographic properties 

Downloads

Download data is not yet available.

Article Details

How to Cite
Examination of Relation Between Personality Types and Demographic Properties of Academic Staff. (2016). Global Journal of Psychology Research: New Trends and Issues, 6(1), 31–34. https://doi.org/10.18844/gjpr.v6i1.476
Section
Articles

References

Baran, M., & Maskan, A. (2011). The effect of project-based learning on pre-service physics teachers electrostatic achievements. Cypriot Journal of Educational Sciences, 5(4), 243-257.

Bartscher, K. (1995). Increasing Student Motivation through Project-Based Learning.

Basturk, R. (2005). The Effectiveness of Computer-Assisted Instruction in Teaching Introductory Statistics. Educational Technology & Society, 8(2), 170-178.

Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating project-based learning: Sustaining the doing, supporting the learning. Educational psychologist, 26(3-4), 369-398.

Bodenheimer, B., Williams, B., Kramer, M. R., Viswanath, K., Balachandran, R., Belynne, K., & Biswas, G. (2009). Construction and Evaluation of Animated Teachable Agents. Educational Technology & Society, 12(3), 191-205.

Bottino, R. M., & Robotti, E. (2007). Transforming classroom teaching & learning through technology: Analysis of a case study. Educational Technology & Society, 10, 174-186.

Chang, C. C., & Tseng, K. H. (2011). Using a web-based portfolio assessment system to elevate project-based learning performances. Interactive Learning Environments, 19(3), 211-230.

Demirci, C. (2010). The project-based learning approach in a science lesson: a sample project study. Cypriot Journal of Educational Sciences, 5(1), 66-79.

Eskrootchi, R., & Oskrochi, G. R. (2010). A Study of the Efficacy of Project-based Learning Integrated with Computer-based Simulation-STELLA.Educational Technology & Society, 13(1), 236-245.

Gibbes, M., & Carson, L. (2014). Project-based language learning: an activity theory analysis. Innovation in Language Learning and Teaching, 8(2), 171-189.

Haake, M., & Gulz, A. (2008). Visual Stereotypes and Virtual Pedagogical Agents. Educational Technology & Society, 11(4), 1-15.

Karahoca, A., Karahoca, D., & Yengin, Ä°. (2010). Computer assisted active learning system development for critical thinking in history of civilization. Cypriot Journal of Educational Sciences, 5(1), 4-25.

Kim, P., Hong, J. S., Bonk, C., & Lim, G. (2011). Effects of group reflection variations in project-based learning integrated in a Web 2.0 learning space.Interactive Learning Environments, 19(4), 333-349.

Köse, U. (2010). A web based system for project-based learning activities in “web design and programming†course. Procedia-Social and Behavioral Sciences, 2(2), 1174-1184.

Krajcik, J. S., Blumenfeld, P. C., Marx, R. W., & Soloway, E. (1994). A collaborative model for helping middle grade science teachers learn project-based instruction. The elementary school journal, 483-497.

Kubinova, M., Novotna, J., & Littler, G. H. (1999). Projects and Mathematical Puzzles-a Tool for Development of Mathematical Thinking. Mathematics Education I. II, 53.

Mergendoller, J. R., & Thomas, J. W. (2000). Managing project based learning: Principles from the field. In Annual Meeting of the American Educational Research Association, New Orleans.

Moursund, D. (1998). Project-based learning in an information-technology environment. Learning and Leading with Technology, 25, 4-5.

Moursund, D. G. (2003). Project-based learning using information technology.

Nation, M. L. (2008). Project-based learning for sustainable development.Journal of Geography, 107(3), 102-111.

Piccinini, N., & Scollo, G. (2006). Cooperative project-based learning in a web-based software engineering course. Educational Technology & Society, 9(4), 54-62.

Raghavan, K., Cohenâ€Regev, S., & Strobel, S. A. (2001). Student outcomes in a local systemic change project. School Science and Mathematics, 101(8), 417-426.

Schroeder, N. L., & Adesope, O. O. (2014). A Systematic Review of Pedagogical Agents’ Persona, Motivation, and Cognitive Load Implications for Learners. Journal of Research on Technology in Education, 46(3), 229-251.

Dewey, J. (1938). Education and experience.

Campbell, N. R. (1996). How safe are folic acid supplements?. Archives of Internal Medicine, 156(15), 1638-1644.

O’Neill, D. K., & Polman, J. L. (2004). Why educate “little scientists?†Examining the potential of practice-based scientific literacy. Journal of Research in Science Teaching, 41, 234–266

Bransford, J., Brophy, S., & Williams, S. (2000). When computer technologies meet the learning sciences: Issues and opportunities. Journal of Applied Developmental Psychology, 21(1), 59-84.

Harel, I. E., & Papert, S. E. (1991). Constructionism. Ablex Publishing.

Barab. S.A., & Luehmann, A.L. (2003). Building sustainable science curriculum: Acknowledging and accommodating local adaptation. Wiley Periodicals, Inc. Science Education, 87, 454-467.