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Dr. Sema Kalaian

Professor

Statistics and Data Analytics

School of Technology and Professional Services Management

161 Sill Hall

734.487.2307

Skalaian@emich.edu

Education

Ph.D. in Quantitative Methods and Measurement from Michigan State University
Sema Kalaian

Professional Summary

Interests and Expertise

Professor Kalaian’s research interests focus on the development of new statistical methods and its applications to technology, management, education, psychology, medicine, business, health, and social and behavioral research. Much of her methodological developments have focused on

  • The development of the multivariate meta-analytic techniques for combining evidence from multiple primary studies
  • The applications of the meta-analysis methods to multi-site and multi-center studies
  • The developments of the new statistical methods for analyzing Delphi survey data
  • The applications of Hierarchical Linear Modeling and Structural Equation Modeling (SEM) to large-scale multilevel and longitudinal data sets
  • The applications of the meta-analysis and multilevel meta-analysis methods to Science, Technology, Engineering, and Mathematics (STEM) teaching and learning research.
Over the years, Dr. Kalaian taught introductory and advanced statistical and measurement courses such as Hierarchical Linear Modeling, Multivariate Statistics, Methods of Survey Research, Research Design, Structural Equation Modeling, Meta-Analysis, and program evaluation.

Courses

  • Introductory Research Design and Applied Statistics (COT 710)
  • Advanced Research Design and Applied Statistics (COT 711)
  • Introductory Statistics
  • Hierarchical Linear Modeling
  • Meta-Analysis Methods
  • Structural Equation Modeling
  • Multivariate Statistics
  • Survey Research Methods
  • Research Design
  • Quantitative Methods I
  • Quantitative Methods II
  • Program Evaluation

Selected Publications

  • Kalaian, S. A., & Kasim, R. M. (2014). A Meta-analytic Review of Studies of the Effectiveness of Small-Group Learning Methods on Statistics Achievement. Journal of Statistics Education, 22(1). Available Online atwww.amstat.org/publications/jse/v22n1/kalaian.pdf
  • Kalaian, S. A., & Kasim, R. M. (2012). Terminating Sequential Delphi Survey Data Collection. Practical Assessment, Research & Evaluation, 17(5). Available online:http://pareonline.net/getvn.asp?v=17&n=5
  • Kasim, R. M., & Kalaian, S. A. (2010). Measuring Mean-Change in Organizational Research. Proceedings of the 39th Annual Meeting of the Midwest Decision Science Institute, 711-716.
  • Kalaian, S. A., & Kasim, R. M. (2008). Longitudinal Studies. In Paul J. Lavarkas (Ed.),  Encyclopedia of Survey Research Methods. Thousand Oaks, CA: Sage Publications.
  • Kalaian, S. A. (2008). Research Design. In Paul J. Lavarkas (Ed.), Encyclopedia of Survey Research Methods. Thousand Oaks, CA: Sage Publications.
  • Kalaian, S. A., & Kasim, R. M. (2007). Hierarchical Linear Modeling. In Neil Salkind (Ed.). Encyclopedia of Measurement and Statistics (pp. 432-435). Thousand Oaks, CA: Sage Publications.
  • Kalaian, S. A., & Kasim, R. M. (2007). Longitudinal//Repeated Measures Analysis. In Neil Salkind (Ed.). Encyclopedia of Measurement and Statistics (pp. 558-561). Thousand Oaks, CA: Sage Publications.
  • Jitpaiboon, T., & Kalaian, S. A. (2006). Impacts of IS dependency on IS strategy  formulation. International Journal of Information Systems and Change Management, 1(2), 187-201.
  • Jipaiboon, T., & Kalaian, S. A. (2005). Using Hierarchical Linear Modeling to Examine Moderator Effects: IS Organization-by-Industrial Sector Interactions. Journal of International Technology and Information Management, 14 (2), 131-143. 
  • Kalaian, S. A., & Kasim, R. M.  (2004). Comparison between Multivariate Fixed-Effects and Mixed-Effects Meta-Analytic Approaches. Research Methods 2004 Forum of the Academy of Management. No. 9, 1-16. Available online at 
    http://aom.pace.edu/rmd/2004forum.html
  • Kalaian, S. A. (2003).  Applications of Hierarchical Linear Modeling (HLM) to Multi-site Evaluation Studies: A Meta-Analytic Approach. Practical Assessment, Research & Evaluation, 8(15)Available online:http://www.PAREonline.org/getv.asp?v=8&n=15
  • Kalaian, H. A., Mullan, P. B., & Kasim, R. M. (1999).  What Can Studies of Problem-Based Learning Tell Us? Synthesizing and Modeling PBL Effects on National Board of Medical Examination Performance: Hierarchical Linear Modeling Meta-Analytic Approach. Advances in Health Sciences Education, 4, 209-221.
  • Kalaian, H. A., & Raudenbush, S. W. (1996).  A Multivariate Mixed-Effects Linear Model for Meta-Analysis. Psychological Methods, 1(3). 227-235.
  • Kalaian, H. A., & Mullan, P. B. (1996).  Exploratory Factor Analysis of Students' Ratings of a Problem-based Learning Curriculum.  Academic Medicine, 71(4), 390-392.
  • Raudenbush, S. W., Becker, B. J., & Kalaian, S. A. (1988). Modeling Multivariate Effect Sizes. Psychological Bulletin, 103(1), 111‑120.

 More Publications

Selected Presentations

  • Kalaian, S. A., & Kasim, R. M. (2015, April). Effectiveness of Small-Group Learning in STEM College Classrooms: An International Meta-Analytic Review. A poster will be presented at the Annual Meeting of the American Educational Research Association (AERA). Chicago.
  • Kasim, R. M., & Kalaian, S. A. (2015, April). Small-Group Learning versus Lecture-Based Instruction in Engineering, Technology, and Computer Science College Classrooms. A poster will be presented at the Annual Meeting of the American Educational Research Association (AERA). Chicago.                          
  • Kasim, R. M., & Kalaian, S. A. (2012, April).  Small-Group Learning Versus Lecture Based Instruction in Mathematics College Classrooms: A Meta-Analysis . A paper presented at the Annual Meeting of the American Educational Research Association (AERA) on April 2012. Vancouver, Canada.
  • Kalaian, S. A., & Kasim, R. M. (2011, October).  A Meta-Analysis of the Effectiveness of Small- Group Instruction Compared to Lecture-Based Instruction in Science, Technology, Engineering, and Mathematics (STEM) College Classes.  Poster presented at the Principal   Investigator (PI) meeting of the National Science Foundation’s (NSF) REESE program. Washington, D.C.
  • Kalaian, S. A., & Kasim, R. M. (2011, April).  The Effectiveness of Small Group Learning in Health Science College Classrooms .  Paper presented at the Annual Meeting of the American Educational Research Association (AERA) in April 2011. New Orleans, Louisiana.
  • Kalaian, S. A., & Kasim, R. M. (2010, October).  A Global Perspective on the Effectiveness of Small-Group Learning in STEM College Classrooms. Paper presented at the Midwest Regional Comparative and International Education Society 2010 Conference. Ypsilanti, Michigan.
  • Kalaian, S. A., & Kasim, R. M. (2010, May).  Effectiveness of Cooperative Learning Compared   to Lecture-Based Learning in College STEM Classes. Paper presented at the Annual Meeting of the American Educational Research Association (AERA) in May 2010. Denver, Colorado.
  • Kalaian, S. A., & Kasim, R. M. (2010, April). Effectiveness of Response Rates of Online  surveys: A Meta-Analytic Review. Paper presented at the Annual Meeting of the Midwest Decision Science Institute (MWDSI). Toledo, Ohio.
  •   Kalaian, S. A., & Kasim, R. M. (2009, April).  Should We Use the Mixed-or-Fixed-Effects Meta-Analysis Approaches for Analyzing STEM Effectiveness Data?  Paper presented at the Annual Meeting of the American Educational Research Association (AERA). San Diego.
  • Kalaian, S. A., & Kasim, R. M. (2008, October).  Why Multivariate Meta-Analysis Methods for Studies with Multivariate Outcomes?  Paper presented at the Annual Meeting of the Mid-Western Educational Research Association. Columbus, Ohio.
  •  Kalaian, S. A., & Kasim, R. M. (2007, October).  Fixed-Effects vs. Mixed-Effects   Approaches to Meta-Analysis . Paper presented at the Annual Meeting of the Mid-Western  Educational Research Association. St. Louis, Missouri.
  • Kalaian, S. A., & Kasim, R. M. (2007, October).  Multilevel Model for Meta-Analytic Data with Categorical Outcomes . Paper presented at the Annual Meeting of the Mid-Western Educational Research Association. St. Louis, Missouri.
  • Kalaian, S. A., & Kasim, R. M. (2007, April).  Comparing Univariate and Multivariate  Multilevel Meta-Analysis Methods.  Paper presented at the Annual Meeting of the American Educational Research Association (AERA). Chicago, Illinois.
  • Kalaian, S. A., & Kasim, R. M. (2006, March).  Comparing Univariate and Multivariate  Multilevel Meta-Analysis Methods.  Paper presented at the Annual Meeting of the Midwest Decision Science Institute. Indianapolis, Indiana.
  • Kalaian, S. A., & Kasim, R. M. (2005, October).  Correlates of Response Rates in Survey  Research: A Meta-Analytic Review .Paper presented at the Annual Meeting of the Mid-Western Educational Research Association. Columbus, Ohio.
  • Kang, Z., & Kalaian, S. A.(2005, October)College Teachers? Performances and College Students Motivation to Learn: a Quantitative Comparison of Graduates and  Undergraduates . Paper presented at the Annual Meeting of the Mid-Western Educational Research Association. Columbus, Ohio.
  • Kalaian, S. A., Shah, H., & Anderson, D. (2005, October).  Delphi Methodology: A Systematic Decision-Making Framework for Educational Research .Paper presented at the Annual Meeting of the Mid-Western Educational Research Association. Columbus, Ohio.
  • Kasim, R. M., & Kalaian, S. A. (2005, April).  Rasch Modeling via Multilevel Models. Paper presented at the Annual Meeting of the Education Research Exchange (ERE). Cleveland, Ohio.

 More Presentations

Professional Memberships and Affiliations

Grants

Awards and Patents

  • “Best Paper Award” from the American Educational Research Association (AERA), Annual Meeting in Chicago (April 16, 1998). Paper entitled:

    “Modeling the Effects of PBL and Traditional Curriculum on NBME I and II Performance: A Hierarchical Linear Model Meta-Analytic perspective.”

  • “Distinguished Paper Award” from the Society for the Advancement of Information Systems (SAIS). Quantitative Methods at the SAIS 2003 Midwest Business Administration Association (MBAA) 2003 Conference in Chicago (March 14, 2003). Paper entitled:

    “Structural Linear Modeling for Information Systems Strategic Grid.”

  • “Strong Research” highlighted paper. The paper was highlighted at the Business Meeting of the Learning and Instruction Division of the American Educational Research Association’s (AERA) Annual Meeting in San Francisco, California (April 29, 2013). Paper titled:

    “Effectiveness of Small-Group Learning in Science College Classrooms: A Meta-Analytic Study

Additional Information

Prior to joining Eastern Michigan faculty in Fall 2004, Dr. Kalaian served as a faculty member of Research and Statistical Methods

  • In the College of Human Medicine at Michigan State University.
  • In the College of Education at The University of Toledo.
  • In the College of Health and Human Services at the University of Alabama in Birmingham.

Over the years, Dr. Kalaian taught introductory and advanced statistical and measurement courses such as Hierarchical Linear Modeling, Multivariate Statistics, Methods of Survey Research, Research Design, Structural Equation Modeling, Meta-Analysis, and program evaluation.

Recently, Professor Kalaian completed a major National Science Foundation (NSF) grant project to investigate the effectiveness of active small-group learning methods (cooperative, collaborative, team-based learning, problem-based learning, Peer learning, peer-led team learning, etc.) in STEM disciplines. The project was funded by the Research and Evaluation on Education in Science and Engineering (REESE) program of the National Science Foundation (NSF). For more information about the project visit
https://arc.uchicago.edu/reese/users/skalaian 
http://people.emich.edu/skalaian/stem/index.htm

Dr. Sema Kalaian has extensive expertise in the following areas:

  • Predictive Analytics
  • Descriptive Data Analytics
  • Data Visualization
  • Research Design
  • Multilevel Modeling
  • Statistical Modeling of Change and Growth
  • Statistical Modeling of Organizational Effectiveness
  • Meta-Analysis Methods
  • Factor Analysis
  • Structural Equation Modeling
  • Survey Research Methods
  • STEM Teaching/Learning Methods
  • Longitudinal/Trend Research Methods
  • Program Evaluation