Towards the Quest for Scientific Discipline in HRD Research: Designs that Support Causal Inference
Special issue call for papers from European Journal of Training and Development
Towards the Quest for Scientific Discipline in HRD Research:
Designs that Support Causal Inference
Submission Deadlines for Proposals: February 28, 2015
Submission Deadline for Papers: June 30, 2015
Kim Nimon, University of Texas at Tyler
Daniel H. Robinson, Colorado State University
Thomas N. Garavan, Ronan Carbery
The mainstay of contemporary quantitative research in the human resource development (HRD) field appears to be based on cross-sectional self-report data gathered at a single point in time. Although the authors of such research are likely to avoid making direct claims of causality, it is not uncommon for said authors (guest editors included) to lapse into making prescriptive claims by way of implications for practice. Although recommendations for practice is somewhat defacto in HRD journals, one could say that it should be reserved for research articles that are supported by experimental or quasi-experimental design. If the HRD field follows suit of our counterparts in education, one might expect that the danger of HRD professionals considering recommendations that are based on correlational or descriptive designs would be limited to the readers of such articles. However, educational research shows that such unsubstantiated prescriptive claims make their way into future articles as a means to support a prescriptive statement. The purpose of this special issue, therefore, is two part.
First, we aim to benchmark where HRD research is as a scientific discipline and are interested in articles such as those that review the types of designs reported in published articles (see, for example, Hsieh, Hsieh, Chung, Acee, Thomas, Kim, You, Levin, & Robinson, 2005), the relationship between research design and causal statements offered (see, for example, Reinhart, Haring, Levin, Patall, & Robinson, 2013; Robinson, Levin, Thomas, Pituch, & Vaughn, 2007), and secondary effect of unsubstantiated claims of causality in subsequent publications (see, for example, Dacy, Nihalani, Cestone, & Robinson, 2011; Shaw, Walls, Dacy, Levin, & Robinson, 2010).
Second, we aim to educate the HRD field in design features to strengthen causal claims are interested in articles such as those that consider causal issues in mediation studies (see, for, example, Frazier, Tix, & Barron, 2004), quasi experimental designs including the retrospective pretest design (see, for example, Hill & Betz, 2005), propensity score analysis (see, for example, Lane & Gibbs, 2014), regression discontinuity design (see, for example, Murnane & Willett, 2000), interrupted time series design (Shadish, Cook, & Campbell, 2001), articles relating to data analytics including analyzing data from pretest-posttest control group designs (see, for example, Huck & McLean, 1975) and using qualitative data to make causal claims (see, for example, Maxwell, 2004), and articles that discuss innovative techniques to support experimental or quasi experimental designs (see, for example, Mistler & Enders, 2012).
Recognizing that a substantive amount of published HRD research is not based on experimental or quasi-experimental design, we also invite authors to contribute articles that demonstrate how published reports of non-experimental research can be used to move the field forward or ponder the question does HRD need intervention-based studies?
Details of Paper Content, Length, and Due Date
Prospective contributors should submit a proposal to the guest editors by February 28, 2015. Proposals should be in APA format and not exceed 4 pages, excluding title page, abstract, references, tables (optional), and figures (optional). Proposals should be emailed to the guest editors who will provide developmental feedback. We encourage potential contributors to use the proposal process; but will also consider papers that are submitted without being preceded by a proposal. The deadline for first draft submissions (7,000 words maximum) is June 30, 2015. The Scholar One submission system for full papers will open March 1, 2015.
For questions regarding the content of this special issue, please contact the guest editors:
• Kim Nimon, University of Texas at Tyler, [email protected]
• Daniel H. Robinson, Colorado State University, [email protected]
Dacy, B. S., Nihalani, P., Cestone, C., & Robinson, D. H. (2011). (Lack of) support for prescriptive statements in teacher education textbooks. Journal of Educational Research, 104, 1-6.
Lane, F. C., & Gibbs, S. (2014). Propensity Score Analysis A Secondary Data Analysis of Work–Life Policy and Performance Outcomes. Advances in Developing Human Resources, 1523422314559809.
Frazier, P. A., Tix, A. P., & Barron, K. E. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51, 115-134.
Hill, L. G., & Betz, D. L. (2005). Revisiting the retrospective pretest. American Journal of Evaluation, 26, 501-507.
Huck, S. W., & McLean, R. A. (1975). Using a repeated measures ANOVA to analyze the data from a pretest-posttest design: A potentially confusing task. Psychological Bulletin, 82, 511-518.
Hsieh, P.-H., Hsieh, Y.-P., Chung, W.-H., Acee, T., Thomas, G. D., Kim, H.-J., You, J., Levin, J. R., & Robinson, D. H. (2005). Is educational intervention research on the decline? Journal of Educational Psychology, 97, 523-529.
Maxwell, J. A. (2004). Causal explanation, qualitative research, and scientific inquiry in education. Educational researcher, 33(2), 3-11.
Mistler, S. A., & Enders, C. K. (2012). Planned missing data designs for developmental research. Handbook of developmental research methods, 742-754.
Murnane, Richard and John Willett (2011). Methods Matter.
Reinhart, A. L., Haring, S. H., Levin, J. R., Patall, E. A., & Robinson, D. H. (2013). Models of not-so-good behavior: Yet another way to squeeze causality and recommendations for practice out of correlational data. Journal of Educational Psychology, 105, 241-247.
Robinson, D. H., Levin, J. R., Thomas, G. D., Pituch, K. A., & Vaughn, S. R. (2007). The incidence of “causal” statements in teaching and learning research journals. American Educational Research Journal, 44, 400-413.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2001). Experimental and quasi-experimental designs for generalized causal inference (2nd ed.). Boston, MA: Houghton Mifflin Co.
Shaw, S. M., Walls, S. M., Dacy, B. S., Levin, J. R., & Robinson, D. H. (2010). A follow-up note on prescriptive statements in nonintervention research studies. Journal of Educational Psychology, 102, 982-988.