Invitational Education Theory in Quantitative Research: ICORT can be an independent or dependent variable

The basic elements of Invitational Education (IE) theory: Intentionality, care, optimism, respect, and trust (ICORT) as noted by Purkey and Novak (2015) as well as Anderson (2021)) can be the reliable dependent or independent variable(s) in quantitative research involving social emotional learning initiatives. The ICORT elements of IE theory focus on creating a positive and inclusive learning environment. While IE theory is more qualitative and philosophy-oriented, it is possible to incorporate ICORT as reliable, dependent or independent variables in quantitative research involving social-emotional learning (SEL) initiatives. For instance, when developing your quantitative methodology with ICORT as the dependent variable, potential researchers are invited to consider the following:

•  Explicate ICORT to create operational definitions. Clearly define and operationalize each of the ICORT variables in measurable terms. For instance, develop specific indicators or survey items that capture behaviors or attitudes related to intentionality, care, optimism, respect, and trust.
•  Create quantitative measurement tools.  Design surveys or questionnaires that align with the operational definitions of ICORT. These instruments should be quantifiable and capable of producing numerical data. Likert scales or other quantitative measurement scales can be used to assess participants' perceptions of the learning environment in terms of intentionality, care, optimism, respect, and trust.
•  Plan for pre- and post-assessments. Implement pre- and post-assessments to measure changes in ICORT variables before and after the SEL initiatives. This allows for subsequent analysis of the impact of social-emotional learning interventions on the perceived level of intentionality, care, optimism, respect, and trust within the educational setting.
•  Establish comparison groups.  Create control or comparison groups to compare the outcomes of SEL initiatives. Ensure that there is a group that does not receive the intervention, thereby assessing whether changes in ICORT variables are specific to the SEL program.
•  Plan for statistical analysis. Utilize appropriate statistical analyses to examine the relationships between SEL initiatives and ICORT variables. This may involve t-tests, ANOVA, regression analysis, or other statistical techniques depending on the research design and data distribution. In this regard, either become astute yourself or network well with a quantitative methodologist.
•  Embrace the efficacy of longitudinal studies. Consider conducting longitudinal studies to track changes in ICORT variables over an extended period. This approach provides a more in-depth understanding of the sustained impact of SEL initiatives on intentionality, care, optimism, respect, and trust.
•  Incorporate qualitative data.  While the focus is on quantitative measures, consider integrating qualitative data through interviews or open-ended survey questions. Mixed methodology can provide additional insights into the participants' experiences and perceptions related to ICORT variables.
•  Validate your measurement scale (Boateng, Neilands, Frongillo, Melgar-Quiñonez, & Young, 2018). Ensure any measurement scales developed for ICORT variables are valid and reliable. This involves testing the instruments to confirm that they are accurately measuring what they intend to measure.

Alternatively, when conducting quantitative research involving social-emotional learning (SEL) initiatives, the basic Invitational Education (IE) tenets: Intentionality, care, optimism, respect, and trust (ICORT) can be considered as independent variables. Potential researchers seeking to develop their methodology in this way must still operationalize concepts, but their strategies will differ to establish each aspect of ICORT as the independent variables in the quantitative study.  Therefore, when developing your quantitative methodology with ICORT as the independent variable, potential researchers are invited to consider the following:

• Separate the ICORT mnemonic to create operational definitions. Clearly define each of the ICORT variables in measurable terms. Develop operational definitions that can be translated into specific behaviors, attitudes, or observable indicators within the context of the SEL initiatives.
•  Create quantitative measurement tools.  Design reliable and valid measurement tools to assess the level of intentionality, care, optimism, respect, and trust. This could involve developing survey items, questionnaires, or other quantitative instruments that capture participants' perceptions of these variables.
•   Establish baseline measurement.  Conduct a baseline measurement of the ICORT variables before implementing the SEL initiatives. This will serve as a reference point to compare changes and assess the impact of the interventions.
•  Establish experimental and control groups.  When (ethically) possible, establish both experimental and control groups. The experimental group would receive the SEL interventions, while the control group would not. This allows for a comparison of changes in ICORT variables between the two groups.
•  Plan for either randomization or matching.  Whenever randomization is not feasible, consider using matching techniques.  This will help to ensure that the experimental and control groups are comparable in terms of ICORT variables at the beginning of the study.
•  Implement well-developed SEL initiatives.  Once the research-based SEL initiatives are clearly developed, implement with the experimental group. This could include activities, programs, or interventions designed to enhance social-emotional skills and well-being.
•   Conduct post-intervention measurement.  After the completion of the SEL initiatives, measure the ICORT variables again. This post-intervention measurement will help assess whether there are significant changes in intentionality, care, optimism, respect, and trust as a result of the SEL interventions.
•  Plan for statistical analysis. Use appropriate statistical analyses to examine the impact of SEL initiatives on the ICORT variables. This may involve conducting inferential statistical tests, such as t-tests or ANOVA, to determine whether there are significant differences between the experimental and control groups. Seriously, if you took Statistics as pass/fail, you are encouraged to network well with a quantitative methodologist or plan to hire a research assistant proficient with a quantitative analysis tool such as IBM’s Statistical Package for the Social Sciences (SPSS).  SPSS is a comprehensive statistical software package used for data analysis in social science research. SPSS includes a wide range of statistical procedures, data manipulation capabilities, and data visualization tools. Common analyses include descriptive statistics, inferential statistics (t-tests, ANOVA, regression), factor analysis, and more.
•  Alternatively, Microsoft’s Excel is a spreadsheet program widely used for data entry, manipulation, and basic statistical analysis.  While not as sophisticated as dedicated statistical software such as SPSS, Excel is readily accessible.  Excel can perform basic statistical analyses, including descriptive statistics, t-tests, and correlations.
•  Utilize a tool to conduct correlation analysis. Explore correlations between specific components of SEL initiatives and changes in ICORT variables. This can help identify which aspects of the interventions are most strongly associated with improvements in intentionality, care, optimism, respect, and trust.
•  Embrace the efficacy of longitudinal studies. While time is always a factor in conducting and completing research projects, consider conducting longitudinal analyses to assess the sustainability of changes in ICORT variables over time.  The result could provide clearer insights into the long-term impact of SEL initiatives.

By following the steps suggested above, researchers can quantitatively investigate the relationship between SEL initiatives, and ICORT as either a dependent variable or as independent variables represented by the ICORT mnemonic as explicated in Invitational Education theory. This structured approach provides a quantifiable way to evaluate the effectiveness of social-emotional learning interventions in fostering positive and inclusive educational environments.

 

To Cite:

Anderson, C.J. (December 31, 2023) Invitational Education theory in quantitative research: ICORT can be an independent or dependent variable. [Web log post] Retrieved from http://www.ucan-cja.blogspot.com/

 

References:

Anderson, C. J. (2021). Developing your students' emotional intelligence and philosophical perspective begins with I-CORT. Journal of Invitational Theory and Practice, 27, 36-50.

Boateng GO, Neilands TB, Frongillo EA, Melgar-Quiñonez HR and Young SL (2018) Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer. Front. Public Health 6:149. doi: 10.3389/fpubh.2018.00149

Purkey, W. W., & Novak, J. M. (2015). Fundamentals of invitational education. (2^nd Ed) International Alliance for Invitational Education. Retrieved from: BOOKS | IAIE (invitationaleducation.org)

Purkey, W. W., & Siegel, B. L. (2013). Becoming an invitational leader: A new approach to professional and personal success. Humanics. Retrieved from: http://invitationaleducation.net/featuredbooks.html

 

Slife, B. D., Wright, C. D., & Yanchar, S. C. (2016). Using operational definitions in research: A best-practices approach. Journal of Mind and Behavior, 37(2), 119–139.