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-QuiƱonez, & 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-QuiƱonez 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. (2nd 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.