Data-Informed Education: Examining the Role of Administrators in Student Achievement - Research Paper

Introduction

While the study recognizes the centrality of evidence-based practice in modern educational settings, it is theorized that school leadership continues to lack a shared vision with the teachers regarding the proactive position of data-informed methods on student achievement and holistic learning. The proposed study, thus, questions the dominance of top-down quality assurance approaches of administrators in educational settings that have continued to isolate teachers in the processes of interpretation of school data into scientifically-backed instructional practices. Furthermore, this study aims to depart from the case-by-case approach to data-backed decision systems in the schools by the principals and administrators. The study, as such, intends to propose a framework for continuous community interactions among the teachers and school administrators.

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Research Questions

The crucial questions that the study will focus on include:

RQ1: What model(s) of data collection methods do administrators use to promote data-informed instructional decisions?

RQ2: What obstacles do principals and teachers encounter and what drivers [motivators] do principals and teachers employ when utilizing data?

Objectives of the Study

As already implied in the research questions, the key objectives of this study include:

• To assess the perspectives of teachers and school administrators regarding the role of communication and co-analysis of essential educational data in the learning processes.
• To understand – and propose solutions to – disconnects that exist between teachers and school administrators regarding the application of data-informed practices in classroom learning scenarios.
• To understand the roles of various stakeholders (teachers, principals, and administrators) in the assessment processes of the different educative process through data-informed learning processes.
• To uncover the challenges and obstacles principals and administrators face in co-sharing the experiences gained from data-informed practices in the learning processes and metacognitive abilities of the teachers in assessing their self-efficacy.
• To uncover the motivators and drivers for communication and data-informed decision making between teachers and administrators.
• To investigate the various methods of acquiring data to inform educational practices and use the empirical data to back the phenomenological studies around data-informed learning.Importance of the study

Organizations continue to bridge the communicative gaps between their employees and management structures (Ozberk & Altinay, 2019). Whereas employee involvement in evidence-based, innovative processes in corporations continue to form a basis of most paradigmatic developments, such all-encompassing, multi-level approaches have not appeared to penetrate the educational system. In the institutional structure, there is still limited, current, data-focused instructional decision making-specific literature (Moore & Croft, 2018; Neugebauer et al., 2018). The communicative linkages between teachers and administrators regarding the teaching and learning processes appear to occur only sporadically and without a thought-out co-analysis of the educative data (Fernandes, 2019). The immense focus on performance-based accountability culture (Bernhardt, 2013; Fernandes, 2019) that currently drives most school improvement plans in the US is theorized to limit the holistic engagement of the teachers and, as such, require a humanistic approach. Lastly, drivers and motivators to data-informed decision making and dual communication channels between the teachers and the school administrators have not often been properly mapped and leveraged in such interactions. This study intends to identify and link such motivators to the success of teaching experiences through collaborative feedback processes between teachers and administrators.

Terms to Be Defined

Some of the terminologies that shall be defined for this study include (but are not limited to); data-driven versus data-informed learning practices, Race to the Top (RTTT) and No Child Left Behind (NCLB) legislation, Response to intervention (RTI) approach, Data-focused Instructional Decision Making, Extant Models in Professional Development, the Five-stage Continuous Improvement Model and Feedback Loop for Engaging with Data.

Topics of the Literature to Be Reviewed

The crucial literature topics that shall be applied in this investigation include – but are not limited to – the following: a history of data-informed instruction and how it departs from the data-driven approaches; the types and categories of data in school settings; data-focused decision-making in school administrative systems; Teacher-Administrator Communication and Data-focused Decision Making interactions; models of teacher professional development interventions and perceived self-efficacy beliefs; and perceived obstacles to Data-informed Instructional Decision Making.

Limitations of the Study

As this will mostly be a study focused on perceptions, the author anticipates the Hawthorne Effect bias to skew the qualitative and quantitative findings (Gachabayov, Dyatlov, & Bergamaschi, 2019). It is posited that the administrators and teachers might display desirable behavior that is prompted by the presence of the authors of the study and not the normal functioning of the subjects. Furthermore, the approach of the study (case study approach) may limit the generalizability of the study results. Case studies generally lack sufficient scientific rigor to be scalable and replicable to broader populations. Lastly, the approach might be time-consuming and expensive through an intense focus on qualitative results that require a relativistic linkage of participants´ responses and a comprehensive thematic analysis during results interpretation.

Proposed Methodology Data Collection

As already shown above, the study shall employ a case study methodology to investigate the current gaps in communication and decision-making and teacher-administrator interactions in educational settings. Case studies focus on multiple types of data sources to gain a wholesome view of the phenomena and the reported perceptions. As such, the case study approach shall employ phenomenology and grounded theory to gain experiential information from the administrators and teachers regarding learning and teaching practices. The case study for this analysis shall involve group discussion, interviews,and reports from the cohorts of teachers and school administrators (Hancock & Algozzine, 2017). Such a combination of data collection techniques is proposed to minimize the Hawthorne’s bias and gain a broad perspective on the communicative and decision-making processes between the teachers and school administrators. The grounded theory approach serves to approach the study through transformative learning theory by Mezirow’s (1997) as well as Knowles’s (1977) adult learning theory and relating the two theories to the communicative and data-informed decision-making processes among the teachers and administrators.

Data Analysis

Thematic analysis, decoding, and open and axial coding of discussion and interview transcripts will provide the main analysis processes for the qualitative data from the study. Axial coding shall follow the open coding approach and attempt to gain a linkage between the data categories. While using the computer-based coding approach, a choice shall be made between Atlas ti 6.0, HyperRESEARCH 2.8, and Max QDA for the qualitative data analysis and coding. Quantitative treatment of the numerical results from the reports shall, furthermore, help in generalizing the available data on teacher-administrator interactions.

References

Bernhardt, V. (2013). Data analysis for continuous school improvement. Abingdon, Oxon, UK: Routledge.

Fernandes, V. (2019). Investigating the Role of Data-Driven Decision-Making within School Improvement Processes.

In R. G. Hamlin, A. Ellinger, & J. Jones (Eds.) Evidence-Based Initiatives for Organizational Change and Development (pp. 201-219). Hershey, PA: IGI Global.

Gachabayov, M., Dyatlov, A., & Bergamaschi, R. (2019). Hawthorne Effect Should Be Controlled for in Quality Control Studies. JAMA Surgery, 154(10), 977. https://doi.org/10.1001/jamasurg.2019.2159

Hancock, D. R., & Algozzine, R. (2017). Doing case study research: a practical guide for beginning researchers. Teachers College Press.

Knowles, M. S., Holton, E. F., & Swanson, R. A. (1998). The adult learner: The definitive classic in adult education and human resource development. New York: Routledge.

Mezirow, J. (1997). Transformative learning: Theory to practice. New directions for adult and continuing education, 1997(74), 5-12. https://doi.org/10.1002/ace.7401

Moore, R., & Croft, M. (2018). Reducing Barriers to Educator Data Use. ACT Research & Policy [online]. http://www.act.org/content/dam/act/unsecured/documents/R1662-data-use-barriers-2018-01.pdf

Neugebauer, S. R., Morrison, D., Karahalios, V., Kibblewhite, J., Weinstein, A., Harper, E., & Tindall, C. (2018). 7 Data-based Decision Making across Educational Stakeholders and Systems.

In A. J. Heineke and A. M. Ryan (Eds.), Teaching, Learning, and Leading with Schools and Communities: Field-Based Teacher Education. New York, NY: Routledge.

Ozberk, K., & Altinay, F. (2019). Opinions of Teachers and School Administrators about Organizational Citizenship Behaviors and Disability Services. International Journal of Disability, Development and Education, 66(6), 551–564. https://doi.org/https://doi.org/10.1080/1034912X.2019.1642453

Reddy, L. A., Dudek, C. M., Peters, S., Alperin, A., Kettler, R. J., & Kurz, A. (2017). Teachers’ and school administrators’ attitudes and beliefs of teacher evaluation: a preliminary investigation of high poverty school districts. Educational Assessment, Evaluation and Accountability, 30(1), 47–70. https://doi.org/https://doi.org/10.1007/s11092-017-9263-3