Commitment and Motivation: Keys to a Program’s Overall Success

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With fall and the “back to school” feeling in the air, you may be among the many leaders in the field of early care and education who are rallying new and existing staff. Staff commitment and motivation are critical to sustaining or improving your program’s day-to-day work and its overall direction. So, how can you deepen staff commitment and bolster motivation? Let’s begin by addressing commitment.


COMMITMENT

Organizational commitment is the relative strength of an educator’s identification with and involvement in a particular program (Mowday, Steers, & Porter, 1979; Bloom, 1988). It is characterized by at least three related factors: a strong belief in and acceptance of the organization’s goals and values, a willingness to exert oneself on behalf of the program, and a strong desire to remain working at the program.


To a large extent, the success of organizational change depends on the degree to which individuals can integrate the goals of the program into their own structure of needs and values. This sense of belonging represents the anticipation that one will be able to achieve personal satisfaction within an organization. It is the essence of organizational commitment. Interdependence through achieving a common goal leads to relationships of trust and respect.


The challenge for leaders is to help educators develop a strong sense of personal ownership and responsibility within the context of an organization. According to Hall (1988), three conditions are essential to achieve this: impact, relevance, and community.

  • Impact. People need to know that what they are doing makes a difference. Teachers, in particular, may feel like they make a difference in the lives of young children and may derive a great deal of personal satisfaction from their work each day. But, they also need feedback that the work they do has a positive impact on what happens in the program. Impact relates to our personal feelings of importance.
  • Relevance. Particularly in early childhood work settings, people need to expect that their talents are being used appropriately and the time they spend on important tasks helps move the program forward in achieving its mission. Many times, staff perceive they are stuck with meaningless, time-consuming tasks. Hall (1988) found that irrelevant tasks undermine the sense of purpose that is so critical to commitment. They spawn frustration and resistance. They stifle motivation.
  • Community. Hall (1988) noted that for relevance to become a shared experience, and for the sense of personal challenge and contribution to become a collective feature of the organization, there must be a norm of interdependence and mutual reliance. Little (1982) calls these norms of Collegiality and interdependence foster mutual respect and a sense of shared responsibility for each other’s well-being. Community refers to the sense of oneness or a spirit of belonging. It is the belief that people can depend on one another.


As a leader in an early care and education program, you are keenly aware of differences in your staff’s levels of commitment. The individual with a strong sense of commitment demonstrates active involvement in the program and in the field of early childhood. That educator arrives early to prepare the classroom, turns in requested paperwork on time, and takes an active role in external professional activities.


Conversely, the educator who does not demonstrate a strong commitment may not be eager to initiate or participate in personal development opportunities. It becomes your responsibility, then, to address this lack of commitment if you feel it is interfering with job performance. Perhaps there are basic unmet needs. Or, perhaps the educator is confused about your expectations or the organization’s vision. Helping such individuals build greater self-awareness of the factors that contribute to their personal and professional satisfaction is a start. Determining the degree of fit between an educator’s needs and expectations and those of the program will help you determine whether the individual should continue to work at your program.


MOTIVATION

Commitment to a program is directly related to the level of motivation an individual exhibits. Leaders frequently find themselves asking why some staff show a lot of initiative and a strong desire to contribute to the organization while others do not. Leaders also wonder why certain incentives motivate peak performance in some staff and not others. Put simply, there is a difference between the can do and want to do factors that regulate behavior in all employees. The first has to do with level of competence, the latter relates to attitude. The attitude part of the equation rests squarely on one’s level of motivation.


Motivation results from the expectation that one’s efforts will lead to anticipated outcomes. Numerous theories of motivation have been proposed over the years, but perhaps the most well known in the education field is Abraham Maslow’s hierarchy of needs (1954). The fundamental premise of Maslow’s theory is that higher-level needs become activated as lower-level needs are satisfied. For example, if children come to a preschool program not having had breakfast in the morning, hunger presents itself as the prime motivator. It will be difficult for them to attend to other higher-level needs like achievement. Likewise, if teachers feel there is little job security where they work, they may be unable to focus on other goals.


A director reported that one of her most enthusiastic and dedicated teachers resisted attending staff meetings scheduled for late afternoons. Upon a closer look, the director discovered that this teacher, a single parent, did not have the financial means to cover the child care costs that would result from her attendance. She also found that the teacher was too embarrassed to admit to her colleagues how financially strapped she was. Lower-level needs must be largely satisfied before higher-level needs can be felt and pursued. An understanding of Maslow’s theory can assist directors in considering whether an individual’s basic needs are met and whether that person is able to focus on higher-level goals relating to self and the organization.


Frederick Herzberg’s (1966) landmark research on motivation supports Maslow’s hierarchy of needs. Herzberg distinguishes between the positive aspects of an individual’s job that are satisfiers and the negative aspects of the job that are dissatisfiers. The two categories, Herzberg asserts, are quite distinct as they relate to motivation issues.


Dissatisfiers include such things as salary, working conditions, status, job security, technical supervision, and organizational policies. Satisfiers, on the other hand, include the nature of the work itself, the individual’s degree of responsibility, opportunities for growth and advancement, and a sense of achievement. Herzberg believes that eliminating dissatisfiers seldom improves an individual’s performance; it merely reduces the irritations and frustrations in doing one’s job. To motivate individuals to higher levels of performance, changes in the structure and nature of the work itself (the satisfiers) need to be addressed.


One resource to explore these concepts and ideas for enhancing commitment and motivation is the McCormick Center’s online module, Promoting Peak Performance, which is based on Paula Jorde Bloom’s Blueprint for Action (2015). This module is part of our online national director credential, Aim4Excellence™. You can learn more about the credential on our website, or directly access the Promoting Peak Performance module here.


Dr. Jane Humphries serves as a Professional eLearning Specialist for the McCormick Center for Early Childhood Leadership at National Louis University. She has written curriculum and facilitated online learning in graduate and undergraduate level courses since 2004. She is currently the curriculum developer of the Aim4Excellence™ program, an online National Director Credential recognized by the National Association for the Education of Young Children (NAEYC) Accreditation and several states’ quality rating and improvement systems (QRIS).

References


Bloom, P. J. (2015). Blueprint for action (3rd ed.). Lake Forest, IL: New Horizons.

Bloom, P. J. (1988). Factors influencing administrators’ decisions regarding the adoption of computer technology. Journal of Educational Computing Research, 4(1), 31-47.

Hall, J. (1988). The competence connection. The Woodlands, TX: Woodstead.

Herzberg, F. (1966). Work and the nature of man. New York, NY: World Publishing.

Little, J.W. (1982). Norms of collegiality and experimentation: Workplace conditions of school success. American Educational Research Journal, 19(3), 325-340.

Maslow, A. H. (1954). Motivation and personality. New York, NY: Harper & Row.

Mowday, R., Steers, R., Porter, L. (1979). The measurement of organizational commitment. Journal of Vocational Behavior, 14, 224-47.

By McCormick Center May 13, 2025
Leaders, policymakers, and systems developers seek to improve early childhood programs through data-driven decision-making. Data can be useful for informing continuous quality improvement efforts at the classroom and program level and for creating support for workforce development at the system level. Early childhood program leaders use assessments to help them understand their programs’ strengths and to draw attention to where supports are needed.  Assessment data is particularly useful in understanding the complexity of organizational climate and the organizational conditions that lead to successful outcomes for children and families. Several tools are available for program leaders to assess organizational structures, processes, and workplace conditions, including: Preschool Program Quality Assessment (PQA) 1 Program Administration Scale (PAS) 2 Child Care Worker Job Stress Inventory (ECWJSI) 3 Early Childhood Job Satisfaction Survey (ECJSS) 4 Early Childhood Work Environment Survey (ECWES) 5 Supportive Environmental Quality Underlying Adult Learning (SEQUAL) 6 The Early Education Essentials is a recently developed tool to examine program conditions that affect early childhood education instructional and emotional quality. It is patterned after the Five Essentials Framework, 7 which is widely used to measure instructional supports in K-12 schools. The Early Education Essentials measures six dimensions of quality in early childhood programs: Effective instructional leaders Collaborative teachers Supportive environment Ambitious instruction Involved families Parent voice A recently published validation study for the Early Education Essentials 8 demonstrates that it is a valid and reliable instrument that can be used to assess early childhood programs to improve teaching and learning outcomes. METHODOLOGY For this validation study, two sets of surveys were administered in one Midwestern city; one for teachers/staff in early childhood settings and one for parents/guardians of preschool-aged children. A stratified random sampling method was used to select sites with an oversampling for the percentage of children who spoke Spanish. The teacher surveys included 164 items within 26 scales and were made available online for a three-month period in the public schools. In community-based sites, data collectors administered the surveys to staff. Data collectors also administered the parent surveys in all sites. The parent survey was shorter, with 54 items within nine scales. Rasch analyses was used to combine items into scales. In addition to the surveys, administrative data were analyzed regarding school attendance. Classroom observational assessments were performed to measure teacher-child interactions. The Classroom Assessment Scoring System TM (CLASS) 9 was used to assess the interactions. Early Education Essentials surveys were analyzed from 81 early childhood program sites (41 school-based programs and 40 community-based programs), serving 3- and 4-year old children. Only publicly funded programs (e.g., state-funded preschool and/or Head Start) were included in the study. The average enrollment for the programs was 109 (sd = 64); 91% of the children were from minority backgrounds; and 38% came from non-English speaking homes. Of the 746 teacher surveys collected, 451 (61%) were from school-based sites and 294 (39%) were from community-based sites. There were 2,464 parent surveys collected (59% school; 41% community). About one-third of the parent surveys were conducted in Spanish. Data were analyzed to determine reliability, internal validity, group differences, and sensitivity across sites. Child outcome results were used to examine if positive scores on the surveys were related to desirable outcomes for children (attendance and teacher-child interactions). Hierarchical linear modeling (HLM) was used to compute average site-level CLASS scores to account for the shared variance among classrooms within the same school. Exploratory factor analysis was performed to group the scales. RESULTS The surveys performed well in the measurement characteristics of scale reliability, internal validity, differential item functioning, and sensitivity across sites . Reliability was measured for 25 scales with Rasch Person Reliability scores ranging from .73 to .92; with only two scales falling below the preferred .80 threshold. The Rasch analysis also provided assessment of internal validity showing that 97% of the items fell in an acceptable range of >0.7 to <1.3 (infit mean squares). The Teacher/Staff survey could detect differences across sites, however the Parent Survey was less effective in detecting differences across sites. Differential item functioning (DIF) was used to compare if individual responses differed for school- versus community-based settings and primary language (English versus Spanish speakers). Results showed that 18 scales had no or only one large DIF on the Teacher/Staff Survey related to setting. There were no large DIFs found related to setting on the Parent Survey and only one scale that had more than one large DIF related to primary language. The authors decided to leave the large DIF items in the scale because the number of large DIFs were minimal and they fit well with the various groups. The factor analysis aligned closely with the five essentials in the K-12 model . However, researchers also identified a sixth factor—parent voice—which factored differently from involved families on the Parent Survey. Therefore, the Early Education Essentials have an additional dimension in contrast to the K-12 Five Essentials Framework. Outcomes related to CLASS scores were found for two of the six essential supports . Positive associations were found for Effective Instructional Leaders and Collaborative Teachers and all three of the CLASS domains (Emotional Support, Classroom Organization, and Instructional Support). Significant associations with CLASS scores were not found for the Supportive Environment, Involved Families, or Parent Voice essentials. Ambitious Instruction was not associated with any of the three domains of the CLASS scores. Table 1. HLM Coefficients Relating Essential Scores to CLASS Scores (Model 1) shows the results of the analysis showing these associations. Outcomes related to student attendance were found for four of the six essential supports . Effective Instructional Leaders, Collaborative Teachers, Supportive Environment, and Involved Families were positively associated with student attendance. Ambitious Instruction and Parent Voice were not found to be associated with student attendance. The authors are continuing to examine and improve the tool to better measure developmentally appropriate instruction and to adapt the Parent Survey so that it will perform across sites. There are a few limitations to this study that should be considered. Since the research is based on correlations, the direction of the relationship between factors and organizational conditions is not evident. It is unknown whether the Early Education Essentials survey is detecting factors that affect outcomes (e.g., engaged families or positive teacher-child interactions) or whether the organizational conditions predict these outcomes. This study was limited to one large city and a specific set of early childhood education settings. It has not been tested with early childhood centers that do not receive Head Start or state pre-K funding. DISCUSSION The Early Education Essentials survey expands the capacity of early childhood program leaders, policymakers, systems developers, and researchers to assess organizational conditions that specifically affect instructional quality. It is likely to be a useful tool for administrators seeking to evaluate the effects of their pedagogical leadership—one of the three domains of whole leadership. 10 When used with additional measures to assess whole leadership—administrative leadership, leadership essentials, as well as pedagogical leadership—stakeholders will be able to understand the organizational conditions and supports that positively impact child and family outcomes. Many quality initiatives focus on assessment at the classroom level, but examining quality with a wider lens at the site level expands the opportunity for sustainable change and improvement. The availability of valid and reliable instruments to assess the organizational structures, processes, and conditions within early childhood programs is necessary for data-driven improvement of programs as well as systems development and applied research. Findings from this validation study confirm that strong instructional leadership and teacher collaboration are good predictors of effective teaching and learning practices, evidenced in supportive teacher-child interactions and student attendance. 11 This evidence is an important contribution to the growing body of knowledge to inform embedded continuous quality improvement efforts. It also suggests that leadership to support teacher collaboration like professional learning communities (PLCs) and communities of practice (CoPs) may have an effect on outcomes for children. This study raises questions for future research. The addition of the “parent voice” essential support should be further explored. If parent voice is an essential support why was it not related to CLASS scores or student attendance? With the introduction of the Early Education Essentials survey to the existing battery of program assessment tools (PQA, PAS, ECWJSI, ECWES, ECJSS and SEQUAL), a concurrent validity study is needed to determine how these tools are related and how they can best be used to examine early childhood leadership from a whole leadership perspective. ENDNOTES 1 High/Scope Educational Research Foundation, 2003 2 Talan & Bloom, 2011 3 Curbow, Spratt, Ungaretti, McDonnell, & Breckler, 2000 4 Bloom, 2016 5 Bloom, 2016 6 Whitebook & Ryan, 2012 7 Bryk, Sebring, Allensworth, Luppescu, & Easton, 2010 8 Ehrlich, Pacchiano, Stein, Wagner, Park, Frank, et al., 2018 9 Pianta, La Paro, & Hamre, 2008 10 Abel, Talan, & Masterson, 2017 11 Bloom, 2016; Lower & Cassidy, 2007 REFERENCES Abel, M. B., Talan, T. N., & Masterson, M. (2017, Jan/Feb). Whole leadership: A framework for early childhood programs. Exchange(19460406), 39(233), 22-25. Bloom, P. J. (2016). Measuring work attitudes in early childhood settings: Technical manual for the Early Childhood Job Satisfaction Survey (ECJSS) and the Early Childhood Work Environment Survey (ECWES), (3rd ed.). Lake Forest, IL: New Horizons. Bryk, A. S., Sebring, P. B., Allensworth, E., Luppescu, S., & Easton, J. Q. (2010). Organizing schools for improvement: Lessons from Chicago. Chicago, IL: The University of Chicago Press. Curbow, B., Spratt, K., Ungaretti, A., McDonnell, K., & Breckler, S. (2000). Development of the Child Care Worker Job Stress Inventory. Early Childhood Research Quarterly, 15, 515-536. DOI: 10.1016/S0885-2006(01)00068-0 Ehrlich, S. B., Pacchiano, D., Stein, A. G., Wagner, M. R., Park, S., Frank, E., et al., (in press). Early Education Essentials: Validation of a new survey tool of early education organizational conditions. Early Education and Development. High/Scope Educational Research Foundation (2003). Preschool Program Quality Assessment, 2nd Edition (PQA) administration manual. Ypsilanti, MI: High/Scope Press. Lower, J. K. & Cassidy, D. J. (2007). Child care work environments: The relationship with learning environments. Journal of Research in Childhood Education, 22(2), 189-204. DOI: 10.1080/02568540709594621 Pianta, R. C., La Paro, K. M., & Hamre, B. K. (2008). Classroom Assessment Scoring System (CLASS). Baltimore, MD: Paul H. Brookes Publishing Co. Talan, T. N., & Bloom, P. J. (2011). Program Administration Scale: Measuring early childhood leadership and management (2 nd ed.). New York, NY: Teachers College Press. Whitebook, M., & Ryan, S. (2012). Supportive Environmental Quality Underlying Adult Learning (SEQUAL). Berkeley, CA: Center for the Study of Child Care Employment, University of California.
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