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Standards-Based Evaluation and Teacher Career Satisfaction: A Structural Equation Modeling Analysis

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Abstract

Structural equation modeling was used to assess the plausibility of a conceptual model specifying hypothesized linkages among perceptions of characteristics of standards-based evaluation, work environment mediators, and career satisfaction and other outcomes. Four comprehensive high schools located in two neighboring counties in southern California provided the data for this study. The schools’ districts had recently developed and implemented evaluation systems based on six California Standards for the Teaching Profession generated in 1997. One hundred and seventy-eight teachers responded to survey questions designed to capture the following constructs: understandable/relevant standards, satisfactory/helpful evaluation, role ambiguity, effort performance-rating linkage, work criteria autonomy, career satisfaction, organizational commitment, and perceptions of the effectiveness of the evaluation system. Confirmatory factor analysis was used to assess whether the items measuring evaluation fit two hypothesized constructs. Structural equation modeling results indicated that there are two mediators in the evaluation-career satisfaction relationship: role ambiguity and work criteria autonomy.

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Notes

  1. Among high performers, some positive outcomes declined slightly, attributed to “the use of bonus payments” and “discouragement to learn that a peer(s) received a [higher] bonus when they worked hard and believed their performance to be indisputable” (p. 445).

  2. Beehr (1995) cautioned that focusing on job or career satisfaction exclusively may place an undue focus on individual well being as opposed to outcomes that are valued by the organization such as organizational commitment. Indeed, research based solely on satisfaction-related outcomes may provide managers a weak rationale for changing the work conditions such as role stress; they may ask how reduced role stress benefits outcomes for the organization as well as the individual (Beehr, 1995). School administrators may have a stronger rationale for monitoring, and possibly altering, those aspects of the evaluation system that influence teachers’ commitment to their school site and belief that the evaluation system is effective.

  3. A contrasting conceptualization is that of Hackman & Oldham (1976) who suggest that work autonomy is a general job characteristic, which taps the degree to which employees generally have the discretion to decide how to carry out their work activities.

  4. The authors are grateful to Mitchell Jancic for this point.

  5. This corresponds to a base API (accountability performance index) of 600 or higher.

  6. We also computed the fit index SRMR in two ways: (a) after mean-substitution for missing values and (b) after listwise deletion. We obtained SRMR values of 0.072 and 0.070 for our finally chosen CFA model and SEM model, respectively. However, noting that our sample size is relatively small (N=178), calculating the SRMR fit index meant a loss of data in our study. As pointed out by a reviewer of this manuscript, however, Hu & Bentler (1999) is recommended for their suggestion of employing combinational rules for model evaluation.

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Acknowledgements

The authors wish to thank Shirley Shaw, Catherine Ulrich, Laura Galido, and Adrian Palazuelos for their assistance with data collection and Sal Castillo, Sehee Hong and one anonymous reviewer for their helpful suggestions for the data analysis and other phases of the research.

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Authors and Affiliations

  1. Department of Education, University of California-Santa Barbara, Santa Barbara, CA, 93106, USA

    Sharon Conley

  2. Santa Monica Unified School District, Santa Monica, CA, USA

    Donna E. Muncey

  3. University of California-Santa Barbara, Santa Barbara, CA, USA

    Sukkyung You

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  1. Sharon Conley
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  2. Donna E. Muncey
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  3. Sukkyung You
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Correspondence to Sharon Conley.

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Conley, S., Muncey, D.E. & You, S. Standards-Based Evaluation and Teacher Career Satisfaction: A Structural Equation Modeling Analysis. J Pers Eval Educ 18, 39–65 (2005). https://doi.org/10.1007/s11092-006-9008-1

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