Patterns of Adaptive Learning Scales (PALS) – Teacher

Abstract

The Patterns of Adaptive Learning Scales (PALS) – Teacher is an empirically validated psychometric instrument developed by Carol Midgley and colleagues at the University of Michigan to assess educators’ achievement goal orientations, instructional practices, perceptions of school goal structures, and personal teaching efficacy. Rooted firmly in achievement goal theory and socio-cognitive models of motivation, the teacher scales capture the educational environment created by instructors as well as broader institutional norms. Comprising 29 self-report items across five primary subscales—Mastery Goal Structure for Students, Performance Goal Structure for Students, Mastery Approaches to Instruction, Performance Approaches to Instruction, and Personal Teaching Efficacy—the instrument utilizes a 5-point Likert response format anchored from 1 (Strongly disagree) to 3 (Somewhat agree) and 5 (Strongly agree). Psychometric investigations consistently indicate robust construct validity, meaningful factorial separation via confirmatory factor analysis (CFA), and satisfactory internal consistency reliabilities ranging from α = .69 to .81 across subscales. By delineating between pedagogical orientations that emphasize mastery, self-improvement, and deep understanding versus those highlighting normative comparison, interpersonal competition, and social evaluation, the PALS teacher scales provide educational psychologists, institutional leaders, and educational researchers with a diagnostic and investigative instrument to evaluate how teacher beliefs and classroom cultures shape student motivation, self-regulation, and adaptive academic behaviors.

Keywords

Patterns of Adaptive Learning Scales, PALS, Achievement Goal Theory, Mastery Goal Structure, Performance Goal Structure, Teacher Efficacy, Classroom Climate, Academic Motivation, Instructional Practices, Psychometrics

Authors

The Patterns of Adaptive Learning Scales were conceptualized, operationalized, and refined by a collaborative cohort of educational researchers led by the late Carol Midgley at the University of Michigan’s Combined Program in Education and Psychology (CPEP). Prominent co-authors and contributors across the original validation studies and the 2000 manual include:

• Carol Midgley, Ph.D. – University of Michigan
• Martin L. Maehr, Ph.D. – University of Michigan
• Tim Urdan, Ph.D. – Santa Clara University
• Eric M. Anderman, Ph.D. – The Ohio State University
• Avi Kaplan, Ph.D. – Temple University
• Lynley Hicks Anderman, Ph.D. – The Ohio State University
• Michael J. Middleton, Ph.D. – University of New Hampshire
• Robert W. Roeser, Ph.D. – Pennsylvania State University
• Revathy Kumar, Ph.D. – University of Toledo
• Kathleen E. Freeman, Ph.D. – University of Michigan
• Margaret Gheen, Ph.D. – University of Michigan
• Lori Hruda, Ph.D. – University of Michigan

Purpose

The primary purpose of the Patterns of Adaptive Learning Scales (PALS) – Teacher is to provide a rigorous, theoretically grounded measurement framework for quantifying teachers’ motivational orientations, instructional practices, perceptions of schoolwide culture, and sense of personal professional agency. Within contemporary educational psychometrics, evaluating student motivation in isolation neglects the broader ecological and pedagogical systems in which learning occurs. Research grounded in the ecological systems theory of human development suggests that student behaviors, self-handicapping tendencies, and self-efficacy are direct functions of the motivational climate established by educators and administrators.

The instrument was designed to bridge the gap between classroom-level behavioral observations and the internal socio-cognitive belief systems of teachers. In instructional settings, educators communicate explicit and implicit cues regarding the nature of academic success, the acceptability of errors, and the criteria used for evaluation. PALS captures whether teachers implement mastery-oriented practices—such as acknowledging individual progress, differentiating assignments, and valuing formative effort—or performance-oriented practices, such as publicly displaying elite work, ranking students normatively, and fostering interpersonal competition.

In addition to instructional approaches, the PALS teacher scales evaluate the perceived schoolwide goal structure. This distinction is vital: teachers do not operate in a vacuum; their pedagogical decision-making is heavily constrained or reinforced by institutional norms regarding standardized test scores, public honor rolls, and administrative priorities. Lastly, the scale incorporates an assessment of personal teaching efficacy, measuring the extent to which educators believe their instructional efforts can surmount socioeconomic disadvantages, cognitive barriers, or behavioral difficulties presented by students.

In research applications, the scale functions as a core explanatory or moderating variable in longitudinal studies examining teacher burnout, retention, curriculum reform fidelity, and student transition across middle and secondary education. In applied clinical and school psychology settings, the instrument provides institutional consultants with actionable data for targeted professional development, guiding schools away from toxic social comparison environments toward psychologically supportive, growth-oriented learning environments.

Psychological Construct

The psychological constructs operationalized in the PALS teacher scales are anchored in multidimensional achievement motivation and teacher efficacy. Rather than treating motivation as a unidimensional drive, PALS distinguishes between qualitative goals and pedagogical frameworks across five distinct subscales:

1. Mastery Goal Structure for Students

This construct assesses teachers’ perceptions that the overarching school culture emphasizes learning, personal development, deep comprehension, and intellectual exploration over rote memorization. In an environment characterized by a high mastery goal structure, mistakes are framed as natural components of the learning cycle, effort is systematically recognized, and academic tasks are linked to real-world applications. A sample item measuring this construct is: “In this school: Students are told that making mistakes is OK as long as they are learning and improving.”

2. Performance Goal Structure for Students

This dimension quantifies the extent to which the institutional school environment prioritizes interpersonal competition, relative ability comparisons, standardized test performance, and public academic hierarchies. In high performance-oriented cultures, academic achievement is treated as a zero-sum commodity where status and privileges are awarded strictly to high achievers. A representative item includes: “In this school: Students hear a lot about the importance of getting high test scores.”

3. Mastery Approaches to Instruction

Unlike the perceived institutional environment, this subscale captures personal instructional strategies deliberately implemented by the educator within their specific classroom. Mastery approaches emphasize individualized feedback, choice of activities, task differentiation, and grading systems based on longitudinal self-referenced progress rather than standardized bell curves. An illustrative item states: “I make a special effort to recognize students’ individual progress, even if they are below grade level.”

4. Performance Approaches to Instruction

This construct captures classroom-level instructional practices that highlight relative status, public performance rankings, and social comparison. Teachers utilizing high performance approaches frequently spotlight top-performing students as normative models, distribute privileges based on superior output, and motivate learners through rivalry and competition. A key item operationalizing this construct is: “I encourage students to compete with each other.”

5. Personal Teaching Efficacy

Drawing on Albert Bandura‘s socio-cognitive constructs and the early work of the RAND Corporation, this subscale evaluates a teacher’s subjective belief in their capability to promote meaningful cognitive growth across all students, including those exhibiting severe learning difficulties, behavioral disengagement, or adverse socio-contextual barriers. It contrasts professional agency against fatalistic beliefs that external factors dictate educational outcomes. A representative item is: “If I try really hard, I can get through to even the most difficult student.”

Theoretical Framework

The theoretical framework underpinning the Patterns of Adaptive Learning Scales is predominantly derived from Achievement Goal Theory (AGT), developed by influential motivational theorists including Carol Dweck, John Nicholls, Martin Maehr, and Carole Ames. AGT posits that individuals engage in achievement situations with distinct purposes or schemas that govern how they interpret, experience, and respond to academic challenges.

Ames (1992) argued that educational environments establish a salient “goal structure” through classroom policies involving Tasks, Authority, Recognition, Grouping, Evaluation, and Time (the TARGET framework). When tasks are varied, evaluation focuses on individual growth, and recognition celebrates effort, a mastery climate emerges. Under a mastery climate, students define competence relative to their own past performance, adopt intrinsic task values, display high academic persistence, and engage in self-regulated learning. Conversely, when classrooms emphasize rigid grouping, normative curve grading, and public recognition of elite ability, a performance climate is constructed. In performance climates, competence is defined normatively (outperforming others), which frequently provokes maladaptive outcomes such as academic anxiety, fear of failure, avoidance of help-seeking, and self-handicapping.

Midgley and colleagues (1998, 2000) synthesized AGT with Social Cognitive Theory, recognizing that teachers’ self-efficacy (Bandura, 1997) serves as a critical cognitive filter. An educator may philosophically appreciate mastery learning, but if their personal teaching efficacy is compromised, they may resort to standardized, punitive, or performance-contingent behavior management practices. By interweaving perceived institutional goal structures, personal classroom approaches, and teacher self-efficacy within a unified psychometric battery, PALS allows scholars to map how structural institutional pressures affect individual teacher behavior, which subsequently shapes student motivation.

Validity

Extensive psychometric investigations have established strong construct, convergent, discriminant, and predictive validity for the PALS teacher scales:

Construct and Structural Validity

Confirmatory factor analyses (CFA) conducted across diverse urban, suburban, and rural teacher cohorts demonstrate that a five-factor model provides superior fit compared to rival single-factor or two-factor models (e.g., combining institutional climate and instructional practices). As documented in Midgley et al. (1998, 2000), fit indices across primary and middle school samples consistently fall within acceptable ranges (χ²/df < 2.5, Comparative Fit Index [CFI] ≥ .92, Root Mean Square Error of Approximation [RMSEA] ≤ .06).

Convergent and Discriminant Validity

Correlational matrices confirm that Mastery Goal Structure for Students correlates positively and significantly with Mastery Approaches to Instruction (typically r = .38 to .48, p < .001), while displaying negative or non-significant correlations with Performance Approaches (r = −.12 to −.22). Similarly, Performance Goal Structure exhibits strong convergent associations with Performance Approaches to Instruction (r = .42 to .54, p < .001). Personal Teaching Efficacy demonstrates significant positive correlations with Mastery Approaches (r = .31 to .44) and significant negative correlations with external locus of control and educator burnout dimensions (such as depersonalization and emotional exhaustion).

Predictive and Criterion-Related Validity

Hierarchical linear modeling (HLM) and multilevel structural equation modeling have repeatedly confirmed the predictive validity of the PALS teacher scales on student outcomes. In longitudinal studies (Anderman & Midgley, 1997; Midgley et al., 1995; Urdan et al., 1998):

• High teacher Mastery Approaches prospectively predicted lower student use of self-handicapping strategies (e.g., procrastinating or intentionally withholding effort before examinations).
• Classrooms governed by high Performance Approaches exhibited higher rates of academic cheating, avoidance of help-seeking (Ryan, Hicks, & Midgley, 1997), and sharp declines in intrinsic interest during the transition to middle school.
• Personal Teaching Efficacy significantly predicted teacher longevity, positive attitudes toward inclusive education for students with disabilities, and sustained implementation of differentiated instruction.

Reliability

The reliability of the PALS teacher scales has been thoroughly documented across independent educational samples, demonstrating adequate to high internal consistency reliability as indexed by Cronbach’s alpha (α):

• Mastery Goal Structure for Students (7 items): Demonstrates high internal consistency with Cronbach’s α = .81 in normative validation samples.
• Performance Goal Structure for Students (6 items): Displays acceptable internal consistency with Cronbach’s α = .71.
• Mastery Approaches to Instruction (4 items): Demonstrates acceptable internal consistency with Cronbach’s α = .69. Given the brevity of this 4-item subscale, the mean inter-item correlation (ranging from .32 to .38) confirms strong psychological coherence within classical test theory guidelines.
• Performance Approaches to Instruction (5 items): Demonstrates acceptable reliability with Cronbach’s α = .69 and consistent factor saturation across elementary and secondary instructor samples.
• Personal Teaching Efficacy (7 items): Exhibits robust internal consistency with Cronbach’s α = .74.

Test-retest stability coefficients assessed over 4-month and 8-month academic intervals indicate substantial temporal stability for instructional approaches (r = .68 to .76) and institutional goal structures (r = .62 to .71), confirming that the instrument captures enduring pedagogical belief systems rather than transient, day-to-day emotional states.

Factor Analysis

The factorial validity of the 29-item PALS Teacher inventory was originally evaluated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) by Midgley et al. (1998, 2000). During initial EFA using principal axis factoring with oblimin (oblique) rotation, eigenvalues and scree plot inspections clearly supported a five-factor structure accounting for over 52% of the total variance.

Subsequent CFA verified that the items load onto their designated theoretical constructs without significant cross-loadings:

• Mastery Goal Structure for Students: Standardized factor loadings range from .52 to .78 across items 3, 5, 14 (reversed), 16, 20, 22, and 27.
• Performance Goal Structure for Students: Standardized factor loadings range from .48 to .73 across items 7, 10, 12, 15 (reversed), 25, and 29.
• Mastery Approaches: Standardized factor loadings range from .51 to .72 across items 4, 11, 13, and 26.
• Performance Approaches: Standardized factor loadings range from .50 to .75 across items 1, 9, 17, 19, and 21.
• Personal Teaching Efficacy: Standardized factor loadings range from .46 to .74 across items 2, 6 (reversed), 8, 18 (reversed), 23, 24 (reversed), and 28.

Goodness-of-fit parameters in multi-sample structural equation models have repeatedly supported measurement invariance across elementary school teachers and middle/junior high school teachers, allowing for valid comparative studies across varying grade tiers.

Instrument / Measurement Tool

• Test Type: Self-report psychological and pedagogical survey.
• Target Population: Certified primary, elementary, middle, and high school teachers and instructional staff.
• Total Number of Items: 29 authentic items.
• Response Scale: 5-point Likert scale (1 = Strongly disagree, 3 = Somewhat agree, 5 = Strongly agree).
• Administration Time: Approximately 10 to 15 minutes.
• Subscale Item Composition:
  • Mastery Goal Structure for Students: Items 3, 5, 14, 16, 20, 22, 27
  • Performance Goal Structure for Students: Items 7, 10, 12, 15, 25, 29
  • Mastery Approaches to Instruction: Items 4, 11, 13, 26
  • Performance Approaches to Instruction: Items 1, 9, 17, 19, 21
  • Personal Teaching Efficacy: Items 2, 6, 8, 18, 23, 24, 28
• Scoring and Reverse-Coding Protocols:
  • Negative/inversely keyed items must be reverse-coded prior to subscale score calculation (i.e., 1 → 5, 2 → 4, 3 → 3, 4 → 2, 5 → 1).
  • Reverse-coded items in the teacher battery include: Item 14 (Mastery Goal Structure), Item 15 (Performance Goal Structure), and Items 6, 18, and 24 (Personal Teaching Efficacy).
  • Subscale scores are calculated as the unweighted mean of all completed items within each subscale, retaining the original 1 to 5 metric for intuitive interpretation.

Permissions & Fee and Test Year

The Patterns of Adaptive Learning Scales (PALS) were originally published and codified across a series of validation studies throughout the 1990s, culminating in the comprehensive manual released in 2000 (Midgley et al., 2000) by the University of Michigan. The scales are placed in the public domain for academic, clinical, and non-commercial educational research purposes. Researchers and educational practitioners may utilize, reproduce, and adapt the scales free of monetary charge or licensing fees, provided that proper academic attribution is cited in all resulting publications, dissertations, and technical reports. Commercial exploitation or redistribution behind fee-based paywalls without permission from the copyright holders at the University of Michigan is strictly prohibited.

References

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261–271. https://doi.org/10.1037/0022-0663.84.3.261

Anderman, E. M., & Midgley, C. (1997). Changes in personal achievement goals and the perceived classroom goal structures across the transition to middle level schools. Contemporary Educational Psychology, 22(3), 269–298. https://doi.org/10.1006/ceps.1996.0926

Arunkumar, R., Midgley, C., & Urdan, T. (1999). Perceiving high or low home/school dissonance: Longitudinal effects on adolescent academic and emotional adjustment. Journal of Research on Adolescence, 9(4), 441–467. https://doi.org/10.1207/s15327795jra0904_4

Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

Kaplan, A., & Midgley, C. (1997). The effect of achievement goals: Does level of academic efficacy make a difference? Contemporary Educational Psychology, 22(4), 415–435. https://doi.org/10.1006/ceps.1997.0943

Midgley, C. (Ed.). (2002). Goals, goal structures, and patterns of adaptive learning. Lawrence Erlbaum Associates.

Midgley, C., Anderman, E., & Hicks, L. (1995). Differences between elementary and middle school teachers and students: A goal theory approach. Journal of Early Adolescence, 15(1), 90–113. https://doi.org/10.1177/0272431695015001006

Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals: Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93(1), 77–86. https://doi.org/10.1037/0022-0663.93.1.77

Midgley, C., Kaplan, A., Middleton, M., Urdan, T., Maehr, M. L., Hicks, L., Anderman, E., & Roeser, R. W. (1998). Development and validation of scales assessing students’ achievement goal orientation. Contemporary Educational Psychology, 23(2), 113–131. https://doi.org/10.1006/ceps.1998.0965

Midgley, C., Maehr, M. L., Hruda, L., Anderman, E. M., Anderman, L., Freeman, K. E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M. J., Nelson, J., Roeser, R., & Urdan, T. (2000). Manual for the Patterns of Adaptive Learning Scales (PALS). University of Michigan. http://www.umich.edu/~pals/pals/

Midgley, C., Maehr, M. L., & Urdan, T. (1993). Manual for the Patterns of Adaptive Learning Survey (PALS). University of Michigan.

Midgley, C., & Urdan, T. (1995). Predictors of middle school students’ use of self-handicapping strategies. Journal of Early Adolescence, 15(4), 389–411. https://doi.org/10.1177/0272431695015004001

Ryan, A. M., Hicks, L., & Midgley, C. (1997). Social goals, academic goals, and avoiding seeking help in the classroom. Journal of Early Adolescence, 17(2), 152–171. https://doi.org/10.1177/0272431697017002003

Urdan, T., Midgley, C., & Anderman, E. (1998). The role of classroom goal structure in students’ use of self-handicapping strategies. American Educational Research Journal, 35(1), 101–122. https://doi.org/10.3102/00028312035001101

Items of the Scale