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Introduction

Students and teachers commonly differ when judging student motivation (meta-analytic: r = .18; Urhahne & Wijnia, 2021). Different judgments occur among others due to different perceptions of student motivation. The lens model (Brunswik, 1956) can help identify how students and teachers perceive motivation when jduging it. The perception is characterized by the degree to which teachers and students utilize cues in motivation judgments. If both students and teachers show similar cue utilizations in motivation judgments high agreement results. However, for students it was shown that they perceive themselves motivated when being intrinsically motivated (Dutke & Hinnersmann, 2015). There are only tiny differences between boys and girls as well as between students with and without migration background (Brandmiller et al., 2020). Academic achievement is associated to motivation but causal influence is rather mediated by students' causal attributions (cf. Weiner, 1985). Opposingly, teachers were shown to consider extrinsic motivations (Dutke & Hinnersmann, 2015), gender, migration background (Brandmiller et al., 2020), and academic achievement (Kaiser et al., 2013) to judge motivation. Low student-teacher agreement is thus likely due to different cue utilization in motivation judgments.

Research Aims

Examination of the degree to which students and teachers utilize cues in motivation judgments.

  1. H1: Student-teacher-agreement is rather low
  2. H2: Students base their judgments on goal orientations (learning goals, performance-approach goals, performance-avoidance goals, work avoidance).
  3. H3: Teachers base their judgments on academic achievement, gender, and migration background

 

Figure 1. Example of a Lens Model for Motivation Judgments (We Examined This Lens Model in Our Study)
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Results

Figure 3. Lens Model Parameters of Students' and Teachers' Perception

 

View the results in an interactive way in a shinyapp: https://singlspeed.shinyapps.io/app_aera2023

 

Student-Teacher Agreement:

The correlation of teachers' and students' judgements of student motivation revealed low agreement (r = .32, p < .001). 

 

Cue Utilizations:

Both multilevel models showed that goal orientations:

  • are utilized by students (learning goals: β = -.18; performance-approach goals: β = .19; work avoidance: β = -.18) despite performance-avoidance goals (β = -.07).
  • are neglected by teachers (learning goals: β = .1; performance-approach goals: β = .06; performance-avoidance goals: β = -.06; work avoidance: β = -.09).

However, the tendency of students' and teachers' utilization of goal orientation is the same. Learning goals and performance-approach goals are positively associated with judgments; performance-avoidance goals and work avoidance negatively.

Analyses further showed that:

  • Grades are utilized stronger by teachers (German: β = -.26; mathematics: β = -.21) than by students (German: β = -.06; mathematics: β = -.09) indicating a positive relation between academic achievement and judgments of motivation.
  • Teachers utilize gender stronger (z = -0.26)  than students (z = 0.04) favoring girls over boys.
  • Migration background is utilized almost equally (students: z = 0.09; teachers: z = 0.11).

 

Lens Model Parameters:

Regarding the characteristics of the lens models (i.e., the combination of both Model 2), the linear predicted values (G) correlated with r = .73; their errors (C) correlated with r = .20. The fixed slopes of predictors explained R = .49 of total variance in students’ self-rated motivation (Re) and R = .50 of total variance in teacher judgments (Rs).

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Method

Participants

= 2,056 students (Mage = 14.3, SDage = 4.2, 53.4% female, 30.2% with an immigration background) and 63 of their teachers (Mage = 42.0 years, SDage = 11.4, 55.6% female)

Measures
  • Teachers' motivation judgments: Single item “How motivated do you rate the following student in school?” on a 7-point Likert scale ranging from “low motivation” to “high motivation”.
  • Students' motivation judgments: Single item “How motivated are you in school?” on a 7-point Likert scale ranging from “low motivation” to “high motivation”.
  • Students' goal orientations: 31 items (measurement scales for learning and performance motivation; Spinath et al., 2012) on a 5-point Likert scale from “does not apply at all” to “fully applies” measuring learning goals (Cronbach's α = .81) performance-approach goals (Cronbach's α = .79), performance-avoidance goals (Cronbach's α = .86), and work avoidance (Cronbach's α = .83).
  • Students' gender: Gender was assessed with the options male (1) and female (0).
  • Students' migration background: We assessed students with the item “I have an immigration background.” and the options “yes” and “no”.
  • Students' grades in German/mathematics: Grades in German and mathematics of the last report: “On my last report I had the following grades: German/mathematics.” Answers could range from 1 to 6 with 1 being the best grade.
Procedure

Students filled in the questionnaire via pencil. Subsequently, teachers received a questionnaire with items concerning students from two of their classes. Teachers were requested to rate their students’ motivation based on their individual impression without using formal diagnostic procedures.

Statistical Analyses

All variables were grand-mean centered and standardized except gender and migration background for ease of interpretation. In Figure 2 it is shown which statistical analyses were employed.

Figure 2. Employed Statistical Procedures (Highlighted in Blue)

 

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Discussion

  • Student-teacher agreement was indeed rather low (r = .28) implying teachers and students could have different perceptions of what motivates students.
  • Lens model analyses showed that students rather associated their goal orientations with motivation. This is in line with previous research on goal orientation theory (Elliot & Church, 1997; Elliot & Dweck, 1988; Spinath et al., 2012).
  • Opposingly, teachers rather neglected goal orientations in their judgments. This stresses:
    • Difficulties in perceiving motivational variables (low availability, Dicke et al., 2012)
    • Insufficient teacher knowledge of motivation (Glogger-Frey et al., 2018)
    • Insufficient communication which studfent behavior indicates which motivational quality
  • Students unsystematically associate gender and immigration background with their motivation. Grades in German and mathematics explain only little variation in students' self-rated motivation. These results are in line with previous findings (Brandmiller et al., 2020; Kaiser et al., 2013).
  • Teachers on the other hand, favor girls over boys in motivation judgments and overemphasize grades. Students' migration background is rather neglected and utilized to the same degree as students did. Cues could be utilized due to:
    • High availability of academic achievement due to regular assessments and high availability of gender
    • Stereotypical beliefs that girls are more motivated than boys due to their social behaviors in school (cf. Duckworth & Seligman, 2006; Salisbury et al., 1999)
    • Insufficient differentation between academic achievement and motivational orientations

 

The linear models of students' and teachers' judgments could only lowly be explained by cues (cf. Re, Rs). Previous lens model studies showed considerably higher Rs but were conducted in laboratory settings (Karelaia & Hogarth, 2008). Adding further motivational variables could have led to higher predictability of the models. This also could have reduced the high residual correlation (C) that indicated students and teachers utilized cues not integrated in our analyses.

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