Thomas Hörstermann

Predictive Validity of Tracking Decisions: Application of a New Validation Criterion

Although tracking decisions are primarily based on students’ achievements, distributions of academic competences in secondary school strongly overlap between school tracks. However, the correctness of tracking decisions usually is based on whether or not a student has kept the track she or he was initially assigned to. To overcome the neglect of misclassified students, we propose an alternative validation criterion for tracking decisions. We applied this criterion to a sample of N = ;2, ;300 Luxembourgish 9th graders in order to identify misclassifications due to tracking decisions. In Luxembourg, students in secondary school attend either an academic track or a vocational track. Students’ scores of academic achievement tests were obtained at the beginning of 9th grade. The test-score distributions, separated by tracks, overlapped to a large degree. Based on the distributions’ intersection, we determined two competence levels. With respect to their individual scores, we assigned each student to one of these levels. It turned out that about 21 % of the students attended a track that did not match their competence level. Whereas the agreement between tracking decisions and actual tracks in 9th grade was fairly high (κ = 0. 93), the agreement between tracking decisions and competence levels was only moderate (κ = 0. 56).

Teachers’ School Tracking Decisions

Teachers’ tracking decisions strongly influence students’ future academic and professional careers, and are assumed to contribute to social inequalities in the German school system. Drawing on dual process models, we focused on the cognitive processes underlying teachers’ tracking decisions and developed a two-component model of teachers’ adaptive diagnostic competence. This model involves a cognitive component that refers to the ability to process information in either heuristic or rule-based ways in making a decision. The situation-specific component refers to the ability to switch flexibly between the different strategies, according to situational demands: case consistency and accountability for the decision. Teachers’ expertise is a necessary precondition for both components. Employing student case vignettes that were developed and tested in two pre-studies, two (quasi) experiments supported the assumptions of the model: Teachers adapted their processing strategies according to the situational demands. Pre-service teachers, as novices, lacked this competency as yet. Therefore, we designed a training program to help pre-service teachers develop the ability to optimize their decision making. Preliminary results indicate that as the quality of pre-service teachers’ tracking decisions improved, the influence of social background variables was reduced. The results may prove helpful for reducing the social inequalities that are intensified by biased tracking decisions.

Teachers’ typology of student categories. A cluster analytic study

The present study demonstrates the application of cluster analysis to examine the typology of student categories of novice Luxembourgish teachers. Student categories are mental representations of groups of students in which teachers classify their students. The investigation of student categories is a relevant topic in education, because subsequent assessments of students may be biased by prior classification. Eighty two novice Luxemburgish teachers were asked to mention types of students they became acquainted with during teaching and described these types by characterizing attributes. Twenty types of students and 65 characterizing attributes were frequently mentioned by the teachers. These data formed the basis of a hierarchical-agglomerative cluster analysis, using average-linkage and complete-linkage clustering methods. The average-linkage-method resulted in 10 clusters, which were largely resembled by the resulting clusters of the complete-linkage-method. This indicates a clear structure in the student categories of Luxembourgish novice teachers. The clusters are compared to Hofer’s (Informationsverarbeitung und Entscheidungsverhalten von Lehrern, Beitrage zu einer Handlungstheorie des Unterrichtens, Urban & Schwarzenberg, Munchen, 1981) typology of student categories. The comparison leads to the assumption that the content of student categories may be partly influenced by educational and political discussion.

Teachers’ Judgments and Decision-Making: Studies Concerning the Transition from Primary to Secondary Education and Their Implications for Teacher Education

Accuracy in assessing academic achievement and potential is a core component of teachers’ diagnostic competence. Large-scale studies in the Luxembourgish and German educational systems show that teachers’ secondary school track decisions are biased by a student’s social background. Therefore, biased assessment of students may contribute to the social inequalities observed in secondary schools in both countries. Within a social cognitive framework of dual-process theories, bias is explained by heuristic information processing, which, in contrast to information-integrating processing, relies on stereotype-based expectations to form judgments about students. A series of experimental studies investigated the information processing strategies of teachers, identifying a low accountability of the decision setting and a high consistency of student information as key moderators that promote stereotype-based information processing strategies in teachers’ school track decisions. Results on intervention modules gave insights how to increase diagnostic competence in teacher education programs.

Linear Modelling of Differences in Teacher Judgment Formation of School Tracking Recommendations

The present paper investigates the application of two regression-based approaches, individual multiple regression and hierarchical linear modelling, in modelling differences in judgment formation of primary school teachers’ secondary school track recommendations. Both approaches share the same theoretical framework of judgment formation as a weighted linear information integration, but differ in their capacity to take differences in judgment formation into account. First, both approaches were applied to empirical data on teachers’ track recommendations and led to deviating conclusions on differences in judgment formation. To investigate which approach results in more reliable representation of actual differences in judgment formation, both approaches were compared based on simulated data and hierarchical linear modelling performed slightly more accurate than individual regression. Thus, hierarchical linear modelling might be considered the preferable modelling approach in research on judgments on school tracking recommendations.

Comparing Regression Approaches in Modelling Compensatory and Noncompensatory Judgment Formation

Applied research on judgment formation, e.g. in education, is interested in identifying the underlying judgment rules from empirical judgment data. Psychological theories and empirical results on human judgment formation support the assumption of compensatory strategies, e.g. (weighted) linear models, as well as noncompensatory (heuristic) strategies as underlying judgment rules. Previous research repeatedly demonstrated that linear regression models well fitted empirical judgment data, leading to the conclusion that the underlying cognitive judgment rules were also linear and compensatory. This simulation study investigated whether a good fit of a linear regression model is a valid indicator of a compensatory cognitive judgment formation process. Simulated judgment data sets with underlying compensatory and noncompensatory judgment rules were generated to reflect typical judgment data from applied educational research. Results indicated that linear regression models well fitted even judgment data with underlying noncompensatory judgment rules, thus impairing the validity of the fit of the linear model as an indicator of compensatory cognitive judgment processes.