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When it comes to teacher attitudes towards teaching and learning, research relies heavily on explicit measures (e.g., questionnaires). These attitudes are generally conceptualized as constructivist and transmissive views on teaching and learning with constructivism often considered to be more desirable. In explicit measures, this can have drawbacks like socially desirable responding. It is for this reason that, in this study, we investigated implicit attitudes as well as explicit attitudes towards constructivism and transmission. N = 100 preservice teachers worked on a questionnaire and two Single-Target Implicit Association Tests (ST-IAT constructivism and ST-IAT transmission) before (T1) and after (T2) a single master’s semester. One group (n = 50) did student teaching while a second group (n = 50) took master’s courses. We evaluated preservice teachers’ views on teaching at the end of their masters’ studies. Participants agreed with transmission and constructivism (T1) on both an explicit and implicit level. Implicit measures seem to exceed explicit measures in differentially assessing constructivist and transmissive views on teaching and learning. After student teaching (T2), there was no overall effect of attitude development but changes in rank indicate that participants’ implicit attitudes towards constructivism and transmission developed differently for each individual.
When it comes to teacher attitudes towards teaching and learning, research relies heavily on explicit measures (e.g., questionnaires). These attitudes are generally conceptualized as constructivist and transmissive views on teaching and learning with constructivism often considered to be more desirable. In explicit measures, this can have drawbacks like socially desirable responding. It is for this reason that, in this study, we investigated implicit attitudes as well as explicit attitudes towards constructivism and transmission. N = 100 preservice teachers worked on a questionnaire and two Single-Target Implicit Association Tests (ST-IAT constructivism and ST-IAT transmission) before (T1) and after (T2) a single master’s semester. One group (n = 50) did student teaching while a second group (n = 50) took master’s courses. We evaluated preservice teachers’ views on teaching at the end of their masters’ studies. Participants agreed with transmission and constructivism (T1) on both an explicit and implicit level. Implicit measures seem to exceed explicit measures in differentially assessing constructivist and transmissive views on teaching and learning. After student teaching (T2), there was no overall effect of attitude development but changes in rank indicate that participants’ implicit attitudes towards constructivism and transmission developed differently for each individual.
Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback.
Science education researchers typically face a trade-off between more quantitatively oriented confirmatory testing of hypotheses, or more qualitatively oriented exploration of novel hypotheses. More recently, open-ended, constructed response items were used to combine both approaches and advance assessment of complex science-related skills and competencies. For example, research in assessing science teachers' noticing and attention to classroom events benefitted from more open-ended response formats because teachers can present their own accounts. Then, open-ended responses are typically analyzed with some form of content analysis. However, language is noisy, ambiguous, and unsegmented and thus open-ended, constructed responses are complex to analyze. Uncovering patterns in these responses would benefit from more principled and systematic analysis tools. Consequently, computer-based methods with the help of machine learning and natural language processing were argued to be promising means to enhance assessment of noticing skills with constructed response formats. In particular, pretrained language models recently advanced the study of linguistic phenomena and thus could well advance assessment of complex constructs through constructed response items. This study examines potentials and challenges of a pretrained language model-based clustering approach to assess preservice physics teachers' attention to classroom events as elicited through open-ended written descriptions. It was examined to what extent the clustering approach could identify meaningful patterns in the constructed responses, and in what ways textual organization of the responses could be analyzed with the clusters. Preservice physics teachers (N = 75) were instructed to describe a standardized, video-recorded teaching situation in physics. The clustering approach was used to group related sentences. Results indicate that the pretrained language model-based clustering approach yields well-interpretable, specific, and robust clusters, which could be mapped to physics-specific and more general contents. Furthermore, the clusters facilitate advanced analysis of the textual organization of the constructed responses. Hence, we argue that machine learning and natural language processing provide science education researchers means to combine exploratory capabilities of qualitative research methods with the systematicity of quantitative methods.
er vorliegende Beitrag beschäftigt sich mit den Publikationen, die in der Zeitschrift für Erziehungswissenschaft (ZfE) in den Jahren 1998–2017 veröffentlicht wurden. Angesichts der Veränderungen in der erziehungswissenschaftlichen Forschungslandschaft in der jüngeren Vergangenheit untersuchen wir, inwiefern sich eine veränderte Schwerpunktsetzung auch in den Beiträgen der ZfE nachweisen lassen. Dazu führen wir zunächst eine quantitative Textanalyse durch und identifizieren die häufigsten sowie die charakteristischen Bigramme (Zweiwortsequenzen) in vier aufeinanderfolgenden Fünfjahres-Abschnitten (1998–2002, 2003–2007, 2008–2012, 2013–2017). Zudem prüfen wir, inwiefern bestimmte Wortstämme (bspw. „erziehungswissenschaft“, „bildungsforsch“, „didakt“) über die Jahre hinweg häufiger auftreten. Schließlich erstellen wir mit dem Textmining Tool Leximancer™ concept maps, die Hinweise auf die semantische Struktur der Themengebiete und Schlüsselkonzepte geben. Die Ergebnisse deuten darauf hin, dass im gesamten Zeitraum mehrheitlich Beiträge mit empirischem Fokus publiziert wurden, ein inhaltlicher Fokus auf sozialen Aspekten von Bildung lag und die Beschäftigung mit der allgemeinen Erziehungswissenschaft abnahm.
The present study explored teachers' perspectives on one specific type of acceleration, namely, grade skipping. In addition, we investigated the extent to which teachers' beliefs about students' academic, motivational, and social development after grade skipping may explain teachers' acceptance of this accelerative strategy. Moreover, we examined whether teachers' acceptance is linked to their decisions about using this intervention. Using data from the PARS project, which included 316 teachers from 18 secondary schools in the German federal state of North Rhine-Westphalia, we assessed teachers' acceptance, beliefs, and perceived knowledge about grade skipping using 4-point rating scales. Teachers also reported whether they had advised a student to skip a grade. Multilevel regression analyses indicated that teachers' beliefs about students' social, motivational, and academic development largely explained their acceptance. Teachers who showed a higher level of acceptance and perceived knowledge were more likely to have recommended grade skipping before. Educational implications are discussed.
Previous research has identified students' personality traits, especially conscientiousness, as highly relevant predictors of academic success. Less is known about the role of Big Five personality traits in students when it comes to teachers' decisions about students' educational trajectories and whether personality traits differentially affect these decisions by teachers in different grade levels. This study examines to what extent students' Big Five personality traits affect teacher decisions on grade retention, looking at two cohorts of 12,146 ninth-grade and 6002 seventh-grade students from the German National Educational Panel Study. In both grade levels, multilevel logistic mediation models show that students' conscientiousness indirectly predicts grade retention through the assignment of grades by teachers. In the ninth-grade sample, students' conscientiousness was additionally a direct predictor of retention, distinct from teacher-assigned grades. We discuss potential underlying mechanisms and explore whether teachers base their decisions on different indicators when retaining seventh-grade students or ninth-grade students.
The Big Five personality traits play a major role in student achievement. As such, there is consistent evidence that students that are more conscientious receive better teacher-assigned grades in secondary school. However, research often does not support the claim that students that are more conscientious similarly achieve higher scores in domain-specific standardized achievement tests. Based on the Invest-and-Accrue Model, we argue that conscientiousness explains to some extent why certain students receive better grades despite similar academic accomplishments (i.e., achieving similar scores in domain-specific standardized achievement tests). Therefore, the present study examines to what extent the relationship between student personality and teacher-assigned grades consists of direct as opposed to indirect associations (via subject-specific standardized test scores). We used a representative sample of 14,710 ninth-grade students to estimate these direct and indirect pathways in mathematics and German. Structural equation models showed that test scores explained between 8 and 11% of the variance in teacher-assigned grades in mathematics and German. The Big Five personality traits in students additionally explained between 8 and 10% of the variance in grades. Finally, the personality-grade relationship consisted of direct (0.02 | β| ≤ 0.27) and indirect associations via test scores (0.01 | β| ≤ 0.07). Conscientiousness explained discrepancies between teacher-assigned grades and students’ scores in domain-specific standardized tests to a greater extent than any of the other Big Five personality traits. Our findings suggest that students that are more conscientious may invest more effort to accomplish classroom goals, but fall short of mastery.
The Big Five personality traits play a major role in student achievement. As such, there is consistent evidence that students that are more conscientious receive better teacher-assigned grades in secondary school. However, research often does not support the claim that students that are more conscientious similarly achieve higher scores in domain-specific standardized achievement tests. Based on the Invest-and-Accrue Model, we argue that conscientiousness explains to some extent why certain students receive better grades despite similar academic accomplishments (i.e., achieving similar scores in domain-specific standardized achievement tests). Therefore, the present study examines to what extent the relationship between student personality and teacher-assigned grades consists of direct as opposed to indirect associations (via subject-specific standardized test scores). We used a representative sample of 14,710 ninth-grade students to estimate these direct and indirect pathways in mathematics and German. Structural equation models showed that test scores explained between 8 and 11% of the variance in teacher-assigned grades in mathematics and German. The Big Five personality traits in students additionally explained between 8 and 10% of the variance in grades. Finally, the personality-grade relationship consisted of direct (0.02 | β| ≤ 0.27) and indirect associations via test scores (0.01 | β| ≤ 0.07). Conscientiousness explained discrepancies between teacher-assigned grades and students’ scores in domain-specific standardized tests to a greater extent than any of the other Big Five personality traits. Our findings suggest that students that are more conscientious may invest more effort to accomplish classroom goals, but fall short of mastery.
Background
Building on the Realistic Accuracy Model, this paper explores whether it is easier for teachers to assess the achievement of some students than others. Accordingly, we suggest that certain individual characteristics of students, such as extraversion, academic self-efficacy, and conscientiousness, may guide teachers' evaluations of student achievement, resulting in more appropriate judgements and a stronger alignment of assigned grades with students' actual achievement level (as measured using standardized tests).
Aims
We examine whether extraversion, academic self-efficacy, and conscientiousness moderate the relations between teacher-assigned grades and students' standardized test scores in mathematics.
Sample
This study uses a representative sample of N = 5,919 seventh-grade students in Germany (48.8% girls; mean age: M = 12.5, SD = 0.62) who participated in a national, large-scale assessment focusing on students' academic development.
Methods
We specified structural equation models to examine the inter-relations of teacher-assigned grades with students' standardized test scores in mathematics, Big Five personality traits, and academic self-efficacy, while controlling for students' socioeconomic status, gender, and age.
Results
The correlation between teacher-assigned grades and standardized test scores in mathematics was r = .40. Teacher-assigned grades more closely related to standardized test scores when students reported higher levels of conscientiousness (beta = .05, p = .002). Students' extraversion and academic self-efficacy did not moderate the relationship between teacher-assigned grades and standardized test scores.
Conclusions
Our findings indicate that students' conscientiousness is a personality trait that seems to be important when it comes to how closely mathematics teachers align their grades to standardized test scores.