Arbeitspapier

The effect of teacher characteristics on students' science achievement

Using data from TIMSS 2015, an international large-scale assessment of student skills, I investigate the effect of teacher characteristics on students' science achievement. My identification strategy exploits the feature that in many education systems different science domains (physics, biology, chemistry, and earth science) are taught by different teachers. The availability of students' test scores as well as teachers' questionnaires for each of these domains allows me to implement a withinstudent approach which controls for unobserved student heterogeneity. I find a positive and significant effect of teacher specialization in the specific science domain on students' results, equivalent to 1.7% of a standard deviation. Holding a Master's degree, pedagogical preparation and teaching experience have no significant effect. Teachers' experience has a negative impact on the extent to which students like to study a subject or find teaching engaging.

Sprache
Englisch

Erschienen in
Series: ifo Working Paper ; No. 348

Klassifikation
Wirtschaft
Analysis of Education
Education: Other
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Human Capital; Skills; Occupational Choice; Labor Productivity
Thema
Teachers
student achievement
teacher characteristics
education production function
TIMSS

Ereignis
Geistige Schöpfung
(wer)
Sancassani, Pietro
Ereignis
Veröffentlichung
(wer)
ifo Institute - Leibniz Institute for Economic Research at the University of Munich
(wo)
Munich
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Sancassani, Pietro
  • ifo Institute - Leibniz Institute for Economic Research at the University of Munich

Entstanden

  • 2021

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