Details
| Original language | English |
|---|---|
| Article number | 103213 |
| Journal | Teaching and teacher education |
| Volume | 97 |
| Early online date | 17 Oct 2020 |
| Publication status | Published - Jan 2021 |
Abstract
Teachers need to continuously monitor students’ engagement in classrooms, but novice teachers have difficulties paying attention to individual behavioral cues in all learners. To investigate these interaction processes in more detail, we re-analyzed eye-tracking data from preservice teachers teaching simulated learners who engaged in different behaviors (Stürmer, Seidel, Müller, Häusler, & Cortina, 2017). With a new methodological approach, we synchronized the data with a continuous annotation of observable student behavior and conducted time series analysis on 3646 s of video material. Results indicate that novice teachers’ attention is attracted most often when learners show (inter)active learning-related behavior.
Keywords
- Mobile eye-tracking research, Multinomial regression, Student behavior, Teacher-student interaction, Teachers’ attention, Time series analysis
ASJC Scopus subject areas
- Social Sciences(all)
- Education
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In: Teaching and teacher education, Vol. 97, 103213, 01.2021.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - How does learners’ behavior attract preservice teachers’ attention during teaching?
AU - Goldberg, Patricia
AU - Schwerter, Jakob
AU - Seidel, Tina
AU - Müller, Katharina
AU - Stürmer, Kathleen
N1 - Funding Information: Patricia Goldberg and Jakob Schwerter are doctoral students at the LEAD Graduate School & Research Network [GSC1028], which was funded within the framework of the Excellence Initiative of the German federal and state governments. This work was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) , grant number PR 473/6-3 .
PY - 2021/1
Y1 - 2021/1
N2 - Teachers need to continuously monitor students’ engagement in classrooms, but novice teachers have difficulties paying attention to individual behavioral cues in all learners. To investigate these interaction processes in more detail, we re-analyzed eye-tracking data from preservice teachers teaching simulated learners who engaged in different behaviors (Stürmer, Seidel, Müller, Häusler, & Cortina, 2017). With a new methodological approach, we synchronized the data with a continuous annotation of observable student behavior and conducted time series analysis on 3646 s of video material. Results indicate that novice teachers’ attention is attracted most often when learners show (inter)active learning-related behavior.
AB - Teachers need to continuously monitor students’ engagement in classrooms, but novice teachers have difficulties paying attention to individual behavioral cues in all learners. To investigate these interaction processes in more detail, we re-analyzed eye-tracking data from preservice teachers teaching simulated learners who engaged in different behaviors (Stürmer, Seidel, Müller, Häusler, & Cortina, 2017). With a new methodological approach, we synchronized the data with a continuous annotation of observable student behavior and conducted time series analysis on 3646 s of video material. Results indicate that novice teachers’ attention is attracted most often when learners show (inter)active learning-related behavior.
KW - Mobile eye-tracking research
KW - Multinomial regression
KW - Student behavior
KW - Teacher-student interaction
KW - Teachers’ attention
KW - Time series analysis
UR - http://www.scopus.com/inward/record.url?scp=85092627258&partnerID=8YFLogxK
U2 - 10.1016/j.tate.2020.103213
DO - 10.1016/j.tate.2020.103213
M3 - Article
AN - SCOPUS:85092627258
VL - 97
JO - Teaching and teacher education
JF - Teaching and teacher education
SN - 0742-051X
M1 - 103213
ER -