Project Details
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Interaction II: teachers' attentional and diagnostic processes of cognitive and motivational-affective student characteristics

Subject Area General and Domain-Specific Teaching and Learning
Term from 2012 to 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 225239286
 
Final Report Year 2024

Final Report Abstract

The project Interaction II provides substantial insights into teachers’ attentional processes and their ability to observe and diagnose learner characteristics in the classroom, using Eye Movement Tracking (EMT) as the main research tool. One of the key findings was that experienced teachers, in contrast to novices, showed a focus on specific learner profiles that required pedagogical intervention, such as students who appeared disinterested, underestimated their abilities, or were struggling. This suggests a refined ability among experienced teachers to identify and prioritize students who might benefit most from their guidance. In addition, the study examined teachers' diagnostic processes and found that experienced teachers used a wider range of valid behavioral, cognitive, and motivational-affective cues to diagnose student profiles. Novice teachers, on the other hand, relied primarily on more directly observable indicators such as hand raising and the quality of student responses. The project also pioneered the study of systematic relationships between teacher actions, such as initiating interactions with students, and the subsequent attentional processes involved in monitoring student engagement. Methodologically, the project introduced significant advances in EMT to teacher research. Teacher gaze patterns were found to vary systematically across classroom sub-events, with more apparent expert-novice differences in scenes where students worked individually. The introduction of the Gaze Relational Index (GRI) based on mobile EMT data also marked a significant improvement in the sensitive measurement of teachers' visual expertise. In addition, the project contributed to the EMT field by developing guidelines for creating Areas of Interest (AOIs) and attempting to automate this process, thereby promoting more valid and reliable research. Furthermore, scanpath analysis was recognized as a powerful tool for understanding visual attention and cognitive processing, particularly relevant in the diagnostic process of student behavior. Finally, the use of Epistemic Network Analysis (ENA) proved invaluable in visualizing, exploring, and contrasting the complex relationships between teachers’ levels of experience and their use of diagnostically relevant student cues, thereby significantly advancing the field of EMT-based and multimodal teacher research.

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