Teacher Use of Motivational Messages in the Classroom

• Applicant: Professorin Dr. Rebecca Lazarides
• Subject Area: General and Domain-Specific Teaching and Learning
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 549301331

Teachers’ motivational beliefs are a key component of teachers’ professional competence because they guide and influence their attitudes, goal setting, decision making processes and emotional experiences. A large body of research demonstrates the relevance of a range of teacher motivational beliefs on student outcomes (e.g., Han & Gao, 2023; Klassen & Tze, 2014). However, there is limited research exploring the psychological and instructional mechanisms through which teachers’ motivational beliefs are transmitted to their students. The proposed research project seeks to address this gap by drawing on situated expectancy-value theory (SEVT; Eccles & Wigfield, 2020) to explore how teachers’ motivational beliefs influence students’ motivational outcomes via the use of motivational messages. SEVT proposes that socializers (including teachers) influence the motivational beliefs of students through their beliefs and support behaviours (Eccles & Wigfield, 2020). There is a growing body of evidence suggesting that the use of motivational messages may be a specific teacher support behaviour that is influenced by teachers’ own motivational beliefs (Falcon et al., 2023). Motivational messages have further been shown to affect students’ motivation (Putwain & Symes, 2014; Symes & Putwain, 2016). Yet, although it is known that teachers’ motivational messages are affected by teachers’ motivational beliefs, and in turn, shape students’ motivation, until now, research has not explored whether teacher use of motivational messages is a mechanism that explains why certain teachers’ motivational beliefs influence students’ motivation. We plan to address this research gap by examining the longitudinally mediated links between teacher and students’ motivations through teachers’ motivational message use in class. To assess the type and frequency of motivational messages used, we will use audio-recordings of teachers’ verbal messages during their regular classroom practice, and self-report questionnaires to assess students’ perceptions of these messages. We will use innovative AI-based methods, namely large language models (LLMs), to reliably and accurately identify and code the motivational messages used by teachers. This will allow us to make use of large quantities of naturalistic data to gain deeper insight into the process of motivational transmission in authentic classrooms settings.

• DFG Programme: Research Grants
• International Connection: United Kingdom
• Cooperation Partner: Professor Dr. Dave Putwain
• Co-Investigators: Dr. Eejain Huang; Dr. Yindong Wang