Wendy Symes

Background: Previous research has consistently shown that students’ math motivation declines across the school years. However, less is known about individual differences in these developmental trajectories. Aim: This study investigated the development of students’ math self-concept of abilities, intrinsic value, utility value and emotional cost from Grades 4 to 8 at the average level and by identifying distinct growth trajectory profiles. Profile membership was further related to gender and performance. Sample: The sample comprised 875 Finnish students (53 % girls) from Grades 4 to 8 using an accelerated longitudinal design. Method: Latent growth curve models and growth mixture modeling were utilized. Gender differences were analyzed using the 3-step approach and differences in math performance were examined using the BCH method.Results: On average, self-concept of abilities, intrinsic value, and utility value declined whereas emotional cost increased over time. Three trajectory profiles were identified: Positive declining reflected the normative developmental pattern, while students in the Struggling profile showed lower initial motivation, increasing emotional cost, and the lowest math performance. Further, students in the Fading interest profile, predominantly boys, maintained high self-concept and performance despite low/moderate utility value and steeply declining intrinsic value. Conclusion: The average developmental trends concealed individual differences in students’ motivational development. While most students followed the expected decline, distinct profiles showed that motivation can develop differently across students and have different implications for academic performance.

Introduction: The rapid advancement of artificial intelligence (AI) has created new opportunities in educational research, particularly in the efficient analysis of complex social interactions within classrooms. One promising area involves the classification of teachers' motivational messages. Traditionally, such assessments have relied on self‐reports and observer evaluations, which require a lot of staff and time resources. Recently, large language models (LLMs) have been employed to classify teachers' motivational messages, offering novel, less labour‐intensive approaches for classification. Aims: Building on these recent developments, this work presents a comprehensive literature overview exploring the applications, potential, and limitations of using LLMs to classify teachers' motivational messages. Results: The present comprehensive literature overview indicates that the use of LLMs for classifying teachers' motivational messages is a promising yet still emerging field of research. Recent studies have applied LLMs in innovative ways, drawing on established motivational theories and employing novel classification techniques, such as zero‐shot and few‐shot prompting or fine‐tuning, to classify motivational messages. Open questions remain, particularly concerning the structure, quantity, and quality of annotated material. Discussion: Whereas recent studies have demonstrated the potential of LLMs to offer scalable and time‐efficient alternatives for classifying motivational messages in the classroom, several challenges persist. These include concerns related to the quality and quantity of training data, model generalisability, the ability to capture the complexity of classroom interactions, and biases involved in integrating LLMs as a classification method. This comprehensive literature overview provides practical recommendations for the responsible use of LLMs in educational research and school practice.

Background: Recent studies have examined the relation between teacher motivation, motivational messages and student learning but are limited to an achievement‐related context, primarily using survey data. Moreover, our understanding of the relation between various teacher characteristics, such as teacher self‐efficacy (TSE), and their motivational message use remains limited. Aims: Our study tested whether teacher speech can be classified into self‐determination (SDT)‐based motivational messages and reliably assessed with a large language model (LLM). Additionally, we analysed the relation between pre‐service TSE and their motivational message use. Sample: For our first aim, we used human‐rater annotations from 119 pre‐service teachers' classroom recordings. For our second aim, we used data from 103 pre‐service teachers (52.69% female; M _age = 22.98, SD _age = 3.26, Min _age = 19, Max _age = 34) who participated in a survey and were video‐recorded while teaching. Methods: First, we manually classified pre‐service teachers' motivational messages based on transcripts and used human‐rater annotations to fine‐tune an LLM. Second, we analysed the relation between pre‐service TSE and motivational message use. Results and Conclusions: The fine‐tuned LLM demonstrated promising performance in assessing SDT‐based motivational messages but needs further refining to assess thwarting messages. The analysis with human annotation showed that pre‐service TSE for classroom management positively affected the frequency of relatedness‐supportive messages. Pre‐service TSE for student engagement increased the likelihood of never using a competence‐ or relatedness‐thwarting message. Pre‐service TSE for instructional strategies reduced the frequency of autonomy‐supportive messages. LLM‐based analyses showed slightly different results but did not contradict human annotation‐based analyses.

Background: Achievement emotions are important for mathematical achievement. However, it is currently unclear how specific combinations of emotions—and their associated control and value appraisals—relate to mathematics performance, especially in younger students. Aims: The aims of this study were to (i) identify heterogeneous profiles of control, value and achievement emotions (enjoyment, boredom and anxiety) experienced during primary‐school mathematics lessons, and to explore how profile membership related to (ii) mathematics test scores and (iii) gender. Sample: Our sample comprised 883 students (50% girls, M _age = 9.34 years, SD = .48) from 23 primary schools in England. Methods: Data were collected longitudinally over one academic year. Students completed mathematics tests at T ₁ and T ₃ , and self‐reported their control, value and achievement emotions in mathematics lessons at T ₂ . A latent profile analysis was conducted to identify profiles of appraisals and emotions. To validate the profiles, T ₃ mathematics test scores and gender were included as covariates of profile membership. Results: Three profiles were identified: The Positive profile, Negative profile and Mixed profile. Students in the Positive profile had significantly higher mathematics test scores at T ₃ than students in the Mixed profile. Being a girl increased the likelihood of belonging to the Mixed or Negative profile relative to the Positive profile. Conclusions: Primary school students' control and value appraisals and achievement emotions co‐occur in line with the theoretical assumptions of CVT. Combinations of emotions should be considered when exploring the impact of emotions on student learning and achievement in mathematics.

Reflecting on teaching experience is meaningful in teacher education because it enables student teachers to evaluate their professional behaviours in the classroom and to develop new instructional strategies. Little is known, however, about the motivational aspects of the reflection process, such as self-efficacy for reflection. Self-efficacy is an important resource in teacher education which relates negatively to stress and burnout, and positively to professional behaviour. This longitudinal intervention study with data from N = 600 student teachers investigates how self-efficacy for reflection can be enhanced over the course of one semester. Our findings show that student teachers’ self-efficacy increased significantly in an intervention group in which student teachers systematically reflected on teaching situations in the context of micro-teaching experiences. There was no increase in self-efficacy in the control group in which student teachers did not teach in schools, nor systematically reflect. The increase in self-efficacy for reflection in the intervention group was moderated by previous pedagogical experiences in teaching of student teachers. Our findings are discussed for further development in teacher training.