1. Introduction

Building on eye-tracking and cognitive perspectives, teacher attention refers to the selective allocation of cognitive resources to classroom events that teachers perceive as instructionally relevant (Witt et al., 2024). This multidimensional construct encompasses cognitive, affective, and behavioral foci (Hamre et al., 2013), aligning with the global shift toward cultivating well-rounded learners equipped with 21st-century competencies through student-centered education (UNESCO, 2021).

However, how this multidimensional attention manifests varies substantially across contexts. In high-stakes systems, some teachers prioritize content delivery and behavioral monitoring (Au, 2007), while others attend to students' cognitive engagement and learning processes (Chaudhuri et al., 2022). Increasingly, teachers also focus on students' emotional needs, cultivating supportive classroom climates (Ruzek et al., 2016). These attentional orientations often coexist and interact dynamically, reflecting the context-dependent nature of teacher attention.

Prior research has largely examined isolated aspects of attention—such as caring and noticing—using teacher-centered methods like eye-tracking or video analysis (König et al., 2022). Yet students' perceptions of teacher attention, which more directly shape their motivation and learning, remain underexplored. Moreover, most studies investigate separate dimensions rather than examining how different attentional foci combine into meaningful patterns in authentic classrooms.

The present study addresses these gaps by employing latent profile analysis (LPA) to identify distinct profiles of teacher attention as perceived by students and examining how these configurations relate to students' holistic development. This approach offers a unique vantage point for understanding how instructional focus is experienced in real learning environments.

2. Theoretical Framework

We operationalize teacher attention as the selective allocation of teachers' verbal expressions toward students during instructional dialogue, encompassing content guidance, relational support, and classroom management. This conceptualization emphasizes behavioral manifestations as perceived by students.

Drawing on achievement goal theory (AGT), we distinguish three primary attentional dimensions. Performance-oriented teachers’ direct attention toward observable academic outcomes—grades, accuracy, and test performance—emphasizing external evaluation (Elliot & Church, 1997). Mastery-oriented teachers focus on students' cognitive processes, reasoning strategies, and understanding (Throndsen & Turmo, 2012). Additionally, teachers may attend to students' personal and socioemotional development, fostering psychologically safe climates (Wentzel, 2009).

While AGT integrates cognitive and affective aims under mastery-oriented goals, these domains represent distinct constructs in classroom practice. The present study extends AGT by differentiating: (1) Attention to learning outcomes (performance-oriented focus), (2) Attention to learning processes (cognitive mastery-oriented focus), and (3) Attention to students' personal lives (affective/socioemotional focus).

Research demonstrates that teacher attention significantly impacts academic achievement (Chan et al., 2025), motivation and self-efficacy Guo et al., 2025), and behavioral engagement (Sherin et al., 2011). However, these effects have been studied in isolation. Our framework proposes that these attentional dimensions combine into distinct profiles that differentially influence student outcomes across developmental domains (see Figure 1).

3. Research Questions

To address existing gaps, this study is guided by three research questions:

RQ1: What distinct profiles of teacher attention do students perceive in classroom settings?

RQ2: How do students' academic, motivational, emotional, and behavioral outcomes differ across these attention profiles?

RQ3: Within each teacher attention profile, how do motivational and emotional–behavioral factors influence students' academic achievement?

By employing a person-centered approach through LPA, this study moves beyond variable-centered analyses to reveal how different configurations of teacher attention relate to students' comprehensive development, offering implications for both theory and practice in teacher professional development and educational policy.

Figure 1. The Research Framework of This Study

4. Methods 4.1 Participants and Sampling Data were drawn from the 2024 Region Education Quality Assessment Project (REAP), conducted across 1,837 primary schools in 129 counties in a southern Chinese province. We employed a two-stage stratified sampling design, randomly selecting 85% of schools in each district or county in accordance with stratified sampling requirements (Johnson & Christensen, 2019). The sample targeted fourth-grade students in spring 2024 and is representative of the province's overall fourth-grade population. Of 54,396 participating students, 53,703 valid responses were retained after data cleaning (28,909 male [53.8%]; 24,794 females [46.2%]). 4.2 Instruments All instruments underwent rigorous reliability and validity testing during development. Teacher attention was assessed through student perceptions across three dimensions: attention to outcomes (e.g., "The teacher cares whether my scores have improved"), processes (e.g., "The teacher encourages me to develop independent thinking"), and lives (e.g., "The teacher is concerned about my emotional well-being"). Items used a five-point Likert scale, reverse-coded so higher scores indicated greater attention. Academic factors included standardized mathematics performance and problem-solving ability, assessed through tests developed based on National Curriculum Standards. Test development followed systematic procedures including expert review, cognitive interviews, pilot testing (n=30), pretesting (n=300), and international expert evaluation. Scores were scaled with M=500, SD=100. Motivational factors encompassed learning interest, confidence, internal motivation, and pressure, measured via validated scales (α=0.607-0.931). Emotional and behavioral factors included subjective well-being (9 items, 7-point scale), teacher-student relationship (5 items), and smartphone addiction (5 items, 4-point scale). All scales demonstrated acceptable reliability (Cronbach's α≥0.607) and construct validity (CFI≥0.912, TLI≥0.877). Although RMSEA values for some scales exceeded 0.08, they were retained given acceptable CFI/TLI values and strong content validity. Robustness checks excluding weaker measures yielded consistent results. 4.3 Procedures and Analysis Students completed an 80-minute paper-based mathematics test followed by a 20-minute online questionnaire. Tests were scored by trained graduate students achieving 95% inter-rater reliability. Professional data services handled data entry and verification. Latent Profile Analysis (LPA) was conducted using R to identify optimal teacher attention profiles based on the three attention dimensions. Model fit was evaluated using log-likelihood, AIC, BIC, sample-adjusted BIC, and entropy, with lower information criteria and higher entropy (>0.80) indicating better fit. Following the elbow criterion when fit indices diverged (Nylund et al., 2007), we selected the optimal model and classified students accordingly. Profile differences across academic, motivational, and emotional-behavioral outcomes were examined using ANOVA and post-hoc tests in SPSS 27.

5. Key Findings This large-scale study (N=26,512 Chinese elementary students) examined how teachers' attentional orientations cluster into distinct profiles and their associations with student outcomes across academic, motivational, emotional, and behavioral domains. 5.1 Three Distinct Teacher Attention Profiles Latent profile analysis revealed three teacher attention types: (1) Outcome-Oriented (14.6%), emphasizing test results and performance; (2) Average-Oriented (35.5%), showing moderate attention across all dimensions; and (3) Process- and Emotion-Oriented (49.9%), prioritizing learning processes and students' emotional lives. Notably, attention to learning processes and personal lives consistently co-occurred, suggesting these dimensions may represent a unified student-oriented construct contrasting with performance-oriented attention. 5.2 Differential Impact on Student Development Students under Process- and Emotion-Oriented teachers demonstrated significantly superior outcomes: higher problem-solving ability (M=37.36 vs. 35.24), learning interest (M=4.21 vs. 3.24), intrinsic motivation (M=4.28 vs. 3.51), and subjective well-being (M=12.51 vs. 10.28), alongside lower academic pressure (M=1.85 vs. 2.39) and smartphone addiction (M=1.55 vs. 1.91) compared to Outcome-Oriented classrooms. Mathematics achievement remained comparable between Process-Emotion-Oriented and Outcome-Oriented groups, indicating that process-focused attention supports academic performance while simultaneously enhancing holistic development. 5.3 Moderating Role of Teacher Attention Teacher attention profiles moderated the motivation-achievement relationship. Motivational factors explained 8.2% of achievement variance under Process- and Emotion-Oriented teachers versus only 2.5% under Outcome-Oriented teachers, suggesting that process-focused attention amplifies motivation's academic impact by creating autonomy-supportive learning environments. 6. Implications These findings challenge stereotypes of East Asian education as narrowly performance-focused and demonstrate that teacher attention operates through dual cognitive-affective pathways. Professional development should cultivate process- and emotion-oriented attention through reflective practice and emotional intelligence training. By integrating Achievement Goal Theory and Self-Determination Theory, this study provides a theoretically grounded framework showing that quality of teacher attention—not merely its presence—decisively shapes both cognitive and socioemotional student development.

Witt, J., Schorer, J., Loffing, F., & Roden, I. (2024). Eye-tracking research on teachers’ professional vision: A scoping review. Teaching and Teacher Education, 144, 104568. Hamre, B. K., Pianta, R. C., Downer, J. T., DeCoster, J., Jones, S. M., Brown, J. L., … & Cappella, E. (2013). Teaching through interactions: Testing a developmental framework of teacher effectiveness in over 4,000 classrooms. American Educational Research Journal, 50(4), 686–722. UNESCO. (2021). Education for sustainable development: A roadmap. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000374802.locale=fr Au, W. (2007). High-stakes testing and curricular control: A qualitative meta synthesis. Educational Researcher, 36(5), 258–267. Chaudhuri, S., Muhonen, H., Pakarinen, E., & Lerkkanen, M. K. (2022). Teachers' visual focus of attention in relation to students' basic academic skills and teachers' individual support for students: An eye-tracking study. Learning and Individual Differences, 98, 102179. Ruzek, E. A., Hafen, C. A., Allen, J. P., Gregory, A., Mikami, A. Y., & Pianta, R. C. (2016). How teacher emotional support motivates students: The mediating roles of perceived peer relatedness, autonomy support, and competence. Learning and Instruction, 42, 95-103. König, J., Santagata, R., Scheiner, T., Adleff, A.-K., Yang, X., & Kaiser, G. (2022). Teacher noticing: A systematic literature review of conceptualizations, research designs, and findings on learning to notice. Educational Research Review, 36, 100453. Elliot, A. J., & Church, M. (1997). A Hierarchical Model of Approach and Avoidance Achievement Motivation. Journal of Personality & Social Psychology, 72(01), 218-232. Throndsen, I., & Turmo, A. (2012). Primary mathematics teachers’ goal orientations and student achievement. Instructional Science, 41(2):307-322. Wentzel, K. R. (2009). Students' relationships with teachers as motivational contexts. In K. R. Wenzel & A. Wigfield (Eds.), Handbook of motivation at school (pp. 301–322). New York, NY: Routledge/Taylor & Francis Group. Chan, K, K, H., Jan van driel, S, J., & Hu, X. (2025). Does Teacher Noticing Matter for Students’ Science Content Learning Outcomes? Evidence From a Large-Scale Empirical Study. Journal of Teacher Education. Guo, W., Wang, J., Li, N. et al. The impact of teacher emotional support on learning engagement among college students mediated by academic self-efficacy and academic resilience. Scientific Reports, 15, 3670 (2025). Sherin, M.G., Russ, R. S., & Colestock, A. A. (2011). Accessing mathematics teachers’ in-the-moment noticing: Seeing through teachers’ eyes. New York, NY: Routledge. Johnson, R. B., & Christensen, L. (2019). Educational research: Quantitative, qualitative, and mixed approaches (7th ed.). SAGE Publications.