Bodily maps of subject-specific feelings and academic emotions among high school students

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However, the bodily manifestation of learning-related emotions, potential gender differences in these patterns, and their impact on academic performance remain unclear. We examined high school students’ bodily sensation maps (BSMs) during learning in different school subject contexts, and assessed their associations with gender and academic achievement. Methods This study mapped high school students’ BSMs across subject-specific feelings and academic emotions, examining gender differences and links with academic achievement. A total of 588 students marked body regions of increased or decreased activity on two-dimensional silhouettes in response to nine subjects and five academic emotions. Statistical analyses examined learning-related BSM patterns, gender differences, and relationships with academic performance. Results Distinct embodied profiles emerged: humanities subjects primarily activated the head and distal upper limbs, whereas science subjects engaged the head, chest, and proximal upper limbs. Positive emotions elicited widespread bodily activation, while negative emotions induced localized or global deactivation. Gender differences were minimal in learning contexts but evident for anxiety, with females showing stronger head and torso activation. BSMs were positively correlated with academic achievement (particularly in English, Physics, Chemistry, Biology, and History), suggesting that bodily responses mirror the interplay of cognitive engagement and emotional arousal. Conclusions These findings reveal systematic embodied signatures of subject-specific feelings and academic emotions, elucidating how cognitive and emotional processes are integrated in the body. They provide actionable insights for personalized, emotion-sensitive, and domain-specific educational practices. bodily maps embodied cognition academic emotions subject-specific feelings gender differences academic achievement Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Learning is the core mechanism through which individuals adapt to academic and environmental demands, shaping both cognitive development and academic success [ 1 ]. In high school, students progressively enhance their disciplinary understanding and cognitive competence through structured instruction and cumulative experience. Different academic domains engage distinct cognitive processes: science subjects such as mathematics and physics depend on logical reasoning and analytical problem-solving, whereas humanities subjects like Chinese and history emphasize comprehension, interpretation, and expression [ 2 – 4 ]. Persistent gender disparities have been documented across these domains, with boys often excelling in science and girls performing better in humanities [ 5 – 11 ]. Exploring students’ conscious emotional experiences during learning, and how these experiences differ by gender, may therefore yield critical insight into the mechanisms that underline academic development. Learning evokes a spectrum of conscious emotional experiences that shape attention, motivation, and achievement [ 12 – 14 ]. These emotions can be broadly divided into subject-specific feelings (emotion embedded in a subject) and academic emotions (emotion toward studying and achievement in general). Subject-specific feelings refer to domain-specific emotional experiences that arise when students engage with particular academic subjects. They are tightly linked to the content, demands, and cognitive style of a discipline. For example, solving a challenging physics problem may evoke feelings of tension or excitement, while reading literature may elicit curiosity or empathy. These feelings are thus context-bound, reflecting how learners emotionally experience specific subject matter. Academic emotions, in contrast, are domain-general emotional states that occur within academic contexts regardless of subject. They include emotions such as enjoyment, hope, anxiety, boredom, or pride (Pekrun, 2006), which are tied to learning, achievement, and classroom experiences rather than any particular discipline. Academic emotions influence motivation, attention, and performance across subjects [ 12 , 15 – 17 ]. Despite extensive research on the cognitive and emotional determinants of academic achievement, the embodied dimension of learning remains largely overlooked [ 18 ]. Students often exhibit salient bodily responses during learning and emotional experiences (responses that may index cognitive load, attentional engagement, and affective arousal), yet their patterns and underlying mechanisms are poorly understood. Theories of embodied cognition propose that bodily engagement externalizes cognitive processes during learning [ 19 – 24 ], while embodied emotion frameworks posit that emotional experiences arise not only from cognitive appraisal but also from bodily responses to emotional stimuli and their interpretation [ 25 – 28 ]. Within this framework, bodily sensation maps (BSMs) provide a quantifiable means to visualize and examine the embodied signatures of learning-related emotions. Prior studies have demonstrated that BSMs are stable and distinct across basic or situational emotions [ 29 , 30 ]. For instance, anger is typically associated with heightened bodily sensations in the upper limbs and chest, reflecting increased physiological arousal and readiness for action. Similarly, different cognitive processes manifest distinct embodied patterns. Memorizing tends to produce localized sensations in the head region, reflecting the activation of working memory and information retrieval processes that demand focused yet sustained mental effort. In contrast, thinking evokes broader and stronger activations across the head, extending beyond those seen during memorizing, and indicating deeper engagement of cognitive control, reasoning, and attentional processes [ 30 , 31 ]. However, their patterns across academic domains and emotions remains largely uncharted. Furthermore, potential gender modulation of these embodied responses, and their links to academic achievement, has yet to be systematically investigated. To address these gaps, we examined high school students’ BSMs during learning in different school subject contexts, and assessed their associations with gender and academic achievement. Our aims were twofold: first, to characterize BSM patterns across subject domains and academic emotions, and to test for gender differences; second, to determine whether BSM features predict academic performance, thereby elucidating how embodied experiences contribute to learning outcomes. We hypothesized that BSMs would exhibit distinct and stable configurations across subjects and academic emotional contexts; that gender would modulate these embodied patterns; and that BSM intensity or topology would be associated with academic achievement. By integrating subject-specific learning, academic emotion, and embodiment, this study advances a cognitive-emotional framework linking emotional and bodily processes to educational performance, offering a theoretical and empirical basis for personalized learning strategies. Methods Participants A total of 588 first-year high school students (341 females; age: M ± SD = 15.90 ± 0.50 years) from a mid-level school in Southwest China participated. Most were right-handed (n = 564), with the reminder left-handed (n = 24). All participants had normal or corrected-to-normal vision and no history of motor or neurological disorders, and none had previously taken part in similar experiments. Informed consent was obtained from all participants after explanation of the study aims and procedures. The study adhered to the ethical principles of the Declaration of Helsinki and was approved the ethics committee of Zhejiang University (No. 2022009). Procedure The experimental program was adapted and optimized from previous work, with the fron-end implemented in Hyper Text Markup Language (HTML) and the back-end logic in Hypertext Preprocessor (PHP) [30]. It was deployed on Alibaba Cloud servers to provide public access to the Chinese version of the experiment, with all data transmitted and stored using encrypted, isolated processes to ensure privacy. Experiments were conducted with identical computer models and standardized display settings to ensure uniform stimulus presentation. After providing informed consent, participants’ demographic and academic information was collected, including gender, age, weight, height, medical history, handedness, and recent midterm grades and class rankings. On-screen instructions guided participants through the procedures to minimize potential misunderstandings. Fifteen verbal cues served as stimuli to probe participants’ bodily representations of emotions and academic subjects: five emotions (enjoyment, hope, anger, anxiety, and boredom), nine subjects (Chinese, Mathematics, English, Physics, Chemistry, Biology, Politics, History, and Geography), and a neutral state. Each stimulus was presented once in a randomized order to control for sequence effects. During the task, participants viewed two abstract, two-dimensional human silhouettes accompanied by stimulus words in randomized order. They were instructed to reflect on their bodily sensations during specific subject-domain learning or emotional experiences. Areas of increased activity were colored on the left silhouette, and areas of decreased activity on the right silhouette ( Fig. 1A ). Trials were self-paced, with an option to reset in case of coloring errors. Coloring was performed by dragging the mouse over the body template (12-pixel tool diameter), with repeated strokes increasing opacity ( Fig. 1B ). Each silhouette contained 50,364 pixels, and resulting images were stored as matrices with intensity values from 0 to 100. Data analyses Preprocessing Data preprocessing followed established procedures [30]. Participants who left more than the mean + 2.5 SDs of body areas uncolored, or who completed fewer than 14 of 15 stimuli, were excluded. Activation and deactivation maps were combined into a single body sensation map (BSM) representing the spatial distribution of bodily activity (Fig. 1C ). Manual inspection removed artifacts such as symbolic drawings or random scribbles. After quality control, 576 valid datasets (334 females) were retained for further analyses. Statistica l analyses Statistical analyses were performed in MATLAB R2024a ( Fig. 2 ). First, BSMs for subject-specific feelings and academic emotions were constructed using one-sample t -tests, with false-discovery-rate (FDR) correction to account for multiple comparisons across the whole-body template (threshold at q < 0.05). Statistically significant regions of increased or decreased activation were visualized to represent the bodily correlates of each learning experience and emotional state. Second, sex differences were evaluated by performing one-sample t -tests on male and female BSMs separately, with FDR correction applied (threshold at q < 0.05). Independent-samples t -tests were then used to identify regions showing significant male-female differences, generating difference maps in which positive and negative values indicate greater activation in males and females, respectively. Spearman correlation coefficients were calculated between male and female difference maps under each academic subject condition to quantify the consistency and divergence of bodily response patterns. Furthermore, to examine sex-related differences across and within conditions, the number of activated and deactivated pixels was also calculated separately for each sex and condition; within-group differences were tested with Friedman’s ANOVA, and between-group differences with the Mann–Whitney U test. Finally, associations between bodily sensation and academic achievement were assessed using pixelwise generalized linear models (GLM) with FDR correction (threshold at q < 0.05). Regions with positive values indicate a significant positive correlation between bodily sensation and academic achievement, whereas regions with negative values indicate a negative correlation. Results Gender differences in academic performance After preprocessing, the final sample included 242 male participants (age 15.97 ± 0.51 years; 94% right-handed) and 334 female participants (age 15.85 ± 0.49 years; 98% right-handed). Independent-samples t -tests revealed that female participants scored significantly higher than males in Chinese, English, and Politics ( p s < .02), whereas males outperformed females in Mathematics, Physics, Chemistry, Geography, and overall academic achievement ( p s .06) ( Table 1 ). Table 1 . Gender differences in a cademic performance . Mean academic scores Male (N = 242) Female (N = 334) t p Chinese 82.42 ± 7.93 84.12 ± 7.66 -2.55 .011* Mathematics 78.98 ± 22.37 71.33 ± 20.21 4.16 < .001** English 79.79 ± 19.28 85.82 ± 19.52 -3.64 < .001** Physics 58.88 ± 15.04 50.19 ± 15.56 6.66 < .001** Chemistry 59.71 ± 15.68 54.06 ± 16.28 4.15 < .001** Biology 63.91 ± 17.85 63.37 ± 15.49 0.38 .707 Politics 53.00 ± 9.90 55.50 ± 9.41 -3.00 .003** History 72.03 ± 9.96 73.57 ± 9.45 -1.85 .065 Geography 69.58 ± 11.95 66.66 ± 10.92 2.96 .003** Total score 617.99 ± 82.58 603.97 ± 84.36 1.97 .049* * p < .05 ；** p < .01. Bodily sensation maps: General patterns High school students’ bodily sensation maps revealed subject- and emotion-specific patterns ( Fig. 3A ). Humanities subjects (Chinese, English, Politics, History) were primarily associated with increased activation in the head and distal upper limbs, accompanied by deactivations in the lower limbs. Geography, though classified as a humanities subject, exhibited a pattern more akin to the sciences (Biology). Science subjects (Physics, Chemistry, Biology) generally showed stronger activation in the head, chest, and proximal upper limbs, whereas Mathematics displayed a distinct pattern within the sciences, with increased activity in the head, upper limbs, and upper torso. Academic emotions also exhibited distinct bodily signatures. Positive emotions (hope, enjoyment) were characterized by increased activity in the head, upper limbs, and upper torso. Negative emotions differed by type: anger elicited widespread activation, anxiety selectively engaged the head and chest, boredom induced broad deactivation, and the neutral state decreased activity in the lower limbs. Bodily sensation maps: Sex-specific patterns Sex-specific analyses revealed largely similar bodily responses across academic subjects ( Fig. 3B ). Independent-samples t-tests identified a significant sex difference only for anxiety, with females showing stronger head and torso activation than males ( p s < .05, q s < .05; Fig. 3C ). Spearman correlation coefficients between male and female BSMs ( Fig. 4 ) showed the highest consistency for science subjects (Physics: Spearman r = 0.938 [0.937, 0.939], p < .001; Mathematics: Spearman r = 0.920 [0.919, 0.921], p < .001; Biology: Spearman r = 0.910 [0.908, 0.911], p < .001), whereas correlations were lower for negative and neutral emotions (Neutral: Spearman r = 0.644 [0.639, 0.649], p < .001; Anxiety: Spearman r = 0.607 [0.601, 0.612], p < .001). Analysis of the number of activated and deactivated pixels per stimulus by sex ( Fig. 5 ) indicated significant effects of both subject-specific feelings and academic emotions in males (Friedman ANOVA, χ² = 438.1026 and = 139.4389, p s < .001) and females (χ² = 643.1968 and 176.3039, p s < .001). Mann–Whitney U tests showed that, compared with males, females marked significantly more activation pixels for anxiety (U = 26683.00, Z = -6.230, p < .001, q < .05) and significantly fewer deactivation pixels for neutral emotion (U = 32082.00, Z = -3.393, p < .001, q < .05), with no significant differences for other subjects or emotions (all U < 38509.50, Z .05). Associations between bodily sensation maps and academic achievement GLM analyses further revealed modest positive associations between body sensations in the head and torso regions and academic performance in the corresponding subject domains (in particular, English, Physics, Chemistry, Biology, and History). In contrast, for academic emotions, only head activity during boredom showed a weak negative correlation with overall academic achievement ( Fig. 6 ). Discussion The present study investigated bodily sensation maps (BSMs) in high school students across different subject-specific learning contexts and academic emotional experiences, revealing both domain-specific and domain-general patterns. The findings demonstrate that the embodiment of cognitive and emotional processes conforms to the principles of embodied cognition and embodied emotion theories, which posit that cognition and affect are inherently linked with bodily states [ 19 , 21 , 22 , 24 , 28 ]. In subject-domain learning, humanities subjects such as Chinese and history primarily engaged linguistic comprehension and memory processing, reflected by activations in the head and distal upper limbs in BSMs. By contrast, science subjects such as physics and chemistry, which rely more on logical reasoning and problem solving, elicited activations in the head, torso, and proximal upper limbs. Consistent with previous research, activations in the head region may reflect high-level cognitive processing, as a variety of cognitive functions such as thinking, attention, memory, and reasoning are closely associated with head sensations [ 31 , 32 ]. Thus, the widespread head activation observed across both humanities and science learning contexts may indicate a high degree of cognitive engagement during learning. Furthermore, activations in the chest region may reflect physiological arousal, such as increased heart rate or altered breathing patterns, which are common across both positive and negative emotional experiences [ 33 ]. These subject-dependent topographies likely mirror differential cognitive demands of language-based versus analytic reasoning processes and suggest that bodily activity may index cognitive investment [ 34 – 36 ]. This interpretation accords with the embodied language comprehension framework, which emphasizes that meaning is grounded in sensorimotor representations and that cognitive processing is intrinsically linked to bodily states [ 37 – 42 ]. Distinct embodied profiles also emerged across academic emotions. Positive emotions such as hope and enjoyment were associated with widespread activation in the head, upper limbs, and torso, consistent with motivational engagement and goal-directed arousal, whereas negative states such as anxiety and boredom produced localized or global deactivations, reflecting diminished attention, avoidance tendencies, and reduced cognitive resource allocation [ 30 , 32 , 43 , 44 ]. Friedman analyses confirmed significant within-subject variability across both learning and emotional conditions, suggesting that BSMs are context-sensitive yet exhibit systematic, group-level patterns. Together, these findings reinforce the view that bodily responses serve as reliable indicators of cognitive-emotional load associated with learning. Sex-specific analyses revealed largely convergent embodied profiles across male and female students. Spearman correlations indicated particularly strong cross-gender similarity in science subjects, suggesting that both sexes recruit comparable perception-action systems under high cognitive load [ 23 , 45 , 46 ]. However, gender similarity decreased in emotional contexts: correlations were lower for neutral and negative emotions, and females showed stronger head and torso activations under anxiety—a pattern consistent with higher self-reported anxiety in females [ 47 , 48 ]. These results imply that while the embodiment of domain-specific learning experiences is largely gender-invariant, the embodiment of domain-general emotions shows sex-dependent modulation, underscoring the need for gender-sensitive approaches to academic emotional regulation. Associations between bodily activity and academic performance further revealed that activation in the head and torso correlated positively, albeit modestly, with subject-specific achievement, suggesting that embodied engagement may facilitate cognitive control and sustained attention [ 49 – 51 ]. Conversely, head deactivation during boredom was negatively associated with overall academic performance, implying that attenuated embodied engagement may signal reduced motivation or attentional withdrawal [ 52 ]. These results highlight the potential of BSMs as nonverbal indicators of learning engagement and as a window into the cognitive–emotional mechanisms underpinning academic success. Despite yielding important findings, the present study has several limitations. First, although it addressed both subject-specific learning and academic emotions, the measurement of academic emotions was limited to Pekrun’s classical five categories and did not encompass additional dimensions developed in subsequent research [ 12 – 14 , 53 – 57 ]. This may underestimate the complexity of emotional experiences and their embodied manifestations. Future studies could explore a broader range of academic emotional dimensions. Second, the cross-sectional design precludes conclusions regarding the dynamic changes of bodily responses during learning. Future research could adopt longitudinal designs combined with multimodal approaches, integrating physiological, behavioral, and classroom data, to provide a more comprehensive characterization of the dynamic embodiment of subject-specific learning and academic emotions. Furthermore, the sample was limited to high school students, so the generalizability of the findings requires verification across other educational stages. Future studies could extend the investigation to elementary and middle school students to examine the stability and variation of embodied patterns across developmental stages. In sum, high school students exhibit systematic, interpretable bodily sensation patterns across learning domains, with gender selectively modulating embodied responses under emotional conditions. Moreover, these bodily signatures relate to academic achievement, bridging the gap between cognitive–emotional processes and bodily expression. The results provide empirical support for embodied frameworks of learning and suggest practical avenues for developing responsive pedagogical strategies that integrate emotional regulation, domain-specific engagement, and individualized learning support. Future research should employ longitudinal and multimodal designs, combining physiological, behavioral, and classroom data, to elucidate the dynamic interplay between embodiment, emotion, and cognition in real-world educational settings [ 58 , 59 ]. In addition, studies could examine a broader range of academic emotional dimensions beyond Pekrun’s classical five categories and extend investigations to younger students, in order to explore developmental variations and the stability of embodied patterns across educational stages. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Zhejiang University, Department of Psychology and Behavioral Sciences (Approval No. 2022-009). Written informed consent was obtained from all participants and their parents/guardians prior to participation. Consent for publication All participants and/or their parents/guardians provided consent for publication of the data and findings. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. The analyses were conducted using MATLAB, which is publicly accessible. Custom scripts and code are available from the corresponding author upon reasonable request for research purposes. Competing interests The authors declare no competing interests. Funding This work was supported by the Fundamental Research Funds for the Central Universities (No. 226-2025-00127) to Y.P., the Humanities and Social Sciences Research Project of the Ministry of Education of China (No. 24YJC190006) to X.C., the National Natural Science Foundation of China (Nos. 62577047 and 62337001) to Y.P., and the Zhejiang Provincial Natural Science Foundation of China (No. LMS25C090002) to Y.P. Author contributions S.Z. and Y.P. developed the study concept and design. Testing and data collection was performed by S.Z. and Y.P., and S.Z. analyzed the data. S.Z. interpreted the data and drafted the manuscript, and Y.P., X.C. and X.T. provided critical revisions. All authors approved the final version of the manuscript for submission. Acknowledgements The authors thank all the participating students and teachers for their cooperation and contribution to this study. References De Houwer J, Barnes-Holmes D, Moors A. What is learning? On the nature and merits of a functional definition of learning. Psychon Bull Rev. 2013;20:631–42. https://doi.org/10.3758/s13423-013-0386-3. Reiners CS, Bliersbach M, Marniok K. The Cultural Argument for Understanding Nature of Science. Sci Educ. 2017;26:583–610. https://doi.org/10.1007/s11191-017-9912-4. Steen GJ. Genre between the humanities and the sciences. In: Callies M, Keller WR, Lohöfer A, editors. Bi-Directionality in the Cognitive Sciences: Avenues, challenges, and limitations. John Benjamins Publishing Company; 2011. p. 21–42. Zhou J. The Difference in Cognition Consistency Between the Sciences and Humanities. Genomics Proteomics Bioinformatics. 2003;1:243–6. https://doi.org/10.1016/S1672-0229(03)01030-1. Breda T, Napp C. Girls’ comparative advantage in reading can largely explain the gender gap in math-related fields. Proc Natl Acad Sci. 2019;116:15435–40. https://doi.org/10.1073/pnas.1905779116. Chan RCH. A social cognitive perspective on gender disparities in self-efficacy, interest, and aspirations in science, technology, engineering, and mathematics (STEM): the influence of cultural and gender norms. Int J STEM Educ. 2022;9:37. https://doi.org/10.1186/s40594-022-00352-0. Charles M, Harr B, Cech E, Hendley A. Who likes math where? Gender differences in eighth-graders’ attitudes around the world. Int Stud Sociol Educ. 2014. Guo J, Marsh HW, Parker PD, Hu X. Cross-Cultural Patterns of Gender Differences in STEM: Gender Stratification, Gender Equality and Gender-Equality Paradoxes. Educ Psychol Rev. 2024;36:37. https://doi.org/10.1007/s10648-024-09872-3. Marsh HW, Parker PD, Guo J, Basarkod G, Niepel C, Van Zanden B. Illusory gender-equality paradox, math self-concept, and frame-of-reference effects: New integrative explanations for multiple paradoxes. J Pers Soc Psychol. 2021;121:168–83. https://doi.org/10.1037/pspp0000306. Stoet G, Geary DC. The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education. Psychol Sci. 2018. https://doi.org/10.1177/0956797617741719. Wrigley-Asante C, Ackah CG, Frimpong LK. Gender differences in academic performance of students studying Science Technology Engineering and Mathematics (STEM) subjects at the University of Ghana. SN Soc Sci. 2023;3:12. https://doi.org/10.1007/s43545-023-00608-8. Pekrun R. The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries, and Implications for Educational Research and Practice. Educ Psychol Rev. 2006;18:315–41. https://doi.org/10.1007/s10648-006-9029-9. Pekrun R. Control-Value Theory: From Achievement Emotion to a General Theory of Human Emotions. Educ Psychol Rev. 2024;36:83. https://doi.org/10.1007/s10648-024-09909-7. Shao K, Stockinger K, Marsh HW, Pekrun R. Applying control-value theory for examining multiple emotions in L2 classrooms: Validating the Achievement Emotions Questionnaire – Second Language Learning. Lang Teach Res. 2023. https://doi.org/10.1177/13621688221144497. Bandura A. Social Cognitive Theory: An Agentic Perspective. Annu Rev Psychol. 2001;52 Volume 52, 2001:1–26. https://doi.org/10.1146/annurev.psych.52.1.1. Rodríguez-Muñoz A, Antino M, Ruiz-Zorrilla P, Ortega E. Positive emotions, engagement, and objective academic performance: A weekly diary study. Learn Individ Differ. 2021;92:102087. https://doi.org/10.1016/j.lindif.2021.102087. Tan J, Mao J, Jiang Y, Gao M. The Influence of Academic Emotions on Learning Effects: A Systematic Review. Int J Environ Res Public Health. 2021;18:9678. https://doi.org/10.3390/ijerph18189678. Pöysä S, Vasalampi K, Muotka J, Lerkkanen M-K, Poikkeus A-M, Nurmi J-E. Variation in situation-specific engagement among lower secondary school students. Learn Instr. 2018;53:64–73. https://doi.org/10.1016/j.learninstruc.2017.07.007. Khatin-Zadeh O, Farsani D, Eskandari Z, Marmolejo-Ramos F. The roles of motion, gesture, and embodied action in the processing of mathematical concepts. Front Psychol. 2022;13. https://doi.org/10.3389/fpsyg.2022.969341. Risko EF, Gilbert SJ. Cognitive Offloading. Trends Cogn Sci. 2016;20:676–88. https://doi.org/10.1016/j.tics.2016.07.002. Schaefer S. Embodied Counting: Touching Objects Reduces Errors in Counting Under Cognitive Load. J Cogn Enhanc. 2025;9:206–13. https://doi.org/10.1007/s41465-025-00321-9. Soni N, Darrow A, Luc A, Gleaves S, Schuman C, Neff H, et al. Affording embodied cognition through touchscreen and above-the-surface gestures during collaborative tabletop science learning. Int J Comput-Support Collab Learn. 2021;16:105–44. https://doi.org/10.1007/s11412-021-09341-x. Wilson M. Six views of embodied cognition. Psychon Bull Rev. 2002;9:625–36. https://doi.org/10.3758/BF03196322. Zou L, Zhang Z, Mavilidi M, Chen Y, Herold F, Ouwehand K, et al. The synergy of embodied cognition and cognitive load theory for optimized learning. Nat Hum Behav. 2025;9:877–85. https://doi.org/10.1038/s41562-025-02152-2. Damasio AR. Time-locked multiregional retroactivation: A systems-level proposal for the neural substrates of recall and recognition. Cognition. 1989;33:25–62. https://doi.org/10.1016/0010-0277(89)90005-X. Niedenthal PM. Embodying Emotion. Science. 2007;316:1002–5. https://doi.org/10.1126/science.1136930. Niedenthal PM, Winkielman P, Mondillon L, Vermeulen N. Embodiment of emotion concepts. J Pers Soc Psychol. 2009;96:1120–36. https://doi.org/10.1037/a0015574. Niedenthal PM, Wood A, Rychlowska M, Orlowska A. Embodied emotion concepts. In: The Routledge Handbook of Embodied Cognition. 2nd edition. Routledge; 2024. Herman AM, Zaremba D, Kossowski B, Marchewka A. The utility of the emBODY tool as a novel method of studying complex phenomena-related emotions. Sci Rep. 2022;12:19884. https://doi.org/10.1038/s41598-022-23734-4. Nummenmaa L, Glerean E, Hari R, Hietanen JK. Bodily maps of emotions. Proc Natl Acad Sci. 2014;111:646–51. https://doi.org/10.1073/pnas.1321664111. Nummenmaa L, Hari R, Hietanen JK, Glerean E. Maps of subjective feelings. Proc Natl Acad Sci. 2018;115:9198–203. https://doi.org/10.1073/pnas.1807390115. Novembre G, Zanon M, Morrison I, Ambron E. Bodily sensations in social scenarios: Where in the body? PLOS ONE. 2019;14:e0206270. https://doi.org/10.1371/journal.pone.0206270. Kreibig SD. Autonomic nervous system activity in emotion: A review. Biol Psychol. 2010;84:394–421. https://doi.org/10.1016/j.biopsycho.2010.03.010. Goldberg H. Growing Brains, Nurturing Minds—Neuroscience as an Educational Tool to Support Students’ Development as Life-Long Learners. Brain Sci. 2022;12:1622. https://doi.org/10.3390/brainsci12121622. Grant D, Oswick C, Hardy C. The SAGE Handbook of Organizational Discourse. 2004;:1–448. Shiang R-F, Chern C-L, Chen H-C. Embodied cognition and L2 sentence comprehension: an eye-tracking study of motor representations. Front Hum Neurosci. 2024;18. https://doi.org/10.3389/fnhum.2024.1410242. Casteel MA. The influence of motor simulations on language comprehension. Acta Psychol (Amst). 2011;138:211–8. https://doi.org/10.1016/j.actpsy.2011.06.006. de Koning BB, Wassenburg SI, Bos LT, van der Schoot M. Mental simulation of four visual object properties: similarities and differences as assessed by the sentence–picture verification task. J Cogn Psychol. 2017;29:420–32. https://doi.org/10.1080/20445911.2017.1281283. Kaschak MP, Madden CJ, Therriault DJ, Yaxley RH, Aveyard M, Blanchard AA, et al. Perception of motion affects language processing. Cognition. 2005;94:B79–89. https://doi.org/10.1016/j.cognition.2004.06.005. Kronrod A, Ackerman JM. Under-standing: How embodied states shape inference-making. Acta Psychol (Amst). 2021;215:103276. https://doi.org/10.1016/j.actpsy.2021.103276. Moreno I, de Vega M, León I. Understanding action language modulates oscillatory mu and beta rhythms in the same way as observing actions. Brain Cogn. 2013;82:236–42. https://doi.org/10.1016/j.bandc.2013.04.010. Tettamanti M, Buccino G, Saccuman MC, Gallese V, Danna M, Scifo P, et al. Listening to Action-related Sentences Activates Fronto-parietal Motor Circuits. J Cogn Neurosci. 2005;17:273–81. https://doi.org/10.1162/0898929053124965. Domschke K, Stevens S, Pfleiderer B, Gerlach AL. Interoceptive sensitivity in anxiety and anxiety disorders: An overview and integration of neurobiological findings. Clin Psychol Rev. 2010;30:1–11. https://doi.org/10.1016/j.cpr.2009.08.008. van Hooft EAJ, van Hooff MLM. The state of boredom: Frustrating or depressing? Motiv Emot. 2018;42:931–46. https://doi.org/10.1007/s11031-018-9710-6. Bradley MM, Lang PJ. Measuring emotion: The self-assessment manikin and the semantic differential. J Behav Ther Exp Psychiatry. 1994;25:49–59. https://doi.org/10.1016/0005-7916(94)90063-9. Russell JA. A circumplex model of affect. J Pers Soc Psychol. 1980;39:1161–78. https://doi.org/10.1037/h0077714. McLean CP, Anderson ER. Brave men and timid women? A review of the gender differences in fear and anxiety. Clin Psychol Rev. 2009;29:496–505. https://doi.org/10.1016/j.cpr.2009.05.003. Seo D, Ahluwalia A, Potenza MN, Sinha R. Gender Differences in Neural Correlates of Stress-Induced Anxiety. J Neurosci Res. 2017;95:115–25. https://doi.org/10.1002/jnr.23926. Barack DL, Krakauer JW. Two views on the cognitive brain. Nat Rev Neurosci. 2021;22:359–71. https://doi.org/10.1038/s41583-021-00448-6. Diamond A. Executive Functions. Annu Rev Psychol. 2013;64 Volume 64, 2013:135–68. https://doi.org/10.1146/annurev-psych-113011-143750. Hertrich I, Dietrich S, Blum C, Ackermann H. The Role of the Dorsolateral Prefrontal Cortex for Speech and Language Processing. Front Hum Neurosci. 2021;15. https://doi.org/10.3389/fnhum.2021.645209. Bekker CI, Rothmann S, Kloppers MM. The happy learner: Effects of academic boredom, burnout, and engagement. Front Psychol. 2023;13:974486. https://doi.org/10.3389/fpsyg.2022.974486. Pekrun R, Linnenbrink-Garcia L. Academic Emotions and Student Engagement. In: Christenson SL, Reschly AL, Wylie C, editors. Handbook of Research on Student Engagement. Boston, MA: Springer US; 2012. p. 259–82. https://doi.org/10.1007/978-1-4614-2018-7_12. Camacho-Morles J, Slemp GR, Pekrun R, Loderer K, Hou H, Oades LG. Activity Achievement Emotions and Academic Performance: A Meta-analysis. Educ Psychol Rev. 2021;33:1051–95. https://doi.org/10.1007/s10648-020-09585-3. Pekrun R, Marsh HW, Elliot AJ, Stockinger K, Perry RP, Vogl E, et al. A three-dimensional taxonomy of achievement emotions. J Pers Soc Psychol. 2023;124:145–78. https://doi.org/10.1037/pspp0000448. Kristina Stockinger, Markus Dresel, Herbert W. Marsh, Reinhard Pekrun. Strategies for regulating achievement emotions: Conceptualization and relations with university students’ emotions, well-being, and health. Learn Instr. 2025;98:102089. https://doi.org/10.1016/j.learninstruc.2025.102089. Wuensch M, Frenzel AC, Pekrun R, Sun L. Enjoyable for some, stressful for others? Physiological and subjective indicators of achievement emotions during adaptive versus fixed-item testing. Contemp Educ Psychol. 2025;82:102388. https://doi.org/10.1016/j.cedpsych.2025.102388. Gkintoni E, Antonopoulou H, Sortwell A, Halkiopoulos C. Challenging Cognitive Load Theory: The Role of Educational Neuroscience and Artificial Intelligence in Redefining Learning Efficacy. Brain Sci. 2025;15:203. https://doi.org/10.3390/brainsci15020203. Lyu C, Deng S. Effectiveness of embodied learning on learning performance: A meta-analysis based on the cognitive load theory perspective. Learn Individ Differ. 2024;116:102564. https://doi.org/10.1016/j.lindif.2024.102564. Additional Declarations No competing interests reported. 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11:41:12","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":124411,"visible":true,"origin":"","legend":"","description":"","filename":"a7a1306848ca44bda464d0a72b0edd021structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/6004cc22903a7f8f4be14dd1.xml"},{"id":98065244,"identity":"54dc9081-127e-4f62-86e2-9b334d451a2a","added_by":"auto","created_at":"2025-12-12 11:41:12","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":137250,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/6bbe1985ec285229e4f1a8b6.html"},{"id":98065223,"identity":"c6d1a280-5c6b-4719-b387-d9ad1c126672","added_by":"auto","created_at":"2025-12-12 11:41:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":256770,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe emBODY tool.\u003c/strong\u003e (A) Participantsindicated bodily sensations by coloring blank silhouettes: areas of increased activity on the left and decreased activity on the right. (B) Each body was represented by 50,364 data points, with activation and deactivation recorded as integer values. (C) The resulting maps were combined to create a single body sensation map for subsequent statistical analyses.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/65e9fd86bd39b2c1e0ea738b.png"},{"id":98428448,"identity":"8106beac-4243-4054-a999-ccaee8686883","added_by":"auto","created_at":"2025-12-17 16:42:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":291431,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStatistical analysis workflow\u003c/strong\u003e.\u003cem\u003e \u003c/em\u003eFlowchart summarizing the main analyses of BSM data: one-sample \u003cem\u003et\u003c/em\u003e-tests to identify bodily activation and deactivation associated with subject-specific feelings and academic emotions; independent-samples \u003cem\u003et\u003c/em\u003e-tests to compare male and female patterns; and pixelwise generalized linear models (GLMs) to examine associations with academic achievement. False discovery rate (FDR) correction was applied in all analyses.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/7304069853710d0f6b6f191c.png"},{"id":98429249,"identity":"488fbc30-fa4c-45c0-a801-1873179a6174","added_by":"auto","created_at":"2025-12-17 16:43:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":688107,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBodily sensation maps of subject-specific feelings and academic emotions among high school students\u003c/strong\u003e.\u003cem\u003e \u003c/em\u003e(A) Pixelwise t-statistics showing regions of increased (warm colors) or decreased (cool colors) activity across subject-specific feelings and academic emotions (\u003cem\u003eq\u003c/em\u003e \u0026lt; .05). (B) Maps for male (top) and female (bottom) participants. (C) Sex-difference t-test maps: warm colors indicate greater activity in males, cool colors in females (\u003cem\u003eq\u003c/em\u003e \u0026lt; .05), N.S., nonsignificant.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/4cb3a3b2694efb6d4a2ed77b.png"},{"id":98065227,"identity":"9a7ac866-f4d2-4ac9-9433-d78078a4bc47","added_by":"auto","created_at":"2025-12-12 11:41:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":190719,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpearman correlations of bodily sensations by sex\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e \u003c/em\u003eSpearman correlation coefficients between male and female BSMs are shown for each subject-specific feeling and academic emotion. Example maps depict male (left) and female (right) responses for the most similar (Physics) and least similar (Anxiety) experiences. Error bars for 95% confidence intervals are omitted due to negligible size.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/874d8c268a4906861d5efb41.png"},{"id":98429260,"identity":"742eeeff-b71a-45d5-b4ad-af8301de12e0","added_by":"auto","created_at":"2025-12-17 16:43:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":335453,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of activated and deactivated pixels by sex.\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eBox-and-whisker plots show medians (horizontal line) and interquartile ranges; whiskers extend to 1.5 × Interquartile Range, with all individual data points (including outliers) shown. * \u003cem\u003ep\u003c/em\u003e \u0026lt; .05, FDR corrected.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/1fb45e9c9546b1684531ce0c.png"},{"id":98065229,"identity":"ad929738-2991-40ba-bfdc-248f64987de4","added_by":"auto","created_at":"2025-12-12 11:41:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":361456,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGLM regression maps of bodily activity and academic achievement.\u003c/strong\u003e GLM regression maps linking bodily activity to academic achievement: activity for subject-specific feelings corresponds to subject-specific grades, and activity for academic emotions corresponds to overall performance; warm = positive, cool = negative correlations (\u003cem\u003eq\u003c/em\u003e \u0026lt; .05).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/22ec650e304b6c901c59670d.png"},{"id":104250762,"identity":"c7dd9879-a3b9-4e37-8fc9-f4bb96d45606","added_by":"auto","created_at":"2026-03-09 16:07:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2711161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8172258/v1/8b624eaf-eebc-4ca3-9f47-0f9b13c37771.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bodily maps of subject-specific feelings and academic emotions among high school students","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLearning is the core mechanism through which individuals adapt to academic and environmental demands, shaping both cognitive development and academic success [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In high school, students progressively enhance their disciplinary understanding and cognitive competence through structured instruction and cumulative experience. Different academic domains engage distinct cognitive processes: science subjects such as mathematics and physics depend on logical reasoning and analytical problem-solving, whereas humanities subjects like Chinese and history emphasize comprehension, interpretation, and expression [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Persistent gender disparities have been documented across these domains, with boys often excelling in science and girls performing better in humanities [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Exploring students\u0026rsquo; conscious emotional experiences during learning, and how these experiences differ by gender, may therefore yield critical insight into the mechanisms that underline academic development.\u003c/p\u003e\u003cp\u003eLearning evokes a spectrum of conscious emotional experiences that shape attention, motivation, and achievement [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These emotions can be broadly divided into \u003cem\u003esubject-specific feelings\u003c/em\u003e (emotion embedded in a subject) and \u003cem\u003eacademic emotions\u003c/em\u003e (emotion toward studying and achievement in general). Subject-specific feelings refer to \u003cem\u003edomain-specific\u003c/em\u003e emotional experiences that arise when students engage with particular academic subjects. They are tightly linked to the content, demands, and cognitive style of a discipline. For example, solving a challenging physics problem may evoke feelings of tension or excitement, while reading literature may elicit curiosity or empathy. These feelings are thus context-bound, reflecting how learners emotionally experience specific subject matter. Academic emotions, in contrast, are \u003cem\u003edomain-general\u003c/em\u003e emotional states that occur within academic contexts regardless of subject. They include emotions such as enjoyment, hope, anxiety, boredom, or pride (Pekrun, 2006), which are tied to learning, achievement, and classroom experiences rather than any particular discipline. Academic emotions influence motivation, attention, and performance across subjects [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite extensive research on the cognitive and emotional determinants of academic achievement, the embodied dimension of learning remains largely overlooked [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Students often exhibit salient bodily responses during learning and emotional experiences (responses that may index cognitive load, attentional engagement, and affective arousal), yet their patterns and underlying mechanisms are poorly understood. Theories of embodied cognition propose that bodily engagement externalizes cognitive processes during learning [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], while embodied emotion frameworks posit that emotional experiences arise not only from cognitive appraisal but also from bodily responses to emotional stimuli and their interpretation [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Within this framework, bodily sensation maps (BSMs) provide a quantifiable means to visualize and examine the embodied signatures of learning-related emotions. Prior studies have demonstrated that BSMs are stable and distinct across basic or situational emotions [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. For instance, anger is typically associated with heightened bodily sensations in the upper limbs and chest, reflecting increased physiological arousal and readiness for action. Similarly, different cognitive processes manifest distinct embodied patterns. Memorizing tends to produce localized sensations in the head region, reflecting the activation of working memory and information retrieval processes that demand focused yet sustained mental effort. In contrast, thinking evokes broader and stronger activations across the head, extending beyond those seen during memorizing, and indicating deeper engagement of cognitive control, reasoning, and attentional processes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, their patterns across academic domains and emotions remains largely uncharted. Furthermore, potential gender modulation of these embodied responses, and their links to academic achievement, has yet to be systematically investigated.\u003c/p\u003e\u003cp\u003eTo address these gaps, we examined high school students\u0026rsquo; BSMs during learning in different school subject contexts, and assessed their associations with gender and academic achievement. Our aims were twofold: first, to characterize BSM patterns across subject domains and academic emotions, and to test for gender differences; second, to determine whether BSM features predict academic performance, thereby elucidating how embodied experiences contribute to learning outcomes. We hypothesized that BSMs would exhibit distinct and stable configurations across subjects and academic emotional contexts; that gender would modulate these embodied patterns; and that BSM intensity or topology would be associated with academic achievement. By integrating subject-specific learning, academic emotion, and embodiment, this study advances a cognitive-emotional framework linking emotional and bodily processes to educational performance, offering a theoretical and empirical basis for personalized learning strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eParticipants\u003c/h2\u003e\n\u003cp\u003eA total of 588 first-year high school students (341 females; age: \u003cem\u003eM\u003c/em\u003e \u0026plusmn; \u003cem\u003eSD\u003c/em\u003e = 15.90 \u0026plusmn; 0.50 years) from a mid-level school in Southwest China participated. Most were right-handed (n = 564), with the reminder left-handed (n = 24). All participants had normal or corrected-to-normal vision and no history of motor or neurological disorders, and none had previously taken part in similar experiments. Informed consent was obtained from all participants after explanation of the study aims and procedures. The study adhered to the ethical principles of the Declaration of Helsinki and was approved the ethics committee of Zhejiang University (No. 2022009).\u003c/p\u003e\n\u003ch2\u003eProcedure\u003c/h2\u003e\n\u003cp\u003eThe experimental program was adapted and optimized from previous work, with the fron-end implemented in Hyper Text Markup Language (HTML) and the back-end logic in Hypertext Preprocessor (PHP) [30]. It was deployed on Alibaba Cloud servers to provide public access to the Chinese version of the experiment, with all data transmitted and stored using encrypted, isolated processes to ensure privacy. Experiments were conducted with identical computer models and standardized display settings to ensure uniform stimulus presentation.\u003c/p\u003e\n\u003cp\u003eAfter providing informed consent, participants\u0026rsquo; demographic and academic information was collected, including gender, age, weight, height, medical history, handedness, and recent midterm grades and class rankings. On-screen instructions guided participants through the procedures to minimize potential misunderstandings.\u003c/p\u003e\n\u003cp\u003eFifteen verbal cues served as stimuli to probe participants\u0026rsquo; bodily representations of emotions and academic subjects: five emotions (enjoyment, hope, anger, anxiety, and boredom), nine subjects (Chinese, Mathematics, English, Physics, Chemistry, Biology, Politics, History, and Geography), and a neutral state. Each stimulus was presented once in a randomized order to control for sequence effects.\u003c/p\u003e\n\u003cp\u003eDuring the task, participants viewed two abstract, two-dimensional human silhouettes accompanied by stimulus words in randomized order. They were instructed to reflect on their bodily sensations during specific subject-domain learning or emotional experiences. Areas of increased activity were colored on the left silhouette, and areas of decreased activity on the right silhouette (\u003cstrong\u003eFig. 1A\u003c/strong\u003e). Trials were self-paced, with an option to reset in case of coloring errors. Coloring was performed by dragging the mouse over the body template (12-pixel tool diameter), with repeated strokes increasing opacity (\u003cstrong\u003eFig. 1B\u003c/strong\u003e). Each silhouette contained 50,364 pixels, and resulting images were stored as matrices with intensity values from 0 to 100.\u003c/p\u003e\n\u003ch2\u003eData analyses\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePreprocessing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData preprocessing followed established procedures [30]. Participants who left more than the mean + 2.5 SDs of body areas uncolored, or who completed fewer than 14 of 15 stimuli, were excluded. Activation and deactivation maps were combined into a single body sensation map (BSM) representing the spatial distribution of bodily activity\u003cstrong\u003e\u0026nbsp;(Fig.\u003c/strong\u003e \u003cstrong\u003e1C\u003c/strong\u003e). Manual inspection removed artifacts such as symbolic drawings or random scribbles. After quality control, 576 valid datasets (334 females) were retained for further analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistica\u003c/strong\u003e\u003cstrong\u003el\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed in MATLAB R2024a (\u003cstrong\u003eFig. 2\u003c/strong\u003e). First, BSMs for subject-specific feelings and academic emotions were constructed using one-sample \u003cem\u003et\u003c/em\u003e-tests, with false-discovery-rate (FDR) correction to account for multiple comparisons across the whole-body template (threshold at \u003cem\u003eq\u003c/em\u003e \u0026lt; 0.05). Statistically significant regions of increased or decreased activation were visualized to represent the bodily correlates of each learning experience and emotional state.\u003c/p\u003e\n\u003cp\u003eSecond, sex differences were evaluated by performing one-sample \u003cem\u003et\u003c/em\u003e-tests on male and female BSMs separately, with FDR correction applied (threshold at \u003cem\u003eq\u003c/em\u003e \u0026lt; 0.05). Independent-samples \u003cem\u003et\u003c/em\u003e-tests were then used to identify regions showing significant male-female differences, generating difference maps in which positive and negative values indicate greater activation in males and females, respectively. Spearman correlation coefficients were calculated between male and female difference maps under each academic subject condition to quantify the consistency and divergence of bodily response patterns. Furthermore, to examine sex-related differences across and within conditions, the number of activated and deactivated pixels was also calculated separately for each sex and condition; within-group differences were tested with Friedman\u0026rsquo;s ANOVA, and between-group differences with the Mann\u0026ndash;Whitney U test.\u003c/p\u003e\n\u003cp\u003eFinally, associations between bodily sensation and academic achievement were assessed using pixelwise generalized linear models (GLM) with FDR correction (threshold at \u003cem\u003eq\u003c/em\u003e \u0026lt; 0.05). Regions with positive values indicate a significant positive correlation between bodily sensation and academic achievement, whereas regions with negative values indicate a negative correlation.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eGender differences in academic performance\u003c/h2\u003e\n\u003cp\u003eAfter preprocessing, the final sample included 242 male participants (age 15.97 \u0026plusmn; 0.51 years; 94% right-handed) and 334 female participants (age 15.85 \u0026plusmn; 0.49 years; 98% right-handed). Independent-samples \u003cem\u003et\u003c/em\u003e-tests revealed that female participants scored significantly higher than males in Chinese, English, and Politics (\u003cem\u003ep\u003c/em\u003es \u0026lt; .02), whereas males outperformed females in Mathematics, Physics, Chemistry, Geography, and overall academic achievement (\u003cem\u003ep\u003c/em\u003es \u0026lt; .05). No significant gender differences were observed in Biology or History (\u003cem\u003ep\u003c/em\u003es \u0026gt; .06) (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eGender differences in\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;a\u003c/strong\u003e\u003cstrong\u003ecademic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eperformance\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMean academic scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eMale (N = 242)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eFemale (N = 334)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eChinese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e82.42 \u0026plusmn; 7.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e84.12 \u0026plusmn; 7.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.011*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMathematics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e78.98 \u0026plusmn; 22.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e71.33 \u0026plusmn; 20.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eEnglish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e79.79 \u0026plusmn; 19.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e85.82 \u0026plusmn; 19.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePhysics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e58.88 \u0026plusmn; 15.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e50.19 \u0026plusmn; 15.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e6.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eChemistry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e59.71 \u0026plusmn; 15.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e54.06 \u0026plusmn; 16.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026lt;\u0026nbsp;.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eBiology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e63.91 \u0026plusmn; 17.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e63.37 \u0026plusmn; 15.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.707\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePolitics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e53.00 \u0026plusmn; 9.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e55.50 \u0026plusmn; 9.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.003**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eHistory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e72.03 \u0026plusmn; 9.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e73.57 \u0026plusmn; 9.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eGeography\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e69.58 \u0026plusmn; 11.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e66.66 \u0026plusmn; 10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.003**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eTotal score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e617.99 \u0026plusmn; 82.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e603.97 \u0026plusmn; 84.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e.049*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e*\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .05 ；** \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .01.\u003c/p\u003e\n\u003ch2\u003eBodily sensation maps: General patterns\u003c/h2\u003e\n\u003cp\u003eHigh school students\u0026rsquo; bodily sensation maps revealed subject- and emotion-specific patterns (\u003cstrong\u003eFig. 3A\u003c/strong\u003e). Humanities subjects (Chinese, English, Politics, History) were primarily associated with increased activation in the head and distal upper limbs, accompanied by deactivations in the lower limbs. Geography, though classified as a humanities subject, exhibited a pattern more akin to the sciences (Biology). Science subjects (Physics, Chemistry, Biology) generally showed stronger activation in the head, chest, and proximal upper limbs, whereas Mathematics displayed a distinct pattern within the sciences, with increased activity in the head, upper limbs, and upper torso.\u003c/p\u003e\n\u003cp\u003eAcademic emotions also exhibited distinct bodily signatures. Positive emotions (hope, enjoyment) were characterized by increased activity in the head, upper limbs, and upper torso. Negative emotions differed by type: anger elicited widespread activation, anxiety selectively engaged the head and chest, boredom induced broad deactivation, and the neutral state decreased activity in the lower limbs.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eBodily sensation maps: Sex-specific patterns\u003c/h2\u003e\n\u003cp\u003eSex-specific analyses revealed largely similar bodily responses across academic subjects (\u003cstrong\u003eFig. 3B\u003c/strong\u003e). Independent-samples t-tests identified a significant sex difference only for anxiety, with females showing stronger head and torso activation than males (\u003cem\u003ep\u003c/em\u003es \u0026lt; .05, \u003cem\u003eq\u003c/em\u003es \u0026lt; .05; \u003cstrong\u003eFig. 3C\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eSpearman correlation coefficients between male and female BSMs (\u003cstrong\u003eFig. 4\u003c/strong\u003e) showed the highest consistency for science subjects (Physics: Spearman \u003cem\u003er\u003c/em\u003e = 0.938 [0.937, 0.939], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Mathematics: Spearman \u003cem\u003er\u003c/em\u003e = 0.920 [0.919, 0.921], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Biology: Spearman \u003cem\u003er\u003c/em\u003e = 0.910 [0.908, 0.911], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001), whereas correlations were lower for negative and neutral emotions (Neutral: Spearman \u003cem\u003er\u003c/em\u003e = 0.644 [0.639, 0.649], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001; Anxiety: Spearman \u003cem\u003er\u003c/em\u003e = 0.607 [0.601, 0.612], \u003cem\u003ep\u003c/em\u003e \u0026lt; .001).\u003c/p\u003e\n\u003cp\u003eAnalysis of the number of activated and deactivated pixels per stimulus by sex (\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e) indicated significant effects of both subject-specific feelings and academic emotions in males (Friedman ANOVA, \u0026chi;\u0026sup2; = 438.1026 and = 139.4389, \u003cem\u003ep\u003c/em\u003e\u003cem\u003es\u003c/em\u003e \u0026lt; .001) and females (\u0026chi;\u0026sup2; = 643.1968 and 176.3039, \u003cem\u003ep\u003c/em\u003e\u003cem\u003es\u003c/em\u003e \u0026lt; .001). Mann\u0026ndash;Whitney U tests showed that, compared with males, females marked significantly more activation pixels for anxiety (U = 26683.00, Z = -6.230, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eq\u0026nbsp;\u003c/em\u003e\u0026lt; .05) and significantly fewer deactivation pixels for neutral emotion (U = 32082.00, Z = -3.393, \u003cem\u003ep\u003c/em\u003e \u0026lt; .001, \u003cem\u003eq\u003c/em\u003e \u0026lt; .05), with no significant differences for other subjects or emotions (all U \u0026lt; 38509.50, Z \u0026lt; -.016, \u003cem\u003eq\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAssociations between bodily sensation maps and academic achievement\u003c/h2\u003e\n\u003cp\u003eGLM analyses further revealed modest positive associations between body sensations in the head and torso regions and academic performance in the corresponding subject domains (in particular, English, Physics, Chemistry, Biology, and History). In contrast, for academic emotions, only head activity during boredom showed a weak negative correlation with overall academic achievement (\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e6\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study investigated bodily sensation maps (BSMs) in high school students across different subject-specific learning contexts and academic emotional experiences, revealing both domain-specific and domain-general patterns. The findings demonstrate that the embodiment of cognitive and emotional processes conforms to the principles of embodied cognition and embodied emotion theories, which posit that cognition and affect are inherently linked with bodily states [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn subject-domain learning, humanities subjects such as Chinese and history primarily engaged linguistic comprehension and memory processing, reflected by activations in the head and distal upper limbs in BSMs. By contrast, science subjects such as physics and chemistry, which rely more on logical reasoning and problem solving, elicited activations in the head, torso, and proximal upper limbs. Consistent with previous research, activations in the head region may reflect high-level cognitive processing, as a variety of cognitive functions such as thinking, attention, memory, and reasoning are closely associated with head sensations [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Thus, the widespread head activation observed across both humanities and science learning contexts may indicate a high degree of cognitive engagement during learning. Furthermore, activations in the chest region may reflect physiological arousal, such as increased heart rate or altered breathing patterns, which are common across both positive and negative emotional experiences [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These subject-dependent topographies likely mirror differential cognitive demands of language-based versus analytic reasoning processes and suggest that bodily activity may index cognitive investment [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This interpretation accords with the embodied language comprehension framework, which emphasizes that meaning is grounded in sensorimotor representations and that cognitive processing is intrinsically linked to bodily states [\u003cspan additionalcitationids=\"CR38 CR39 CR40 CR41\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDistinct embodied profiles also emerged across academic emotions. Positive emotions such as hope and enjoyment were associated with widespread activation in the head, upper limbs, and torso, consistent with motivational engagement and goal-directed arousal, whereas negative states such as anxiety and boredom produced localized or global deactivations, reflecting diminished attention, avoidance tendencies, and reduced cognitive resource allocation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Friedman analyses confirmed significant within-subject variability across both learning and emotional conditions, suggesting that BSMs are context-sensitive yet exhibit systematic, group-level patterns. Together, these findings reinforce the view that bodily responses serve as reliable indicators of cognitive-emotional load associated with learning.\u003c/p\u003e\u003cp\u003eSex-specific analyses revealed largely convergent embodied profiles across male and female students. Spearman correlations indicated particularly strong cross-gender similarity in science subjects, suggesting that both sexes recruit comparable perception-action systems under high cognitive load [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, gender similarity decreased in emotional contexts: correlations were lower for neutral and negative emotions, and females showed stronger head and torso activations under anxiety\u0026mdash;a pattern consistent with higher self-reported anxiety in females [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These results imply that while the embodiment of domain-specific learning experiences is largely gender-invariant, the embodiment of domain-general emotions shows sex-dependent modulation, underscoring the need for gender-sensitive approaches to academic emotional regulation.\u003c/p\u003e\u003cp\u003eAssociations between bodily activity and academic performance further revealed that activation in the head and torso correlated positively, albeit modestly, with subject-specific achievement, suggesting that embodied engagement may facilitate cognitive control and sustained attention [\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Conversely, head deactivation during boredom was negatively associated with overall academic performance, implying that attenuated embodied engagement may signal reduced motivation or attentional withdrawal [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. These results highlight the potential of BSMs as nonverbal indicators of learning engagement and as a window into the cognitive\u0026ndash;emotional mechanisms underpinning academic success.\u003c/p\u003e\u003cp\u003eDespite yielding important findings, the present study has several limitations. First, although it addressed both subject-specific learning and academic emotions, the measurement of academic emotions was limited to Pekrun\u0026rsquo;s classical five categories and did not encompass additional dimensions developed in subsequent research [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR54 CR55 CR56\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This may underestimate the complexity of emotional experiences and their embodied manifestations. Future studies could explore a broader range of academic emotional dimensions. Second, the cross-sectional design precludes conclusions regarding the dynamic changes of bodily responses during learning. Future research could adopt longitudinal designs combined with multimodal approaches, integrating physiological, behavioral, and classroom data, to provide a more comprehensive characterization of the dynamic embodiment of subject-specific learning and academic emotions. Furthermore, the sample was limited to high school students, so the generalizability of the findings requires verification across other educational stages. Future studies could extend the investigation to elementary and middle school students to examine the stability and variation of embodied patterns across developmental stages.\u003c/p\u003e\u003cp\u003eIn sum, high school students exhibit systematic, interpretable bodily sensation patterns across learning domains, with gender selectively modulating embodied responses under emotional conditions. Moreover, these bodily signatures relate to academic achievement, bridging the gap between cognitive\u0026ndash;emotional processes and bodily expression. The results provide empirical support for embodied frameworks of learning and suggest practical avenues for developing responsive pedagogical strategies that integrate emotional regulation, domain-specific engagement, and individualized learning support. Future research should employ longitudinal and multimodal designs, combining physiological, behavioral, and classroom data, to elucidate the dynamic interplay between embodiment, emotion, and cognition in real-world educational settings [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In addition, studies could examine a broader range of academic emotional dimensions beyond Pekrun\u0026rsquo;s classical five categories and extend investigations to younger students, in order to explore developmental variations and the stability of embodied patterns across educational stages.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Zhejiang University, Department of Psychology and Behavioral Sciences (Approval No. 2022-009). Written informed consent was obtained from all participants and their parents/guardians prior to participation.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eAll participants and/or their parents/guardians provided consent for publication of the data and findings.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. The analyses were conducted using MATLAB, which is publicly accessible. Custom scripts and code are available from the corresponding author upon reasonable request for research purposes.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Fundamental Research Funds for the Central Universities (No. 226-2025-00127) to Y.P., the Humanities and Social Sciences Research Project of the Ministry of Education of China (No. 24YJC190006) to X.C., the National Natural Science Foundation of China (Nos. 62577047 and 62337001) to Y.P., and the Zhejiang Provincial Natural Science Foundation of China (No. LMS25C090002) to Y.P.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eS.Z. and Y.P. developed the study concept and design. Testing and data collection was performed by S.Z. and Y.P., and S.Z. analyzed the data. S.Z. interpreted the data and drafted the manuscript, and Y.P., X.C. and X.T. provided critical revisions. All authors approved the final version of the manuscript for submission.\u003c/p\u003e\n\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors thank all the participating students and teachers for their cooperation and contribution to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDe Houwer J, Barnes-Holmes D, Moors A. What is learning? On the nature and merits of a functional definition of learning. Psychon Bull Rev. 2013;20:631\u0026ndash;42. https://doi.org/10.3758/s13423-013-0386-3.\u003c/li\u003e\n\u003cli\u003eReiners CS, Bliersbach M, Marniok K. The Cultural Argument for Understanding Nature of Science. Sci Educ. 2017;26:583\u0026ndash;610. https://doi.org/10.1007/s11191-017-9912-4.\u003c/li\u003e\n\u003cli\u003eSteen GJ. Genre between the humanities and the sciences. In: Callies M, Keller WR, Loh\u0026ouml;fer A, editors. Bi-Directionality in the Cognitive Sciences: Avenues, challenges, and limitations. John Benjamins Publishing Company; 2011. p. 21\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eZhou J. The Difference in Cognition Consistency Between the Sciences and Humanities. Genomics Proteomics Bioinformatics. 2003;1:243\u0026ndash;6. https://doi.org/10.1016/S1672-0229(03)01030-1.\u003c/li\u003e\n\u003cli\u003eBreda T, Napp C. Girls\u0026rsquo; comparative advantage in reading can largely explain the gender gap in math-related fields. Proc Natl Acad Sci. 2019;116:15435\u0026ndash;40. https://doi.org/10.1073/pnas.1905779116.\u003c/li\u003e\n\u003cli\u003eChan RCH. A social cognitive perspective on gender disparities in self-efficacy, interest, and aspirations in science, technology, engineering, and mathematics (STEM): the influence of cultural and gender norms. Int J STEM Educ. 2022;9:37. https://doi.org/10.1186/s40594-022-00352-0.\u003c/li\u003e\n\u003cli\u003eCharles M, Harr B, Cech E, Hendley A. Who likes math where? Gender differences in eighth-graders\u0026rsquo; attitudes around the world. Int Stud Sociol Educ. 2014.\u003c/li\u003e\n\u003cli\u003eGuo J, Marsh HW, Parker PD, Hu X. Cross-Cultural Patterns of Gender Differences in STEM: Gender Stratification, Gender Equality and Gender-Equality Paradoxes. Educ Psychol Rev. 2024;36:37. https://doi.org/10.1007/s10648-024-09872-3.\u003c/li\u003e\n\u003cli\u003eMarsh HW, Parker PD, Guo J, Basarkod G, Niepel C, Van Zanden B. Illusory gender-equality paradox, math self-concept, and frame-of-reference effects: New integrative explanations for multiple paradoxes. J Pers Soc Psychol. 2021;121:168\u0026ndash;83. https://doi.org/10.1037/pspp0000306.\u003c/li\u003e\n\u003cli\u003eStoet G, Geary DC. The Gender-Equality Paradox in Science, Technology, Engineering, and Mathematics Education. Psychol Sci. 2018. https://doi.org/10.1177/0956797617741719.\u003c/li\u003e\n\u003cli\u003eWrigley-Asante C, Ackah CG, Frimpong LK. Gender differences in academic performance of students studying Science Technology Engineering and Mathematics (STEM) subjects at the University of Ghana. SN Soc Sci. 2023;3:12. https://doi.org/10.1007/s43545-023-00608-8.\u003c/li\u003e\n\u003cli\u003ePekrun R. The Control-Value Theory of Achievement Emotions: Assumptions, Corollaries, and Implications for Educational Research and Practice. Educ Psychol Rev. 2006;18:315\u0026ndash;41. https://doi.org/10.1007/s10648-006-9029-9.\u003c/li\u003e\n\u003cli\u003ePekrun R. Control-Value Theory: From Achievement Emotion to a General Theory of Human Emotions. Educ Psychol Rev. 2024;36:83. https://doi.org/10.1007/s10648-024-09909-7.\u003c/li\u003e\n\u003cli\u003eShao K, Stockinger K, Marsh HW, Pekrun R. Applying control-value theory for examining multiple emotions in L2 classrooms: Validating the Achievement Emotions Questionnaire \u0026ndash; Second Language Learning. Lang Teach Res. 2023. https://doi.org/10.1177/13621688221144497.\u003c/li\u003e\n\u003cli\u003eBandura A. Social Cognitive Theory: An Agentic Perspective. Annu Rev Psychol. 2001;52 Volume 52, 2001:1\u0026ndash;26. https://doi.org/10.1146/annurev.psych.52.1.1.\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Mu\u0026ntilde;oz A, Antino M, Ruiz-Zorrilla P, Ortega E. Positive emotions, engagement, and objective academic performance: A weekly diary study. Learn Individ Differ. 2021;92:102087. https://doi.org/10.1016/j.lindif.2021.102087.\u003c/li\u003e\n\u003cli\u003eTan J, Mao J, Jiang Y, Gao M. The Influence of Academic Emotions on Learning Effects: A Systematic Review. Int J Environ Res Public Health. 2021;18:9678. https://doi.org/10.3390/ijerph18189678.\u003c/li\u003e\n\u003cli\u003eP\u0026ouml;ys\u0026auml; S, Vasalampi K, Muotka J, Lerkkanen M-K, Poikkeus A-M, Nurmi J-E. Variation in situation-specific engagement among lower secondary school students. Learn Instr. 2018;53:64\u0026ndash;73. https://doi.org/10.1016/j.learninstruc.2017.07.007.\u003c/li\u003e\n\u003cli\u003eKhatin-Zadeh O, Farsani D, Eskandari Z, Marmolejo-Ramos F. The roles of motion, gesture, and embodied action in the processing of mathematical concepts. Front Psychol. 2022;13. https://doi.org/10.3389/fpsyg.2022.969341.\u003c/li\u003e\n\u003cli\u003eRisko EF, Gilbert SJ. Cognitive Offloading. Trends Cogn Sci. 2016;20:676\u0026ndash;88. https://doi.org/10.1016/j.tics.2016.07.002.\u003c/li\u003e\n\u003cli\u003eSchaefer S. Embodied Counting: Touching Objects Reduces Errors in Counting Under Cognitive Load. J Cogn Enhanc. 2025;9:206\u0026ndash;13. https://doi.org/10.1007/s41465-025-00321-9.\u003c/li\u003e\n\u003cli\u003eSoni N, Darrow A, Luc A, Gleaves S, Schuman C, Neff H, et al. Affording embodied cognition through touchscreen and above-the-surface gestures during collaborative tabletop science learning. Int J Comput-Support Collab Learn. 2021;16:105\u0026ndash;44. https://doi.org/10.1007/s11412-021-09341-x.\u003c/li\u003e\n\u003cli\u003eWilson M. Six views of embodied cognition. Psychon Bull Rev. 2002;9:625\u0026ndash;36. https://doi.org/10.3758/BF03196322.\u003c/li\u003e\n\u003cli\u003eZou L, Zhang Z, Mavilidi M, Chen Y, Herold F, Ouwehand K, et al. The synergy of embodied cognition and cognitive load theory for optimized learning. Nat Hum Behav. 2025;9:877\u0026ndash;85. https://doi.org/10.1038/s41562-025-02152-2.\u003c/li\u003e\n\u003cli\u003eDamasio AR. Time-locked multiregional retroactivation: A systems-level proposal for the neural substrates of recall and recognition. Cognition. 1989;33:25\u0026ndash;62. https://doi.org/10.1016/0010-0277(89)90005-X.\u003c/li\u003e\n\u003cli\u003eNiedenthal PM. Embodying Emotion. Science. 2007;316:1002\u0026ndash;5. https://doi.org/10.1126/science.1136930.\u003c/li\u003e\n\u003cli\u003eNiedenthal PM, Winkielman P, Mondillon L, Vermeulen N. Embodiment of emotion concepts. J Pers Soc Psychol. 2009;96:1120\u0026ndash;36. https://doi.org/10.1037/a0015574.\u003c/li\u003e\n\u003cli\u003eNiedenthal PM, Wood A, Rychlowska M, Orlowska A. Embodied emotion concepts. In: The Routledge Handbook of Embodied Cognition. 2nd edition. Routledge; 2024.\u003c/li\u003e\n\u003cli\u003eHerman AM, Zaremba D, Kossowski B, Marchewka A. The utility of the emBODY tool as a novel method of studying complex phenomena-related emotions. Sci Rep. 2022;12:19884. https://doi.org/10.1038/s41598-022-23734-4.\u003c/li\u003e\n\u003cli\u003eNummenmaa L, Glerean E, Hari R, Hietanen JK. Bodily maps of emotions. Proc Natl Acad Sci. 2014;111:646\u0026ndash;51. https://doi.org/10.1073/pnas.1321664111.\u003c/li\u003e\n\u003cli\u003eNummenmaa L, Hari R, Hietanen JK, Glerean E. Maps of subjective feelings. Proc Natl Acad Sci. 2018;115:9198\u0026ndash;203. https://doi.org/10.1073/pnas.1807390115.\u003c/li\u003e\n\u003cli\u003eNovembre G, Zanon M, Morrison I, Ambron E. Bodily sensations in social scenarios: Where in the body? PLOS ONE. 2019;14:e0206270. https://doi.org/10.1371/journal.pone.0206270.\u003c/li\u003e\n\u003cli\u003eKreibig SD. Autonomic nervous system activity in emotion: A review. Biol Psychol. 2010;84:394\u0026ndash;421. https://doi.org/10.1016/j.biopsycho.2010.03.010.\u003c/li\u003e\n\u003cli\u003eGoldberg H. Growing Brains, Nurturing Minds\u0026mdash;Neuroscience as an Educational Tool to Support Students\u0026rsquo; Development as Life-Long Learners. Brain Sci. 2022;12:1622. https://doi.org/10.3390/brainsci12121622.\u003c/li\u003e\n\u003cli\u003eGrant D, Oswick C, Hardy C. The SAGE Handbook of Organizational Discourse. 2004;:1\u0026ndash;448.\u003c/li\u003e\n\u003cli\u003eShiang R-F, Chern C-L, Chen H-C. Embodied cognition and L2 sentence comprehension: an eye-tracking study of motor representations. Front Hum Neurosci. 2024;18. https://doi.org/10.3389/fnhum.2024.1410242.\u003c/li\u003e\n\u003cli\u003eCasteel MA. The influence of motor simulations on language comprehension. Acta Psychol (Amst). 2011;138:211\u0026ndash;8. https://doi.org/10.1016/j.actpsy.2011.06.006.\u003c/li\u003e\n\u003cli\u003ede Koning BB, Wassenburg SI, Bos LT, van der Schoot M. Mental simulation of four visual object properties: similarities and differences as assessed by the sentence\u0026ndash;picture verification task. J Cogn Psychol. 2017;29:420\u0026ndash;32. https://doi.org/10.1080/20445911.2017.1281283.\u003c/li\u003e\n\u003cli\u003eKaschak MP, Madden CJ, Therriault DJ, Yaxley RH, Aveyard M, Blanchard AA, et al. Perception of motion affects language processing. Cognition. 2005;94:B79\u0026ndash;89. https://doi.org/10.1016/j.cognition.2004.06.005.\u003c/li\u003e\n\u003cli\u003eKronrod A, Ackerman JM. Under-standing: How embodied states shape inference-making. Acta Psychol (Amst). 2021;215:103276. https://doi.org/10.1016/j.actpsy.2021.103276.\u003c/li\u003e\n\u003cli\u003eMoreno I, de Vega M, Le\u0026oacute;n I. Understanding action language modulates oscillatory mu and beta rhythms in the same way as observing actions. Brain Cogn. 2013;82:236\u0026ndash;42. https://doi.org/10.1016/j.bandc.2013.04.010.\u003c/li\u003e\n\u003cli\u003eTettamanti M, Buccino G, Saccuman MC, Gallese V, Danna M, Scifo P, et al. Listening to Action-related Sentences Activates Fronto-parietal Motor Circuits. J Cogn Neurosci. 2005;17:273\u0026ndash;81. https://doi.org/10.1162/0898929053124965.\u003c/li\u003e\n\u003cli\u003eDomschke K, Stevens S, Pfleiderer B, Gerlach AL. Interoceptive sensitivity in anxiety and anxiety disorders: An overview and integration of neurobiological findings. Clin Psychol Rev. 2010;30:1\u0026ndash;11. https://doi.org/10.1016/j.cpr.2009.08.008.\u003c/li\u003e\n\u003cli\u003evan Hooft EAJ, van Hooff MLM. The state of boredom: Frustrating or depressing? Motiv Emot. 2018;42:931\u0026ndash;46. https://doi.org/10.1007/s11031-018-9710-6.\u003c/li\u003e\n\u003cli\u003eBradley MM, Lang PJ. Measuring emotion: The self-assessment manikin and the semantic differential. J Behav Ther Exp Psychiatry. 1994;25:49\u0026ndash;59. https://doi.org/10.1016/0005-7916(94)90063-9.\u003c/li\u003e\n\u003cli\u003eRussell JA. A circumplex model of affect. J Pers Soc Psychol. 1980;39:1161\u0026ndash;78. https://doi.org/10.1037/h0077714.\u003c/li\u003e\n\u003cli\u003eMcLean CP, Anderson ER. Brave men and timid women? A review of the gender differences in fear and anxiety. Clin Psychol Rev. 2009;29:496\u0026ndash;505. https://doi.org/10.1016/j.cpr.2009.05.003.\u003c/li\u003e\n\u003cli\u003eSeo D, Ahluwalia A, Potenza MN, Sinha R. Gender Differences in Neural Correlates of Stress-Induced Anxiety. J Neurosci Res. 2017;95:115\u0026ndash;25. https://doi.org/10.1002/jnr.23926.\u003c/li\u003e\n\u003cli\u003eBarack DL, Krakauer JW. Two views on the cognitive brain. Nat Rev Neurosci. 2021;22:359\u0026ndash;71. https://doi.org/10.1038/s41583-021-00448-6.\u003c/li\u003e\n\u003cli\u003eDiamond A. Executive Functions. Annu Rev Psychol. 2013;64 Volume 64, 2013:135\u0026ndash;68. https://doi.org/10.1146/annurev-psych-113011-143750.\u003c/li\u003e\n\u003cli\u003eHertrich I, Dietrich S, Blum C, Ackermann H. The Role of the Dorsolateral Prefrontal Cortex for Speech and Language Processing. Front Hum Neurosci. 2021;15. https://doi.org/10.3389/fnhum.2021.645209.\u003c/li\u003e\n\u003cli\u003eBekker CI, Rothmann S, Kloppers MM. The happy learner: Effects of academic boredom, burnout, and engagement. Front Psychol. 2023;13:974486. https://doi.org/10.3389/fpsyg.2022.974486.\u003c/li\u003e\n\u003cli\u003ePekrun R, Linnenbrink-Garcia L. Academic Emotions and Student Engagement. In: Christenson SL, Reschly AL, Wylie C, editors. Handbook of Research on Student Engagement. Boston, MA: Springer US; 2012. p. 259\u0026ndash;82. https://doi.org/10.1007/978-1-4614-2018-7_12.\u003c/li\u003e\n\u003cli\u003eCamacho-Morles J, Slemp GR, Pekrun R, Loderer K, Hou H, Oades LG. Activity Achievement Emotions and Academic Performance: A Meta-analysis. Educ Psychol Rev. 2021;33:1051\u0026ndash;95. https://doi.org/10.1007/s10648-020-09585-3.\u003c/li\u003e\n\u003cli\u003ePekrun R, Marsh HW, Elliot AJ, Stockinger K, Perry RP, Vogl E, et al. A three-dimensional taxonomy of achievement emotions. J Pers Soc Psychol. 2023;124:145\u0026ndash;78. https://doi.org/10.1037/pspp0000448.\u003c/li\u003e\n\u003cli\u003eKristina Stockinger, Markus Dresel, Herbert W. Marsh, Reinhard Pekrun. Strategies for regulating achievement emotions: Conceptualization and relations with university students\u0026rsquo; emotions, well-being, and health. Learn Instr. 2025;98:102089. https://doi.org/10.1016/j.learninstruc.2025.102089.\u003c/li\u003e\n\u003cli\u003eWuensch M, Frenzel AC, Pekrun R, Sun L. Enjoyable for some, stressful for others? Physiological and subjective indicators of achievement emotions during adaptive versus fixed-item testing. Contemp Educ Psychol. 2025;82:102388. https://doi.org/10.1016/j.cedpsych.2025.102388.\u003c/li\u003e\n\u003cli\u003eGkintoni E, Antonopoulou H, Sortwell A, Halkiopoulos C. Challenging Cognitive Load Theory: The Role of Educational Neuroscience and Artificial Intelligence in Redefining Learning Efficacy. Brain Sci. 2025;15:203. https://doi.org/10.3390/brainsci15020203.\u003c/li\u003e\n\u003cli\u003eLyu C, Deng S. Effectiveness of embodied learning on learning performance: A meta-analysis based on the cognitive load theory perspective. Learn Individ Differ. 2024;116:102564. https://doi.org/10.1016/j.lindif.2024.102564.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"bodily maps, embodied cognition, academic emotions, subject-specific feelings, gender differences, academic achievement","lastPublishedDoi":"10.21203/rs.3.rs-8172258/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8172258/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eLearning is an embodied process in which emotion and cognition converge through the body\u0026rsquo;s expressive patterns. However, the bodily manifestation of learning-related emotions, potential gender differences in these patterns, and their impact on academic performance remain unclear. We examined high school students\u0026rsquo; bodily sensation maps (BSMs) during learning in different school subject contexts, and assessed their associations with gender and academic achievement.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study mapped high school students\u0026rsquo; BSMs across subject-specific feelings and academic emotions, examining gender differences and links with academic achievement. A total of 588 students marked body regions of increased or decreased activity on two-dimensional silhouettes in response to nine subjects and five academic emotions. Statistical analyses examined learning-related BSM patterns, gender differences, and relationships with academic performance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eDistinct embodied profiles emerged: humanities subjects primarily activated the head and distal upper limbs, whereas science subjects engaged the head, chest, and proximal upper limbs. Positive emotions elicited widespread bodily activation, while negative emotions induced localized or global deactivation. Gender differences were minimal in learning contexts but evident for anxiety, with females showing stronger head and torso activation. BSMs were positively correlated with academic achievement (particularly in English, Physics, Chemistry, Biology, and History), suggesting that bodily responses mirror the interplay of cognitive engagement and emotional arousal.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings reveal systematic embodied signatures of subject-specific feelings and academic emotions, elucidating how cognitive and emotional processes are integrated in the body. They provide actionable insights for personalized, emotion-sensitive, and domain-specific educational practices.\u003c/p\u003e","manuscriptTitle":"Bodily maps of subject-specific feelings and academic emotions among high school students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 11:41:07","doi":"10.21203/rs.3.rs-8172258/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-04T05:31:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-03T20:51:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-03T06:55:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T11:43:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23743823882489894332217081625324689825","date":"2026-01-22T22:34:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254037831844877063619275134477806663613","date":"2026-01-19T04:44:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318233413310945146008983336703006698476","date":"2026-01-03T11:04:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"113300286406642389592667926298667135760","date":"2025-12-24T14:38:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T00:32:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-25T14:39:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-24T11:13:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-24T11:13:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-11-21T09:36:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8b5748da-3ceb-4364-9e42-7a05f09c970f","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:05:04+00:00","versionOfRecord":{"articleIdentity":"rs-8172258","link":"https://doi.org/10.1186/s40359-026-04283-1","journal":{"identity":"bmc-psychology","isVorOnly":false,"title":"BMC Psychology"},"publishedOn":"2026-03-04 15:59:40","publishedOnDateReadable":"March 4th, 2026"},"versionCreatedAt":"2025-12-12 11:41:07","video":"","vorDoi":"10.1186/s40359-026-04283-1","vorDoiUrl":"https://doi.org/10.1186/s40359-026-04283-1","workflowStages":[]},"version":"v1","identity":"rs-8172258","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8172258","identity":"rs-8172258","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}