In the dynamic landscape of modern education, it is essential to understand and recognize the psychological habits that underpin students’ learning processes. These habits play a crucial role in shaping students’ learning outcomes, motivation, and overall educational experiences. This paper shifts the focus towards a more nuanced exploration of these psychological habits in learning, particularly among secondary school students. We propose an innovative assessment model that integrates multimodal data analysis with the quality function deployment theory and the subjective-objective assignment method. This model employs the G-1-entropy value method for an objective evaluation of students’ psychological learning habits. The G-1-entropy method stands out for its comprehensive, objective, and practical approach, offering valuable insights into students’ learning behaviors. By applying this method to assess the psychological aspects of learning, this study contributes to educational research and informs educational reforms. It provides a robust framework for understanding students’ learning habits, thereby aiding in the development of targeted educational strategies. The findings of this study offer strategic directions for educational management, teacher training, and curriculum development. This research not only advances theoretical knowledge in the field of educational psychology but also has practical implications for enhancing the quality of education. It serves as a scientific foundation for educators, administrators, and policymakers in shaping effective educational practices.

Anderson, J. K., Ford, T., Soneson, E., et al. (2018). A systematic review of effectiveness and cost-effectiveness of school-based identification of children and young people at risk of, or currently experiencing mental health difficulties. Psychological Medicine, 49(1), 9–19. https://doi.org/10.1017/s0033291718002490

Anniko, M. K., Boersma, K., & Tillfors, M. (2018). Sources of stress and worry in the development of stress-related mental health problems: A longitudinal investigation from early- to mid-adolescence. Anxiety, Stress, & Coping, 32(2), 155–167. https://doi.org/10.1080/10615806.2018.1549657

Baghdadi, Y., Harfouche, A. (2019). Using QFD Method for Assessing Higher Education Programs: An Examination of Key Stakeholders’ Visions. Switzerland: Springer International Publishing AG, 30, 83-98.

Bakhru, K. M. (2018). Aligning teaching methods for learning outcomes: a need for educational change in management education using quality function deployment approach. International Journal of Learning and Change, 10(1), 54. https://doi.org/10.1504/ijlc.2018.089533

Brann, K. L., Naser, S. C., Splett, J. W., et al. (2021). A mixed‐method analysis of the implementation process of universal screening in a tiered mental health system. Psychology in the Schools, 58(11), 2089–2113. https://doi.org/10.1002/pits.22579

Broglia, E., Millings, A., & Barkham, M. (2017). Challenges to addressing student mental health in embedded counselling services: a survey of UK higher and further education institutions. British Journal of Guidance & Counselling, 46(4), 441–455. https://doi.org/10.1080/03069885.2017.1370695

Broglia, E., Millings, A., & Barkham, M. (2017). The Counseling Center Assessment of Psychological Symptoms (CCAPS‐62): Acceptance, feasibility, and initial psychometric properties in a UK student population. Clinical Psychology & Psychotherapy, 24(5), 1178–1188. https://doi.org/10.1002/cpp.2070

Chen, I. H., Ahorsu, D. K., Pakpour, A. H., et al. (2020). Psychometric Properties of Three Simplified Chinese Online-Related Addictive Behavior Instruments Among Mainland Chinese Primary School Students. Frontiers in Psychiatry, 11. https://doi.org/10.3389/fpsyt.2020.00875

Chen, S. P., Chang, W. P., & Stuart, H. (2020). Self-reflection and screening mental health on Canadian campuses: validation of the mental health continuum model. BMC Psychology, 8(1). https://doi.org/10.1186/s40359-020-00446-w

Cheon, S. H., Reeve, J., Lee, Y., et al. (2019). Expanding autonomy psychological need states from two (satisfaction, frustration) to three (dissatisfaction): A classroom-based intervention study. Journal of Educational Psychology, 111(4), 685–702. https://doi.org/10.1037/edu0000306

Chong, W. H., Liem, G. A. D., Huan, V. S., et al. (2018). Student perceptions of self‐efficacy and teacher support for learning in fostering youth competencies: Roles of affective and cognitive engagement. Journal of Adolescence, 68(1), 1–11. https://doi.org/10.1016/j.adolescence.2018.07.002

Conner, J., Posner, M., & Nsowaa, B. (2022). The Relationship Between Student Voice and Student Engagement in Urban High Schools. The Urban Review, 54(5), 755–774. https://doi.org/10.1007/s11256-022-00637-2

Fisher, H. L. (2022). Editorial: The near ubiquity of comorbidity—what are the implications for children’s mental health research and practice? Journal of Child Psychology and Psychiatry, 63(5), 505–506. https://doi.org/10.1111/jcpp.13612

Herman, K. C., Reinke, W. M., Huang, F. L., et al. (2021). An investigation of the psychometric properties of the early identification system–student report in a middle school sample. School Psychology, 36(1), 34–46. https://doi.org/10.1037/spq0000414

Huang, X., Zhang, J., & Hudson, L. (2018). Impact of math self-efficacy, math anxiety, and growth mindset on math and science career interest for middle school students: the gender moderating effect. European Journal of Psychology of Education, 34(3), 621–640. https://doi.org/10.1007/s10212-018-0403-z

Huhtiniemi M, Saakslahti A, Watt A, et al. (2019). Associations among Basic Psychological Needs, Motivation and Enjoyment within Finnish Physical Education Students. J Sports Sci Med., 218(2), 239-247.

Kim, H., Park, K. H., & Park, S. (2021). Gender Differences in Lifestyle and Mental Health among Senior High School Students in South Korea. International Journal of Environmental Research and Public Health, 18(20), 10746. https://doi.org/10.3390/ijerph182010746

Kinker, P., Swarnakar, V., Singh, A. R., et al. (2022). A fuzzy Kano-QFD approach for prioritising NBA quality parameters for service quality enhancement: a case of Indian PEIs. International Journal of Quality Engineering and Technology, 8(4), 406. https://doi.org/10.1504/ijqet.2022.123498

Korpershoek, H., Canrinus, E. T., Fokkens-Bruinsma, M., Boer H. (2019). The relationships between school belonging and students ‘motivational, social-emotional, behavioural, and academic outcomes in secondary education: a meta-analytic review. Research Papers in Education, 35(1), 1-40.

Lei, H., Cui, Y., & Chiu, M. M. (2018). The Relationship between Teacher Support and Students’ Academic Emotions: A Meta-Analysis. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.02288

Lei, X., Liu, C., & Jiang, H. (2021). Mental health of college students and associated factors in Hubei of China. PLOS ONE, 16(7). https://doi.org/10.1371/journal.pone.0254183

Lustig, S., Kaess, M., Schnyder, N., et al. (2022). The impact of school-based screening on service use in adolescents at risk for mental health problems and risk-behaviour. European Child & Adolescent Psychiatry, 32(9), 1745–1754. https://doi.org/10.1007/s00787-022-01990-z

Ma, Z., Idris, S., Zhang, Y., et al. (2021). The impact of COVID-19 pandemic outbreak on education and mental health of Chinese children aged 7–15 years: an online survey. BMC Pediatrics, 21(1). https://doi.org/10.1186/s12887-021-02550-1

Magson, N. R., Freeman, J. Y. A., Rapee, R. M., et al. (2020). Risk and Protective Factors for Prospective Changes in Adolescent Mental Health during the COVID-19 Pandemic. Journal of Youth and Adolescence, 50(1), 44–57. https://doi.org/10.1007/s10964-020-01332-9

McIntyre, J. C., Worsley, J., Corcoran, R., et al. (2018). Academic and non-academic predictors of student psychological distress: the role of social identity and loneliness. Journal of Mental Health, 27(3), 230–239. https://doi.org/10.1080/09638237.2018.1437608

Molinari, L., & Mameli, C. (2017). Basic psychological needs and school engagement: a focus on justice and agency. Social Psychology of Education, 21(1), 157–172. https://doi.org/10.1007/s11218-017-9410-1

Moore, S., Long, A. C. J., Coyle, S., et al. (2023). A roadmap to equitable school mental health screening. Journal of School Psychology, 96, 57–74. https://doi.org/10.1016/j.jsp.2022.11.001

Nishio, A., Kakimoto, M., Bermardo, T. Ma. S., et al. (2020). Current situation and comparison of school mental health in ASEAN countries. Pediatrics International, 62(4), 438–443. https://doi.org/10.1111/ped.14137

Oberle, E., Ji, X. R., Guhn, M., et al. (2019). Benefits of Extracurricular Participation in Early Adolescence: Associations with Peer Belonging and Mental Health. Journal of Youth and Adolescence, 48(11), 2255–2270. https://doi.org/10.1007/s10964-019-01110-2

Reardon, T., Harvey, K., Baranowska, M., et al. (2017). What do parents perceive are the barriers and facilitators to accessing psychological treatment for mental health problems in children and adolescents? A systematic review of qualitative and quantitative studies. European Child & Adolescent Psychiatry, 26(6), 623–647. https://doi.org/10.1007/s00787-016-0930-6

Roberts, A. C., Yeap, Y. W., Seah, H. S., et al. (2019). Assessing the suitability of virtual reality for psychological testing. Psychological Assessment, 31(3), 318–328. https://doi.org/10.1037/pas0000663

Scherrer, V., & Preckel, F. (2018). Development of Motivational Variables and Self-Esteem During the School Career: A Meta-Analysis of Longitudinal Studies. Review of Educational Research, 89(2), 211–258. https://doi.org/10.3102/0034654318819127

Schwartz, K. D., Exner-Cortens, D., McMorris, C. A., et al. (2021). COVID-19 and Student Well-Being: Stress and Mental Health during Return-to-School. Canadian Journal of School Psychology, 36(2), 166–185. https://doi.org/10.1177/08295735211001653

Simms, L. J., Zelazny, K., Williams, T. F., et al. (2019). Does the number of response options matter? Psychometric perspectives using personality questionnaire data. Psychological Assessment, 31(4), 557–566. https://doi.org/10.1037/pas0000648

Singh, A. K., & Rawani, A. M. (2021). Industry oriented quality management of engineering education: an integrated QFD-TOPSIS approach. International Journal of System Assurance Engineering and Management, 13(2), 904–922. https://doi.org/10.1007/s13198-021-01360-z

Tang, Y., Wei, J., Xin, Y., et al. (2022). Curriculum design for vocational industrial robotics: the quality function deployment (QFD) approach used in China for vocational course design. SN Social Sciences, 2(5). https://doi.org/10.1007/s43545-022-00366-z

Venta, A., Cuervo, M., Bautista, A., et al. (2022). A strong contender for mental health screening in Latinx immigrant youth: Psychometric properties of the Strengths and Difficulties Questionnaire. Psychiatry Research, 316, 114780. https://doi.org/10.1016/j.psychres.2022.114780

Xiong, T., Kaltenbach, E., Yakovenko, I., et al. (2022). How to measure barriers in accessing mental healthcare? Psychometric evaluation of a screening tool in parents of children with intellectual and developmental disabilities. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-08762-0

Yahia-Berrouiguet, A., Belabid, Y. (2022). Improving the Quality of Higher Education Service by Using the Quality Function Deployment: A Case Study. Management and economics review, 7(2), 173–181. https://doi.org/10.24818/mer/2022.06-05

Zhang, C., Ye, M., Fu, Y., et al. (2020). The Psychological Impact of the COVID-19 Pandemic on Teenagers in China. Journal of Adolescent Health, 67(6), 747–755. https://doi.org/10.1016/j.jadohealth.2020.08.026

Zhou, S. J., Zhang, L. G., Wang, L. L., et al. (2020). Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19. European Child & Adolescent Psychiatry, 29(6), 749–758. https://doi.org/10.1007/s00787-020-01541-4