CoChat
Sign Up
Cited by 13Educational Environments and Student OutcomesColor perception and designFacilities and Workplace Management

The DOI matches its Crossref record; its reference list is not available.

Effects of Visual Perception of Building Materials on Human Emotional States and Cognitive Functioning in a Physical Learning Environment

Open access
Zhou, Yufeng, Zhao, Xiaochen, Feng, Yongbo, Xuan, Changzheng, Yang, Changhan, Jia, Xiaohu·2025·Buildings
DOI 10.3390/buildings15071163
Open this paper in CoChat — free accountOpen PDF

Abstract

The influence of building materials on the physical aspects of educational spaces is significant, shaping both functionality and aesthetic appeal while directly affecting the emotional and cognitive states of students. Despite its significance, this area has not been extensively explored. This study investigated the effects of the visual perception of architectural materials on emotional states and cognitive functions in learning environments. Four materials, namely, red brick, concrete, wood, and white paint, were selected for a material substitution experiment conducted via VR simulations with 46 participants. To assess these effects, eye movement data and bioelectrical responses were methodically recorded, along with the participants’ self-reported emotional states through structured questionnaires. The results indicated that settings featuring wood and red bricks significantly enhanced emotional states, fostering relaxation and positive experiences that contributed to increased creativity. Conversely, settings with concrete and white paint improved cognitive functioning and promoted emotional stability and rational thinking, which enhanced focus and educational efficiency. These findings suggest the impact of visual perception of building materials on emotional and cognitive states, emphasizing the importance of material selection in creating learning spaces that balance cognitive demands with emotional activation. This study provides valuable insights for designing conducive physical learning environments and exploring the psychological and physiological effects of architectural materials.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/buildings15071163

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

Cited by 13

Research works printed but not linked: 95

  1. Cleveland, B.; Fisher, K. The Evaluation of Physical Learning Environments: A Critical Review of the Literature. Learn. Environ. Res. 2014, 17, 1-28. [CrossRef] · DOI
  2. Choi, H.-H.; Van Merriënboer, J.J.; Paas, F. Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load. Educ. Psychol. Rev. 2014, 26, 225-244. [CrossRef] · DOI · Paper page
  3. Evans, G.W.; Stecker, R. Motivational Consequences of Environmental Stress. J. Environ. Psychol. 2004, 24, 143-165. [CrossRef] · DOI
  4. 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. [CrossRef] · DOI · Paper page
  5. Barrett, P.; Zhang, Y.; Moffat, J.; Kobbacy, K. A Holistic, Multi-Level Analysis Identifying the Impact of Classroom Design on Pupils' Learning. Build. Environ. 2013, 59, 678-689. [CrossRef] · DOI
  6. Demattè, M.L.; Zucco, G.M.; Roncato, S.; Gatto, P.; Paulon, E.; Cavalli, R.; Zanetti, M. New Insights into the Psychological Dimension of Wood-Human Interaction. Eur. J. Wood Wood Prod. 2018, 76, 1093-1100. [CrossRef] · DOI
  7. Wang, C.; Lu, W.; Ohno, R.; Gu, Z. Effect of Wall Texture on Perceptual Spaciousness of Indoor Space. Int. J. Environ. Res. Public Health 2020, 17, 4177. [CrossRef] · DOI
  8. Zhang, X.; Lian, Z.; Wu, Y. Human Physiological Responses to Wooden Indoor Environment. Physiol. Behav. 2017, 174, 27-34.
  9. Zhao, J.; Nagai, Y.; Gao, W.; Shen, T.; Fan, Y. The Effects of Interior Materials on the Restorativeness of Home Environments. Int. J. Environ. Res. Public Health 2023, 20, 6364. [CrossRef] · DOI
  10. Bertheaux, C.; Zimmermann, E.; Gazel, M.; Delanoy, J.; Raimbaud, P.; Lavoué, G. Effect of Material Properties on Emotion: A Virtual Reality Study. Front. Hum. Neurosci. 2024, 17, 1301891. [CrossRef] · DOI
  11. Coşgun, B.; Yıldırım, K.; Hidayetoglu, M.L. Effect of Wall Covering Materials on the Perception of Cafe Environments. Facilities 2022, 40, 214-232.
  12. Demers, C.; Landry, V.; Jafarian, H.; Blanchet, P. Effects of Interior Wood Finishes on the Lighting Ambiance and Materiality of Architectural Spaces. Indoor Built Environ. 2017, 27, 786-804.
  13. Liu, J.; Lughofer, E.; Zeng, X. Aesthetic Perception of Visual Textures: A Holistic Exploration Using Texture Analysis, Psychological Experiment, and Perception Modeling. Front. Comput. Neurosci. 2015, 9, 134. [CrossRef] · DOI
  14. MASUDA, M. Why Wood Is Excellent for Interior Design? From Vision Physical Point of View. In Proceedings of the 8th World Conference on Timber Engineering, Lahti, Finland, 14-17 June 2004; pp. 101-106.
  15. Burnard, M.D.; Kutnar, A. Wood and Human Stress in the Built Indoor Environment: A Review. Wood Sci. Technol. 2015, 49, 969-986.
  16. Ojala, A.; Kostensalo, J.; Viik, J.; Matilainen, H.; Wik, I.; Virtanen, L.; Muilu-Mäkelä, R. Psychological and Physiological Effects of a Wooden Office Room on Human Well-Being: Results from a Randomized Controlled Trial. J. Environ. Psychol. 2023, 89, 102059.
  17. Wastiels, L.; Schifferstein, H.N.; Heylighen, A.; Wouters, I. Red or Rough, What Makes Materials Warmer? Mater. Des. 2012, 42, 441-449.
  18. Lan, L.; Wargocki, P.; Wyon, D.P.; Lian, Z. Effects of Thermal Discomfort in an Office on Perceived Air Quality, SBS Symptoms, Physiological Responses, and Human Performance. Indoor Air 2011, 21, 376-390.
  19. Knez, I.; Hygge, S. Irrelevant Speech and Indoor Lighting: Effects on Cognitive Performance and Self-Reported Affect. Appl. Cogn. Psychol. Off. J. Soc. Appl. Res. Mem. Cogn. 2002, 16, 709-718. [CrossRef] · DOI
  20. Marx, A.; Fuhrer, U.; Hartig, T. Effects of Classroom Seating Arrangements on Children's Question-Asking. Learn. Environ. Res. 1999, 2, 249-263. [CrossRef] · DOI · Paper page
  21. China Architecture & Design; Research Group. New Building of the School of Urban Design, Wuhan University. Archit. J. 2024, 50-55. [CrossRef] · DOI
  22. Jiang, B.; Nordin, J.; Mohd Salleh, M.N. Design Preferences for Learning Spaces among Rural Primary School Students in China: A Case Study. Build. Res. Inf. 2024, 52, 1-21. [CrossRef] · DOI
  23. Wang, G.; Ye, W. The Social Response of Educational Architecture: The Design of Shizishan School Complex in Chongqing. New Archit. 2022, 40, 44-47.
  24. Zhang, Y.; Wang, F.; Dong, X. Enclosure Without Closure-Design of Huzhou Hehe Elementary School Affiliated to Hangzhou Normal University. Archit. J. 2019, 69, 80-81.
  25. Lyons, A. Materials for Architects and Builders; Routledge: London, UK, 2014.
  26. Alapieti, T.; Mikkola, R.; Pasanen, P.; Salonen, H. The Influence of Wooden Interior Materials on Indoor Environment: A Review. Eur. J. Wood Wood Prod. 2020, 78, 617-634. [CrossRef] · DOI
  27. Picard, R.W. Affective Computing: Challenges. Int. J. Hum.-Comput. Stud. 2003, 59, 55-64. [CrossRef] · DOI · Paper page
  28. Marín-Morales, J.; Llinares, C.; Guixeres, J.; Alcañiz, M. Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing. Sensors 2020, 20, 5163. [CrossRef] · DOI
  29. Baños, R.M.; Botella, C.; Alcañiz, M.; Liaño, V.; Guerrero, B.; Rey, B. Immersion and Emotion: Their Impact on the Sense of Presence. Cyberpsychol. Behav. 2004, 7, 734-741. [CrossRef] · DOI
  30. Zhang, Y.; Liu, H.; Kang, S.-C.; Al-Hussein, M. Virtual Reality Applications for the Built Environment: Research Trends and Opportunities. Autom. Constr. 2020, 118, 103311. [CrossRef] · DOI
  31. Ergan, S.; Radwan, A.; Zou, Z.; Tseng, H.; Han, X. Quantifying Human Experience in Architectural Spaces with Integrated Virtual Reality and Body Sensor Networks. J. Comput. Civ. Eng. 2019, 33, 04018062. [CrossRef] · DOI
  32. Kim, S.; Yun, B.Y.; Choi, J.Y.; Kim, Y.U.; Kim, S. Quantification of Visual Thermal Perception Changes in a Wooden Interior Environment Using Physiological Responses and Immersive Virtual Environment. Build. Environ. 2023, 240, 110420. [CrossRef] · DOI
  33. Asad, M.M.; Naz, A.; Churi, P.; Tahanzadeh, M.M. Virtual Reality as Pedagogical Tool to Enhance Experiential Learning: A Systematic Literature Review. Educ. Res. Int. 2021, 2021, 7061623.
  34. Yin, J.; Zhu, S.; MacNaughton, P.; Allen, J.G.; Spengler, J.D. Physiological and Cognitive Performance of Exposure to Biophilic Indoor Environment. Build. Environ. 2018, 132, 255-262.
  35. Llinares Millan, C.; Higuera-Trujillo, J.L.; Montañana i Aviñó, A.; Torres, J.; Sentieri, C. The Influence of Classroom Width on Attention and Memory: Virtual-Reality-Based Task Performance and Neurophysiological Effects. Build. Res. Inf. 2021, 49, 813-826.
  36. Harley, J.M.; Bouchet, F.; Azevedo, R. Measuring Learners' Co-Occurring Emotional Responses during Their Interaction with a Pedagogical Agent in MetaTutor. In Intelligent Tutoring Systems, Proceedings of the 11th International Conference, ITS 2012, Chania, Greece, 14-18 June 2012; Proceedings 11; Springer: Berlin/Heidelberg, Germany, 2012; pp. 40-45.
  37. Pekrun, R. Emotion and Achievement during Adolescence. Child Dev. Perspect. 2017, 11, 215-221.
  38. Carruthers, P. The Cognitive Functions of Language. Behav. Brain Sci. 2002, 25, 657-674.
  39. Baig, M.; Kavakli, M. A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems. Multimodal Technol. Interact. 2019, 3, 37. [CrossRef] · DOI · Paper page
  40. Reaves, J.; Flavin, T.; Mitra, B.; Mahantesh, K.; Nagaraju, V. Assessment and Application of EEG: A Literature Review. J. Appl. Bioinform. Comput. Biol. 2021, 10, 7.
  41. Healey, J. Physiological sensing of emotion. In The Oxford Handbook of Affective Computing;
  42. Calvo, R.A., D'Mello, S., Gratch, J., Kappas, A., Eds.; Oxford University Press: Oxford, UK, 2014; p. 204.
  43. Sirois, S.; Brisson, J. Pupillometry. Wiley Interdiscip. Rev. Cogn. Sci. 2014, 5, 679-692. [CrossRef] · DOI
  44. Cruz-Garza, J.G.; Darfler, M.; Rounds, J.D.; Gao, E.; Kalantari, S. EEG-Based Investigation of the Impact of Classroom Design on Cognitive Performance of Students. arXiv 2021, arXiv:2102.03629. · arXiv
  45. Pijeira-Díaz, H.J.; Drachsler, H.; Kirschner, P.A.; Järvelä, S. Profiling Sympathetic Arousal in a Physics Course: How Active Are Students? J. Comput. Assist. Learn. 2018, 34, 397-408.
  46. Aranberri Ruiz, A.; Nevado, B.; Migueles Seco, M.; Aritzeta Galán, A. Heart Rate Variability Biofeedback Intervention Programme to Improve Attention in Primary Schools. Appl. Psychophysiol. Biofeedback 2024, 49, 651-664. [PubMed]
  47. Cai, Y.; Li, X.; Li, J. Emotion Recognition Using Different Sensors, Emotion Models, Methods and Datasets: A Comprehensive Review. Sensors 2023, 23, 2455. [CrossRef] [PubMed] · DOI
  48. Horvers, A.; Tombeng, N.; Bosse, T.; Lazonder, A.W.; Molenaar, I. Detecting Emotions through Electrodermal Activity in Learning Contexts: A Systematic Review. Sensors 2021, 21, 7869. [CrossRef] · DOI
  49. GB 50189-2015; Code for Design of Educational Buildings. China Standards Press: Beijing, China, 2015.
  50. Faul, F.; Erdfelder, E.; Lang, A.-G.; Buchner, A. G* Power 3: A Flexible Statistical Power Analysis Program for the Social, Behavioral, and Biomedical Sciences. Behav. Res. Methods 2007, 39, 175-191.
  51. Shield, B.M.; Dockrell, J.E. The Effects of Noise on Children at School: A Review. Build. Acoust. 2003, 10, 97-116.
  52. Pashler, H. Dual-Task Interference in Simple Tasks: Data and Theory. Psychol. Bull. 1994, 116, 220.
  53. Weijs, M.L.; Jonauskaite, D.; Reutimann, R.; Mohr, C.; Lenggenhager, B. Effects of Environmental Colours in Virtual Reality: Physiological Arousal Affected by Lightness and Hue. R. Soc. Open Sci. 2023, 10, 230432.
  54. Greene, S.; Thapliyal, H.; Caban-Holt, A. A Survey of Affective Computing for Stress Detection: Evaluating Technologies in Stress Detection for Better Health. IEEE Consum. Electron. Mag. 2016, 5, 44-56.
  55. Benedek, M.; Kaernbach, C. A Continuous Measure of Phasic Electrodermal Activity. J. Neurosci. Methods 2010, 190, 80-91.
  56. Van Der Mee, D.; Gevonden, M.; Westerink, J.H.; De Geus, E. Validity of Electrodermal Activity-Based Measures of Sympathetic Nervous System Activity from a Wrist-Worn Device. Int. J. Psychophysiol. 2021, 168, 52-64. [CrossRef] [PubMed] · DOI
  57. Herborn, K.A.; Graves, J.L.; Jerem, P.; Evans, N.P.; Nager, R.; McCafferty, D.J.; McKeegan, D.E. Skin Temperature Reveals the Intensity of Acute Stress. Physiol. Behav. 2015, 152, 225-230. [CrossRef] [PubMed] · DOI
  58. Ernst, G. Heart-Rate Variability-More than Heart Beats? Front. Public Health 2017, 5, 240. [CrossRef] [PubMed] · DOI · Paper page
  59. Niemic, C. Studies of Emotion: A Theoretical and Empirical Review of Psychophysiological Studies of Emotion. J. Undergrad. Res. 2002, 1, 15-18.
  60. Alarcao, S.M.; Fonseca, M.J. Emotions Recognition Using EEG Signals: A Survey. IEEE Trans. Affect. Comput. 2017, 10, 374-393. [CrossRef] · DOI · Paper page
  61. Henry, J.C. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. Neurology 2006, 67, 2092. [CrossRef] · DOI · Paper page
  62. Jatupaiboon, N.; Pan-Ngum, S.; Israsena, P. Emotion Classification Using Minimal EEG Channels and Frequency Bands. In Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE), Khon Kaen, Thailand, 29-31 May 2013; IEEE: Piscataway, NJ, USA, 2013; pp. 21-24.
  63. Liu, Y.; Sourina, O.; Nguyen, M.K. Real-Time EEG-Based Emotion Recognition and Its Applications. In Transactions on Computa- tional Science XII Special Issue on Cyberworlds; Springer: Berlin/Heidelberg, Germany, 2011; pp. 256-277.
  64. Choi, D.; Sekiya, T.; Minote, N.; Watanuki, S. Relative Left Frontal Activity in Reappraisal and Suppression of Negative Emotion: Evidence from Frontal Alpha Asymmetry (FAA). Int. J. Psychophysiol. 2016, 109, 37-44. [CrossRef] · DOI
  65. Harmon-Jones, E.; Gable, P.A. On the Role of Asymmetric Frontal Cortical Activity in Approach and Withdrawal Motivation: An Updated Review of the Evidence. Psychophysiology 2018, 55, e12879. [CrossRef] · DOI
  66. Niu, H.; Zhai, Y.; Huang, Y.; Wang, X.; Wang, X. Investigating the Short-Term Cognitive Abilities under Local Strong Thermal Radiation through EEG Measurement. Build. Environ. 2022, 224, 109567. [CrossRef] · DOI
  67. Ma, X.; Li, Y.; Li, Y.; Zheng, Y.; Hong, B. Effects of Outdoor Activity Intensities on College Students' Indoor Thermal Perception and Cognitive Performance. J. Build. Eng. 2024, 87, 109017. [CrossRef] · DOI
  68. Mavros, P.; J Wälti, M.; Nazemi, M.; Ong, C.H.; Hölscher, C. A Mobile EEG Study on the Psychophysiological Effects of Walking and Crowding in Indoor and Outdoor Urban Environments. Sci. Rep. 2022, 12, 18476. [CrossRef] [PubMed] · DOI
  69. Carter, B.T.; Luke, S.G. Best Practices in Eye Tracking Research. Int. J. Psychophysiol. 2020, 155, 49-62. [CrossRef] [PubMed] · DOI · Paper page
  70. Lim, J.Z.; Mountstephens, J.; Teo, J. Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges. Sensors 2020, 20, 2384. [CrossRef] · DOI
  71. Skaramagkas, V.; Ktistakis, E.; Manousos, D.; Kazantzaki, E.; Tachos, N.S.; Tripoliti, E.; Fotiadis, D.I.; Tsiknakis, M. eSEE-d: Emotional State Estimation Based on Eye-Tracking Dataset. Brain Sci. 2023, 13, 589. [CrossRef] · DOI
  72. Schubert, T.; Friedmann, F.; Regenbrecht, H. Decomposing the Sense of Presence: Factor Analytic Insights. In Proceedings of the 2nd International Workshop on Presence, Colchester, UK, 6-7 April 1999; University of Essex: Colchester, UK, 1999; Volume 1999.
  73. Fleming, R.W. Material Perception. Annu. Rev. Vis. Sci. 2017, 3, 365-388. [CrossRef] · DOI
  74. Russell, J.A. A Circumplex Model of Affect. J. Personal. Soc. Psychol. 1980, 39, 1161. [CrossRef] · DOI · Paper page
  75. Kreibig, S.D. Autonomic Nervous System Activity in Emotion: A Review. Biol. Psychol. 2010, 84, 394-421. [CrossRef] · DOI · Paper page
  76. Sugenoya, J.; Iwase, S.; Mano, T.; Ogawa, T. Identification of Sudomotor Activity in Cutaneous Sympathetic Nerves Using Sweat Expulsion as the Effector Response. Eur. J. Appl. Physiol. Occup. Physiol. 1990, 61, 302-308. [CrossRef] · DOI
  77. Leonidou, C.; Panayiotou, G. Can We Predict Experiential Avoidance by Measuring Subjective and Physiological Emotional Arousal? Curr. Psychol. 2022, 41, 7215-7227. [CrossRef] · DOI
  78. Egger, M.; Ley, M.; Hanke, S. Emotion Recognition from Physiological Signal Analysis: A Review. Electron. Notes Theor. Comput. Sci. 2019, 343, 35-55. [CrossRef] · DOI
  79. Kuzinas, A.; Noiret, N.; Bianchi, R.; Laurent, É. The Effects of Image Hue and Semantic Content on Viewer's Emotional Self-Reports, Pupil Size, Eye Movements, and Skin Conductance Response. Psychol. Aesthet. Creat. Arts 2016, 10, 360.
  80. Ismail, W.W.; Hanif, M.; Mohamed, S.; Hamzah, N.; Rizman, Z.I. Human Emotion Detection via Brain Waves Study by Using Electroencephalogram (EEG). Int. J. Adv. Sci. Eng. Inf. Technol. 2016, 6, 1005-1011. [CrossRef] · DOI
  81. Lipovac, D.; Burnard, M.D. Effects of Visual Exposure to Wood on Human Affective States, Physiological Arousal and Cognitive Performance: A Systematic Review of Randomized Trials. Indoor Built Environ. 2021, 30, 1021-1041.
  82. Elliot, A.J. Color and Psychological Functioning: A Review of Theoretical and Empirical Work. Front. Psychol. 2015, 6, 127893.
  83. Li, J.; Wu, J.; Lam, F.; Zhang, C.; Kang, J.; Xu, H. Effect of the Degree of Wood Use on the Visual Psychological Response of Wooden Indoor Spaces. Wood Sci. Technol. 2021, 55, 1485-1508. [CrossRef] · DOI
  84. Appelhans, B.M.; Luecken, L.J. Heart Rate Variability as an Index of Regulated Emotional Responding. Rev. Gen. Psychol. 2006, 10, 229-240.
  85. Gullett, N.; Zajkowska, Z.; Walsh, A.; Harper, R.; Mondelli, V. Heart Rate Variability (HRV) as a Way to Understand Associations between the Autonomic Nervous System (ANS) and Affective States: A Critical Review of the Literature. Int. J. Psychophysiol. 2023, 192, 35-42. [CrossRef] · DOI
  86. Pham, T.; Lau, Z.J.; Chen, S.A.; Makowski, D. Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial. Sensors 2021, 21, 3998. [CrossRef] · DOI
  87. Wong, C.H.; Aziz, A.A. Perceptions of Youngsters on Interior Space Quality in Relation to Materiality and Spatial Design. Int. J. Built Environ. Sustain. 2021, 8, 103-119. [CrossRef] · DOI
  88. Subramanian, R.; Shankar, D.; Sebe, N.; Melcher, D. Emotion Modulates Eye Movement Patterns and Subsequent Memory for the Gist and Details of Movie Scenes. J. Vis. 2014, 14, 31.
  89. Wan, Q.; Li, X.; Zhang, Y.; Song, S.; Ke, Q. Visual Perception of Different Wood Surfaces: An Event-Related Potentials Study. Ann. For. Sci. 2021, 78, 25. [CrossRef] · DOI
  90. Haji, F.A.; Rojas, D.; Childs, R.; de Ribaupierre, S.; Dubrowski, A. Measuring Cognitive Load: Performance, Mental Effort and Simulation Task Complexity. Med. Educ. 2015, 49, 815-827. [CrossRef] [PubMed] · DOI
  91. Ahmad, N.; Jamin, A.; Beta, R.M.D.M.; Ismail, S.; Sakarji, S.R.; Zain, Z.M. The Importance of Office Layout for Employee Productivity. Din. Pendidik. 2020, 15, 164-171. [CrossRef] · DOI
  92. Xiong, L.; Huang, X.; Li, J.; Mao, P.; Wang, X.; Wang, R.; Tang, M. Impact of Indoor Physical Environment on Learning Efficiency in Different Types of Tasks: A 3 × 4 × 3 Full Factorial Design Analysis. Int. J. Environ. Res. Public Health 2018, 15, 1256. [CrossRef] · DOI
  93. Vischer, J.C. The Effects of the Physical Environment on Job Performance: Towards a Theoretical Model of Workspace Stress. Stress Health J. Int. Soc. Investig. Stress 2007, 23, 175-184. [CrossRef] · DOI · Paper page
  94. Ross, M.; Mason, G.J. The Effects of Preferred Natural Stimuli on Humans' Affective States, Physiological Stress and Mental Health, and the Potential Implications for Well-Being in Captive Animals. Neurosci. Biobehav. Rev. 2017, 83, 46-62. [CrossRef] · DOI
  95. Häyrinen, L.; Toppinen, A.; Toivonen, R. Finnish Young Adults' Perceptions of the Health, Well-Being and Sustainability of Wooden Interior Materials. Scand. J. For. Res. 2020, 35, 394-402. [CrossRef · DOI

Metadata

Authors
Zhou, Y., Zhao, X., Feng, Y., Xuan, C., Yang, C., & Jia, X.
Affiliations
  • Inner Mongolia University of Technology (CN)
  • Beijing University of Civil Engineering and Architecture (CN)
Corresponding author
Jia, Xiaohu
ORCID
Venue
Buildings
Publisher
MDPI AG
Published
2025-04-02
Volume
15
Issue
7
Pages
1163
ISSN
2075-5309 (ISSN-L)
DOI
10.3390/buildings15071163
OpenAlex
W4409096976
Cited by
13
References
0
Citations by year
2026: 9 · 2025: 4
FWCI
40.63
Type
journal article
Language
en
Open access
Licence
Locations
  • Buildings (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
First-Class Discipline Research Special College Team Project titled “Grassland Human Settlements Construction System and Key Technologies” (YLXKZX-NGD-004)
Topics
  • Social Sciences › Education › Educational Environments and Student Outcomes
  • Social Sciences › Psychology › Social Psychology › Color perception and design
  • Physical Sciences › Engineering › Architecture › Facilities and Workplace Management
Keywords
building materials, visual perception, learning environment, emotional state, cognitive function, wood, red brick, concrete, white paint, material substitution, virtual reality simulation, eye movements, creativity, focus, school design

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Effects of Visual Perception of Building Materials on Human Emotional States and Cognitive Functioning in a Physical Learning Environment. https://app.cochat.ai/papers/10.3390/buildings15071163
The paper
Zhou, Y., Zhao, X., Feng, Y., Xuan, C., Yang, C., & Jia, X. (2025). Effects of Visual Perception of Building Materials on Human Emotional States and Cognitive Functioning in a Physical Learning Environment. Buildings. https://doi.org/10.3390/buildings15071163