Home⇛Psychology and Education: A Multidisciplinary Journal⇛vol. 39 no. 2 (2025)

The Effects of Selective and Divided Attention on Visual Perception among College Students in Lipa City

Trixie Claire Ofenia | Chrisana Ira Capillo | Angela Ayieh Magsombol | Mikaela Nicole Pontejos | Rechel Anne Comentan | Jonas Sadiwa | Fran Cheska Nicole Dimaandal | Fairah Alexie Soleto | Jeremich Serafica | Noralyn Muria

Discipline: others in psychology

 

Abstract:

Selective and divided attention have significant impacts on visual perception. Several studies have explored how these attention types influence visual processing. However, more extensive research is needed to explore how environmental factors, like stimulus difficulty, impact selective and divided attention in educational settings. Thus, this study aimed to investigate the effects of attention on the visual perception of college students using single-factor experimental approach involving 60 participants. Results indicated that visual perception was higher under selective attention (Mn = 24.7; SD = 4.71) than divided attention (Mn = 21.7; SD = 4.79), with a mean difference of 3.76 points. Moreover, there is a very significant difference between the experimental and the control group, with a p-value of 0.002. The analysis yielded a Cohen’s d of 0.863, indicating that both selective and divided attention have a large effect size on student’s visual perception. Therefore, researchers recommend creating quiet study spaces to minimize distractions within the institution. Teachers could use visual aids and educate the students about the possible consequences of multitasking. Students can improve visual perception by highlighting key information, color-coding materials, and practicing visual exercises like board games and puzzles. Further studies could examine attention effects across different age groups and genders.



References:

  1. Agmon, G., Yahav, P. H. S., Ben-Shachar, M., & Golumbic, E. Z. (2022). Attention to speech: mapping distributed and selective attention systems. Cerebral Cortex, 32(17), 3763-3776.
  2. Andersen, S. K., & Hillyard, S. A. (2024). The time course of feature-selective attention inside and outside the focus of spatial attention. Proceedings of the National Academy of Sciences, 121(16), e2309975121.
  3. Ash, P., Collum, R. & Owens, R. (2023). A reflexive thematic analysis (RTA) examining lived experience patterns in misophonia and the usefulness of reddit as an online support network. 10.31234/osf.io/wgvju.
  4. Bater, L. & Jordan, S (2019). Selective attention. ResearchGate, www.researchgate.net/publication/334635632_Selective_Attention
  5. Bonacci, L. M., Bressler, S., Kwasa, J. A., Noyce, A. L., & Shinn-Cunningham, B. G. (2020). Effects of visual scene complexity on neural signatures of spatial attention. Frontiers in Human Neuroscience, 14, 91.
  6. Bürki, A. & Vasishth, S. (2024). Assessing effect sizes, variability, and power in the web-based study of language production. 10.21203/rs.3.rs-4520462/v1.
  7. Carrasco, M. (2011). Visual attention: The past 25 years. Vision research, 51(13), 1484-1525.
  8. Castellà, J., Pina, R., Baqués, J., & Allen, R. J. (2020). Differential effects of working memory load on priming and recognition of real images. Memory & cognition, 48(8), 1460–1471. https://doi.org/10.3758/s13421-020-01064-y
  9. Castro, S. C., Strayer, D. L., Matzke, D., & Heathcote, A. (2019). Cognitive workload measurement and modeling under divided attention. Journal of Experimental Psychology: Human Perception and Performance, 45(6), 826–839. https://doi.org/10.1037/xhp0000638
  10. Chao, W.-C., Hong, L.-Y., Hsieh, M.-C., Wang, E. M.-Y., Yang, C.-C., & Su, L.-C. (2019). Effect of correlated colour temperature and illuminance levels on user’s visual perception under LED lighting in Taiwan. Ergonomics, 63(2), 175–190. https://doi.org/10.1080/00140139.2019.1699964
  11. Chapman, A.F., Chunharas, C. & Störmer, V.S. Feature-based attention warps the perception of visual features. Sci Rep 13, 6487 (2023). https://doi.org/10.1038/s41598-023-33488-2
  12. Chen, H., & Yang, J. (2020). Multiple exposures enhance both item memory and contextual memory over time. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.565169
  13. Chen, R., & Li, L. (2022). Effects of divided attention on visual control of steering toward a goal. Journal of Experimental Psychology: Human Perception and Performance, 48(6), 597–612. https://doi.org/10.1037/xhp0001010
  14. Cheng, C., & Kibbe, M. M. (2022). Development of updating in working memory in 4–7-year- old children. Developmental Psychology, 58(5), 902–912. https://doi.org/10.1037/dev0001337
  15. Cole, S., & Balcetis, E. (2021). Motivated perception for self-regulation: How visual experience serves and is served by goals. In Advances in Experimental Social Psychology (Vol. 64, pp. 129-186). Academic Press.
  16. Dahl, M. J., Mather, M., Sander, M. C., & Werkle-Bergner, M. (2020). Noradrenergic responsiveness supports selective attention across the adult lifespan. Journal of Neuroscience, 40(22), 4372-4390
  17. DeCarlo, M., Cummings, C., & Agnelli, K. (2020). 13. Experimental design. Pressbooks. https://viva.pressbooks.pub/mswresearch/chapter/13-experimental-design/#chapter-321- section-1
  18. Enge, A., Süß, F., & Rahman, R. A. (2023). Instant effects of semantic information on visual perception. Journal of Neuroscience, 43(26), 4896-490
  19. Ersin, K., Gundogdu, O., Kaya, S. N., Aykiri, D., & Serbetcioglu, M. B. (2021). Investigation of the effects of auditory and visual stimuli on attention. Heliyon, 7(7).
  20. Evans, K. K. (2020). The role of selective attention in cross-modal interactions between auditory and visual features. Cognition, 196, 104119.
  21. Faßbender, K., Baumert, P. M., Wintergerst, M. W., Terheyden, J. H., Aslan, B., M. Harmening, W., & Ettinger, U. (2023). GABAergic involvement in selective attention. Journal of Cognitive Neuroscience, 35(6), 976-989.
  22. Fiebelkorn, I. C., & Kastner, S. (2019). Functional specialization in the attention network. Annual Review of Psychology, 71(1), 221–249. https://doi.org/10.1146/annurev-psych- 010418-103429
  23. Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage Publications Limited
  24. Fodor, J. A. (1983). The modularity of mind. Cambridge, MA: The MIT Press. https://doi.org/10.7551/mitpress/4737.001.0001
  25. Golzar, J., Noor, S., & Tajik, O. (2022). Convenience sampling. International Journal of Education & Language Studies, 1(2), 72-77.
  26. Grundler, W., & Strasburger, H. (2020). Visual attention outperforms visual-perceptual parameters required by law as an indicator of on-road driving performance. PLoS one, 15(8), e0236147.
  27. Guan, Z., Lin, M., Wu, Q., Wu, J., Chen, K., Han, H., ... & Li, C. (2023). Neural mechanisms of top-down divided and selective spatial attention in visual and auditory perception. Brain Science Advances, 9(2), 95-113.
  28. Gupta, M., Ireland, A. C., & Bordoni, B. (2022). Neuroanatomy, Visual Pathway. In StatPearls. StatPearls Publishing
  29. Hamed, S. B., & van Kerkoerle, T. (2024). The neural bases of visual attention.
  30. Hammer, C. (2011). The importance of participant demographics. American Speech-Language- Hearing Association. 20. 261. 10.1044/1058-0360(2011/ed-04).
  31. Harrison, A.H., Ling, S. & Foster, J.J. (2022). The cost of divided attention for detection of simple visual features primarily reflects limits in post-perceptual processing. Atten Percept Psychophys 85, 377–386. https://doi.org/10.3758/s13414-022-02547-7
  32. Hofheimer, J.A. (2020). Encyclopedia of infant and early childhood development (2nd ed.) (pp.
  33. 396-410).
  34. How the eyes work.(2022, April 20).National Eye Institute. https://www.nei.nih.gov/learn-about- eye-health/healthy-vision/how-eyes-work
  35. Ji, Z., Huang, H., & Wang, Z. (2021, December). The Effects of Divided Attention and Selective Attention on the Accuracy of Memory. In 2021 4th International Conference on Humanities Education and Social Sciences (ICHESS 2021) (pp. 1557-1561). Atlantis Press.
  36. Koutras, D. (2022). Investigating the association between visual perception disorders and difficulties in first reading and writing. International Journal of Progressive Sciences and Technologies, 31(2), 135-140. doi: http://dx.doi.org/10.52155/ijpsat.v31.2.4161
  37. Lappin, J. S., & Bell, H. H. (2021). Form and function in information for visual perception. i- Perception, 12(6), 20416695211053352. https://doi.org/10.1177/20416695211053352
  38. Lappin, J.S., Seiffert, A.E. & Bell, H.H. (2020). A limiting channel capacity of visual perception: Spreading attention divides the rates of perceptual processes. Atten Percept Psychophys 82, 2652–2672. https://doi.org/10.3758/s13414-020-01973-9
  39. Lev-Ari, T., Beeri, H., & Gutfreund, Y. (2022). The ecological view of selective attention. Frontiers in Integrative Neuroscience, 16, 856207.
  40. Liang, G., & Scolari, M. (2020). Limited interactions between space- and feature-based attention in visually sparse displays. Journal of Vision, 20.
  41. Liu, C., Zhang, Y., Sun, L., Gao, W., Zang, Q., & Li, J. (2022). The effect of classroom wall color on learning performance: A virtual reality experiment. In Building Simulation (Vol. 15, No. 12, pp. 2019-2030). Beijing: Tsinghua University Press.
  42. Lui, K. F., Yip, K. H., & Wong, A. C. (2021). Gender differences in multitasking experience and performance. Quarterly Journal of Experimental Psychology, 74(2), 344-362.\
  43. McLeod, S., (2018). Theories of selective attention in psychology
  44. Moerel, D., Rich, A. N., & Woolgar, A. (2024). Selective attention and decision-making have separable neural bases in space and time. Journal of Neuroscience, 44(38).
  45. Moore C. M., Pai, J., & Palmer, J. (2022). Divided attention effects in visual search are caused by objects not by space. Journal of Vision, 22(12):2-2. doi: 10.1167/jov.22.12.2
  46. Moreland, J. C., Palmer, J., & Boynton, G. M. (2020). Set-size effects in change detection depend on failures of retrieval and/or comparison and not on perception, encoding or storage. bioRxiv, 2020-01.
  47. Murphy, D. & Castel, A. (2022). Responsible attention: the effect of divided attention on metacognition and responsible remembering. Psychological Research. 87. 10.1007/s00426-022-01711-w.
  48. Noor, S., Omid, T., & Golzar, J. (2022). Simple random sampling. 1. 78-82. 10.22034/ijels.2022.162982.
  49. Oberauer, K. (2019). Working memory and attention – A conceptual analysis and review. Journal of Cognition, 2(1). https://doi.org/10.5334/joc.58
  50. Okamoto, S., Wakamatsu, K., Nakauchi, S., Kwon, J., and Sakamoto, K. (2020). Computation of sensory-affective relationships depending on material categories of pictorial stimuli. IEEE Transactions on Affective Computing, vol. 14, no. 1, doi: 10.1109/TAFFC.2020.3039684.
  51. Olipas, C. N. P., & Luciano, R. G. (2020). Understanding the impact of using countdown timer on the academic motivation and computer programming anxiety of IT students: The case of a state university in the Philippines. Online Submission, 9(3), 235-240.
  52. Ozsu, A. B., & Urgen, B. A. (2024). The role of predictive processing and perceptual load in selective visual attention: An examination with semantically salient and less salient distractors. bioRxiv, 2024-10.
  53. Pagnotta, M. F., Pascucci, D., & Plomp, G. (2022). Selective attention involves a feature-specific sequential release from inhibitory gating. Neuroimage, 246, 118782.
  54. Peng, Y., & Tullis, J. G. (2021). Dividing attention impairs metacognitive control more than monitoring. Psychonomic Bulletin & Review, 28(6), 2064-2074.
  55. Persuh, M. & Suero, G., (2020). Role of attention in visual perception. BMCC Office of Research and Scholarly Inquiry. https://openlab.bmcc.cuny.edu/research-and- scholarship/2020/05/12/role-of-attention-in-visual-perception/
  56. Pirinen, A. (2021). Reinforcement learning for active visual perception. Lund University.
  57. Popovkina, D. V., Palmer, J., Moore, C. M., & Boynton, G. M. (2021). Is there a serial bottleneck in visual object recognition? Journal of Vision, 21(3), 15. https://doi.org/10.1167/jov.21.3.15
  58. Roussy, M., Mendoza-Halliday, D., & Martinez-Trujillo, J. C. (2021). Neural substrates of visual perception and working memory: two sides of the same coin or two different coins?. Frontiers in Neural Circuits, 15, 764177.
  59. Różańska, A., & Gruszka, A. (2020). Current research trends in multitasking: a bibliometric mapping approach. Journal of Cognitive Psychology, 32(3), 278-286
  60. Rüttgens, T., Suchan, B., Wolf, O. T., & Merz, C. J. (2024). Acute stress does not modulate selective attention in a composite letter task. Stress, 27(1), 2330704.
  61. Şahin, M., & Aybek, E. (2020). Jamovi: An easy to use statistical software for the social scientists. International Journal of Assessment Tools in Education, 6(4), 670-692. https://doi.org/10.21449/ijate.661803
  62. Sharp, P. (2019). Selective attention modulates temporal processing. University of Trento. http://eprints-phd.biblio.unitn.it/3558/1/corrected_thesis_PSharp.pdf
  63. Soldan, A., Mangels, J. A., & Cooper, L. A. (2008). Effects of dividing attention during encoding on perceptual priming of unfamiliar visual objects. Memory, 16(8), 873–895. https://doi.org/10.1080/09658210802360595
  64. Szumowska, E., & Kruglanski, A. W. (2022). The psychology of getting busy: Multitasking as a consequence of goal activation. Journal of Experimental Psychology: General, 151(1), 137.
  65. Treisman, A. M., Sykes, M., & Gelade, G. (1997). Attention and Performance VI (1st ed.).
  66. Uluave, K. S. (2024). The impact of divided attention tasks on stress: Insights from heart rate variability and galvanic skin response.
  67. Wang, J., Sun, K., Cheng, T., Jiang, B., Deng, C., Zhao, Y., ... & Xiao, B. (2020). Deep high- resolution representation learning for visual recognition. IEEE transactions on pattern analysis and machine intelligence, 43(10), 3349-3364.
  68. Wang, X., Zhou, H., & Zhu, X. (2020). Attention deficits in adults with Major depressive disorder: A systematic review and meta-analysis. Asian journal of psychiatry, 53, 102359.
  69. Wei, B., Zhao, Y., Hao, K., & Gao, L. (2021). Visual sensation and perception computational models for deep learning: State of the art, challenges and prospects. arXiv preprint arXiv:2109.03391.
  70. Westfall, J., Kenny, D. A., & Judd, C. M. (2014). Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli. Journal of Experimental Psychology: General, 143(5), 2020–2045. https://doi.org/10.1037/xge0000014
  71. Wickens, C. (2021). Attention: Theory, principles, models and applications. International Journal of Human–Computer Interaction, 37(5), 403–417. https://doi.org/10.1080/10447318.2021.1874741
  72. Yang, J.. Wang, C., Jiang, B., Song, H., Meng, Q., (2020). Visual perception enabled industry intelligence: State of the art, challenges and prospects. IEEE Transactions on Industrial Informatics, doi:10.1109/TII.2020.2998818
  73. Yang, W., Li, S., Xu, J., Li, Z., Yang, X., & Ren, Y. (2020). Selective and divided attention modulates audiovisual integration in adolescents. Cognitive development, 55, 100922.
  74. Zavadil, P. P., Levitas, J., & Roundy, L. (2023). Experimental & control group | definition, difference & examples.
  75. Zivony, A., & Eimer, M. (2023). The temporal dynamics of selective attention are reflected by distractor intrusions. Scientific Reports, 13(1), 408.
  76. Zivony A., & Eimer M., (2023). Direct attention-independent expectation effects on visual perception. Journal of Vision, 23(9):4803-4803. doi: 10.1167/jov.23.9.4803

Tools


Copyright © 2025  KITE Digital Educational Solutions |  Exclusively distributed by CE-Logic