Journals / Turkish Journal of Special Education Research and Practice / 2026 / Cilt: 8 Sayı: 2

Cognitive Load Theory in Special Education: A Concept Analysis of Its Meaning, Attributes, and Educational Applications

Özel Eğitimde Bilişsel Yük Kuramı: Anlamı, Temel Özellikleri ve Eğitsel Uygulamalarına İlişkin Bir Kavram Analizi

Mehtab Hussain(Allama Iqbal Open University, Islamabad, Pakistan)0009-0009-5811-9630
Pages
1–25
Publication Date
2026-08-14
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⚡ TL;DR(Too Long; Didn't Read)

The analysis concludes with a proposed operational definition intended to give researchers and practitioners a clearer, more consistent way to discuss cognitive load when working with learners who have disabilities.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Cognitive Load Theory (CLT) is one of the most widely cited frameworks in educational psychology, yet its meaning shifts noticeably when it is applied in the special education literature.
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Key Findings & Data:This paper offers a concept analysis of CLT as it is used in special education, following Walker and Avant's (2019) method.
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Conclusion & Impact:The analysis concludes with a proposed operational definition intended to give researchers and practitioners a clearer, more consistent way to discuss cognitive load when working with learners who have disabilities.
🔬Design:Review & Systematic Survey
📍Scope:2019 Verileri
⚙️Variables:Bilişsel Yük Kuramı · özel eğitim · çalışma belleği

Abstract

Cognitive Load Theory (CLT) is one of the most widely cited frameworks in educational psychology, yet its meaning shifts noticeably when it is applied in the special education literature. Researchers studying students with disabilitiesoften use terms such as cognitive load management, load reduction, instructional efficiency, and scaffolding as though they were interchangeable with CLT itself, even though each term carries a different theoretical history. This paper offers a concept analysis of CLT as it is used in special education, following Walker and Avant's (2019) method. Drawing on an analytic corpus of 70 empirical, theoretical, and review sources spanning the core CLT constructs and twelve disability categories, the analysis identifies the defining attributes of the concept, the conditions that must be present before it can be applied, the outcomes that follow its use, and the ways in which researchers measure it. The paper also traces how the concept has been adapted across disability categories, including learning disabilities, dyslexia, dysgraphia, dyscalculia, autism spectrum disorder, attention-deficit/hyperactivity disorder, hearing impairment, visual impairment, physical and health conditions, multiple disabilities, giftedness, and intellectual disability. The analysis concludes with a proposed operational definition intended to give researchers and practitioners a clearer, more consistent way to discuss cognitive load when working with learners who have disabilities.

Özet

Bilişsel Yük Kuramı (BYK), eğitim psikolojisi alanında en fazla atıf alan kuramsal çerçevelerden biri olmasına rağmen, özel eğitim alan yazınında kullanıldığında anlamı belirgin biçimde farklılaşmaktadır. Yetersizliği olan öğrenciler üzerine çalışan araştırmacılar; bilişsel yükün yönetimi, yükün azaltılması, öğretimsel verimlilik ve destekleyici öğretim gibi kavramları, her biri farklı bir kuramsal geçmişe sahip olmasına rağmen, sıklıkla BYK ile eş anlamlıymış gibi kullanmaktadır. Bu çalışmada, Walker ve Avant’ın (2019) yöntemi izlenerek BYK’nin özel eğitim alanındaki kullanımına yönelik bir kavram analizi gerçekleştirilmiştir. BYK’nin temel yapılarını ve 12 yetersizlik kategorisini kapsayan 70 ampirik, kuramsal ve derleme çalışmasından oluşan analitik bir veri kümesine dayanan analizde; kavramın tanımlayıcı özellikleri, uygulanabilmesi için bulunması gereken öncül koşullar, uygulanması sonucunda ortaya çıkan sonuçlar ve araştırmacıların kavramı ölçme biçimleri belirlenmiştir. Ayrıca kavramın öğrenme güçlüğü, disleksi, disgrafi, diskalkuli, otizm spektrum bozukluğu, dikkat eksikliği ve hiperaktivite bozukluğu, işitme yetersizliği, görme yetersizliği, fiziksel yetersizlikler ve sağlık sorunları, çoklu yetersizlik, özel yeteneklilik ve zihinsel yetersizlik kategorilerinde nasıl uyarlandığı incelenmiştir. Analiz sonucunda, araştırmacıların ve uygulamacıların yetersizliği olan öğrencilerle çalışırken bilişsel yük kavramını daha açık ve tutarlı biçimde ele almalarına katkı sağlamayı amaçlayan işevuruk bir tanım önerilmiştir.

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Cite This Article

Hussain, M. (2026). Cognitive Load Theory in Special Education: A Concept Analysis of Its Meaning, Attributes, and Educational Applications. Turkish Journal of Special Education Research and Practice, Cilt: 8 Sayı: 2, 1–25. https://doi.org/10.37233/trsped.drr.2004007

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References (75)

  1. Ahuja, N. J., Thapliyal, M., Bisht, A., Stephan, T., Kannan, R., Al-Rakhami, M. S., & Mahmud, M. (2022). An investigative study on the effects of pedagogical agents on intrinsic, extraneous and germane cognitive load: Experimental findings with dyscalculia and non-dyscalculia learners. IEEE Access, 10, 3904–3922. https://doi.org/10.1109/ACCESS.2021.3115409
  2. Aiswarya, G. S., & Joseph Ponniah, R. (2024). Dysgraphia and memory: Insights into the cognitive mechanisms, neural correlates, and intervention strategies. Integrative Psychological and Behavioral Science, 58, 1778–1792. https://doi.org/10.1007/s12124-024-09835-x
  3. Akın Bülbül, I. (2025). Early detection of autism in the pre-symptomatic period: Eye-tracking technologies and visual attention biomarkers. Turkish Journal of Special Education Research and Practice, 7(1), 1–28. https://doi.org/10.37233/trsped.drr.1678367
  4. Amjad, A., Amirhosseini, M. H., & Kalabi, F. (2026). Enhancing digital reading for dyslexic learners: An AI-based approach to cognitive load reduction. Journal of Enabling Technologies. Advance online publication. https://doi.org/10.1108/JET-08-2025-0060
  5. Ashkenazi, S., Rubinsten, O., & Henik, A. (2009). Attention, automaticity, and developmental dyscalculia. Neuropsychology, 23(4), 535–540. https://doi.org/10.1037/a0015347
  6. Barbieri, C. A., & Rodrigues, J. (2025). Leveraging cognitive load theory to support students with mathematics difficulty. Educational Psychologist, 60(3), 208–232. https://doi.org/10.1080/00461520.2025.2486138
  7. Barbieri, C., Miller‐Cotto, D., Clerjuste, S. N., & Chawla, K. (2023). A meta-analysis of the worked examples effect on mathematics performance. Educational Psychology Review, 35, Article 11. https://doi.org/10.1007/s10648-023-09745-1
  8. Bayliss, A., & Kritikos, A. (2011). Brief report: Perceptual load and the autism spectrum in typically developed individuals. Journal of Autism and Developmental Disorders, 41, 1573–1578. https://doi.org/10.1007/s10803-010-1159-8
  9. Bishara, S. (2021). Psychological availability, mindfulness, and cognitive load in college students with and without learning disabilities. Cogent Education, 8(1), Article 1929038. https://doi.org/10.1080/2331186x.2021.1929038
  10. Bishara, S. (2022). Linking cognitive load, mindfulness, and self-efficacy in college students with and without learning disabilities. European Journal of Special Needs Education, 37(3), 494–510. https://doi.org/10.1080/08856257.2021.1911521
  11. Bonsang, E., & Caroli, E. (2021). Cognitive load and occupational injuries. Industrial Relations: A Journal of Economy and Society, 60, 219-242. https://doi.org/10.1111/irel.12277
  12. Burcal, C., Needle, A. R., Custer, L., & Rosen, A. B. (2019). The effects of cognitive loading on motor behavior in injured individuals: A systematic review. Sports Medicine, 11(3), 34-46. https://doi.org/10.1007/s40279-019-01116-7
  13. Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62, 233-246. https://doi.org/10.1111/j.2044-8279.1992.tb01017.x
  14. Chen, O., Paas, F., & Sweller, J. (2023). A cognitive load theory approach to defining and measuring task complexity through element interactivity. Educational Psychology Review, 35, Article 63. https://doi.org/10.1007/s10648-023-09782-w
  15. Chen, O., Retnowati, E., & Kalyuga, S. (2020). Element interactivity as a factor influencing the effectiveness of worked example-problem solving and problem solving-worked example sequences. The British Journal of Educational Psychology, 90, 210-223. https://doi.org/10.1111/bjep.12317
  16. Chung, P. J., Patel, D., & Nizami, I. (2020). Disorder of written expression and dysgraphia: Definition, diagnosis, and management. Translational Pediatrics, 9(Suppl 1), S46-S54. https://doi.org/10.21037/tp.2019.11.01
  17. Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why? Current Directions in Psychological Science, 19(1), 51-57. https://doi.org/10.1177/0963721409359277
  18. Doroh, M. R., Maleki, Z. H., Mashhadi, A., & Khamesan, A. (2026). Differential effects of cognitive load on working memory in students with linguistic versus perceptual dyslexia. The Psychological Research in Individuals with Exceptional Needs, 4(1), 1-14. https://doi.org/10.61838/kman.prien.5123
  19. Duran, R., Zavgorodniaia, A., & Sorva, J. (2022). Cognitive load theory in computing education research: A review. ACM Transactions on Computing Education (TOCE), 22(4), Article 40. https://doi.org/10.1145/3483843
  20. Fisher, J. T., Hopp, F., & Weber, R. (2023). Cognitive and perceptual load have opposing effects on brain network efficiency and behavioral variability in ADHD. Network Neuroscience, 7(4), 1483–1496. https://doi.org/10.1162/netn_a_00336
  21. Forster, S., Robertson, D. J., Jennings, A., Asherson, P., & Lavie, N. (2013). Plugging the attention deficit: Perceptual load counters increased distraction in ADHD. Neuropsychology, 28(1), 91–97. https://doi.org/10.1037/neu0000020
  22. Ginns, P. (2005). Meta-analysis of the modality effect. Learning and Instruction, 15(4), 313-331. https://doi.org/10.1016/j.learninstruc.2005.07.001
  23. Greer, D. L., Crutchfield, S. A., & Woods, K. L. (2013). Cognitive theory of multimedia learning, instructional design principles, and students with learning disabilities in computer-based and online learning environments. Journal of Education, 193(2), 41-50. https://doi.org/10.1177/002205741319300205
  24. Hussain, M. (2025). Operationalizing cognitive load theory for students with learning disabilities: A phase-based instructional design framework. ACADEMIA International Journal for Social Sciences, 4(2), 2907-2923. https://doi.org/10.63056/academia.4.2.2025.1651
  25. Jouira, G., Alexe, D., Moraru, C. E., Rekik, G., Alexe, C., Marinău, M. A., & Sahli, S. (2024). The influence of cognitive load and vision variability on postural balance in adolescents with intellectual disabilities. Frontiers in Neurology, 15, Article 1385286. https://doi.org/10.3389/fneur.2024.1385286
  26. Kalyuga, S. (2009). The expertise reversal effect. In P. A. Kirschner (Ed.), Managing cognitive load in adaptive multimedia learning (pp. 58–80). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-60566-048-6.ch003
  27. Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23, 1–19. https://doi.org/10.1007/s10648-010-9150-7
  28. Kennedy, M., & Romig, J. (2021). Cognitive load theory: An applied reintroduction for special and general educators. TEACHING Exceptional Children, 56(6), 440-451. https://doi.org/10.1177/00400599211048214
  29. Kirschner, P. A., Sweller, J., Kirschner, F., & Zambrano Ramírez, J. (2018). From cognitive load theory to collaborative cognitive load theory. International Journal of Computer-Supported Collaborative Learning, 13, 213–233. https://doi.org/10.1007/s11412-018-9277-y
  30. Klepsch, M., & Seufert, T. (2020). Understanding instructional design effects by differentiated measurement of intrinsic, extraneous, and germane cognitive load. Instructional Science, 48, 45–77. https://doi.org/10.1007/s11251-020-09502-9
  31. Klepsch, M., Schmitz, F., & Seufert, T. (2017). Development and validation of two instruments measuring intrinsic, extraneous, and germane cognitive load. Frontiers in Psychology, 8, Article 1997. https://doi.org/10.3389/fpsyg.2017.01997
  32. Korbach, A., Brünken, R., & Park, B. (2018). Differentiating different types of cognitive load: a comparison of different measures. Educational Psychology Review, 30, 503–529. https://doi.org/10.1007/s10648-017-9404-8
  33. Kosch, T., Karolus, J., Zagermann, J., Reiterer, H., Schmidt, A., & Woźniak, P. W. (2023). A survey on measuring cognitive workload in human-computer interaction. ACM Computing Surveys, 55(13s), 283. https://doi.org/10.1145/3582272
  34. Krieglstein, F., Beege, M., Rey, G. D., Ginns, P., Krell, M., & Schneider, S. (2022). A systematic meta-analysis of the reliability and validity of subjective cognitive load questionnaires in experimental multimedia learning research. Educational Psychology Review, 34, 2485–2541. https://doi.org/10.1007/s10648-022-09683-4
  35. Kuznetsova, E., Liashenko, A., Zhozhikashvili, N., & Arsalidou, M. (2024). Giftedness identification and cognitive, physiological and psychological characteristics of gifted children: A systematic review. Frontiers in Psychology, 15, Article 1411981. https://doi.org/10.3389/fpsyg.2024.1411981
  36. Küçükbayrak, Z., & Çakıroğlu, O. (2023). A systematic review of reading fluency and reading comprehension studies for students with mild intellectual disabilities in Türkiye Turkish Journal of Special Education Research and Practice, 5(2), 32–54. https://doi.org/10.37233/TRSPED.2023.0142
  37. Le Cunff, A.-L., Dommett, E., & Giampietro, V. (2023). Neurophysiological measures and correlates of cognitive load in attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and dyslexia: A scoping review and research recommendations. European Journal of Neuroscience, 59(2), 256–282. https://doi.org/10.1111/ejn.16201
  38. Le Cunff, A.-L., Giampietro, V., & Dommett, E. (2024b). Neurodiversity positively predicts perceived extraneous load in online learning: A quantitative research study. Education Sciences, 14(5), 516. https://doi.org/10.3390/educsci14050516
  39. Le Cunff, A.-L., Giampietro, V., & Dommett, E. J. (2024a). Neurodiversity and cognitive load in online learning: A focus group study. PLOS ONE, 19(4), Article e0301932. https://doi.org/10.1371/journal.pone.0301932
  40. Le Cunff, A.-L., Martis, B.-L., Glover, C., Ahmed, E., Ford, R., Giampietro, V., & Dommett, E. J. (2025). Cognitive load and neurodiversity in online education: A preliminary framework for educational research and policy. Frontiers in Education, 9, Article 1437673. https://doi.org/10.3389/feduc.2024.1437673
  41. Lee, T., & So, W. (2015). Inquiry learning in a special education setting: Managing the cognitive loads of intellectually disabled students. European Journal of Special Needs Education, 30(2), 156–172. https://doi.org/10.1080/08856257.2014.986907
  42. Ma, W., Husain, M., & Bays, P. (2014). Changing concepts of working memory. Nature Neuroscience, 17, 347–356. https://doi.org/10.1038/nn.3655
  43. Mayer, R., & Moreno, R. (1998). A split-attention effect in multimedia learning: Evidence for dual processing systems in working memory. Journal of Educational Psychology, 90(2), 312-320. https://doi.org/10.1037/0022-0663.90.2.312
  44. Mishra, A., & Khan, A. (2022). Domain-general and domain-specific cognitive correlates of developmental dyscalculia: a systematic review of the last two decades’ literature. Child Neuropsychology, 29(8), 1179–1229. https://doi.org/10.1080/09297049.2022.2147914
  45. Modanwal, G., Rai, S. B., Jaiswal, A., Singh, T., & Sarawadekar, K. (2022). Can visually impaired use gestures to interact with computers? A cognitive load perspective. IEEE Transactions on Human-Machine Systems, 52(2), 267-275. https://doi.org/10.1109/thms.2022.3144002
  46. Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/s15326985ep3801_1
  47. Paas, F., Tuovinen, J., Tabbers, H., & Van Gerven, P. W. V. (2003). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71. https://doi.org/10.1207/s15326985ep3801_8
  48. Pichora-Fuller, M., Kramer, S., Eckert, M., Edwards, B., Hornsby, B. W. Y., Humes, L., Lemke, U., Lunner, T., Matthen, M., Mackersie, C., Naylor, G., Phillips, N., Richter, M., Rudner, M., Sommers, M., Tremblay, K., & Wingfield, A. (2016). Hearing impairment and cognitive energy: The framework for understanding effortful listening (FUEL). Ear and Hearing, 37, 5S-27S. https://doi.org/10.1097/aud.0000000000000312
  49. Puntambekar, S. (2021). Distributed scaffolding: Scaffolding students in classroom environments. Educational Psychology Review, 34, 451–472. https://doi.org/10.1007/s10648-021-09636-3
  50. Reid, D. (1998). Scaffolding. Journal of Learning Disabilities, 31(4), 386-396. https://doi.org/10.1177/002221949803100408
  51. Remington, A., Swettenham, J., & Lavie, N. (2012). Lightening the load. Journal of Abnormal Psychology, 121(2), 544–551. https://doi.org/10.1037/a0027670
  52. Renati, R., Pfeiffer, S., & Bonfiglio, N. S. (2024). Predictors of parental stress in families with gifted children: The role of cognitive and emotional challenges. Gifted Education International, 41(1), 112-136. https://doi.org/10.1177/02614294241300245
  53. Rodgers, B. L. (2000). Concept analysis: An evolutionary view. In B. L. Rodgers & K. A. Knafl (Eds.), Concept development in nursing: Foundations, techniques, and applications (2nd ed., pp. 77–102). Saunders.
  54. Salden, R., Aleven, V., Schwonke, R., & Renkl, A. (2010). The expertise reversal effect and worked examples in tutored problem solving. Instructional Science, 38, 289–307. https://doi.org/10.1007/s11251-009-9107-8
  55. Schnotz, W., & Kürschner, C. (2007). A reconsideration of cognitive load theory. Educational Psychology Review, 19, 469–508. https://doi.org/10.1007/s10648-007-9053-4
  56. Schroeder, N. L., & Cenkci, A. T. (2018). Spatial contiguity and spatial split-attention effects in multimedia learning environments: A meta-analysis. Educational Psychology Review, 30, 679–701. https://doi.org/10.1007/s10648-018-9435-9
  57. Soğancı, S., & Kulesza, E. M. (2023). Psychosocial effects of dyslexia in terms of students, parents, and school community: Research review. Turkish Journal of Special Education Research and Practice, 5(1), 1–17. https://doi.org/10.37233/TRSPED.2023.0134
  58. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1207/s15516709cog1202_4
  59. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4(4), 295-312. https://doi.org/10.1016/0959-4752(94)90003-5
  60. Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22, 123–138. https://doi.org/10.1007/s10648-010-9128-5
  61. Sweller, J. (2011). Cognitive load theory. In J. P. Mestre & B. H. Ross (Eds.), Psychology of learning and motivation (Vol. 55, pp. 37-76). Academic Press. https://doi.org/10.1016/B978-0-12-387691-1.00002-8
  62. Sweller, J. (2024). Cognitive load theory and individual differences. Learning and Individual Differences, 110, Article 102423. https://doi.org/10.1016/j.lindif.2024.102423
  63. Sweller, J., & Chandler, P. (1991). Evidence for cognitive load theory. Cognition and Instruction, 8(4), 351–362. https://doi.org/10.1207/s1532690xci0804_5
  64. Sweller, J., Ayres, P., & Kalyuga, S. (2011a). The modality effect. In Cognitive load theory (pp. 129-148). Springer. https://doi.org/10.1007/978-1-4419-8126-4_10
  65. Sweller, J., Ayres, P., & Kalyuga, S. (2011b). The redundancy effect. In Cognitive load theory (pp. 149-166). Springer. https://doi.org/10.1007/978-1-4419-8126-4_11
  66. Sweller, J., Ayres, P., & Kalyuga, S. (2011c). The split-attention effect. In Cognitive load theory (pp. 111-128). Springer. https://doi.org/10.1007/978-1-4419-8126-4_9
  67. Tetzlaff, L., Simonsmeier, B., Peters, T., & Brod, G. (2025). A cornerstone of adaptivity – A meta-analysis of the expertise reversal effect. Learning and Instruction, 98, Article 102142. https://doi.org/10.1016/j.learninstruc.2025.102142
  68. Tricot, A., Vandenbroucke, G., & Sweller, J. (2020). Using cognitive load theory to improve text comprehension for students with dyslexia. In A. J. Martin, R. A. Sperling, & K. J. Newton. (Eds.) Handbook of Educational Psychology and Students with Special Needs (1st ed.). Routledge. https://doi.org/10.4324/9781315100654-17
  69. Tsermentseli, S., Pavlidou, A., & Kouklari, E. (2025). Effects of a school-based intervention on executive functions and theory of mind in children with specific learning disorders. Brain Sciences, 16(1), Article 42. https://doi.org/10.3390/brainsci16010042
  70. van de Pol, J., Volman, M., & Beishuizen, J. (2010). Scaffolding in teacher–student interaction: A decade of research. Educational Psychology Review, 22, 271–296. https://doi.org/10.1007/s10648-010-9127-6
  71. Van Nooijen, C. C. A., De Koning, B. D., Bramer, W., Isahakyan, A., Asoodar, M., Kok, E., Van Merriënboer, J. J. G., & Paas, F. (2024). A cognitive load theory approach to understanding expert scaffolding of visual problem-solving tasks: A scoping review. Educational Psychology Review, 36, Article 12. https://doi.org/10.1007/s10648-024-09848-3
  72. Vogan, V., Morgan, B., Lee, W., Powell, T. L., Smith, M., & Taylor, M. J. (2014). The neural correlates of visuo-spatial working memory in children with autism spectrum disorder: Effects of cognitive load. Journal of Neurodevelopmental Disorders, 6, Article 19. https://doi.org/10.1186/1866-1955-6-19
  73. Walker, L. O., & Avant, K. C. (2019). Concept synthesis. In strategies for theory construction in nursing (6th ed., pp. 167-193). Pearson.
  74. Zaphir, J. S., Murphy, K., MacQuarrie, A. J., & Stainer, M. J. (2024). Understanding the role of cognitive load in paramedical contexts: A systematic review. Prehospital Emergency Care. https://doi.org/10.1080/10903127.2024.2370491
  75. Zekveld, A., Kramer, S., & Festen, J. (2011). Cognitive load during speech perception in noise: The influence of age, hearing loss, and cognition on the pupil response. Ear and Hearing, 32(4), 498–510. https://doi.org/10.1097/aud.0b013e31820512bb