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Adapting and Validating a Differentiated Cognitive Load Scale in the Turkish Context

Year 2025, Issue: 59, 130 - 138
https://doi.org/10.33418/education.1516700

Abstract

This study aimed to adapt and validate the Cognitive Load Scale developed by Klepsch and colleagues (2017) into Turkish, focusing on its three core components: extraneous, intrinsic, and germane cognitive load. Although cognitive load theory is widely referenced in educational research and instructional design, instruments that distinguish between these cognitive load types are limited in the Turkish context. To address this gap, an exploratory sequential mixed-methods approach was employed. In the qualitative phase, expert reviews and a pilot implementation with 23 students were used to assess linguistic clarity and cultural relevance. In the quantitative phase, data were collected from 191 seventh-grade students from six public schools. The translated 7-item scale underwent both exploratory and confirmatory factor analyses, which confirmed a three-factor structure consistent with the original. Internal consistency values for each subscale were within acceptable limits. The adapted scale was also reviewed for content and face validity by a panel of experts in science education, educational measurement, and linguistics. The results indicate that the Turkish version of the scale is a valid and reliable instrument for measuring differentiated cognitive load. This tool can be effectively utilized in multimedia and technology-supported learning environments, supporting researchers and instructional designers in developing more cognitively aligned instructional materials. The study contributes to the cross-cultural validation of cognitive load theory and provides an important resource for Turkish educational researchers.

Ethical Statement

Ethics committee approval was obtained from Bogazici University Institutional Review Board in Social Sciences and Humanities (Date: 14.12.2022, Number: 2022-70).

References

  • Anglin, G. J., Vaez, H., & Cunningham, K. L. (2004). Visual representations and learning: The role of static and animated graphics. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (Vol. 2, pp. 865–916). Lawrence Erlbaum Associates Publishers. https://doi.org/10.4324/9781410609519
  • Ayres, P., & Sweller, J. (2014). The split-attention principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd Ed., Vol. 2, pp. 135–146). Cambridge University Press.
  • Benson, J., & Nasser, F. (1998). On the use of factor analysis as a research tool. Journal of Vocational Education Research, 23(1), 13–33.
  • Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Publications.
  • Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25(2), 315–324. https://doi.org/10.1016/j.chb.2008.12.020
  • Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2021). Multivariate statistics for social sciences: Applications with SPSS and LISREL (6th ed.). Pegem Publishing.
  • de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38(2), 105–134. https://doi.org/10.1007/s11251-009-9110-0
  • de Jong, T., & Lazonder, A. W. (2014). The guided discovery principle in multimedia learning. In R. E. Mayer, J. J. G. Merriënboer, W. Schnotz, & J. Elen (Eds.), The Cambridge handbook of multimedia learning (pp. 2015–228). Cambridge University Press.
  • Eysink, T. H. S., de Jong, T., Berthold, K., Kolloffel, B., Opfermann, M., & Wouters, P. (2009). Learner performance in multimedia learning arrangements: An analysis across instructional approaches. American Educational Research Journal, 46(4), 1107–1149. https://doi.org/10.3102/0002831209340235
  • Fathi, R., Teresco, J. D., & Regan, K. (2022). Measuring learners’ cognitive load when engaged with an algorithm visualization tool. In Proceedings of the EDSIG Conference (vol. 8, no. 5776). Information Systems and Computing Academic Professionals.
  • Hair, J. F., Black, W. C., Babin, W. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
  • Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21(6), 713–729. https://doi.org/10.1002/acp.1345
  • Hollender, N., Hofmann, C., Deneke, M., & Schmitz, B. (2010). Integrating cognitive load theory and concepts of human–computer interaction. Computers in Human Behavior, 26(6), 1278–1288. https://doi.org/10.1016/j.chb.2010.05.031
  • Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–31. https://doi.org/10.1207/S15326985EP3801_4
  • Kılıç, E. (2006). Effects of parallel instructional design and task difficulty level on university students’ achievement and cognitive load in multimedia learning environment, (Unpublished master's thesis). Ankara University.
  • Kılıç, E., & Karadeniz, Ş. (2004). Specifying students’ cognitive load and disorientation level in hypermedia. Kuram ve Uygulamada Eğitim Yönetimi, 40(40), 562-579.
  • Kılıç, S. (2016). Cronbach’s alpha reliability coefficient. Journal of Mood Disorders, 6(1), 47–48. https://doi.org/10.5455/jmood.20160307122823
  • Kılıç Çakmak, E. (2007). The bottleneck in multimedia: Cognitive overload. Gazi University Gazi Faculty of Education Journal, 27(2), 1-24.
  • Klepsch, M., Schmitz, F., & Seufert, T. (2017). Development and validation of two instruments measuring intrinsic, extraneous, and germane cognitive load. Frontiers in Psychology, 8, 1997. https://doi.org/10.3389/fpsyg.2017.01997
  • Klepsch, M., & Seufert, T. (2020). Understanding instructional design effects by differentiated measurement of intrinsic, extraneous, and germane cognitive load. Instructional Science, 48(1), 45–77. https://doi.org/10.1007/s11251-020-09502-9
  • Kline, R. B. (2005). Methodology in the social sciences. Principles and practice of structural equation modeling. Guilford Press.
  • Leppink, J., Paas, F. G. W. C., van der Vleuten, C. P. M., van Gog, T., & van Merriënboer, J. J. G. (2013). Development of an instrument for measuring different types of cognitive load. Behavior Research Methods, 45, 1058–1072. https://doi.org/10.3758/s13428-013-0334-1
  • Leppink, J., Paas, F. G. W. C., van Gog, T., van der Vleuten, C. P. M., & van Merriënboer, J. J. G. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30, 32–42. https://doi.org/10.1016/j.learninstruc.2013.12.001
  • Marcus, N., Cooper, M., & Sweller, J. (1996). Understanding instructions. Journal of Educational Psychology, 88(1), 49–63. https://psycnet.apa.org/doi/10.1037/0022-0663.88.1.49
  • Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139. https://doi.org/10.1016/S0079-7421(02)80005-6
  • Osborne, J. W., & Banjanovic, E. S. (2016). Exploratory factor analysis with SAS. SAS Institute.
  • Paas, F., Renkl, A., & Sweller, J. (2003a). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1
  • Paas, F., Tuovinen, J. E., Tabbers, H., & van Gerven, P. W. (2003b). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71). https://doi.org/10.1207/S15326985EP3801_8
  • Paas, F., & van Merriënboer, J. J. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human Factors, 35(4), 737–743. https://doi.org/10.1177/001872089303500412
  • Ragazou, V., & Antonis, K. (2023, November 13-15). The effects of learner expertise on intrinsic, extraneous, and germane cognitive load through instructional videos: An exploratory analysis. Paper presented at the 16th Annual International Conference of Education. Seville, Spain.
  • Seçer, İ. (2013). Practical data analysis with SPSS and LISREL: Analysis and reporting. Anı Publisher.
  • Shin, Y., Jung, J., Choi, S., & Jung, B. (2025). The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming. Education and Information Technologies, 30(1), 583–606. https://doi.org/10.1007/s10639-024-13131-x
  • 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

Farklılaştırılmış Bilişsel Yük Ölçeğinin Türkçe'ye Uyarlanması ve Geçerlik-Güvenirlik Çalışması

Year 2025, Issue: 59, 130 - 138
https://doi.org/10.33418/education.1516700

Abstract

Bu çalışma, Klepsch vd. (2017) tarafından geliştirilen Bilişsel Yük Ölçeği’nin Türkçe'ye uyarlanmasını ve geçerlik–güvenirlik çalışmalarının yapılmasını amaçlamaktadır. Çalışma, ölçeğin üç temel bileşenine—dışsal, içsel ve etkili bilişsel yük—odaklanmaktadır. Bilişsel yük kuramı, eğitim araştırmaları ve öğretim tasarımı alanlarında yaygın biçimde başvurulan bir kuram olmasına rağmen, bu bilişsel yük türlerini birbirinden ayırt edebilen ölçme araçları Türkçe bağlamında oldukça sınırlıdır. Bu eksikliği gidermek amacıyla keşfedici sıralı karma yöntem deseni kullanılmıştır. Nitel aşamada, uzman görüşleri ve 23 öğrenciyle gerçekleştirilen pilot uygulama yoluyla dilsel açıklık ve kültürel uygunluk değerlendirilmiştir. Nicel aşamada ise altı devlet okulundan toplam 191 yedinci sınıf öğrencisinden veri toplanmıştır. Türkçeye uyarlanan 7 maddelik ölçek hem açımlayıcı hem de doğrulayıcı faktör analizine tabi tutulmuş ve özgün çalışmayla uyumlu üç faktörlü yapı doğrulanmıştır. Her alt boyuta ilişkin iç tutarlılık katsayıları kabul edilebilir düzeydedir. Ayrıca ölçek, fen eğitimi, eğitimde ölçme-değerlendirme ve dilbilim alanlarından uzmanların yer aldığı bir kurul tarafından kapsam ve görünüş geçerliği açısından değerlendirilmiştir. Bulgular, ölçeğin Türkçe uyarlamasının farklılaştırılmış bilişsel yükü ölçmede geçerli ve güvenilir bir araç olduğunu göstermektedir. Bu ölçek, özellikle çoklu ortam ve teknoloji destekli öğrenme ortamlarında bilişsel açıdan uyumlu öğretim materyalleri geliştirmek isteyen araştırmacılar ve öğretim tasarımcıları için etkili bir araç sunmaktadır. Çalışma, bilişsel yük kuramının kültürler arası geçerlik çalışmalarına katkı sağlamakta ve Türk eğitim araştırmacıları için önemli bir kaynak oluşturmaktadır.

References

  • Anglin, G. J., Vaez, H., & Cunningham, K. L. (2004). Visual representations and learning: The role of static and animated graphics. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology (Vol. 2, pp. 865–916). Lawrence Erlbaum Associates Publishers. https://doi.org/10.4324/9781410609519
  • Ayres, P., & Sweller, J. (2014). The split-attention principle in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2nd Ed., Vol. 2, pp. 135–146). Cambridge University Press.
  • Benson, J., & Nasser, F. (1998). On the use of factor analysis as a research tool. Journal of Vocational Education Research, 23(1), 13–33.
  • Brown, T. A. (2006). Confirmatory factor analysis for applied research. Guilford Publications.
  • Cierniak, G., Scheiter, K., & Gerjets, P. (2009). Explaining the split-attention effect: Is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Computers in Human Behavior, 25(2), 315–324. https://doi.org/10.1016/j.chb.2008.12.020
  • Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2021). Multivariate statistics for social sciences: Applications with SPSS and LISREL (6th ed.). Pegem Publishing.
  • de Jong, T. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38(2), 105–134. https://doi.org/10.1007/s11251-009-9110-0
  • de Jong, T., & Lazonder, A. W. (2014). The guided discovery principle in multimedia learning. In R. E. Mayer, J. J. G. Merriënboer, W. Schnotz, & J. Elen (Eds.), The Cambridge handbook of multimedia learning (pp. 2015–228). Cambridge University Press.
  • Eysink, T. H. S., de Jong, T., Berthold, K., Kolloffel, B., Opfermann, M., & Wouters, P. (2009). Learner performance in multimedia learning arrangements: An analysis across instructional approaches. American Educational Research Journal, 46(4), 1107–1149. https://doi.org/10.3102/0002831209340235
  • Fathi, R., Teresco, J. D., & Regan, K. (2022). Measuring learners’ cognitive load when engaged with an algorithm visualization tool. In Proceedings of the EDSIG Conference (vol. 8, no. 5776). Information Systems and Computing Academic Professionals.
  • Hair, J. F., Black, W. C., Babin, W. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
  • Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21(6), 713–729. https://doi.org/10.1002/acp.1345
  • Hollender, N., Hofmann, C., Deneke, M., & Schmitz, B. (2010). Integrating cognitive load theory and concepts of human–computer interaction. Computers in Human Behavior, 26(6), 1278–1288. https://doi.org/10.1016/j.chb.2010.05.031
  • Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–31. https://doi.org/10.1207/S15326985EP3801_4
  • Kılıç, E. (2006). Effects of parallel instructional design and task difficulty level on university students’ achievement and cognitive load in multimedia learning environment, (Unpublished master's thesis). Ankara University.
  • Kılıç, E., & Karadeniz, Ş. (2004). Specifying students’ cognitive load and disorientation level in hypermedia. Kuram ve Uygulamada Eğitim Yönetimi, 40(40), 562-579.
  • Kılıç, S. (2016). Cronbach’s alpha reliability coefficient. Journal of Mood Disorders, 6(1), 47–48. https://doi.org/10.5455/jmood.20160307122823
  • Kılıç Çakmak, E. (2007). The bottleneck in multimedia: Cognitive overload. Gazi University Gazi Faculty of Education Journal, 27(2), 1-24.
  • Klepsch, M., Schmitz, F., & Seufert, T. (2017). Development and validation of two instruments measuring intrinsic, extraneous, and germane cognitive load. Frontiers in Psychology, 8, 1997. https://doi.org/10.3389/fpsyg.2017.01997
  • Klepsch, M., & Seufert, T. (2020). Understanding instructional design effects by differentiated measurement of intrinsic, extraneous, and germane cognitive load. Instructional Science, 48(1), 45–77. https://doi.org/10.1007/s11251-020-09502-9
  • Kline, R. B. (2005). Methodology in the social sciences. Principles and practice of structural equation modeling. Guilford Press.
  • Leppink, J., Paas, F. G. W. C., van der Vleuten, C. P. M., van Gog, T., & van Merriënboer, J. J. G. (2013). Development of an instrument for measuring different types of cognitive load. Behavior Research Methods, 45, 1058–1072. https://doi.org/10.3758/s13428-013-0334-1
  • Leppink, J., Paas, F. G. W. C., van Gog, T., van der Vleuten, C. P. M., & van Merriënboer, J. J. G. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30, 32–42. https://doi.org/10.1016/j.learninstruc.2013.12.001
  • Marcus, N., Cooper, M., & Sweller, J. (1996). Understanding instructions. Journal of Educational Psychology, 88(1), 49–63. https://psycnet.apa.org/doi/10.1037/0022-0663.88.1.49
  • Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139. https://doi.org/10.1016/S0079-7421(02)80005-6
  • Osborne, J. W., & Banjanovic, E. S. (2016). Exploratory factor analysis with SAS. SAS Institute.
  • Paas, F., Renkl, A., & Sweller, J. (2003a). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1
  • Paas, F., Tuovinen, J. E., Tabbers, H., & van Gerven, P. W. (2003b). Cognitive load measurement as a means to advance cognitive load theory. Educational Psychologist, 38(1), 63–71). https://doi.org/10.1207/S15326985EP3801_8
  • Paas, F., & van Merriënboer, J. J. (1993). The efficiency of instructional conditions: An approach to combine mental effort and performance measures. Human Factors, 35(4), 737–743. https://doi.org/10.1177/001872089303500412
  • Ragazou, V., & Antonis, K. (2023, November 13-15). The effects of learner expertise on intrinsic, extraneous, and germane cognitive load through instructional videos: An exploratory analysis. Paper presented at the 16th Annual International Conference of Education. Seville, Spain.
  • Seçer, İ. (2013). Practical data analysis with SPSS and LISREL: Analysis and reporting. Anı Publisher.
  • Shin, Y., Jung, J., Choi, S., & Jung, B. (2025). The influence of scaffolding for computational thinking on cognitive load and problem-solving skills in collaborative programming. Education and Information Technologies, 30(1), 583–606. https://doi.org/10.1007/s10639-024-13131-x
  • 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
There are 35 citations in total.

Details

Primary Language English
Subjects Scale Development, Classroom Measurement Practices
Journal Section Research Articles
Authors

Hasan Ozgur Kapıcı 0000-0001-7473-1584

Hakan Akçay 0000-0003-0307-661X

Early Pub Date November 20, 2025
Publication Date November 26, 2025
Submission Date July 15, 2024
Acceptance Date November 5, 2025
Published in Issue Year 2025 Issue: 59

Cite

APA Kapıcı, H. O., & Akçay, H. (2025). Adapting and Validating a Differentiated Cognitive Load Scale in the Turkish Context. Educational Academic Research(59), 130-138. https://doi.org/10.33418/education.1516700

Content of this journal is licensed under a Creative Commons Attribution NonCommercial 4.0 International License
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