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Development of an instrument for measuring different types of cognitive load
Open accessAbstract
According to cognitive load theory, instructions can impose three types of cognitive load on the learner: intrinsic load, extraneous load, and germane load. Proper measurement of the different types of cognitive load can help us understand why the effectiveness and efficiency of learning environments may differ as a function of instructional formats and learner characteristics. In this article, we present a ten-item instrument for the measurement of the three types of cognitive load. Principal component analysis on data from a lecture in statistics for PhD students (n = 56) in psychology and health sciences revealed a three-component solution, consistent with the types of load that the different items were intended to measure. This solution was confirmed by a confirmatory factor analysis of data from three lectures in statistics for different cohorts of bachelor students in the social and health sciences (ns = 171, 136, and 148), and received further support from a randomized experiment with university freshmen in the health sciences (n = 58).
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“Thus, if the sum of these factors exceeds the student's available resources, cognitive overload occurs, hindering the processing of new information (Leppink et al., 2013).”
From Systematic Review of the Effectiveness of Neurodidactic Spaced Learning Strategies in Long-Term Memory (2026) · cites this paper as Leppink et al., 2013
Experimental — accuracy not yet measuredIn the citing paper
“Even if they had to adopt the items to fit the different domains, they found the three factors to be robust.”
From Development and Validation of Two Instruments Measuring Intrinsic, Extraneous, and Germane Cognitive Load (2017) · cites this paper as Leppink et al., 2013
In the citing paper
“However, no separate experiments were performed to verify whether the questionnaire could explicitly differentiate between types of cognitive load, which would be an important criterion for assessing validity.”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Leppink et al. (2013)
In the citing paper
“However, because of problems with the GCL scale (lack of correlation with learning performance), one GCL-related item was added in a further study to explicitly capture the effort required to cope with cognitive load.”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Leppink et al. (2013)
In the citing paper
“a principal component analysis (PCA) was preferred over an exploratory factor analysis (EFA) as it is less stringent in terms of assumptions (e.g., Leppink et al., 2013).”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Leppink et al., 2013
In the citing paper
“Since the previous PCA resulted in a three-component solution and previous cognitive load questionnaires also relied on a three-factor model (Dönmez et al., 2022;Klepsch et al., 2017;Leppink et al., 2013), the a priori hypothesis explicitly assumed that the observed ratings of the items loaded on three latent variables (factors).”
From Development and Validation of a Theory-Based Questionnaire to Measure Different Types of Cognitive Load (2023) · cites this paper as Leppink et al., 2013
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Citations
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“…doubt that it will be possible to fi nd the holy grail of cognitive load theory, reliable and valid individual measures for the three types of cognitive load (see Kirschner et al., 2011), although others report some limited progress (Leppink, Paas, Van der Vleuten, Van Gog, & Van Merriënboer, 2013).”
BackgroundDesktop versus immersive virtual environments: effects on spatial learning
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BackgroundMethodInfluentialPointing and tracing gestures may enhance anatomy and physiology learning
Macken, L., & Ginns, P. (2014) · Medical Teacher · doi:10.3109/0142159x.2014.899684 · Cited by 72
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Self-citationA framework to estimate cognitive load using physiological data
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“Recently, a ten-item instrument was developed that aimed to measure these three types of cognitive load [26, 27].”
Self-citationEffects of cueing by a pedagogical agent in an instructional animation: A cognitive load approach
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“To understand the impact of worked example, domain prior knowledge and task difficulty on cognitive load, the CLM (Leppink et al., 2013) was used.”
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“A total of 34 students completed the CLS instrument.”
MethodResultInfluentialDistractors in Parsons Problems Decrease Learning Efficiency for Young Novice Programmers
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“A cognitive load inventory (see Appendix C) was adapted from a validated instrument (Leppink, Paas, van der Vleuten, van Gog, & van Merriënboer, 2013; Leppink, Paas, van Gog, van der Vleuten, & van Merriënboer, 2014) to reflect the nature of the specific tasks in the present study.”
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“Confirmatory factor analysis (CFA) was not conducted due to the small sample size, but former research has validated the questionnaire and has proven that the questionnaire is reliable (Leppink et al., 2013).”
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“Measurement of the cognitive load used an adaptation of the instrument designed by Leppink et al. (2013).”
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“This criticism can also be levelled at the new measurement instruments that have become available recently (Leppink et al., 2013) to supplement overall estimates of CL.”
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Something old, something new from cognitive load theory
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“During the end phase, the lecturers conducted several lecturing strategies that can enhance students’ GL in the form of SPL.”
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BackgroundRealistic details in visualizations require color cues to foster retention
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“Over time, several validated instruments were developed for measuring the different types of cognitive load along with the ECL (Eysink et al., 2009; Klepsch et al., 2017; Leppink et al., 2013).”
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“Notably, these measures have been found to be reliable, inexpensive, non-intrusive, and sensitive small changes in CL (Ayres 2006; Leppink et al. 2013; Paas et al. 1994, 2003b; Sweller et al. 2011).”
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“Some studies rely on tools that offer an overall measure of cognitive load (Szulewski et al., 2017), while others attempt to develop tools capable of discriminating between different types of cognitive load (Leppink et al., 2013, 2014).”
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BackgroundMethodInfluentialTracing Enhances Recall and Transfer of Knowledge of the Water Cycle
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Cognitive Sciences for Computing Education
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“…measures (Brünken et al., 2004, 2002), (3) direct physiological measures such as fMRI (Whelan, 2007) or electroencephalographic (EEG) (Antonenko et al., 2010) or eye-tracking variables (van Gog & Scheiter, 2010), and (4) subjective measurement rating scales (Leppink et al., 2014, 2013; Paas, 1992).”
BackgroundUsing cognitive strategies overcomes cognitive load in online learning environments
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“Participants ’ cognitive load levels were measured using a 10-point Likert scale (Leppink et al., 2013), ranging from “ extremely easy ” (0) to “ extremely dif fi cult ” (10).”
MethodSubjective cognitive load surveys lead to divergent results for interactive learning media
Skulmowski, A., & Rey, G. D. (2020) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.184 · Cited by 47
“Being instructed to memorize these anatomical structures most likely generates very little extraneous load – yet the measurement of this constituent of learning tasks is a major aspect of Leppink et al.'s (2013) survey (as discussed by Skulmowski & Rey, 2017).”
BackgroundMethodInfluentialFredericks, S., Elsayed, M. A., Hammad, M. A., Abumiddain, O. T., Istwani, L., Rabeea, A., Rashid‐Doubell, F., & Bella, A. (2021) · Medical Education Online · doi:10.1080/10872981.2021.1994691 · Cited by 42
“82 for ICL, ECL and SPL respectively[19].”
MethodLapierre, A., Arbour, C., Maheu‐Cadotte, M., Vinette, B., Fontaine, G., & Lavoie, P. (2022) · Simulation & Gaming · doi:10.1177/10468781221120599 · Cited by 44
“…(n = 20, 45% ; Hart & Staveland, 1988), the Paas Scale (n = 13, 29% ; Paas, 1992), the Surgery-Task Load Index [SURG-TLX] (n = 2, 4% ; Wilson et al., 2011), the Cognitive Load Questionnaire (n = 3, 7% ; Leppink et al., 2013), or a questionnaire specifically developed for the study (n = 1, 2%).”
BackgroundResultInfluentialTang, Q., Wang, Y., Líu, H., Liu, Q., & Jiang, S. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.957037 · Cited by 37
Guidelines for Choosing Cognitive Load Measures in Perceptually Rich Environments
Skulmowski, A. (2022) · Mind Brain and Education · doi:10.1111/mbe.12342 · Cited by 43
Pupillary response to complex interdependent tasks: A cognitive-load theory perspective
Mitra, R., McNeal, K. S., & Bondell, H. D. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0833-y · Cited by 42
“Air Anatomy” – Teaching Complex Spatial Anatomy Using Simple Hand Gestures
Yohannan, D. G., Oommen, A. M., Jayaprasad, A. B., Raju, N. K., Suresh, R. O., & Nair, S. J. (2021) · Anatomical Sciences Education · doi:10.1002/ase.2088 · Cited by 40
“Students, who are not native English speakers, often have difficulty understanding the terms used in anatomy textbooks (Lucas et al., 1997).”
BackgroundSun, J. C., Liu, Y., Lin, X. Y., & Hu, X. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1096337 · Cited by 87
The Effects of Lecture Diversity on Germane Load
Costley, J., & Lange, C. H. (2017) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v18i2.2860 · Cited by 37
Stereopsis, Visuospatial Ability, and Virtual Reality in Anatomy Learning
Luursema, J., Vorstenbosch, M., & Kooloos, J. (2017) · Anatomy Research International · doi:10.1155/2017/1493135 · Cited by 44
“Four of the questions assessed cognitive load (adapted from [23]), four assessed the use of analytic problem solving strategies, and four questions assessed the use of visuospatial problem solving strategies (Appendix).”
BackgroundThe Moderating Effects of Group Work on the Relationship Between Motivation and Cognitive Load
Costley, J., & Lange, C. H. (2018) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v19i1.3325 · Cited by 44
“However, their results differed from Leppink et al. (2013) in that the germane load items were found not to be related to intrinsic load, but a true representative of germane load and how it has been conceptualized by past research.”
ResultComputing EducationLiterature Review and Voices from the Field
Blikstein, P., & Moghadam, S. H. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.004 · Cited by 43
Kühl, T. (2021) · Learning and Instruction · doi:10.1016/j.learninstruc.2021.101457 · Cited by 40
Artificial Intelligence–Augmented Human Instruction and Surgical Simulation Performance
Giglio, B., Albeloushi, A., Alhaj, A. K., Alhantoobi, M. R., Saeedi, R., Davidovic, V., Uthamacumaran, A., Yilmaz, R., Lapointe, J., Balasubramaniam, N., et al. (2025) · JAMA Surgery · doi:10.1001/jamasurg.2025.2564 · Cited by 40
Yorgancı, S. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12658 · Cited by 60
Chen, Y., Zhang, L., & Yin, H. (2022) · Sustainability · doi:10.3390/su141710905 · Cited by 61
Task complexity and cognitive load in simulation‐based education: A randomised trial
Tremblay, M., Rethans, J., & Dolmans, D. H. J. M. (2022) · Medical Education · doi:10.1111/medu.14941 · Cited by 44
Measurement and Management of Cognitive Load in Surgical Education: A Narrative Review
Tokuno, J., Carver, T. E., & Fried, G. M. (2022) · Journal of surgical education · doi:10.1016/j.jsurg.2022.10.001 · Cited by 37
Azher, S., Cervantes, A., Marchionni, C., Grewal, K., Marchand, H., & Harley, J. M. (2023) · Clinical Simulation in Nursing · doi:10.1016/j.ecns.2023.02.009 · Cited by 34
Wang, T., Li, S., Tan, C., Zhang, J., & Lajoie, S. P. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104924 · Cited by 45
Zhu, B., Chau, K. T., & Mokmin, N. A. M. (2024) · Scientific Reports · doi:10.1038/s41598-024-77122-1 · Cited by 47
“The QCL was adapted from Leppink’s Cognitive Load Scale 69 , while the QLA was adapted from the Learning Adaptation Questionnaire for Adult Higher Education Online Learning developed by Junfen and Chuner 70 .”
Method
Metadata
- Authors
- Leppink, J., Paas, F., Van der Vleuten, C. P. M., Van Gog, T., & Van Merriënboer, J. J. G.
- Affiliations
- Maastricht University (NL)
- University of Wollongong (AU)
- Corresponding author
- Leppink, Jimmie
- Venue
- Behavior Research Methods
- Published
- 2013-04-10
- Volume
- 45
- Issue
- 4
- Pages
- 1058-1072
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- OpenAlex
- W1993729533
- Cited by
- 1,066
- References
- 45
- Citations by year
- 2026: 168 · 2025: 136 · 2024: 130 · 2023: 105 · 2022: 88 · 2021: 84 · 2020: 72 · 2019: 98 · 2018: 49 · 2017: 41 · 2016: 38 · 2015: 31 · 2014: 20 · 2013: 5
- FWCI
- 42.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Behavior Research Methods (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- Research Online (University of Wollongong) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Figshare (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Evaluation of Teaching Practices
- Keywords
- cognitive load, intrinsic cognitive load, extraneous load, germane load, instructional design, statistics instruction, university students, factor structure
- MeSH terms
- Adult, Analysis of Variance, Cognition, Female, Humans, Learning, Male, Models, Psychological, Surveys and Questionnaires, Reproducibility of Results, Linear Models, Behavioral Research, Young Adult
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