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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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“Specifically, when intrinsic load is optimal and extraneous load is low, learners can take part in knowledge elaboration processes that impose germane load and further enhance the effect of learning (Leppink, Paas, Van der Vleuten, Van Gog, & Van Merrie¨nboer, 2013).”
BackgroundThe Validity of Physiological Measures to Identify Differences in Intrinsic Cognitive Load
Ayres, P., Lee, J. Y., PAAS, F. G. W. C., & van Merriënboer, J. J. G. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.702538 · Cited by 232
Self-citationThe interplay between self-regulation in learning and cognitive load
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Cognitive Load as Motivational Cost
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“Different methods have been proposed in the literature for measuring cognitive load, such as various rating scales [76] and data from pupillary response [77].”
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What does germane load mean? An empirical contribution to the cognitive load theory
Debue, N., & van de Leemput, C. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.01099 · Cited by 209
“Second, in accordance with Leppink et al. (2013), we did not find any relationship between IL and GL (or even IL 2 ), which could indicate a non-linear association between these two types of load.”
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“…of the CLT and is considered to be capable of distinguishing participants’ subjective impression of the three sub dimensions of cognitive load (Leppink et al ., 2014; Leppink, Paas, Van der Vleuten, Van Gog, & Van Merriënboer, 2013) and can be transferred to other instructional scenarios.”
BackgroundCognitive load theory and its relationships with motivation: A self-determination theory perspective
Evans, P., Vansteenkiste, M., Parker, P., Kingsford-Smith, A., & Zhou, S. (2024) · Educational Psychology Review · doi:10.1007/s10648-023-09841-2 · Cited by 200
“Variations on this cognitive load measure are validated with university students studying health sciences and statistics (Leppink et al., 2013) and language learning (Leppink et al., 2014); it performs as expected with high school science students (Cook et al., 2017) and high school mathematics…”
Ergonomic human-robot collaboration in industry: A review
Lorenzini, M., Lagomarsino, M., Fortini, L., Gholami, S., & Ajoudani, A. (2023) · Frontiers in Robotics and AI · doi:10.3389/frobt.2022.813907 · Cited by 237
Novice Programmers and Introductory Programming
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“Extraneous load is the load placed on working memory that does not contribute directly toward the learning of the material---for example, the resources consumed while understanding poorly written text or diagrams without sufficient clarity [13].”
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The worked example effect, the generation effect, and element interactivity.
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Towards measuring cognitive load through multimodal physiological data
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Validating theta power as an objective measure of cognitive load in educational video
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“Proper measurement of the different types of cognitive load can help understand why effectiveness may differ as a function of instructional formats and learner characteristics and how they may interact (Leppink et al. 2013).”
BackgroundCognitive Load and Working Memory in Multimedia Learning: Conceptual and Measurement Issues
Anmarkrud, Ø., Andresen, A., & Bråten, I. (2019) · Educational Psychologist · doi:10.1080/00461520.2018.1554484 · Cited by 188
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Using a pedagogical agent to deliver conversational style instruction: What benefits can you obtain?
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“A cognitive load measurement modified from Leppink et al. (2013) was adopted.”
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“This approach is generally accepted when developing questionnaires and is therefore used in educational psychology (Leppink et al., 2013) and beyond (e.”
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“For this, one could use the cognitive load questionnaire developed by Leppink et al. (2013).”
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Measuring cognitive load: performance, mental effort and simulation task complexity
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The Cambridge Handbook of Computing Education Research
Fincher, S., Robins, A. V., Margulieux, L. E., Morrison, B. B., Shephard, K., Loui, M., Borrego, M., Lancaster, T., Falkner, K., Sheard, J., et al. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555 · Cited by 141
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Subgoals Help Students Solve Parsons Problems
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“Intrinsic load is a combination of the innate difficulty of the material being learned as well as the learner's characteristics [15].”
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“Following the generally accepted definition of the ICL (e.g., Leppink et al., 2013), the domain-specific prior knowledge should correlate negatively with this cognitive load type.”
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Solving parsons problems versus fixing and writing code
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“For building the scale, various previous studies which studied measuring the cognitive load have been explored (Josephsen, 2018; Kruger, & Doherty, 2016; Leppink, et. al., 2013, 2014; Paas. et. al.”
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“Here we propose the use of an instrument based on the items developed and validated by Leppink et al. (2013; 2014) to distinguish between intrinsic and extraneous load while also looking at possible correlations between online psychophysiological measures of cognitive load (eye tracking and EEG)…”
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“[23].”
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“Multi-subjective rating scales of cognitive load types from [32] in the scale 0 to 10 (0 = not at all, 10 = completely).”
InfluentialSewell, J. L., Maggio, L. A., ten Cate, O., van Gog, T., Young, J. Q., & O’Sullivan, P. (2018) · Medical Teacher · doi:10.1080/0142159x.2018.1505034 · Cited by 124
“An ideal learning task is one in which intrinsic is matched to the level of the learner, germane load is optimized, and extraneous load is minimized (Leppink et al. 2013; Young and Sewell 2015).”
BackgroundMethodCognitive load theory: Practical implications and an important challenge
Leppink, J. (2017) · Journal of Taibah University Medical Sciences · doi:10.1016/j.jtumed.2017.05.003 · Cited by 136
“If the goal of an exercise is to have students learn how to address specific stimuli (e.g., phone ringing, colleagues passing by, patient files) in a workplace environment, cognitive load due to dealing with these stimuli is ICL.”
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Measuring Cognitive Load in Embodied Learning Settings
Skulmowski, A., & Rey, G. D. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01191 · Cited by 132
“Recently, cognitive load surveys measuring the three distinct load types were presented (e.g., Eysink et al., 2009; Leppink et al., 2013).”
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“Scale Leppink et al., 2013 Adapted version used in Study 1”
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Getting the point: Tracing worked examples enhances learning
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Effects of interactivity in E-textbooks on 7th graders science learning and cognitive load
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Ready student one: Exploring the predictors of student learning in virtual reality
Madden, J., Pandita, S., Schuldt, J. P., Kim, B., Won, A. S., & Holmes, N. G. (2020) · PLoS ONE · doi:10.1371/journal.pone.0229788 · Cited by 112
“We note, however, that many of the common methods have several limitations [87], such as that different methods may or may not be able to distinguish different types of cognitive load [28, 84, 87, 88].”
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“We adopted the 10-item cognitive load scale which had developed by Leppink, Paas, Van der Vleuten, Van Gog, and Van Merriënboer (2013).”
MethodMeasuring cognitive load in introductory CS: adaptation of an instrument
Morrison, B. B., Dorn, B., & Guzdial, M. (2014) · Proceedings of the tenth annual conference on International computing education research · doi:10.1145/2632320.2632348 · Cited by 147
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Self-citationMeasurement of cognitive load in multimedia learning: a comparison of different objective measures
Korbach, A., Brünken, R., & Park, B. (2017) · Instructional Science · doi:10.1007/s11251-017-9413-5 · Cited by 98
“Therefore, one item might not be a valid measure of a specific cognitive load factor, whereas self-reports in general could be suitable not only to rate the total cognitive load but also to differentiate between the cognitive load factors (Leppink et al. 2013, 2014).”
BackgroundTwelve tips for medical curriculum design from a cognitive load theory perspective
Leppink, J., & Duvivier, R. (2016) · Medical Teacher · doi:10.3109/0142159x.2015.1132829 · Cited by 96
“Some recent studies have provided psychometric measures of different types of cognitive load (Leppink et al. 2013, 2014).”
BackgroundSelf-citationHochberg, K., Becker, S., Louis, M., Klein, P., & Kühn, J. (2020) · Journal of Science Education and Technology · doi:10.1007/s10956-020-09816-w · Cited by 114
Krell, M. (2017) · Cogent Education · doi:10.1080/2331186x.2017.1280256 · Cited by 91
“Despite this concern, Leppink et al. (2013) proposed an instrument to separately measure contentrelated (intrinsic load), instruction-related (extraneous load) and process-related (germane load) sources of CL (cf. Paas & Van Merriënboer, 1994).”
BackgroundMethodInfluentialCognitive Load Theory in Computing Education Research: A Review
Duran, R., Zavgorodniaia, A., & Sorva, J. (2022) · ACM Transactions on Computing Education · doi:10.1145/3483843 · Cited by 92
“Of those, CER has largely relied on the Paas single-question instrument [74] and Morrison and colleagues’ [69] programming-domain adaptation of Leppink and colleagues’ [50] ten-item questionnaire.”
BackgroundMethodGlogger‐Frey, I., Gaus, K., & Renkl, A. (2016) · Learning and Instruction · doi:10.1016/j.learninstruc.2016.11.002 · Cited by 88
Schneider, S., Krieglstein, F., Beege, M., & Rey, G. D. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104350 · Cited by 100
Interactive digital storytelling: bringing cultural heritage in a classroom
Rizvić, S., Bošković, D., Okanović, V., Šljivo, S., & Zukić, M. (2019) · Journal of Computers in Education · doi:10.1007/s40692-018-0128-7 · Cited by 121
Classroom complexity affects student teachers’ behavior in a VR classroom
Huang, Y., Richter, E., Kleickmann, T., Wiepke, A., & Richter, D. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.104100 · Cited by 99
“Cognitive load has typically been measured with subjective ratings, physiological measures and performance in the secondary task (e.g., Anmarkrud et al., 2019; Leppink et al., 2013; Paas et al., 2003).”
BackgroundWe need more replication research – A case for test-retest reliability
Leppink, J., & Pérez-Fuster, P. (2017) · Perspectives on Medical Education · doi:10.1007/s40037-017-0347-z · Cited by 86
“For example, when interested in the test-retest reliability of a questionnaire of six or more items on cognitive load experienced in a learning period that just finished [32, 37, 38], an interval of ten to fifteen minutes may do.”
BackgroundSelf-citationMakransky, G., Terkildsen, T. S., & Mayer, R. E. (2019) · Learning and Instruction · doi:10.1016/j.learninstruc.2018.12.001 · Cited by 93
Shi, Y., Du, J., & Worthy, D. A. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103367 · Cited by 82
Cognitive load experienced by nurses in simulation-based learning experiences: An integrative review
Rogers, B., & Franklin, A. E. (2021) · Nurse Education Today · doi:10.1016/j.nedt.2021.104815 · Cited by 80
Making an Effort Versus Experiencing Load
Klepsch, M., & Seufert, T. (2021) · Frontiers in Education · doi:10.3389/feduc.2021.645284 · Cited by 79
The effects of video lecture viewing strategies on cognitive load
Costley, J., Fanguy, M., Lange, C. H., & Baldwin, M. (2020) · Journal of Computing in Higher Education · doi:10.1007/s12528-020-09254-y · Cited by 108
Liao, S., Kruger, J., & Doherty, S. (2020) · The Journal of Specialised Translation · doi:10.26034/cm.jostrans.2020.549 · Cited by 80
“Given that intrinsic cognitive load cannot be manipulated by instructional design (Leppink et al. 2013), a vital principle in learning instruction is therefore to reduce extraneous cognitive load so as to free up more cognitive resources, for instance, by optimising the instructional design of the stimuli.”
BackgroundOtt, N., Brünken, R., Vogel, M., & Malone, S. (2018) · Learning and Instruction · doi:10.1016/j.learninstruc.2018.04.010 · Cited by 92
Poquet, O., Lim, L.-A., Mirriahi, N., & Dawson, S. (2018) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3170358.3170376 · Cited by 77
“The interventions in these studies tap into germane load – an element of cognitive load assisting with comprehension, and commonly measured through a validated survey instrument [14].”
BackgroundXie, H., Wang, F., Hao, Y., Chen, J., An, J., Wang, Y., & Liu, H. (2017) · PLoS ONE · doi:10.1371/journal.pone.0183884 · Cited by 93
Curzon, P., Bell, T., Waite, J., & Dorling, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.018 · Cited by 85
The Differential Effects of Comprehensive Feedback Forms in the Second Language Writing Class
López, M. B., Steendam, E. V., Speelman, D., & Buyse, K. (2018) · Language Learning · doi:10.1111/lang.12295 · Cited by 85
Margulieux, L. E., Ketenci, T., & Decker, A. (2019) · Computer Science Education · doi:10.1080/08993408.2018.1562145 · Cited by 78
Liu, T., Lin, Y.-C., & PAAS, F. G. W. C. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.10.019 · Cited by 84
Self-citationSeufert, T. (2020) · Educational Psychology Review · doi:10.1007/s10648-020-09574-6 · Cited by 93
Measuring cognitive load in augmented reality with physiological methods: A systematic review
Suzuki, Y., Wild, F., & Eileen Scanlon, A. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12882 · Cited by 90
“Frequently used cognitive load scales include the NASA Task Load Index (NASA-TLX) (Hart & Staveland, 1988), the Paas Subjecting Rating Scale (Paas, 1992) and Leppink's Cognitive Load Scale (Leppink et al., 2013).”
Faber, T. J. E., Dankbaar, M. E. W., van den Broek, W. W., Bruinink, L. J., Hogeveen, M., & van Merriënboer, J. J. G. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05698-3 · Cited by 120
“Apart from the previously mentioned 10-item scale by Lep-pink et al. [16], the 8-item questionnaire by Klepsch and Seufert [85] and the 15-item scale developed by Kriegl-stein et al. [86] appear promising instruments that distinguish between active and passive mental load.”
MethodA systematic map of research characteristics in studies on augmented reality and cognitive load
Buchner, J., Buntins, K., & Kerres, M. (2021) · Computers and Education Open · doi:10.1016/j.caeo.2021.100036 · Cited by 82
Jiang, D., & Zhang, L. J. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103841 · Cited by 85
Berssanette, J. H., & de Francisco, A. C. (2021) · IEEE Transactions on Education · doi:10.1109/te.2021.3127215 · Cited by 86
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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