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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
Cites
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003
Cognitive Architecture and Instructional Design
Sweller, J., van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998) · Educational Psychology Review · doi:10.1023/a:1022193728205 · Cited by 6,023
Self-citationCognitive Load Theory and Instructional Design: Recent Developments
Paas, F., Renkl, A., & Sweller, J. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_1 · Cited by 3,041
Self-citationEye Tracking: A comprehensive guide to methods and measures
Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R. J., Jarodzka, H. M., & van de Weijer, J. (2015) · Lund University Publications (Lund University) · Cited by 2,919
Cognitive Load Theory and the Format of Instruction
Chandler, P., & Sweller, J. (1991) · Cognition and Instruction · doi:10.1207/s1532690xci0804_2 · Cited by 2,894
Cognitive Load Measurement as a Means to Advance Cognitive Load Theory
Paas, F., Tuovinen, J. E., Tabbers, H., & Van Gerven, P. W. M. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_8 · Cited by 2,527
Self-citationCognitive Load Theory and Complex Learning: Recent Developments and Future Directions
van Merriënboer, J. J. G., & Sweller, J. (2005) · Educational Psychology Review · doi:10.1007/s10648-005-3951-0 · Cited by 2,206
Paas, F. G. W. C. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.4.429 · Cited by 2,150
Self-citationElement Interactivity and Intrinsic, Extraneous, and Germane Cognitive Load
Sweller, J. (2010) · Educational Psychology Review · doi:10.1007/s10648-010-9128-5 · Cited by 2,020
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_4 · Cited by 1,927
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Manipulation of cognitive load variables and impact on auscultation test performance
Chen, R., Grierson, L., & Norman, G. R. (2014) · Advances in Health Sciences Education · doi:10.1007/s10459-014-9573-x · Cited by 22
Wirzberger, M., Herms, R., Bijarsari, S. E., Eibl, M., & Rey, G. D. (2018) · Cognitive Research Principles and Implications · doi:10.1186/s41235-018-0138-z · Cited by 24
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Effects of Response Option Order on Likert-Type Psychometric Properties and Reactions
Robie, C., Meade, A. W., Risavy, S. D., & Rasheed, S. (2022) · Educational and Psychological Measurement · doi:10.1177/00131644211069406 · Cited by 20
“Mental effort was measured with a single item that was adapted from (Leppink et al., 2013): ‘‘Working on this questionnaire required me to exert a high level of mental effort.’’”
MethodPsychometric Properties for Multidimensional Cognitive Load Scale in an E-Learning Environment
Choi, Y., & Lee, H. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19105822 · Cited by 28
“The cognitive load consists of three components: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load [10].”
BackgroundInfluentialA Synthetic Review of Cognitive Load in Distance Interpreting: Toward an Explanatory Model
Zhu, X., & Aryadoust, V. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.899718 · Cited by 36
Colors and Learner’s Gender Evoke Different Emotional and Cognitive Effects in Multimedia Learning
Liew, T. W., Tan, S.-M., Gan, C. L., & Pang, W. M. (2022) · Human Behavior and Emerging Technologies · doi:10.1155/2022/1235732 · Cited by 20
“’s [60] extraneous cognitive load scale is indicative of learners’ perception of difficulty stemming from instructional design flaws, thus, the warm and the cold color tones could have imposed distractions or challenges hampering fluent processing of the multimedia learning contents visually and cognitively.”
BackgroundMethodZhong, L. (2022) · Smart Learning Environments · doi:10.1186/s40561-022-00219-5 · Cited by 31
“Participant’s cognitive load was measured by a survey developed and validated by Leppink et al. (2013).”
MethodAssessing Intrinsic and Extraneous Cognitive Complexity of E-textbook Learning
Novak, E., Daday, J. K., & McDaniel, K. (2018) · Interacting with Computers · doi:10.1093/iwc/iwy001 · Cited by 22
Beege, M., Wirzberger, M., Nebel, S., Schneider, S., Schmidt, N., & Rey, G. D. (2019) · Frontiers in Education · doi:10.3389/feduc.2019.00086 · Cited by 21
Dönmez, O., Akbulut, Y., Telli, E., Kaptan, M., Özdemir, İ. H., & Erdem, M. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11035-2 · Cited by 20
“Available scales and indicators in the recent literature were considered as well (e.g., Klepsch et al., 2017; Leppink et al., 2013).”
MethodJiang, D., Chen, O., Han, Y., & Kalyuga, S. (2023) · British Journal of Educational Psychology · doi:10.1111/bjep.12596 · Cited by 21
Ratmono, D., Sari, R., Warsono, S., Ubaidillah, M., & Wibowo, L. M. (2024) · Cogent Business & Management · doi:10.1080/23311975.2024.2316890 · Cited by 22
“The cognitive-load scale in this study was developed based on the cognitive-load scale proposed by Gerjets et al. (2009) and leppink et al. (2013).”
Joo, H., Park, J., & Kim, D. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12548 · Cited by 26
Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis
Choi, Y., & Kim, J. (2021) · Sustainability · doi:10.3390/su131810149 · Cited by 22
“Specifically, cognitive load theory states that there are three components to cognitive load: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load [13].”
BackgroundHahn, L., & Klein, P. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1012787 · Cited by 28
He, X., & Wu, D. (2023) · Information & Management · doi:10.1016/j.im.2023.103791 · Cited by 22
Yudintseva, A. (2024) · Computers & Education X Reality · doi:10.1016/j.cexr.2024.100076 · Cited by 28
The Effect of Guidance in Problem-Based Learning of Statistics
Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P. M., & Berger, M. P. F. (2013) · The Journal of Experimental Education · doi:10.1080/00220973.2013.813365 · Cited by 19
“Perceived value and usefulness of the learning activity is one of these dimensions, and in the lecture experiment (Leppink et al., 2013), the group that received guiding questions on average scored higher on this dimension than the group that did not receive the guiding questions.”
BackgroundSelf-citationThe Effects of Worked-Out Example and Metacognitive Scaffolding on Problem-Solving Programming
Shin, Y., Jung, J., Zumbach, J., & Yi, E. (2023) · Journal of Educational Computing Research · doi:10.1177/07356331231174454 · Cited by 18
“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).”
MethodCai, Y., Peng, X., & Ge, Q. (2024) · Reading and Writing · doi:10.1007/s11145-024-10580-1 · Cited by 21
“Learners’ perceived task difficulty denotes their perceptions of differing cognitive processing demands in learning materials (Xu et al., 2023), often as a proxy of cognitive load (Leppink et al., 2013).”
Aalioui, L., Gouzi, F., & Tricot, A. (2022) · AJP Advances in Physiology Education · doi:10.1152/advan.00185.2021 · Cited by 18
The Effects of Augmented Reality: A Comparative Study in an Undergraduate Physics Laboratory Course
Kapp, S., Thees, M., Beil, F., Weatherby, T. S., Burde, J., Wilhelm, T. E., & Kühn, J. (2020) · International Conference on Computer Supported Education · doi:10.5220/0009793001970206 · Cited by 19
“The internal consistencies for the cognitive load scale by Leppink et al. (2013) as adapted by Thees et al. (2020b) were acceptable to good (αICL = 0.79, αECL = 0.75, αGCL = 0.84).”
MethodInfluentialSerious game design and learning effect verification supporting traditional pattern learning
Li, Y., Zhou, X., Yang, S., & Hang, Y. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2022.2042032 · Cited by 18
“It is helpful to explore the e ff ectiveness of the learning environment by measuring di ff erent types of cognitive loads correctly (Leppink et al., 2013).”
BackgroundMethodPerformance of a cognitive load inventory during simulated handoffs: Evidence for validity
Young, J. Q., Boscardin, C., van Dijk, S. M., Abdullah, R., Irby, D. M., Sewell, J. L., ten Cate, O., & O’Sullivan, P. (2016) · SAGE Open Medicine · doi:10.1177/2050312116682254 · Cited by 21
Measuring immersion and edutainment in multimedia cultural heritage applications
Bošković, D., Rizvić, S., Okanović, V., Šljivo, S., & Sinanovic, N. (2017) · International Conference on Information, Communication and Automation Technologies (ICAT) · doi:10.1109/icat.2017.8171604 · Cited by 18
“In assessing the edutainment influence on successful learning it is important to include measurements which take into account cognitive load theory [15], [16].”
BackgroundThe Split-Attention Principle in Multimedia Learning
Ayres, P., & Sweller, J. (2021) · The Cambridge Handbook of Multimedia Learning · doi:10.1017/9781108894333.020 · Cited by 18
Cunff, A. L., Giampietro, V., & Dommett, E. J. (2024) · Education Sciences · doi:10.3390/educsci14050516 · Cited by 20
Lavoie, P., Brien, L.-A., Ledoux, I., Gosselin, É., Khetir, I., Crétaz, M., & Turgeon, N. (2025) · Clinical Simulation in Nursing · doi:10.1016/j.ecns.2024.101682 · Cited by 17
Predicting Visuospatial and Verbal Working Memory by Individual Differences in E-Learning Activities
Fellman, D., Lincke, A., Berge, E., & Jonsson, B. (2020) · Frontiers in Education · doi:10.3389/feduc.2020.00022 · Cited by 19
“…these findings to the cognitive load theory (Sweller, 1988), the repetitive behavior observed among low WM individuals might stem from inhibited learning due to cognitive overload in the limited capacity of WM (Kalyuga, 2011; Leppink et al., 2013), thus manifested in an increased repetition.”
BackgroundShi, Y., Yang, H., Yang, Z., Liu, W., Wu, D., & Yang, H. H. (2022) · Australasian Journal of Educational Technology · doi:10.14742/ajet.6688 · Cited by 21
“…and tasks; EL is imposed by the instructional features that hinder students’ learning; GL refers to the effort of the acquisition of knowledge by processing, construction, and automation of schemas (Leppink et al., 2013; Sweller et al., 1998, Sweller, 2010; Van Merriënboer & Sweller, 2005).”
BackgroundMethodInvestigating the role of hand perspective in learning from procedural animations
de Koning, B. B., Mok, K., Marcus, N., & Ayres, P. (2022) · British Journal of Educational Psychology · doi:10.1111/bjep.12542 · Cited by 17
Meier, J., de Jong, B., van Montfort, D., Verdonschot, A., van Wermeskerken, M., & van Gog, T. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12803 · Cited by 17
Zhao, F., & Mayer, R. E. (2023) · Learning and Instruction · doi:10.1016/j.learninstruc.2023.101779 · Cited by 19
Virtual reality for fire safety training: study of factors involved in immersive learning
Ristor, R., Morélot, S., Garrigou, A., & Kaoua, B. N. (2023) · Virtual Reality · doi:10.1007/s10055-022-00743-2 · Cited by 21
Rathnayaka, C., Ganapathi, J., Kickbusch, S., Dawes, L. A., & Brown, R. (2023) · European Journal of Engineering Education · doi:10.1080/03043797.2023.2204813 · Cited by 21
“Although subjective rating scales of measuring cognitive load such as Cognitive Load Scale (CLS) (Leppink et al. 2013) and Naïve Rating Scale (NRS) (Klepsch, Schmitz, and Seufert 2017) could be useful tools for assessing the perceived relative cognitive load, the reliability and internal consistency of such subjective…”
MethodInfluentialInstructional efficiency: The role of prior knowledge and cognitive load
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Worked examples for teaching electrocardiogram interpretation: Salient or discriminatory features?
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Vocational Education and Training in the Age of Digitization
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Effects of Segmentation and Self-Explanation Designs on Cognitive Load in Instructional Videos
Yoon, M., Zheng, H., Jung, E., & Li, T. (2022) · Contemporary Educational Technology · doi:10.30935/cedtech/11522 · Cited by 28
“Paas et al. (2003) and Leppink et al. (2013) declared that cognitive load demand is an assessment dimension that reflects students’ performance of a specific task.”
BackgroundMethodInfluentialLee, T. T. H., & So, W. M. W. (2014) · European Journal of Special Needs Education · doi:10.1080/08856257.2014.986907 · Cited by 19
Schuessler, K., Fischer, V., & Walpuski, M. (2024) · Instructional Science · doi:10.1007/s11251-024-09692-6 · Cited by 22
“…availability of possible answer options being useful criteria for cognitive load ratings) to investigate whether the current study’s results can be replicated for instruments that are able to perform a differentiated measurement of cognitive load (Klepsch et al., 2017; Leppink et al., 2013, 2014).”
Learning Outside the Classroom
Begel, A., & Ko, A. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.027 · Cited by 18
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“This study adopted the 10-item cognitive load scale developed by Leppink et al. (2013), comprising three dimensions: three items for the intrinsic cognitive load (e.g. “ I fi nd the learning content during the activity is di ffi cult to understand.”
Applying Cognitive Load Theory in Teacher Education
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The Negative Impact of Media Diversity on Self-Regulated Learning Strategies and Cognitive Load.
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Supporting traditional handicrafts teaching through eye movement technology
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“The subjective evaluation scale used in research of Leppink et al (2013) and the Academic Self-regulation Questionnaire (SRQ-A) by Kröner et al (2017) have been proved to reflect the changes in students’ cognition and motivation.”
MethodLange, C. H., & Costley, J. (2018) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12269 · Cited by 18
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What is science without replication?
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“That is, if we have a questionnaire of say ten items that are expected to form three factors, the same sets of items should pop up in psychometric analysis in different samples [8].”
BackgroundSelf-citationLi, H., Wang, Z., Ding, L., Zhang, J., & Wang, G. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1635465 · Cited by 19
Zhang, S., Wu, Y. X., Fu, Z., Lu, Y., Wang, Q., & Liu, M. (2019) · Journal of Nursing Management · doi:10.1111/jonm.12919 · Cited by 15
“The possible reason might include the following: (a) there are only three items included in the extraneous CL and Leppink et al. (Leppink et al., 2013) indicated that the stability of a scale or subscale can be affected when there are only few items within a scale or subscale and (b) extraneous CL may vary when the pa…”
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“, [12, 27-30]) which all attempt to measure two or”
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Using scaffolding theory in serious games to enhance traditional Chinese murals culture learning
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“38 The results of the independent sample t-check analysis are shown in Table 3, which revealed a significant difference between the game group and the video group in terms of germane cognitive load, t = 2.4, p = .015, and d = .457.”
MethodResultInfluentialConceptThread: Visualizing Threaded Concepts in MOOC Videos
Zhou, Z., Ye, L., Cai, L., Wang, L., Wang, Y., Wang, Y., Chen, W., & Wang, Y. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3361001 · Cited by 15
“Additionally, we conducted a cognitive load survey (CLS) [67] to measure subjective cognitive load during the learning task.”
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“However, as demonstrated in our criterion validation, a higher number of items generally led to more favorable statistical outcomes (e.g., Andersen & Makransky, 2021; Leppink et al., 2013).”
InfluentialSelf-citationSystematic review of mobile augmented reality applications in geography education
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Cognitive load measures mainly have meaning when they are combined with learning outcome measures
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Triangulation of online and offline measures of processing and reception in AVT
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Computing for Other Disciplines
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“…showed that most previous studies on the CLT have considered subjective rating scales when it comes to assess differences in cognitive variables (Leppink et al., 2013), such as an adapted version of the NASA-Task Load Index (NASA-TLX) by Hart and Staveland (1988), or the nine-point symmetrical…”
Ngu, P., Chien, C., Ho, Y., & Hou, H. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105421 · Cited by 14
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“The questions concerning intrinsic cognitive load and extraneous cognitive load refer mainly to the questions concerning intrinsic cognitive load and extraneous cognitive load in the cognitive load scale developed by Leppink et al. (2013), as shown in Appendix C.”
An Item Response Modeling Approach to Cognitive Load Measurement
Ehrich, J. F., Howard, S. J., Bokosmaty, S., & Woodcock, S. (2021) · Frontiers in Education · doi:10.3389/feduc.2021.648324 · Cited by 14
“Recently, studies have attempted to measure the different aspects of cognitive load (e.g., Leppink et al., 2013; Klepsch et al., 2017; Krell, 2017).”
BackgroundLiu, M., Zuo, J., Tao, Y., Zhao, L., Wu, S., Feng, L., & Liao, L. (2021) · Nurse Education Today · doi:10.1016/j.nedt.2021.105248 · Cited by 19
Cognitive Load Assessment Scales in Simulation
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The influence of learning analytics dashboard information design on cognitive load and performance
Cheng, N., Zhao, W., Xu, X., Liu, H., & Tao, J. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-12606-1 · Cited by 15
“In the context of this study, we employed the cognitive load scale developed by Leppink et al. (2013), as this scale has been applied and validated in the field of education (Liao et al., 2019).”
Learning to avoid biased reasoning: effects of interleaved practice and worked examples
van Peppen, L. M., Verkoeijen, P. P. J. L., Kolenbrander, S. V., Heijltjes, A. E. G., Janssen, E. M., & van Gog, T. (2021) · Journal of Cognitive Psychology · doi:10.1080/20445911.2021.1890092 · Cited by 17
“…if we had included measures of the separate types of cognitive load (although it seems very challenging to distinguish between di ff erent types of cognitive load and available instruments, e.g. the rating scale developed by Leppink et al., 2013, would be too long to apply after each task).”
MethodBarcatta, K., Holl, E. A., Battistutta, L., van der Meulen, M., & Rischer, K. M. (2022) · Frontiers in Pain Research · doi:10.3389/fpain.2021.800258 · Cited by 13
“To assess the degree of perceived task difficulty, participants also rated the perceived cognitive load after each interactive condition (29).”
BackgroundNovak, E., Daday, J. K., & McDaniel, K. (2018) · Educational Technology Research and Development · doi:10.1007/s11423-018-9599-5 · Cited by 17
“The concepts of intrinsic and extraneous load (Leppink et al. 2013; Leppink et al. 2014) relate to general information processing and are essential to the MVP theory (Keller 2008b).”
BackgroundMethodFörderung von Konzeptverständnis und Repräsentationskompetenz durch Tablet-PC-gestützte Videoanalyse
Becker, S., Klein, P., Gößling, A., & Kühn, J. (2019) · Zeitschrift für Didaktik der Naturwissenschaften · doi:10.1007/s40573-019-00089-4 · Cited by 17
Engineering Education Research
Loui, M. C., & Borrego, M. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.012 · Cited by 17
Editorial: Recent Approaches for Assessing Cognitive Load From a Validity Perspective
Krell, M., Xu, K. M., Rey, G. D., & PAAS, F. G. W. C. (2022) · Frontiers in Education · doi:10.3389/feduc.2021.838422 · Cited by 16
“For example, a comparison between subjective and objective measures has been proposed as a source of validity evidence for subjective measures and as a way to learn about what the different measures are measuring (Leppink et al., 2013; Korbach et al., 2018; Solhjoo et al., 2019).”
BackgroundMethodSelf-citationKhasawneh, Y. J. A., & Khasawneh, M. A. S. (2024) · International Journal of ADVANCED AND APPLIED SCIENCES · doi:10.21833/ijaas.2024.12.004 · Cited by 25
“Nevertheless, the efficacy of these technologies in special education settings depends on several elements, such as their influence on cognitive load (Sweller, 1988; Leppink et al., 2013).”
Weißgerber, S. C., & Rummer, R. (2022) · Learning and Instruction · doi:10.1016/j.learninstruc.2022.101679 · Cited by 14
Finger pointing to support learning from split-attention examples
Zhang, S., de Koning, B. B., & PAAS, F. G. W. C. (2023) · Educational Psychology · doi:10.1080/01443410.2023.2193696 · Cited by 16
“Future studies could consider using scales that specify different types of cognitive load (e.g. Leppink et al., 2013) and/or physiological measures such as eye-tracking.”
BackgroundSelf-citationPi, Z., Zhang, Y., Yu, Q., & Yang, J. (2023) · Educational Technology Research and Development · doi:10.1007/s11423-023-10256-7 · Cited by 14
“…multi-dimensional questionnaires such as a 10-item questionnaire, which can measure the intrinsic, extraneous, and germane cognitive loads (Leppink et al., 2013), should be used in future research to better understand the underlying mechanism of the effects of peer presence and level of…”
MethodGutiérrez, G., Lunsky, I. O., Heer, S. V., Szulewski, A., & Chaplin, T. (2023) · Canadian Journal of Emergency Medicine · doi:10.1007/s43678-023-00586-z · Cited by 19
“Faculty and outcome assessors remained blinded to group allocation through the data collection and analysis process [15].”
BackgroundMethodResultAtiomo, W., Ennab, F., Stanley, A. G., & Ezimokhai, M. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1304417 · Cited by 17
“The quantitative domain was based on an expanded cognitive load scale (28) initially developed by Leppink et al. (29) and is one of the most validated and widely used self-report measures of intrinsic load (IL), extraneous load (EL), and germane load (GL).”
MethodChoi, W. C., Choi, W. C., & Choi, I. C. (2024) · IEEE World Engineering Education Conference (EDUNINE) · doi:10.1109/edunine60625.2024.10500551 · Cited by 23
“This study utilized the CS CLCS [17], as detailed in Table II, a version modified from Leppink et al.'s original cognitive load measurement tool [18] and specialized for computer science education.”
MethodThe Potential of Learning With AI-Generated Pedagogical Agents in Instructional Videos
Lim, J. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3647966 · Cited by 15
“It has been developed and used in previous studies [17, 18].”
MethodVideo Tutorials in the Traditional Classroom: The Effects on Different Types of Cognitive Load
Fan, E., Bower, M., & Siemon, J. (2024) · Technology Knowledge and Learning · doi:10.1007/s10758-024-09754-1 · Cited by 21
“This fluidity implies that cognitive load is not static during the learning process, and therefore it is necessary to add dynamic studies of cognitive load in the future (Leppink et al., 2013 ; Paas et al., 2016).”
InfluentialYohannan, D. G., Oommen, A. M., Kumar, A. S., Devanand, S., Minha Resivi, U. T., Sajan, N., Thomas, N. E., Anzer, N., Raju, N. K., Thomas, B., et al. (2024) · BMC Medical Education · doi:10.1186/s12909-024-05910-4 · Cited by 14
“If IL is optimal (which means the right complexity of the task to the right learner) and EL is low, learners can impose GL and engage in activities that elaborate their knowledge and facilitate learning [34].”
InfluentialThe interactive effects of pedagogical agent role and voice emotion design on children’s learning
Liao, M., Luo, X., Yang, H., & Zhu, K. (2024) · Current Psychology · doi:10.1007/s12144-024-06559-4 · Cited by 13
“The Cognitive Load scale developed by Leppink et al. (2013) was used to measure the degree of cognitive load participants experienced watching the instructional video.”
Hawthorne, B. S., Slemp, G. R., Vella‐Brodrick, D., & Hattie, J. (2024) · Learning and Individual Differences · doi:10.1016/j.lindif.2024.102597 · Cited by 15
The Impact of Game-Based Interventions on Adult Cognition: A Systematic Review
Coelho, F., Gonçalves, D. J. V., & Abreu, A. M. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2462746 · Cited by 14
“…from the inherent difficulty of the material; extraneous, caused by irrelevant information or distractions; and germane, which is related to developing memory through activities that support learning strategies (Leppink et al., 2013; Sweller et al., 1998; van Merri € enboer & Sweller, 2005).”
Not easy to “like”: How does cognitive load influence user engagement in online reviews?
Wang, Y., & Li, K. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114436 · Cited by 13
The Effects of Information Request Language and Template Usage on Query Formulation
Vijayasarathy, L. R., & Casterella, G. I. (2016) · Journal of the Association for Information Systems · doi:10.17705/1jais.00440 · Cited by 15
“To understand the range of situations in which the template helps learners, future research should include the impact of the template on the different types of cognitive load (Leppink et al., 2013).”
BackgroundUsing Multimedia to Teach Self-Regulated Strategy Development to Preservice Teachers
Romig, J. E., Sundeen, T. H., Thomas, C. N., Kennedy, M. J., Philips, J., Peeples, K. N., Rodgers, W., & Mathews, H. M. (2018) · Journal of Special Education Technology · doi:10.1177/0162643417746373 · Cited by 17
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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