The DOI matches its Crossref record; 39 of the 52 references it cites were found in a registry or an index.
Variability of worked examples and transfer of geometrical problem-solving skills: A cognitive-load approach.
Open accessAbstract
Four computer-based training strategies for geometrical problem solving in the domain of computer numerically controlled machinery programming were studied with regard to their effects on training performance, transfer performance, and cognitive load. A low- and a high-variability conventional condition, in which conventional practice problems had to be solved (followed by worked examples), were compared with a low- and a high-variability worked condition, in which worked examples had to be studied. Results showed that students who studied worked examples gained most from high-variability examples, invested less time and mental effort in practice, and attained better and less effort-demanding transfer performance than students who first attempted to solve conventional problems and then studied work examples. In complex cognitive domains such as mathematics, phys-ics, or computer programming, problem solutions can often be characterized by a hierarchical goal structure. The goal of these solutions can be attained only by successfully attaining all subgoals. Learning and performance of complex cogni-tive tasks are typically constrained by limited processing ca-
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Citations
Cites
Cognitive Load During Problem Solving: Effects on Learning
Sweller, J. (1988) · Cognitive Science · doi:10.1016/0364-0213(88)90023-7 · Cited by 11,048
Shiffrin, R. M., & Schneider, W. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.127 · Cited by 7,335
Controlled and automatic human information processing: I. Detection, search, and attention.
Schneider, W., & Shiffrin, R. M. (1977) · Psychological Review · doi:10.1037/0033-295x.84.1.1 · Cited by 5,902
A capacity theory of comprehension: individual differences in working memory
Just, M. A., & Carpenter, P. A. (1992) · Psychological Review · doi:10.1037/0033-295x.99.1.122 · Cited by 4,153
Handbook of perception and human performance
Boff, K. R., Kaufman, L., & Thomas, J. P. (1986) · Wiley eBooks · Cited by 4,033
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
Controlled and automatic human information processing: I
Schneider, W. E., & Shiffrin, R. M. (1977) · Cited by 2,228
Paas, F. G. W. C. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.4.429 · Cited by 2,150
Self-citationSelf‐Explanations: How Students Study and Use Examples in Learning to Solve Problems
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989) · Cognitive Science · doi:10.1207/s15516709cog1302_1 · Cited by 1,714
Instructional control of cognitive load in the training of complex cognitive tasks
Paas, F. G. W. C., & Van Merriënboer, J. J. G. (1994) · Educational Psychology Review · doi:10.1007/bf02213420 · Cited by 968
Self-citation
Cited by
Sorted by citations
Items 401–500 of 1,170
Suitner, C., & Maass, A. (2015) · Advances in experimental social psychology · doi:10.1016/bs.aesp.2015.09.004 · Cited by 38
Wynder, M. B. (2017) · Accounting Education · doi:10.1080/09639284.2017.1361847 · Cited by 33
Undesirable Difficulty Effects in the Learning of High-Element Interactivity Materials
Chen, O., Castro-Alonso, J. C., PAAS, F. G. W. C., & Sweller, J. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01483 · Cited by 41
Self-citationSuryanto, H., Degeng, I. N. S., Djatmika, E. T., & Kuswandi, D. (2021) · Creativity Studies · doi:10.3846/cs.2021.12364 · Cited by 66
“In addition, the level of students understanding of problems given creative problem-solving strategies during the problem-solving process is very important (Paas et al., 2001; Paas & van Merriënboer, 1994; Schmidt et al., 2007; Schult et al., 2017; Sternberg, 1985).”
BackgroundKhalil, M. K., PAAS, F. G. W. C., Johnson, T. E., Su, Y. K., & Payer, A. F. (2008) · Anatomical Sciences Education · doi:10.1002/ase.19 · Cited by 31
Self-citationScharfenberg, F., & Bogner, F. X. (2011) · Research in Science Education · doi:10.1007/s11165-011-9251-4 · Cited by 36
Process support in learning tasks for acquiring complex cognitive skills in the domain of law
Nadolski, R. J., Kirschner, P. A., & van Merriënboer, J. J. G. (2006) · Learning and Instruction · doi:10.1016/j.learninstruc.2006.03.004 · Cited by 31
“In our study, investment is measured in terms of task motivation (Bonner, 1994; Maynard & Hakel, 1997), mental effort (Paas & van Merrie¨nboer, 1994), and time on task (Karweit, 1984).”
Self-citationKhalil, M. K., Mansour, M. M., & Wilhite, D. R. (2010) · Journal of Veterinary Medical Education · doi:10.3138/jvme.37.4.353 · Cited by 33
A Training Approach for the Transition of Repeatable Collaboration Processes to Practitioners
Kolfschoten, G. L., de Vreede, G., & Pietron, L. R. (2010) · Group Decision and Negotiation · doi:10.1007/s10726-010-9208-4 · Cited by 32
Tools for the identification and description of competencies.
Stoof, A. (2005) · DSpace (Open University in the Netherlands) · Cited by 32
Kuldas, S., Satyen, L., Ismail, H. N., & Hashim, S. (2014) · Psychologica Belgica · doi:10.5334/pb.aw · Cited by 37
Liu, T., Fan, M. H.-M., & PAAS, F. G. W. C. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.08.001 · Cited by 32
“Therefore, it is considered important to use cognitive load theory (Sweller, Ayres, & Kalyuga, 2011; Sweller, Van Merriënboer, & Paas, 1998) to identify the differential effects of the type of dictionary on vocabulary acquisition.”
BackgroundInfluentialSelf-citationKopainsky, B., & Sawicka, A. (2010) · System Dynamics Review · doi:10.1002/sdr.445 · Cited by 30
Learner Perspectives of Online Problem-Based Learning and Applications from Cognitive Load Theory
Chen, R. (2016) · Psychology Learning & Teaching · doi:10.1177/1475725716645961 · Cited by 31
Tiettmeyer, J. M., Coleman, A. F., Balok, R. S., Harper-Gampp, T., Duffy, P. L., Mazzarone, K. M., & Grove, N. P. (2017) · Journal of Chemical Education · doi:10.1021/acs.jchemed.6b00363 · Cited by 32
Learning from Comparing Multiple Examples: On the Dilemma of “Similar” or “Different”
Guo, J., Pang, M. F., Yang, L.-Y., & Ding, Y. (2012) · Educational Psychology Review · doi:10.1007/s10648-012-9192-0 · Cited by 31
Web-based support for constructing competence maps: design and formative evaluation
Stoof, A., Martens, R. L., & van Merriënboer, J. J. G. (2006) · Educational Technology Research and Development · doi:10.1007/s11423-006-9014-5 · Cited by 31
“Guidelines for designing phenomenaria can be found in the literature on worked examples (e.g., Paas & van Merriënboer, 1994; Sweller, van Merriënboer, & Paas, 1990; Ward & Sweller, 1990).”
Self-citationCognitive load in algebra: element interactivity in solving equations
Ngu, B. H., Chung, S. F., & Yeung, A. S. (2014) · Educational Psychology · doi:10.1080/01443410.2013.878019 · Cited by 37
Chang, C., Warden, C. A., Liang, C., & Chou, P. (2017) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12218 · Cited by 37
Recent advances in expertise research
Rikers, R. M. J. P., & PAAS, F. G. W. C. (2005) · Applied Cognitive Psychology · doi:10.1002/acp.1108 · Cited by 31
Self-citationChatGPT Improves Creative Problem-Solving Performance in University Students: An Experimental StudyPreprint
Urban, M., Děchtěrenko, F., Lukavský, J., et al. (2023) · doi:10.31234/osf.io/9z2tc · Cited by 31
A discussion of the cognitive load in collaborative problem-solving: The decision-making phase
Kolfschoten, G. L., French, S., & Brazier, F. M. T. (2014) · EURO Journal on Decision Processes · doi:10.1007/s40070-014-0034-9 · Cited by 30
Simple Practice Doesn’t Always Make Perfect
Booth, J. L., McGinn, K. M., Young, L. K., & Barbieri, C. (2015) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/2372732215601691 · Cited by 30
Asghar, A., Sladeczek, I. E., Mercier, J., & Beaudoin, E. (2017) · Canadian Psychology/Psychologie canadienne · doi:10.1037/cap0000111 · Cited by 36
Wang, C., & Guo, J. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.01.234 · Cited by 30
“For physiological cognitive load measurements, the two main perspectives are HRV (heart rate variability)[9] and PR (pupillary responses)[10].”
BackgroundMeasuring cognitive load in test items: static graphics versus animated graphics
Dindar, M., Yurdakul, I. K., & Dönmez, F. İ. (2014) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12086 · Cited by 29
Environmental design for a structured network learning society
Chang, B., Cheng, N.-H., Deng, Y.-C., & Chan, T.-W. (2005) · Computers & Education · doi:10.1016/j.compedu.2004.11.008 · Cited by 30
Yang, L., & Hahn, J. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3006930 · Cited by 30
“It triggers reinforcing the association between the strategy/action and success (Audia et al. 2000; Greve 1998), which subsequently improves organizational performance and efficiency (Greve 2003a; Levinthal and March 1993).”
BackgroundCognitive Load Theory in E-Learning
van Mierlo, C. M., Jarodzka, H., Kirschner, F., & Kirschner, P. A. (2012) · IGI Global eBooks · doi:10.4018/978-1-4666-0315-8.ch097 · Cited by 38
Cosic, K., Popovic, S., Sarlija, M., Mijic, I., Kokot, M., Kesedzic, I., Strangman, G., Ivkovic, V., & Zhang, Q. (2019) · IEEE Access · doi:10.1109/access.2019.2957357 · Cited by 29
Varol, B., & Erçetin, G. (2019) · Computer Assisted Language Learning · doi:10.1080/09588221.2019.1643738 · Cited by 29
Cheng, Y.-P., Shen, P.-D., Hung, M.-L., Tsai, C.-W., Lin, C.-H., & Hsu, L. C. (2022) · Universal Access in the Information Society · doi:10.1007/s10209-020-00789-6 · Cited by 30
Mirhoseini, M., Pagé, S.-A., Léger, P., & Sénécal, S. (2021) · Journal of theoretical and applied electronic commerce research · doi:10.3390/jtaer16040047 · Cited by 29
“The concept of mental effort is often taken as an index of cognitive load [35], which in the context of online shopping could be categorized as either intrinsic or extraneous [36,37].”
BackgroundThe effects of verbally redundant information on student learning: An instance of reverse redundancy
Ari, F., Flores, R., Inan, F. A., Cheon, J., Crooks, S. M., Paniukov, D., & Kurucay, M. (2014) · Computers & Education · doi:10.1016/j.compedu.2014.04.002 · Cited by 31
Science teaching based on cognitive load theory: Engaged students, but cognitive deficiencies
Meissner, B. A., & Bogner, F. X. (2012) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2012.10.002 · Cited by 30
Instructional Control of Cognitive Load in the Design of Complex Learning Environments
Kester, L., PAAS, F. G. W. C., & van Merriënboer, J. J. G. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511844744.008 · Cited by 31
Self-citationKim, H. J., Park, Y., & Lee, J. (2024) · Educational Psychology Review · doi:10.1007/s10648-024-09878-x · Cited by 29
“Researchers have recognized and addressed the limitations of self‑report instru‑ ments by pioneering the measurement of psychophysiological variables as a direct and objective reflection of learners’ cognitive and emotional states (e.g., Paas and Van Merriënboer (1994)).”
The Expertise Reversal Effect for Sequential Presentation in Dynamic Soccer Visualizations
Khacharem, A., Zoudji, B., Kalyuga, S., & Ripoll, H. (2013) · Journal of Sport and Exercise Psychology · doi:10.1123/jsep.35.3.260 · Cited by 28
Mavilidi, M. F., & Zhong, L. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09463-7 · Cited by 36
Skuballa, I. T., Xu, K. M., & Jarodzka, H. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.06.016 · Cited by 34
Guzman, L. M., Pennell, M. W., Nikelski, E., et al. (2019) · CBE—Life Sciences Education · doi:10.1187/cbe.19-02-0041 · Cited by 28
Learning from animations and computer simulations: Modality and reverse modality effects
Liu, T., Lin, Y., Hsu, C., Hsu, C., & PAAS, F. G. W. C. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.12996 · Cited by 28
Self-citationStudying the effect of redundancy in a virtual reality classroom
Liu, T., Lin, Y., Wang, T.-N., Yeh, S., & Kalyuga, S. (2021) · Educational Technology Research and Development · doi:10.1007/s11423-021-09991-6 · Cited by 35
The Influence of Presentation, Organization, and Example Context on Text Learning
McCrudden, M. T., Schraw, G. J., Hartley, K., & Kenneth, A. K. (2004) · The Journal of Experimental Education · doi:10.3200/jexe.72.4.289-306 · Cited by 27
Teacher Learning and Professional Development
Fincher, S. A., Kolikant, Y. B., & Falkner, K. E. K. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.026 · Cited by 29
Monitoring accuracy and self‐regulation when learning to play a chess endgame
de Bruin, A. B. H., Rikers, R. M. J. P., & Schmidt, H. G. (2005) · Applied Cognitive Psychology · doi:10.1002/acp.1109 · Cited by 28
Bills, L., & Watson, A. (2008) · Educational Studies in Mathematics · doi:10.1007/s10649-008-9147-z · Cited by 28
Lewis, C. M., Shah, N., & Falkner, K. E. K. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.017 · Cited by 36
Real-Time Mental Workload Estimation Using EEG
Kartali, A., Janković, M. M., Gligorijević, I., et al. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-32423-0_2 · Cited by 27
Effect of on-screen text on multimedia learning with native and foreign-accented narration
Chan, K. Y., Lyons, C. W., Kon, L. L., Stine, K., Manley, M., & Crossley, A. (2020) · Learning and Instruction · doi:10.1016/j.learninstruc.2020.101305 · Cited by 29
Emotional and cognitive effects of learning with computer simulations and computer videogames
Magana, A. J., Hwang, J., Feng, S., Rebello, N. S., Zu, T., & Kao, D. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12654 · Cited by 33
The Impact of Persistent Pain on Working Memory and Learning
Smith, A. K., & Ayres, P. (2013) · Educational Psychology Review · doi:10.1007/s10648-013-9247-x · Cited by 29
Motivation, Attitudes, and Dispositions
Lishinski, A., & Yadav, A. K. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.029 · Cited by 34
Vocational Training in Virtual Reality: A Case Study Using the 4C/ID Model
Mulders, M. (2022) · Multimodal Technologies and Interaction · doi:10.3390/mti6070049 · Cited by 37
“High variability of learning task within the same task class is important to ensure transf r of learning [41].”
BackgroundUse of instructional technology to improve teacher candidate knowledge of vocabulary instruction
Ely, E., Pullen, P. C., Kennedy, M. J., Hirsch, S. E., & Williams, M. C. (2014) · Computers & Education · doi:10.1016/j.compedu.2014.01.013 · Cited by 27
The reverse modality effect: Examining student learning from interactive computer‐based instruction
Inan, F. A., Crooks, S. M., Cheon, J., Ari, F., Flores, R., Kurucay, M., & Paniukov, D. (2013) · British Journal of Educational Technology · doi:10.1111/bjet.12129 · Cited by 26
Going beyond performance scores
Sridhar, P. K., Chan, S., & Nanayakkara, S. C. (2018) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3202185.3202739 · Cited by 26
“The subjective or self-reporting method [41] has been the most commonly used method with adults due to its convenience.”
BackgroundMethodExpertise reversal effect: Cost of generating new schemas
Armougum, A., Gaston‐Bellegarde, A., Marle, C. J.-L., & Piolino, P. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106406 · Cited by 32
The integration of instructional systems design models and constructivistic design principles
DIJKSTRA, S. (1997) · Instructional Science · doi:10.1023/a:1002902427253 · Cited by 26
“…For instance, problems presented to learners at this level might be to predict a particular event (e.g. how long will it take for a ball dropping from a height of 10 metres to reach the surface of the moon) where an analogous solution (e.g., the computation for dropping a ball on earth) is 1994).”
BackgroundFalkner, K. E. K., & Sheard, J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.016 · Cited by 36
Jalani, N. H., & Sern, L. C. (2015) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2015.08.128 · Cited by 27
Darabi, A., Nelson, D. W., & Seel, N. M. (2009) · Computers in Human Behavior · doi:10.1016/j.chb.2009.01.009 · Cited by 25
Color Coding of Circuit Quantities in Introductory Circuit Analysis Instruction
Reisslein, J., Johnson, A. M., & Martin Reisslein, B. (2014) · IEEE Transactions on Education · doi:10.1109/te.2014.2312674 · Cited by 25
“Perceived cognitive load [58], [59] was assessed with two items adopted from [60], " The lesson was difficult " and " Learning the material in the lesson required a lot of effort " , and had an .”
MethodPreparing learners with partly incorrect intuitive prior knowledge for learning
Ohst, A., Fondu, B. M. E., Glogger‐Frey, I., Nückles, M., & Renkl, A. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00664 · Cited by 25
“We used subjective ratings of task difficulty as a measure of mental effort (Paas and van Merriënboer, 1993, 1994).”
MethodCognitive Load Theory: Instruction-based Research with Applications for Designing Tests
Elliott, S. N., Kurz, A., Beddow, P. A., & Frey, J. R. (2009) · Cited by 25
Principles for Designing Effective and Efficient Training of Complex Cognitive Skills
PAAS, F. G. W. C., & van Gog, T. (2009) · Reviews of Human Factors and Ergonomics · doi:10.1518/155723409x448053 · Cited by 31
Self-citationLin, P.-H., Liu, T., & PAAS, F. G. W. C. (2017) · Reading and Writing · doi:10.1007/s11145-017-9734-4 · Cited by 31
“Presumably, the cognitive capacity that is freed by this reduction of extraneous load, can be used to process the correctly spelled word more deeply (germane cognitive load) (Paas & van Merrie¨nboer, 1994; Paas, Renkl, & Sweller, 2003a).”
BackgroundSelf-citationEffects of practice with videos for software training
van der Meij, H., Rensink, I., & van der Meij, J. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.029 · Cited by 25
Design, Development, and Validation of Learning Objects
Nugent, G., Soh, L., & Samal, A. K. (2006) · Journal of Educational Technology Systems · doi:10.2190/9bf6-1kbl-y3cx-6qxg · Cited by 26
“The use of worked examples has shown distinct benefits for reducing extraneous cognitive load and promoting schema formation [19, 20].”
BackgroundThe Beast of Aggregating Cognitive Load Measures in Technology-Based Learning.
Leppink, J., & van Merriënboer, J. J. G. (2015) · Research Publications (Maastricht University) · Cited by 25
Self-citationQualitative Methods for Computing Education
Tenenberg, J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.008 · Cited by 24
Cognitive Effect of Tracing Gesture in the Learning from Mathematics Worked Examples
Yeo, L.-M., & Tzeng, Y. (2019) · International Journal of Science and Mathematics Education · doi:10.1007/s10763-019-09987-y · Cited by 29
Huang, K.-L., Chen, K.-H., & Ho, C.-H. (2014) · Australasian Journal of Educational Technology · doi:10.14742/ajet.538 · Cited by 23
“Recently, a lot of scholars have applied the cognitive load theory to instructional design in order to identify presentation methods that effectively communicate information to learners, thereby enhancing learning outcomes (Pastore, 2012). Starting from the standpoint of learning, psychologists Sweller, van Merriënboe…”
BackgroundÖzoğul, G., Johnson, A. M., Moreno, R., & Martin Reisslein, B. (2012) · IEEE Transactions on Education · doi:10.1109/te.2012.2190072 · Cited by 25
“Or should circuit analysis instruction employ a stepwise integrated design where the relevant equations only remain integrated in the circuit diagram during the particular problem step?”
BackgroundNgu, B. H., Mit, E., Shahbodin, F., & Tuovinen, J. E. (2008) · Instructional Science · doi:10.1007/s11251-008-9072-7 · Cited by 24
Kaba, A., & Beran, T. N. (2016) · Journal of Interprofessional Care · doi:10.3109/13561820.2015.1075967 · Cited by 22
Lu, J., Kalyuga, S., & Sweller, J. (2020) · Applied Cognitive Psychology · doi:10.1002/acp.3668 · Cited by 25
Adapting handwriting recognition for applications in algebra learning
Anthony, L., Yang, J., & Koedinger, K. R. (2007) · ACM International Workshop on Educational Multimedia and Multimedia Education (EMME) · doi:10.1145/1290144.1290153 · Cited by 24
“While this is only a preliminary result, we plan to explore this further in later studies by including a structured self-report of studentperceived cognitive load, modeled after [ 29 ], in which they asked students to rate their perceived amount of mental effort during various instructional paradigms.”
MethodDynamics of cognitive load theory: A model-based approach
Sawicka, A. (2007) · Computers in Human Behavior · doi:10.1016/j.chb.2007.03.007 · Cited by 25
Optimising student cognitive load in computer education
Tuovinen, J. E. (2000) · Australasian Computing Education Conference · doi:10.1145/359369.359405 · Cited by 26
“Provided the les.rnin~ coutent is not so difficult that it totally swamps the working tmmory [ 18 ], exercises that vary in their deep structure more effectively assist students to recognize appropriate solution schema classes than exercises with only one solution structure [12, 19].”
BackgroundChen, O., Retnowati, E., & Kalyuga, S. (2019) · British Journal of Educational Psychology · doi:10.1111/bjep.12317 · Cited by 23
Jaffe, J. B., & Bolger, D. J. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09821-6 · Cited by 34
“The notion of cognitive load has been used to refer to a “multi-dimensional construct that represents the load that performing a particular task imposes on the cognitive system” (Paas & Van Merriënboer, 1994, p. 122).”
MethodThe Influence of Cognitive Load on Transfer With Error Prevention Training Methods
Hutchins, S., Wickens, C. D., Carolan, T. F., & Cumming, J. M. (2013) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720812469985 · Cited by 25
Visual signaling in virtual world-based assessments: The SAVE Science project
Nelson, B. C., Kim, Y., Foshee, C. M., & Slack, K. (2013) · Information Sciences · doi:10.1016/j.ins.2013.09.011 · Cited by 24
“Cognitive load survey After completing the IVE-based assessment module, students answered seven questions on a web-based survey related to perceived cognitive load (adopted from [30]).”
BackgroundMethodMeasurement of Cognitive Load During Multimedia Learning Activities
Cook, A. E. (2009) · IGI Global eBooks · doi:10.4018/978-1-60566-158-2.ch003 · Cited by 24
The Roles of Working Memory and Cognitive Load in Geoscience Learning
Jaeger, A. J., Shipley, T. F., & Reynolds, S. J. (2017) · Journal of Geoscience Education · doi:10.5408/16-209.1 · Cited by 23
“The fourth category of cognitive load measures is physiological measures, which include heart rate (Paas and van Merriënboer, 1994) or brain activity (Antonenko and Niederhauser, 2010).”
BackgroundCognitive Load Theory, Spacing Effect, and Working Memory Resources Depletion
Chen, O., & Kalyuga, S. (2019) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-5225-9833-6.ch001 · Cited by 26
MMOD-COG: A Database for Multimodal Cognitive Load Classification
Mijić, I., Šarlija, M., & Petrinović, D. (2019) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2019.8868678 · Cited by 23
Moreno, R., Reisslein, M., & Delgoda, G. (2006) · 2022 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2006.322285 · Cited by 23
Zamary, A., & Rawson, K. A. (2016) · Educational Psychology Review · doi:10.1007/s10648-016-9396-9 · Cited by 24
Brown, T., Majors, T. M., & Peecher, M. E. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2483221 · Cited by 23
The effects of a theory‐based summary writing tool on students' summary writing
Chew, C. S., Idris, N. B., Loh, E. F., Wu, W. V., Chua, Y. P., & Bimba, A. T. (2019) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12349 · Cited by 23
Qayyum, A., Khan, M. K. A. A., Mazher, M., & Suresh, M. (2018) · IEEE Student Conference on Research and Development (SCOReD) · doi:10.1109/scored.2018.8711150 · Cited by 22
“These methods are based on analytical and empirical approaches [2-3].”
MethodRichter, J., Scheiter, K., Eder, T., Huettig, F., & Keutel, C. (2020) · PLoS ONE · doi:10.1371/journal.pone.0243060 · Cited by 22
“This recommendation is not to be confused with another instructional design principle, for which multiple labels have been used in the literature, that is, the contextual inference effect [53–55], the variability effect [56, 57] or interleaved practice [58], respectively.”
BackgroundCircuits Kit K–12 Outreach: Impact of Circuit Element Representation and Student Gender
Reisslein, J., Özoğul, G., Johnson, A. M., Bishop, K. L., Harvey, J., & Martin Reisslein, B. (2012) · IEEE Transactions on Education · doi:10.1109/te.2012.2222410 · Cited by 24
Prior knowledge moderates instructional effects on conceptual understanding of statistics
Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P. M., & Berger, M. P. F. (2012) · Educational Research and Evaluation · doi:10.1080/13803611.2011.640873 · Cited by 23
“Worked-out examples of problems can guide students into self-explanation, but it depends on the students' prior knowledge (Kalyuga et al, 2001 ) as well as on the design and instructions (Paas & Van Merrienboer, 1994 ; Van Merrienboer, Schuurman, De Croock, & Paas, 2002 ) of the worked-out examples whether students ac…”
Kostons, D. D. N. M., & de Koning, B. B. (2017) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2017.05.001 · Cited by 30
“, (1) very low effort, (2) low effort, (3) average effort, (4) high effort, and (5) very high effort; adapted from the cognitive load theory research paradigm; Paas & Van Merriënboer, 1994).”
Ngu, B. H., Yeung, A. S., Phan, H. P., Hong, K. S., & Usop, H. H. (2017) · The Journal of Experimental Education · doi:10.1080/00220973.2017.1347774 · Cited by 22
“Researchers have incorporated various design features (e.g., variability of worked examples) to generate germane cognitive load in order to benefit learning (Paas & van Merri€enboer, 1994).”
BackgroundGaly, É. (2017) · Theoretical Issues in Ergonomics Science · doi:10.1080/1463922x.2017.1381777 · Cited by 22
Wang, C.-C., Hung, J. C.-S., Chen, S.-N., & Chang, H.-P. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-5754-6 · Cited by 22
“Pass and Merriënboer [58] regarded cognitive load as the loads of the learning activities and the element interactivity of information on learners.”
Background
Metadata
- Authors
- Paas, F. G. W. C., & Van Merriënboer, J. J. G.
- Affiliations
- Maastricht University (NL)
- Venue
- Journal of Educational Psychology
- Published
- 1994-03
- Volume
- 86
- Issue
- 1
- Pages
- 122-133
- ISSN
- 0022-0663 (ISSN-L)
- 1939-2176
- OpenAlex
- W2116669434
- Cited by
- 1,198
- References
- 52
- Citations by year
- 2026: 69 · 2025: 45 · 2024: 51 · 2023: 40 · 2022: 46 · 2021: 50 · 2020: 49 · 2019: 89 · 2018: 42 · 2017: 52 · 2016: 42 · 2015: 68 · 2014: 69 · 2013: 62 · 2012: 59
- FWCI
- 7.63
- Type
- journal article
- Language
- en
- Open access
- green
- research.utwente.nl
- Licence
- other-oa
- Locations
- Journal of Educational Psychology (publishedVersion)
- University of Twente Research Information (publishedVersion, other-oa)
- University of Twente Research Information (submittedVersion, other-oa)
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- worked examples, transfer of learning, cognitive load, computer-based training, practice questions, cognitive effort, training performance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A second model labelled each claim on 2026-10-12 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
