The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective
Abstract
Cognitive load research has shown that learning from worked-out examples, in comparison to problem solving, is very effective during the initial stages of cognitive skill acquisition. In later stages, however, solving problems is superior. In this contribution, theoretical analyses of different types of cognitive load and their changes over the stages of skill acquisition are presented. Two basic arguments are put forth: (a) Intrinsic cognitive load gradually decreases so that a gradual increase of problem-solving demands is possible without inducing cognitive overload. (b) In contrast to the earlier stages, different learner activities during the later stages constitute either germane or extraneous load, because different instructional goals are to be achieved. Based on these analyses, we propose a fading procedure in which problem-solving elements are successively integrated into example study until the learners are expected to solve problems on their own. Empirical evidence supporting this fading procedure is provided, and future research is proposed that focuses on how to ensure that the fading procedure is adaptive to the learners' prior knowledge levels.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Cognitive load effects that are relevant in the beginning of a longer educational program (e.g. guided problem-solving, worked examples) are no longer relevant in later stages of the program, after the learners acquired sufficient expertise.”
From Cognitive Architecture and Instructional Design: 20 Years Later (2019) · cites this paper as Renkl and Atkinson (2003)
Citations
Cites
Anderson, J. R. (2013) · doi:10.4324/9781315799438 · Cited by 6,761
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
Cognitive Tutors: Lessons Learned
Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0402_2 · Cited by 1,982
Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_4 · Cited by 1,927
Self‐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
The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra
Sweller, J., & Cooper, G. A. (1985) · Cognition and Instruction · doi:10.1207/s1532690xci0201_3 · Cited by 1,214
Learning from Examples: Instructional Principles from the Worked Examples Research
Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. W. (2000) · Review of Educational Research · doi:10.3102/00346543070002181 · Cited by 1,109
Self-citationTaking the Load Off a Learner's Mind: Instructional Design for Complex Learning
van Merrienboer, J. J. G., Kirschner, P. A., & Kester, L. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_2 · Cited by 857
Learning from worked-out examples: A study on individual differences
RENKL, A. (1997) · Cognitive Science · doi:10.1016/s0364-0213(99)80017-2 · Cited by 679
Self-citationWhen problem solving is superior to studying worked examples.
Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001) · Journal of Educational Psychology · doi:10.1037/0022-0663.93.3.579 · Cited by 548 · cited 1×
“In a recent study, Kalyuga, Chandler, Tuovinen, and Sweller (2001) analyzed mechanical trade apprentices’ learning about relay circuits and their programming in different stages of skill ac quisition.”
Background
Flagged first, then by citations
Cited by
Sorted by citations
Items 201–300 of 539
Huertas, A., Vargas, O. L., & Rodríguez, L. B. S. (2016) · Journal of Educational Computing Research · doi:10.1177/0735633116656634 · Cited by 24
“…scaffoldings do not favor the learning process to the same extent since they offer the same support to all the students without respecting individual differences and, on the other hand, they do not fade in time making them repetitive independently of the lessons achieved (Renkl & Atkinson, 2003).”
BackgroundDynamics 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
“…(2003), van Merriënboer et al. (2002) Self-explanation/cognitive elaboration › › fl Renkl (1997), Renkl and Atkinson (2003), Renkl et al. (1998), Stark et al. (2002) Renkl and Atkinson (2003) Gerjets et al. (2006) Faded worked examples fl › , Renkl and Atkinson, 2003 Supportive information and…”
BackgroundInfluentialInquiring scaffolds in laboratory tasks: an instance of a “worked laboratory guide effect”?
Schmidt-Borcherding, F., Hänze, M., Wodzinski, R., & Rincke, K. (2013) · European Journal of Psychology of Education · doi:10.1007/s10212-013-0171-8 · Cited by 22
Learning from Computer Games: A Research Review
Tobias, S., & Fletcher, D. (2012) · Communications in computer and information science · doi:10.1007/978-3-642-33814-4_2 · Cited by 22
A Three‐way Interaction Model of Innovative Behavior, Task‐Related Learning, and Job Characteristics
Cangialosi, N., Odoardi, C., & Battistelli, A. (2019) · Performance Improvement Quarterly · doi:10.1002/piq.21322 · Cited by 21
The Worked Example Principle in Multimedia Learning
Renkl, A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333.023 · Cited by 21
Self-citationExploring the necessary conditions for observing interleaved practice benefits in math learning
Mielicki, M. K., & Wiley, J. (2022) · Learning and Instruction · doi:10.1016/j.learninstruc.2022.101583 · Cited by 28
Identifying indicators to guide adaptive scaffolding in games
Faber, T. J. E., Dankbaar, M. E. W., Kickert, R., van den Broek, W. W., & van Merriënboer, J. J. G. (2022) · Learning and Instruction · doi:10.1016/j.learninstruc.2022.101666 · Cited by 24
Evaluation of a medication calculation mobile app using a cognitive load instructional design
McMullan, M. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.07.005 · Cited by 21
“At this point, the major goal to be achieved is to increase the speed and accuracy of the performance and for the skill to become automated, which can only be achieved by the students practicing problem solving as opposed to only studying examples [8].”
InfluentialOsatis, C., & Asavanirandorn, C. (2022) · World Electric Vehicle Journal · doi:10.3390/wevj13060098 · Cited by 21
Rough Set Theory Based Fuzzy TOPSIS on Serious Game Design Evaluation Framework
Su, C.-H., Chen, K. T.-K., & Fan, K.-K. (2013) · Mathematical Problems in Engineering · doi:10.1155/2013/407395 · Cited by 21
“Cognitive load is based on the load when learners understand how to deal with materials [42, 43].”
BackgroundUncovering the problem-solving process to design effective worked examples.
van Gog, T. (2006) · DSpace (Open University in the Netherlands) · Cited by 21
Designing and Implementing Effective Animations and Simulations for Chemistry Learning
Schwartz, R. N., Milne, C. E., Homer, B. D., & Plass, J. L. (2013) · ACS symposium series · doi:10.1021/bk-2013-1142.ch003 · Cited by 22
Cognitive load considerations for Augmented Reality in network security training
Herbert, B. M., Wigley, G., Ens, B. M., & Billinghurst, M. (2021) · Computers & Graphics · doi:10.1016/j.cag.2021.09.001 · Cited by 23
Transitional feedback schedules during computer-based problem-solving practice
Johnson, A. M., Reisslein, J., & Martin Reisslein, B. (2014) · Computers & Education · doi:10.1016/j.compedu.2014.10.020 · Cited by 20
“Once a learner has developed domain-relevant schemas, individual elements are chunked in long-termmemory (Anderson, 1993; Laird, Rosenbloom,& Newell, 1986) and intrinsic cognitive load is decreased for learning tasks within the same domain (Renkl & Atkinson, 2003).”
BackgroundHalabi, A. K. (2006) · Cited by 21
Chang, T., Hsu, J., & Yu, P.-T. (2011) · Educational Technology & Society · Cited by 20
Subramani, M., Wagle, M., Ray, G., & Gupta, A. (2021) · MIS Quarterly · doi:10.25300/misq/2021/15635 · Cited by 22
To Flip or Not to Flip: What Are the Questions?
Simonson, S. R. (2017) · Education Sciences · doi:10.3390/educsci7030071 · Cited by 21
“In these situations, considerable scaffolding may be required to help students understand the content/concepts [13,32,34].”
BackgroundSweller, J., Ayres, P., & Kalyuga, S. (2011) · Springer eBooks · doi:10.1007/978-1-4419-8126-4_13 · Cited by 19
Nievelstein, F., van Gog, T., Boshuizen, H. P. A., & Prins, F. J. (2008) · Instructional Science · doi:10.1007/s11251-008-9076-3 · Cited by 22
“Research on scaffolding or fading instructional guidance has shown that providing high levels of support initially (e.g., by reducing the amount of search required through the use of worked examples or by other means) and then slowly fading this out with increasing student expertise/knowledge, makes the learning proce…”
BackgroundUsing Cognitive Load to Evaluate Participation and Design of an Asynchronous Course
McQuaid, J. W. (2010) · American Journal of Distance Education · doi:10.1080/08923647.2010.519949 · Cited by 20
“According to Renkl and Atkinson (2003), as the learner progresses through instructional content and learns the material, the intrinsic load gradually reduces.”
Williamson, A. K., Antonio, M. G., Davis, S., Kameswaran, V., Dillahunt, T. R., Buis, L. R., & Veinot, T. C. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad257 · Cited by 20
“23 Therefore, CL may be relatively high for low-income people, including those who seek care at FQHCs, who have often had fewer opportunities to access technology than people with higher incomes.”
BackgroundEffect of worked examples and Cognitive Tutor training on constructing equations
Reed, S. K., Corbett, A. T., Hoffman, B., Wagner, A. Z., & MacLaren, B. (2012) · Instructional Science · doi:10.1007/s11251-012-9205-x · Cited by 18
“Ten experiments have compared intelligent-tutor assisted problem solving to either interleaved worked examples or ‘‘faded’’ worked examples (Renkl and Atkinson 2003) in CTs for stoichiometry (McLaren et al. 2008), algebra equation solving (Anthony 2008), geometry problem solving (Salden et al.…”
BackgroundKissane, M., Kalyuga, S., Chandler, P., & Sweller, J. (2008) · Educational Psychology · doi:10.1080/01443410802322069 · Cited by 18
“Renkl, Atkinson, Maier, and Staley (2002), Renkl and Atkinson (2003), and Renkl, Atkinson, and Groβe (2004) demonstrated the advantage of a fading method in comparison with an abrupt switch from worked examples to problems.”
BackgroundSweller, J. (2016) · Education Review · doi:10.14507/er.v23.2025 · Cited by 17
Moon, J. A., & Brockway, D. (2019) · Journal of Research on Technology in Education · doi:10.1080/15391523.2019.1566038 · Cited by 19
“There are a few methods that have been found to induce germane load, for instance, prompting for self-explanation (Renkl & Atkinson, 2003) and the worked examples approach, which presents learners with example problems with step-by-step solutions (Paas & Van Merri € enboer, 1994).”
MethodMalmi, L., Utting, I., & Ko, A. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.022 · Cited by 18
Schulz, A. L., & Leuders, T. (2018) · Learning and Individual Differences · doi:10.1016/j.lindif.2018.04.014 · Cited by 16
Learning Outside the Classroom
Begel, A., & Ko, A. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.027 · Cited by 18
Ross, C., & Orr, R. R. (2007) · Educational Technology Research and Development · doi:10.1007/s11423-007-9047-4 · Cited by 16
“Furthermore, as an understanding of the most effective techniques can be combined with an emerging understanding of the problem domain, the novice troubleshooter is able to devote more effort to the problem and spend less time trying to utilize more general problem solving approaches ( Renkl & Atkinson, 2003 ).”
BackgroundWang, Z., & Adesope, O. (2016) · International Journal of Instruction · doi:10.12973/iji.2016.923a · Cited by 17
Digital Multimedia Perception and Design
(2006) · IGI Global eBooks · doi:10.4018/978-1-59140-860-4 · Cited by 16
Example-based learning: exploring the use of matrices and problem variability
Hancock-Niemic, M. A., Lin, L., Atkinson, R. K., Renkl, A., & Wittwer, J. (2015) · Educational Technology Research and Development · doi:10.1007/s11423-015-9403-8 · Cited by 16
“The advantage of the fading approach is its ability to reduce extraneous cognitive load during skill acquisition and schema building (Renkl and Atkinson 2003; Renkl et al. 2004; van Gerven et al. 2000).”
BackgroundSelf-citationAstleitner, H., & Koller, M. (2006) · Revistes Científiques de la University of Barcelona (University of Barcelona) · Cited by 15
Computing for Other Disciplines
Guzdial, M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.020 · Cited by 20
Application to learning and teaching
Harris, K. R., Graham, S. W., & Urdan, T. (2012) · American Psychological Association eBooks · Cited by 15
Rethinking Cognitive Load Theory
Kalyuga, S., & Plass, J. L. (2025) · doi:10.1093/9780190078539.001.0001 · Cited by 18
Teaching and Assessing for Transfer from Block-to-Text Programming in Middle School Computer Science
Grover, S. (2021) · Research in mathematics education · doi:10.1007/978-3-030-65632-4_11 · Cited by 16
Sequence Matters but How Exactly? A Method for Evaluating Activity Sequences from Data.
Doroudi, S., Holstein, K., Aleven, V. A. W. M. M., & Brunskill, E. (2016) · Educational Data Mining · Cited by 13
Große, C. S. (2018) · Learning and Instruction · doi:10.1016/j.learninstruc.2018.06.004 · Cited by 14
A Theoretical Framework for Fostering Diagnostic Competences with Simulations in Higher Education
Chernikova, O., Heitzmann, N., Opitz, A., Seidel, T., & Fischer, F. (2022) · Springer eBooks · doi:10.1007/978-3-030-89147-3_2 · Cited by 22
Sequencing spatial concepts in problem-based GIS instruction
Howarth, J. T., & Sinton, D. S. (2011) · Procedia - Social and Behavioral Sciences · doi:10.1016/j.sbspro.2011.07.042 · Cited by 16
Cho, Y. H., & Lee, S. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.07.040 · Cited by 14
Wirzberger, M., Bijarsari, S. E., & Rey, G. D. (2017) · Acta Psychologica · doi:10.1016/j.actpsy.2017.07.001 · Cited by 15
“Moreover, the focus on temporal progression aligns with the initially introduced phases of skill acquisition and accompanying changes in learners’ task-related focus (Renkl & Atkinson, 2003; Renkl, 2014).”
BackgroundMethodInfluentialEngineering Education Research
Loui, M. C., & Borrego, M. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.012 · Cited by 17
The Effects of Rapid Assessments and Adaptive Restudy Prompts in Multimedia Learning.
Renkl, A., Skuballa, I. T., Schwonke, R., Harr, N., & Leber, J. (2015) · Educational Technology & Society · Cited by 14
Self-citationA Classification Framework for Practice Exercises in Adaptive Learning Systems
Pelánek, R. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.3027050 · Cited by 13
“A specific example of scaffolding (also called a fading procedure in this context) is the transition from worked-out examples, where students fill in just a few details, to independent problem solving [62].”
BackgroundMethodAre Inductive Teaching Methods Compatible with Cognitive Load Theory?
Gorbunova, A., van Merriënboer, J. J. G., & Costley, J. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09828-z · Cited by 23
“…effect” also shows that teaching methods that are important at the beginning of an educational program (e.g., example study and supported problem-solving) are no longer relevant in later stages of the program after the learners have acquired sufficient expertise (Renkl & Atkinson, 2003).”
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
Hsu, Y., Gao, Y., Liu, T. C., & Sweller, J. (2015) · Educational Technology & Society · Cited by 13
Faded-example as a Tool to Acquire and Automate Mathematics Knowledge
Retnowati, E. (2017) · Journal of Physics Conference Series · doi:10.1088/1742-6596/824/1/012054 · Cited by 13
Leveraging the Integrated Development Environment for Learning Analytics
Carter, A., Hundhausen, C. D., & Olivares, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.024 · Cited by 13
Reading Versus Doing: Methods of Teaching Problem-Solving in Introductory Statistics
Brisbin, A. G., & do Nascimento, E. M. (2019) · Journal of Statistics Education · doi:10.1080/10691898.2019.1637801 · Cited by 14
“…somewhat vague; worked examples have been found to be superior to practice problems for learners as inexperienced as high school students (Paas 1992; Renkl and Atkinson 2003; Salden et al. 2009) up to college students as advanced as in the second semester of a 2-semester course sequence…”
BackgroundMethodInfluentialAssessment Methodology for Computer-Based Instructional Simulations
Koenig, A. D., Iseli, M. R., Wainess, R., & Lee, J. J. (2013) · Military Medicine · doi:10.7205/milmed-d-13-00217 · Cited by 12
Integrating effective learning strategies in basic physics lectures: A thematic analysis
Gjerde, V., Holst, B., & Kolstø, S. D. (2021) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.17.010124 · Cited by 13
Progression Trajectory-Based Student Modeling for Novice Block-Based Programming
Fahid, F. M., Tian, X., Emerson, A., Wiggins, J. B., Bounajim, D., Smith, A., Wiebe, E., Mott, B., Boyer, K. E., & Lester, J. C. (2021) · ACM Conference on User Modeling, Adaptation and Personalization (UMAP) · doi:10.1145/3450613.3456833 · Cited by 12
“The categories of blocks are incrementally populated to reduce the cognitive complexity of tasks [45] and to increase the interface usability [49].”
BackgroundSchons, C., Obersteiner, A., Reinhold, F., Fischer, F., & Reiss, K. M. (2022) · Journal für Mathematik-Didaktik · doi:10.1007/s13138-022-00210-0 · Cited by 14
Effectiveness of Combining Worked Examples and Deliberate Practice for High School Geometry
Pachman, M., Sweller, J., & Kalyuga, S. (2014) · Applied Cognitive Psychology · doi:10.1002/acp.3054 · Cited by 12
“Study hypotheses and research questions The effectiveness of using worked examples for well-structured domains has been confirmed in a wide range of studies (Cooper and Sweller, 1987; Paas and van Merriënboer, 1994; Renkl & Atkinson, 2003).”
BackgroundEffective teaching of economics: A constrained optimization problem?
Hultberg, P. T., & Calonge, D. S. (2017) · The Journal of Economic Education · doi:10.1080/00220485.2017.1353458 · Cited by 12
Sketching and verbal self‐explanation: Do they help middle school children solve science problems?
Miller‐Cotto, D., Booth, J. L., & Newcombe, N. S. (2022) · Applied Cognitive Psychology · doi:10.1002/acp.3980 · Cited by 13
Mihalca, L., Mengelkamp, C., Schnotz, W., & PAAS, F. G. W. C. (2015) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2015.01.001 · Cited by 16
“Several studies have shown that completion problems are more effective than both full worked-out examples and conventional problems in facilitating transfer (e.g., Renkl, 2002; Renkl & Atkinson, 2003; Stark, 1999; Van Merriënboer & de Croock, 1992).”
Teacher Knowledge for Inclusive Computing Learning
Goode, J., & Ryoo, J. J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.025 · Cited by 12
Gjerde, V., Paulsen, V. H., Holst, B., & Kolstø, S. D. (2022) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.18.010136 · Cited by 18
Jung, J., Shin, Y., Chung, H., & Fanguy, M. (2025) · Journal of Computing in Higher Education · doi:10.1007/s12528-024-09407-3 · Cited by 11
“Previous studies have proposed various instructional design strategies to reduce extraneous cognitive load and promote germane cognitive load beneficial to learning (Paas & Sweller, 2012; Renkl & Atkinson, 2003).”
Mills, J. J. (2016) · UKnowledge (University of Kentucky) · doi:10.13023/etd.2016.069 · Cited by 13
“Learners can induce 23 generalized solutions without extraneous cognitive load (Paas, 1992; Renkl & Atkinson, 2003; van Merrienboer, 1990; van Merrienboer & deCroock, 1992; Sweller et al., 1998).”
Backgroundvan Harsel, M., Hoogerheide, V., Janssen, E. M., Verkoeijen, P. P. J. L., & van Gog, T. (2022) · Instructional Science · doi:10.1007/s11251-022-09589-2 · Cited by 18
“…a worked example or a practice problem or opt for completion problems (Experiment 2 and 3), which are partially worked-out examples that provide a medium level of support but require learners to complete some steps themselves (e.g., Paas, 1992; Renkl & Atkinson, 2003; Van Merriënboer et al., 2002).”
BackgroundAssessing Cognitive Load Theory to Improve Student Learning for Mechanical Engineers
Impelluso, T. J. (2009) · American Journal of Distance Education · doi:10.1080/08923640903294569 · Cited by 11
“Furthermore, it has been shown that complete, thorough, and fully commented programming examples provide greater motivation for novices than simply working out problems from scratch (Renkl and Atkinson 2003; Renkl, Atkinson, and Grosse 2004).”
BackgroundSaw, K. G. (2017) · Turkish Online Journal of Distance Education · doi:10.17718/tojde.340405 · Cited by 15
Boldbaatar, N., & Şendurur, E. (2018) · Journal of Educational Computing Research · doi:10.1177/0735633118806747 · Cited by 11
İbi̇li̇, E., İlhanlı, N., Zayim, N., & Yardımcı, A. (2022) · Educational Gerontology · doi:10.1080/03601277.2022.2070710 · Cited by 10
“A high level of perceived ease of use will positively affect the motivational elements of the person such as perceived enjoyment and satisfaction since it will ensure the emergence of a successful experience (Renkl & Atkinson, 2003).”
BackgroundDas Vier-Komponenten Instructional Design (4C/ID) Modell
van Merriënboer, J. J. G. (2019) · Springer Reference Psychologie · doi:10.1007/978-3-662-54373-3_8-1 · Cited by 11
Shin, Y., Jung, J., & Lee, H. J. (2023) · Metacognition and Learning · doi:10.1007/s11409-023-09362-x · Cited by 13
“Moreover, although error-based examples and self-explanation methods have been proposed to facilitate learners’ active thinking, extrinsic load has been generated depending on the time of provision and lack of learners’ prior knowledge (Renkl & Atkinson, 2003; Renkl et al., 2002).”
Lopez, J., Bhandari, S., Perry, L., Ayer, S. K., Hallowell, M. R., & Jones, M. (2025) · Journal of Construction Engineering and Management · doi:10.1061/jcemd4.coeng-15981 · Cited by 10
Computer Science Is Different!
Morrison, B. B. (2015) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/2787622.2787744 · Cited by 10
“A proven method for enhancing learning is to reduce unnecessary cognitive load on the student while they are trying to learn to solve problems [8].”
MethodWhen color coding backfires: A guidance reversal effect when learning with realistic visualizations
Skulmowski, A. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10796-6 · Cited by 10
“Furthermore, Skulmowski and Rey (2018) found a significant reduction of cognitive load through the use of color coding (see also Reisslein et al.”
BackgroundMethodTakır, A., & Aksu, M. (2012) · Creative Education · doi:10.4236/ce.2012.32037 · Cited by 11
“This effect suggests that learners should first be presented worked examples, followed by completion problems and then full problems assignments (Renkl & Atkinson, 2003) which was used in this study.”
MethodThe Efficacy of Using Diagrams When Solving Probability Word Problems in College
Beitzel, B. D., & Staley, R. K. (2014) · The Journal of Experimental Education · doi:10.1080/00220973.2013.876232 · Cited by 12
“A worked-example approach (Atkinson, Derry, Renkl, & Wortham, 2000), coupled with fading (Renkl & Atkinson, 2003), was used for these practice problems.”
MethodKollar, I., & Fischer, F. (2019) · Springer eBooks · doi:10.1007/978-3-662-55754-9_17 · Cited by 12
Active ingredients and factors for deep processing during an example-based training intervention
Hefter, M. H., & Berthold, K. (2021) · Learning Environments Research · doi:10.1007/s10984-020-09347-6 · Cited by 12
The Presentation of Self in Virtual Reality: A Cognitive Load Study
Mejia-Puig, L., & Chandrasekera, T. (2022) · Journal of Interior Design · doi:10.1111/joid.12234 · Cited by 10
“The last, germane CL, is the mental activities that directly relate to learning and building schemas (Renkl & Atkinson, 2003; Sweller et al., 1998).”
BackgroundHow block categories affect learner satisfaction with a block-based programming interface
Rodríguez, F. J., Price, K. M., Isaac, J., Boyer, K. E., & Gardner‐McCune, C. (2017) · IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) · doi:10.1109/vlhcc.2017.8103468 · Cited by 10
“Presenting a user with every possible construct in a language can increase a learner’s cognitive load [1], so organizing these components into coherent categories may improve usability.”
BackgroundDas Vier-Komponenten Instructional Design (4C/ID) Modell
van Merriënboer, J. J. G. (2020) · Springer eBooks · doi:10.1007/978-3-662-54368-9_8 · Cited by 18
Shen, C.-Y., & Chu, H.-P. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-07308-8_55 · Cited by 9
Vahrenhold, J., Cutts, Q. I., & Falkner, K. E. K. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.019 · Cited by 11
Hsu, L., Ueng, R., & Hsieh, S. (2019) · Contemporary Nurse · doi:10.1080/10376178.2019.1682463 · Cited by 11
“A well-designed instruction set ought to help learners alter long-term memory by facilitating schema construction and automation (Fraser et al., 2012; Hoogerheide & Paas, 2012; Kaylor, 2014; Kirschner, Sweller, & Clark, 2006; Renkl & Atkinson, 2003).”
BackgroundTofel‐Grehl, C., Searle, K. A., & Feldon, D. F. (2018) · International Society of the Learning Sciences, Inc. [ISLS]. eBooks · doi:10.22318/cscl2018.560 · Cited by 9
Assessment and grading for CS1
Barros, J. P. (2010) · Koli Calling International Conference on Computing Education Research · doi:10.1145/1930464.1930483 · Cited by 9
“[ 14 ]). Design alignment is schematically presented in Fig. 1, through the definition ofactivity-assignment modules.”
BackgroundAdaptive Feedback In Simulation-based Training
Billings, D. R. (2010) · Journal of International Crisis and Risk Communication Research · Cited by 9
Expressing and Addressing Uncertainty: A Study of Collaborative Problem-Solving Dialogues
Rodríguez, F. J., Price, K. M., & Boyer, K. E. (2017) · doi:10.22318/cscl2017.30 · Cited by 9
“Research on cognitive load theory suggests that having too many simultaneous workflows puts a strain on working memory, limiting the amount of information that can be processed (Renkl & Atkinson, 2010).”
BackgroundLancaster, T., Robins, A. V., & Fincher, S. A. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.015 · Cited by 11
Email Overload: Investigating Technology-fit Antecedents and Job-related Outcome
Tarafdar, M., Wenninger, H., & Stich, J. (2023) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/3595863.3595869 · Cited by 11
“Since individuals have a finite capacity to process and assimilate information, email overload can lead to lowered productivity with the email application (Brown et al., 2014; O’Reilly, 1980; Renkl & Atkinson, 2003).”
BackgroundEffects of Verbalization as a Learning Strategy :
Ito, T. (2009) · The Japanese Journal of Educational Psychology · doi:10.5926/jjep.57.237 · Cited by 8
“…いる。たとえば,数学(Aleven&Koedinger,2002;Neuman & Schwarz,2000;Renkl,Stark,Gruber,&Mandl,1998)や物 理(Chi et al., 1989),プログラミング学習(Bielaczyc et al.,1995)などである。さらに,自己説明を利用できる 学習者の年齢も様々であり,当初中学生(Chi et al.,1994; Neuman& Schwarz,2000)や高校生(Aleven& Koedinger, 2002),そして大学生(Bielaczyc et al.,1995 ;Renkl et…”
Jung, J., Kim, D., & Na, C. (2016) · Educational Technology & Society · Cited by 8
Haden, P. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.007 · Cited by 10
The (in)effectiveness of visual representations as an aid to solving probability word problems
Beitzel, B. D., Staley, R. K., & DuBois, N. F. (2011) · Effective Education · doi:10.1080/19415532.2011.604256 · Cited by 12
“This fading of instructional support thus requires gradually increased independence on the part of students as they solve these problems (Renkl & Atkinson, 2003 ).”
BackgroundLee, Y.-J. (2010) · Journal of Educational Computing Research · doi:10.2190/ec.42.4.b · Cited by 8
“Although several studies have demonstrated the instructional benefits of the completion strategy (Renkl, 1997; Renkl & Atkinson, 2003; Renkl, Atkinson, Maier, & Staley, 2002), much research is still required to identify how much instructional support should be removed from worked examples and…”
BackgroundTesting the additivity hypothesis of cognitive load theory
Park, B. (2010) · Publications of the UdS (Saarland University) · doi:10.22028/d291-23309 · Cited by 9
Aufgabendesign und basismodellorientierter Physikunterricht
Draxler, D. (2006) · DuEPublico (University of Duisburg-Essen) · Cited by 8
Metadata
- Authors
- Renkl, A., & Atkinson, R. K.
- Affiliations
- University of Freiburg (DE)
- Arizona State University (US)
- ORCID
- Renkl, Alexander
- Venue
- Educational Psychologist
- Publisher
- Informa UK Limited
- Published
- 2003-01-01
- Volume
- 38
- Issue
- 1
- Pages
- 15-22
- ISSN
- 0046-1520 (ISSN-L)
- 1532-6985
- OpenAlex
- W2017974841
- Cited by
- 540
- References
- 23
- Citations by year
- 2026: 21 · 2025: 24 · 2024: 15 · 2023: 17 · 2022: 20 · 2021: 33 · 2020: 22 · 2019: 65 · 2018: 18 · 2017: 20 · 2016: 20 · 2015: 31 · 2014: 20 · 2013: 22 · 2012: 21
- FWCI
- 23.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational Psychologist (publishedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (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
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- cognitive load, worked examples, problem solving, cognitive skill acquisition, intrinsic cognitive load, germane load, extraneous load, fading procedure, prior knowledge, cognitive overload
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.
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