Are high-coherent concept maps better for prior knowledge activation? Differential effects of concept mapping tasks on high school vs. university students
Abstract
We investigated whether and how prior knowledge activation improves learning outcomes for high school (less experienced learners) and university students (experienced learners) in a hypertext environment. Map coherence was defined as the extent to which relationships between the concepts in the map were made explicit. Therefore, we classified the mapping task of creating and labelling lines as low‐coherent, and the mapping task of labelling provided lines as high‐coherent. Learners were randomly assigned to the conditions of (1) high‐coherent knowledge activation; (2) low‐coherent knowledge activation; and (3) a baseline condition without prior knowledge activation. We found an overall effect for prior knowledge activation, learning experience, and an interaction between learning experience and the coherence of the prior knowledge activation task on learning outcomes. High school students benefited most from labelling provided lines, while university physics majors benefited most from creating and labelling lines. This interaction effect and effects of the specific mapping tasks on process measures support the claim that different prior knowledge activation tasks are suited for different groups of learners.
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Pre-constructed concept maps are more effective as pre-training for learners with lower prior knowledge than having learners create their own.
“research suggests that pre-constructed concept maps are more effective as pre-training for learners with lower prior knowledge than having them create their own (Gurlitt and Renkl, 2008; Gurlitt and Renkl, 2010).”
From Rethinking pre-training: cognitive load implications for learners with varying prior knowledge (2025) · cites this paper as Gurlitt and Renkl, 2008
A 2008 study found that university physics majors could connect and describe nodes in a way that generated learning, while high school students learned more by labeling existing connectors to the nodes.
“A 2008 study found that, while university physics majors could connect and describe nodes in a way that generated learning, high school students learned more by labeling existing connectors to the nodes (Gurlitt and Renkl, 2008).”
From Moving the Needle: Evidence of an Effective Study Strategy Intervention in a Community College Biology Course (2022) · cites this paper as Gurlitt and Renkl, 2008
Not all students can generate a concept map from scratch.
“There is also evidence that not all students can generate a concept map from scratch.”
From Moving the Needle: Evidence of an Effective Study Strategy Intervention in a Community College Biology Course (2022) · cites this paper as Gurlitt and Renkl, 2008
Cites
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Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction
Kalyuga, S. (2007) · Educational Psychology Review · doi:10.1007/s10648-007-9054-3 · Cited by 1,056 · cited 3× · see citing works
“This is compatible with the expertise reversal effect postulated within Cognitive Load Theory (e.g. Kalyuga et al. 2003; Kalyuga 2007), which describes the finding that more information and structure is favourable for inexperienced learners, whereas less information and structure is favourable for…”
BackgroundResultGerjets, P., & Scheiter, K. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_5 · Cited by 176 · see citing works
A Meta-analysis of the Effects of Advance Organizers on Learning and Retention
Luiten, J., Ames, W., & Ackerson, G. (1980) · American Educational Research Journal · doi:10.3102/00028312017002211 · Cited by 151 · cited 1× · see citing works
“To our knowledge, there have been no studies about effects and interactions of different prior knowledge activation tasks with learning experience (for reviews, see Mayer 1979; Luiten et al. 1980; Dochy 1992; Preiss & Gayle 2006).”
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Generative Learning: Which Strategies for What Age?
Brod, G. (2021) · Educational Psychology Review · doi:10.1007/s10648-020-09571-9 · Cited by 145 · see citing works
Gurlitt, J., & Renkl, A. (2010) · Instructional Science · doi:10.1007/s11251-008-9090-5 · Cited by 103 · see citing works
Self-citationHattan, C., Alexander, P. A., & Lupo, S. M. (2024) · Review of Educational Research · doi:10.3102/00346543221148478 · Cited by 90 · see citing works
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Static and interactive concept maps for chemistry learning
Wong, R. M., Sundararajan, N., Adesope, O. O., & Nishida, K. R. A. (2021) · Educational Psychology · doi:10.1080/01443410.2020.1761299 · Cited by 23 · see citing works
Vemu, S., Denaro, K., Sato, B. K., & Williams, A. E. (2022) · CBE—Life Sciences Education · doi:10.1187/cbe.21-08-0216 · Cited by 15 · see citing works
“A 2008 study found that, while university physics majors could connect and describe nodes in a way that generated learning, high school students learned more by labeling existing connectors to the nodes (Gurlitt and Renkl, 2008).”
Rethinking pre-training: cognitive load implications for learners with varying prior knowledge
Gorbunova, A., Kapuza, A., Chen, O., & Costley, J. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1628047 · Cited by 14 · see citing works
- Authors
- Gurlitt, J., & Renkl, A.
- Affiliations
- University of Freiburg (DE)
- Corresponding author
- Gurlitt, J.
- ORCID
- Renkl, A.
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2008-09-05
- Volume
- 24
- Issue
- 5
- Pages
- 407-419
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W1576621250
- Cited by
- 54
- References
- 5
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 1 · 2020: 4 · 2019: 3 · 2018: 4 · 2017: 4 · 2016: 2 · 2015: 5 · 2014: 7 · 2013: 2 · 2012: 4
- FWCI
- 3.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Assisted Learning (publishedVersion)
- 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 › Information Systems › Educational Technology and Assessment
- Keywords
- prior knowledge activation, concept maps, hypertext learning, learning experience, high school students, university students, physics learning, learning outcomes
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