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The more human, the higher the performance? Examining the effects of anthropomorphism on learning with media.
Abstract
The inclusion of human-like shapes like arms or faces in rather abstract pictures triggers the tendency of anthropomorphism, which is defined as the attribution of human characteristics to nonhuman objects. Anthropomorphism-triggering features in digital learning materials were found to enhance the performance of students. However, the probability of how effective such anthropomorphic features are might be dependent on the degree of the elicited anthropomorphism. In this study, 3 experiments were conducted to examine if varying degrees of anthropomorphism (low vs. medium vs. high) differently affect the learning performance of students. Participants were taken from different class levels; ranging from Class 5 and 6 (Experiment 1) to Class 8 and 9 (Experiment 2), and Class 11 to 13 (Experiment 3). The instructional material covered the topic of blood cell types. Subjective measurements of cognitive load, aesthetics, intrinsic motivation, and valence were included. Results show that an increased degree of anthropomorphism led to significant differences in the learning, intrinsic motivation, and aesthetics scores. The learning results of the 3 experiments were additionally checked by a meta-analysis. On a descriptive level, only students in Class 8 and 9 profited the most from a high degree of anthropomorphism. While students in Class 5 and 6 suffered from a high cognitive load in the high anthropomorphism condition, students in Class 11 to 13 were not as strongly affected by anthropomorphism as the other students. Results are partly explained by differences in prior knowledge. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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Learning in educational contexts is enhanced by anthropomorphic features such as face-like appearance.
“learning in educational contexts is enhanced by anthropomorphic features such as face-like appearance8”
From The influence of mental state attributions on trust in large language models (2025) · cites this paper as [8]
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Metadata
- Authors
- Schneider, S., Häßler, A., Habermeyer, T., Beege, M., & Rey, G. D.
- Affiliations
- Chemnitz University of Technology (DE)
- Venue
- Journal of Educational Psychology
- Published
- 2019-01
- Volume
- 111
- Issue
- 1
- Pages
- 57-72
- ISSN
- 0022-0663 (ISSN-L)
- 1939-2176
- OpenAlex
- W2794552013
- Cited by
- 54
- References
- 0
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 8 · 2023: 5 · 2022: 10 · 2021: 6 · 2020: 3 · 2019: 1
- FWCI
- 3.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Psychology (publishedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Communication › Media Influence and Health
- Keywords
- anthropomorphism, learning performance, intrinsic motivation, cognitive load, aesthetic appeal, valence, prior knowledge, grade level differences, blood cell types, digital learning resources
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