Author(s)

QingQing Xing

Affiliation(s)

College of Education Sciences, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, Guangdong, China.

Corresponding Author

QingQing Xing

ABSTRACT

This study investigates how research student’s self-constructed conceptual metaphors influences learners’ understanding of technical terms. Unlike prior work focused on expert-designed metaphors, we analyze the "PixelFolder" metaphor created by a graduate student to describe her image synthesis research work. Through controlled experiments comparing this progressive construction metaphor against traditional instructional materials, we examine how such student-generated frameworks guide learners' conceptualization of image generation. The experiment compares two groups: an experimental group learning with materials based on the "PixelFolder" progressive pixel synthesis network, and a control group using traditional pixel model materials. We utilized the Tobii Pro Spectrum 1200 eye tracker to capture visual cognitive patterns of the 30 subjects, and employed Tobii Pro Lab to analyze fixation duration and heat maps, thereby revealing the distribution of cognitive focus while students were exposed with materials with and without metaphors. Furthermore, we conducted a series of semi-structured interviews. These were designed with the particular aim of eliciting the subjects' own metaphorical interpretations of the algorithmic process of image generation. This qualitative inquiry was judiciously supplemented by a reading comprehension test, which served as a more formal instrument for gauging the extent and accuracy of their conceptual mastery. Our initial observations may be stated as follows: the data strongly suggest that students exposed to the PixelFolder model exhibited a tendency to conceptualize image generation in terms of a progressive construction process. This mental model was not merely self-reported; it found a compelling correlation in the objective eye-tracking metrics. The visual attention patterns of these subjects revealed a more structured and coherent sequence of fixations, which we interpret as the external manifestation of a systematic and logically sound cognitive pathway. We believe this work contributes a valuable empirical datum to the study of conceptual metaphor formation in complex technical domains. It is also our hope that the methodology and findings herein will provide a solid foundation for the refinement of using conceptual metaphors as pedagogical approaches in the technical communication of computer graphics.

KEYWORDS

Deliberate metaphor; Image generation; Eye tracking; Cognitive load; Progressive construction

CITE THIS PAPER

QingQing Xing. How student-researcher metaphors guide technical understanding: an eye-tracking study. World Journal of Educational Studies. 2025, 3(6): 31-38. DOI: https://doi.org/10.61784/wjes3087.

REFERENCES

[1] Sweller J. Cognitive Load During Problem Solving: Effects on Learning. Cognitive Science, 1988, 12(2): 257-285. https://doi.org/10.1207/s15516709cog1202_4.

[2] Sweller J. Cognitive load theory and individual differences. Learning and Individual Differences, 2024: 102423. https://doi.org/10.1016/j.lindif.2024.102423.

[3] Skulmorski A, Rey GD. Embodied learning: introducing a taxonomy based on bodily engagement and task integration. Cognitive Research: Principles and Implications, 2018, 3(6): 6. https://doi.org/10.1186/s41235-018-0092-9.

[4] Barsalou LW. Grounded cognition. Annual Review of Psychology, 2008, 59: 617-645. https://doi.org/10.1146/annurev.psych.59.103006.093639.

[5] Steen GJ. Deliberate Metaphor Theory: Basic assumptions, main tenets, urgent issues. Intercultural Pragmatics, 2017, 14(1): 1-24.

[6] Exploring cognitive effort and divergent thinking in metaphor translation using eye-tracking and EEG technology. Scientific Reports, 2025, 15(1): 18177. https://doi.org/10.1038/s41598-025-03248-5.

[7] Lakoff G, Johnson M. Metaphors We Live By. University of Chicago Press, 1980.

[8] Steen GJ. The paradox of metaphor: Why we need a three-dimensional model of metaphor. Metaphor and Symbol, 2008, 23(4): 213-241.

[9] Steen GJ. Thinking by metaphor, fast and slow: Deliberate Metaphor Theory offers a new model for metaphor and its comprehension. Front Psychol. 2023, 5(14): 1242888. https://doi.org/10.3389/fpsyg.2023.1242888.

[10] Bowdle BF, Gentner D. The Career of Metaphor. Psychological Review, 2005, 112(1): 193–216. https://doi.org/10.1037/0033-295X.112.1.193.

[11] Cheon J, Grant MM. The effects of metaphorical interface on germane cognitive load in Web-based instruction. Educational Technology Research and Development, 2012: 399–420. https://doi.org/10.1007/s11423-012-9236-7.

[12] Wegner E, Burkhart C, Weinhuber M, et al. What metaphors of learning can (and cannot) tell us about students' learning. Learning and Individual Differences, 2020, 80: 101884. https://doi.org/10.1016/j.lindif.2020.101884.

[13] Gibbs RW. Does deliberate metaphor theory have a future? Journal of Pragmatics, 2015, 90: 73–76. https://doi.org/10.1016/j.pragma.2015.03.016.

[14] Tay D. A variational approach to deliberate metaphors. Cognitive Linguistic Studies, 2016, 3(2): 277–298. https://doi.org/10.1075/cogls.3.2.05ta.

[15] Gatcho AG, Manuel JPG, Sarasua RJG. Eye tracking research on readers' interactions with multimodal texts: A mini-review. Frontiers in Communication, 9, 1482105, 2024. https://doi.org/10.3389/fcomm.2024.1482105.

[16] Matthew G. The effect of subtitle format on cognitive load and comprehension: An eye-tracking study. Technology, Pedagogy and Education, 2024, 34(3): 1–17. https://doi.org/10.1080/1475939X.2024.2433259.

[17] Liu X, Cui Y. Eye tracking technology for examining cognitive processes in education: A systematic review. Computers & Education, 2025, 90: 105263. https://doi.org/10.1016/j.compedu.2025.105263.

[18] Mundokova N, Kubiatko M. Using eye-tracking in education—A review study. Education Sciences, 2025, 15(7): 853. https://doi.org/10.3390/educsci15070853.

[19] Paas F, Renkl A, Sweller J. Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 2003, 38(1): 1–4. https://doi.org/10.1207/S15326985EP3801_1.

[20] He J, Zhou Y, Zhang Q, et al. PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation. Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023: 12547-12556. https://doi.org/10.48550/arXiv.2204.00833.