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Computer-enabled visual creativity: an empirically-based model with implications for learning and instruction

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Abstract

This study focuses on visual creativity and how it can be supported with computer technologies and thereby be used to support learning and instruction. However, studies related to computer-enabled visual creativity have not been frequently explored. As such, the current research proposes a model consisting of four major factors: (a) computer-aided visual art self-efficacy, (b) computer self-efficacy, (c) general creative self-efficacy, and (d) visual creativity. The aim is to explore the causal relationships among these factors so that they can then be used to support creativity, especially in the context of learning and instruction. To test the proposed model, this study firstly collected a total of 736 responses from an American public university to construct a scale using exploratory factor analyses and confirmatory factor analyses for three factors: (a) computer self-efficacy, (b) computer-aided visual art self-efficacy, and (c) general creative self-efficacy. Later, 164 responses were collected to analyze those hypothesized predictors of visual creativity and their relationships using structural equation modeling with Mplus. The results of the study indicate that computer self-efficacy was a significant predictor of computer-aided visual art self-efficacy, which in turn was a significant predictor of general creative self-efficacy. General creative self-efficacy, in turn, was a significant predictor of visual creativity. Finally, the study yielded a significant indirect effect of computer-aided visual art self-efficacy on visual creativity as mediated by general creative self-efficacy. Implications for learning and instruction are discussed as well as future studies to further research to develop relevant models of visual creativity in support of learning.

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Funding

This work is supported by the Peak Discipline Construction Project of Education at East China Normal University.

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Correspondence to A. Y. M. Atiquil Islam.

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The authors state they have no conflicts of interest, financial or otherwise, with regard to this research study.

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Appendix: visual creativity tests

Appendix: visual creativity tests

Instructions for line meaning test

Welcome! On the next page, you are going to play a line game. You will see some lines and figures and after you have looked at each one, please tell us all of the things that the drawing makes you think of.

Here is an example:

figure a

For this figure, you could answer, “Mountain; Crack in a glass table; A squished piece of paper; Stock market trend lines; Kid’s doodling; Electricity; Soundwave; Analysis chart.” There are many more things you can think of, and all of them are legitimate.

If you are ready, please turn to the next page. Let’s begin now.

Line meaning test

List all the things that the drawing could be. You can look at it from any direction (or angle) you want.

figure b

Drawing test 1

Below are the elements you’ve seen in the previous task. Now, how about combining these figures together to make a story? Try to draw an interesting story based on the figures below. And add a title to your story.

figure c

Drawing test 2

Please add details to the squares below to make recognizable objects. Try to make these figures as interesting and unusual as possible. Add names or titles if you think the meaning of the object is not clear.

figure d

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Jiajun, G., Islam, A.Y.M.A., Teo, T. et al. Computer-enabled visual creativity: an empirically-based model with implications for learning and instruction. Instr Sci 47, 609–625 (2019). https://doi.org/10.1007/s11251-019-09487-0

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  • DOI: https://doi.org/10.1007/s11251-019-09487-0

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