Transformation of Meme-Based Learning Assessment: Multimodal Assessment of Generation Z Student Artifacts

Authors

DOI:

https://doi.org/10.20961/joive.v9i3.3691

Keywords:

multimodal assessment, meme, learning artifact, generation z, higher education

Abstract

Digital transformation has reshaped how Generation Z students communicate knowledge, prompting a re-examination of assessment practices in higher education. Assessment must evolve beyond traditional text-based tasks to accommodate multimodal literacies, yet empirical investigation of rubric-based dimensions in student-created multimodal artifacts remains underexplored. This study analyzes the quality of student meme artifacts as multimodal assessments and examines statistical relationships among assessment dimensions. A quantitative descriptive-correlational design was employed to analyze 155 student-generated meme artifacts. The analysis used a researcher-developed six-dimensional rubric to assess the data. Data were analyzed using descriptive statistics and Pearson correlation via IBM SPSS. Results indicate that overall meme quality falls predominantly in the Very High category across five of six dimensions, with Creativity and Originality as the sole dimension in the High category, with Ethics and Audience Appropriateness (M = 3.99) and Scientific Accuracy (M = 3.81) achieving the highest scores, while Creativity and Originality (M = 3.20) showed the greatest variation. Correlation analysis reveals significant positive relationships among most dimensions (p < 0.01). Multimodal Orchestration emerged as the central dimension, showing the strongest linkage with Creativity and Originality (r = 0.643) and Message Clarity (r = 0.420). These findings support the validity of meme-based assessment and highlight multimodal orchestration as a key factor in artifact quality.

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Published

2026-11-01

How to Cite

Rifana, F., & Hikmawan, R. (2026). Transformation of Meme-Based Learning Assessment: Multimodal Assessment of Generation Z Student Artifacts. Journal of Informatics and Vocational Education, 9(3), 34-45. https://doi.org/10.20961/joive.v9i3.3691