Expressing Metaphorically, Writing Creatively: Metaphor Identification for Creativity Assessment in Writing

Abstract

Metaphor, which can implicitly express profound meanings and emotions, is a unique writing technique frequently used in human language. In writing, meaningful metaphorical expressions can enhance the literariness and creativity of texts. Therefore, the usage of metaphor is a significant impact factor when assessing the creativity and literariness of writing. However, little to no automatic writing assessment system considers metaphorical expressions when giving the score of creativity. For improving the accuracy of automatic writing assessment, this paper proposes a novel creativity assessment model that imports a token-level metaphor identification method to extract metaphors as the indicators for creativity scoring. The experimental results show that our model can accurately assess the creativity of different texts with precise metaphor identification. To the best of our knowledge, we are the first to apply automatic metaphor identification to assess writing creativity. Moreover, identifying features (e.g., metaphors) that influence writing creativity using computational approaches can offer fair and reliable assessment methods for educational settings.

Exploring the Role of Artificial Intelligence in Facilitating Assessment of Writing Performance in Second Language Learning

“…One major concern is the ability of AI systems to accurately assess complex or subjective aspects of writing, such as creativity, originality, or nuanced arguments. Zhang et al (2022) proposed a novel creativity assessment model based on the pre-training of deep bidirectional transformers (BERT) that imports a token-level metaphor identification method to extract metaphors as the indicators for creativity scoring. The experimental results showed that the model can accurately assess the creativity of different texts with precise metaphor identification.…”