Analyzing L2 multimodal compositions: Qualitative data analysis and visualization

Dr. Natalie Amgott (CMU Modern Languages)

In today's digital age, language learning goes beyond proficiency in the “four skills” of reading, writing, listening, and speaking. Digital multimodal compositions, which integrate text, images, video, and sounds, have become essential in developing language learners' proficiency, digital literacy, and intercultural competence. This presentation sheds light on the variety of qualitative data analysis and visualization opportunities that help gain insights into the process and product of digital multimodal compositions. 

The presentation will begin with an overview of the field and examples of types of L2 multimodal compositions, as well as their significance in language learning and teaching contexts. Next, we will explore the variety of qualitative methodologies for collecting and analyzing learners’ multimodal compositions, highlighting the importance of capturing not only the final product, but also process data. We will discuss collecting and analyzing interview data, product data, and screen capture process data. We will also discuss using grounded theory (Corbin & Strauss, 2008) to conduct open, axial, and selective coding using tools like NVivo, Dedoose & MaxQDA. 

Lastly, we’ll unpack the integration of visualization techniques including multimodal transcription (Flewitt et al., 2014) and multimodal codemeshing timescapes (Smith et al 2017) to both analyze and visualize the data. Real-world examples will be incorporated to illustrate how these visualizations can uncover hidden patterns, aid in comparative analysis, and enhance the interpretation of qualitative data.

Ultimately, this presentation serves as a comprehensive guide for L2 educators and researchers interested in implementing and analyzing L2 multimodal compositions. By the end of the colloquium, attendees will be equipped with a deeper understanding of qualitative data analysis and visualization techniques, empowering them to explore this evolving field and contribute to the advancement of language learning and assessment practices.