Evaluating Complexity of Digital Learning in a Multilingual Context: A Cross-Linguistic Study on WHO's Emergency
Yu Zhao1, Giuseppe Samo2, Heini Utunen1
1World Health Organization.
Pandemic knowledge sharing is difficult due to reduced information access. Assessing linguistic complexity of online learning content can improve knowledge reproduction, especially for low-resourced languages.
Area of Science:
- Computational linguistics
- Educational technology
- Knowledge management
Background:
- Knowledge reproduction is challenging during pandemics, often hindered by information accessibility issues.
- Tacit knowledge transfer is particularly vulnerable to disruptions in communication and accessibility.
Purpose of the Study:
- To assess the linguistic complexity of online learning materials.
- To explore methods for improving knowledge reproduction during global health crises.
- To establish a baseline for evaluating linguistic accessibility in educational content.
Main Methods:
- Conducted cross-linguistic studies on the World Health Organization (WHO) emergency learning platform.
- Analyzed two online courses across 10 languages.
- Utilized morpho-syntactically annotated treebanks, Wikipedia corpora, and language-specific corpora as controls.
Main Results:
- Preliminary findings indicate reduced linguistic complexity in learning content across candidate languages.
- The simplification of content aimed to retain maximum information.
- Identified a potential for improving information accessibility in translated educational materials.
Conclusions:
- Assessing and managing linguistic complexity can enhance knowledge reproduction, particularly during pandemics.
- Developing baseline studies for low-resourced languages in the learning genre is crucial.
- This research supports the development of more accessible global educational resources.
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