April 2024
ISSN 2148-7278
Volume: 10 Issue: 1


GLOKALde April 2024, ISSN 2148-7278 Volume: 10  Issue: 1, Article 5

HOW TASK ANALYSIS FOSTERS EQUITY AND ACCESSIBILITY FOR MULTILINGUAL LEARNERS

Alex GUZMAN, EdD
ORCID: 0000-0001-9860-8732
Kean University, USA
[email protected]

ABSTRACT

Analyzing academic language demands through systematic task analysis is imperative for fostering equitable and accessible education, particularly for multilingual learners (MLs). In today's world, characterized by linguistic diversity, educational systems must adapt to meet the needs of students from varied linguistic backgrounds. This article underscores the pivotal role of task analysis in identifying and addressing academic language demands, thereby promoting equity and accessibility in education. Task analysis involves meticulously examining the language requirements embedded within diverse academic tasks. For MLs, these language demands pose significant challenges, hindering their comprehension, engagement, and academic success if left unaddressed. By conducting thorough task analyses, educators can pinpoint linguistic barriers and develop targeted interventions to bridge language gaps, fostering a more inclusive learning environment. Task analysis emerges as crucial, providing insights into the linguistic intricacies inherent in academic tasks across various subject areas. Furthermore, task analysis facilitates the design of culturally responsive and linguistically accessible instructional materials, ensuring that language acts as a scaffold rather than a hindrance to academic achievement. This paper presents a comprehensive task analysis process for identifying and dissecting content, cognitive, and academic language demands within academic tasks. By following this guide, educators can effectively tailor instructional strategies and materials to address the diverse linguistic needs of MLs, thereby promoting equitable and accessible educational practices. Through continuous reflection and iteration, educators can refine their approaches to meet the evolving needs of MLs, ultimately fostering an educational environment where language serves as a bridge to success for all.

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