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STEM and ELT: Performance Tasks for MLLs

by Darlyne de Haan |

Performance tasks can be more informative for teachers, students, and parents of all students—particularly multilingual learners (MLLs) of English—than standardized achievement tests, which are used for assessment and accountability purposes. This is because performance tasks can offer multiple opportunities for MLLs to present a more comprehensive picture of what they know and are able to do.

The research says that students must be afforded the opportunity to actively participate in meaningful interactions with other students and teachers in order to learn the new language. By doing this, MLLs learn new patterns of language and expression and have opportunities to develop vocabulary in context. Performance tasks allow these interactions to occur seamlessly if students are allowed to work collaboratively and are provided with multiple modalities to express their solution(s). 

These tasks will provide you with information on how your MLLs think, which skills they are lacking, and which of their skills are strong, all without the students having to say one word. A performance task is just that: an opportunity for your MLLs to perform the work as opposed to relying entirely on language to express their knowledge. This information is more informative than any standardized test: You will be able to see the thinking—not just the answer. Here’s how performance tasks can work:

Performance Tasks: How They Work

Select a performance task in which students are asked to actively communicate in a second language or design and conduct research on a topic of interest. In this situation, the MLLs’ speaking and writing abilities could be directly evaluated on the basis of the actual presentations and texts that they create.

Use a gradual release of responsibility model when first implementing performance tasks in the class. This is not the gradual release of responsibility that is commonly used in the “I do, We do, You do” approach, but instead one that is based on percentage of responsibility. For example:

First Task: The first time you have the class conduct a performance task, you model how to work through the entire performance task (100%) while asking questions of the class.

Second Task: When you have the class complete another performance task, model 75% and students work collaboratively for the remaining 25%.

Third Task: This time, model 50% and have students work collaboratively for the remaining 50%.

Fourth Task: Model 25% and have students work collaboratively for the remaining 75%.

After this series of performance tasks, the students should be able to complete an entire performance task with minimal modeling. And if you implement Two Pairs in a Quad student seating, the outcome for promoting student dialogue should be even more profound.

The Benefits of Performance Tasks vs. Standardized Tests

As we know, language proficiency develops by allowing MLLs opportunities to read, write, speak, and listen in the new language. Abedi, from the Stanford Center for Opportunity Policy in Education, explains that performance task assessments enable you to assess student competency in reading, language arts, science, and mathematics. But what about standardized tests? How do they differ from performance tasks when their purpose is also to assess student knowledge? Let us compare them:

  • Standardized assessments can contain linguistic complexity that impacts an MLL’s ability to make sense of what is being asked of them. According to an article from Colorín Colorado, students need to know 90% of vocabulary words for minimal comprehension, and 95% of vocabulary words for adequate comprehension. By using performance tasks that allow students to work hands-on with objects, you allow MLLs the opportunity to manipulate the objects, aiding them in creating their written/oral responses while also exposing where students may be having difficulties in understanding.
  • Because performance tasks are open ended, there are multiple ways to solve the problem and find solutions. This offers an MLL more freedom in expressing their answers than multiple-choice questions, which often require only one method of solving the problem.
  • Performance tasks provide multimodal interactions, including nonlinguistic (graphs, tables, equations) and linguistic (talk and written text) interactions.  Recognizing the importance of multiple modalities is important in STEM and MLL education because it reorients the focus from what MLLs lack in terms of language to the diverse meaning-making resources they bring to the classroom.
  • Lastly, performance tasks allow MLLs to construct their own understanding of concepts, because although their language ability may be considered “unsophisticated” (depending on their level of language proficiency), they are still able to make claims, generalize, imagine, hypothesize, and make predictions.  This allows them to be able to participate and contribute to the lesson, making them a functioning member in the classroom.

I strongly recommend looking into using performance tasks when trying to determine the academic and cognitive abilities of your MLLs or even if you just want to make sure that the MLL in your class can participate in assignments without the barriers caused by language. But do understand that you will still need to review the performance task to look for difficult language or cultural references that might confuse or impede your MLLs.


Have your tried using performance tasks in your classroom? What were your challenges?  What were your successes? How did you alter the performance tasks for your MLLs? Please share in the comments, below; I’d love to hear from you.

About the author

Darlyne de Haan

Dr. Darlyne de Haan, a former forensic scientist and chemist with more than 20 years of experience in STEM, is a recipient and participant of the coveted Fulbright Administrator Program for Fulbright Leaders for Global Schools, a program sponsored by the U.S. Department of State's Bureau of Educational and Cultural Affairs. She is a strong advocate for changing the face of STEM to reflect the population and is fluent in English and advanced in Spanish.

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