Supporting English Learners

Like strategies for reading in the content area and Universal Design for Learning, supporting English Learners (ELLs) can benefit all students by using strategies to develop academic language.

Consider this statement: All teachers are language teachers. Do you agree or disagree?

Does your thinking shift when you consider that there are four domains that make up language: reading, listening, speaking and writing? Language is everywhere, in every content area and is an important part of student engagement in every class. The four language domains can be separated into two categories that sound very familiar to computer science educators - input (reading, listening) and output (speaking, writing). Our task as educators is to create input that is accessible and provide support and opportunities for meaningful output for all learners.

To get a sense for the English learner (EL) population in schools across the United States, let’s take a look at some demographic statistics:

  • English learners make up an average of 10% of K12 public school student populations, as of Fall of 2017 (NCES Data, 2020)

  • Spanish is the most widely spoken native language by ELs in the US, however many schools and districts serve students with a variety of home languages (NCES Data, 2020)

  • The average graduation rate for ELs was 60%, compared to 84% for non-ELs in 2015-16 (US Department of Education Data)

  • AP CSP Exam enrollment from 2017 and 2018 shows an increase in the total number of Hispanic/Latinx exam takers (College Board). We do not have information on the home language of the exam takers, so it is impossible to know if they are English learners. We do know that students from underrepresented groups passed all CS exams at an average rate of 49%, which is 27% lower than students from majority groups (Code.org). This data helps to demonstrate the urgent need for creating equitable and engaging computer science learning experiences for students from all linguistic and cultural backgrounds.

The Four Language Domains

The four language domains- input: listening & reading, output: speaking & writing

Image source: Andrea Wilson Vazquez

Language Development Overview:

Pause for a moment to consider all of the ways academic language is used in computer science. Also, consider that academic language support and development are necessary and helpful for English learners, as well as for any learner who may have less exposure to academic language. In fact, researcher Jeff Zwiers states that, “Academic language is often cited as one of the key factors affecting the “achievement gap” that exists between high- and low- performing students” (Zwiers, 2009).

  • An English learner first becomes proficient in BICS (Basic Interpersonal Communication Skills) - social language, simple sentence structure, high frequency vocabulary words and familiar content. ELs usually develop BICS in 1-3 years (J. Cummins, University of Toronto).

  • Proficiency in CALP (Cognitive Academic Language Proficiency) typically takes ELs 5+ years to master, and includes the language of lectures, formal, written text, specialized terminology, humor, non-verbal communication, idioms, social appropriateness and textbook language (J. Cummins, University of Toronto).

  • "Academic language is the set of words, grammar, and organizational strategies used to describe complex ideas, higher-order thinking processes, and abstract concepts." (Zwiers, 2009).

Brick & Mortar Terms

Academic language can be understood through a helpful analogy: brick and mortar terms (Zwiers, 2009).

  • Brick terms are content-specific words that would normally be bolded in textbooks.

  • Mortar terms are general academic words and phrases that hold content-specific words together.

Brick Terms:

  • Algorithm

  • Boolean

  • Byte

  • Compiler

  • Debugging

  • Encryption

  • Modulo

  • Pseudocode

  • RAM

  • User Interface

Mortar Terms:

  • Beta testing

  • First, next, then, last

  • If, then, else

  • Input, output

  • Initialize

  • Program

  • Variable

  • Parameters

  • Function

  • While true

Supporting English Learners in CS

Watch the video to learn more about some strategies for supporting the academic language development of English learners, and more broadly, of all learners in your computer science courses. (Slides)

Here’s a quick review of the EL support strategies presented in the video:

  • Comprehensible Language Input

  • Opportunities for Meaningful Student Language Output

  • Metacognitive Analysis of Language Use and Development

  • Culturally Relevant Pedagogy

Reflection Activities

Part 1: Activity

Choose one lesson from Mobile CSP, CSAwesome, or another CS curriculum. Write down the content objective for the lesson, then consider what language functions students can use to show that they have mastered the content. Write at least 2 language objectives to go along with the content objective. (Jump to the content and language objective example in the video. )

Part 2: Reflection

Take a look at one lesson from Mobile CSP (or other CS course). Recall the academic language support strategies shared in this module related to input, output, structured collaboration, meta-analysis and culturally relevant pedagogy.

  • Consider the four language domains: speaking, listening, reading and writing. Write down examples of ways that students in your CS course are asked to engage with content through each of the language domains.

  • What academic language supports can you identify in the CS lesson you selected?

  • Where would you recommend adding additional academic language supports in the lesson you selected?

  • Name 3 specific academic language supports you would recommend adding to your CS lesson.


Resources

Academic Language Development:

AP CSP Exam Taker Data:

Data on ELs in US Public Schools

  • NCES, "English language learners in public schools," 2020. https://nces.ed.gov/programs/coe/indicator_cgf.asp Accessed: 20 May, 2020.

  • US Department of Education, "Academic performance and outcomes for English learners," 2017. https://www2.ed.gov/datastory/el-outcomes/index.html. Accessed: 20 May, 2020.

EL Supports:

  • ColorinColorado: "Academic Language Functions" https://www.colorincolorado.org/sites/default/files/Academic-Language-Function.pdf

  • Jacob, S., Nguyen, H., Tofel-Grehl, C., Richardson, D., Warschauer, M. (2018). Teaching computational thinking to English learners. NYS TESOL Journal.5(2), 12-24.

  • Vogel, S., Hoadley, C., Ascenzi-Moreno, L., Menken, K. The role of translanguaging in computational literacies. https://research.steinhardt.nyu.edu/scmsAdmin/media/users/ch97/publications/The_Role_of_Translanguaging_in_Computational_Literacies.pdf. Accessed: 22 May, 2020.

  • WIDA, "The English language learner can do descriptor booklet, grades 9-12," 2012. https://wida.wisc.edu/sites/default/files/resource/CanDo-Booklet-Gr-9-12.pdf. Accessed: 21 May, 2020.

  • WIDA, "The English language development standards," 2017. https://wida.wisc.edu/sites/default/files/resource/2012-ELD-Standards.pdf. Accessed: 21 May, 2020.

  • Zwiers, J., Dieckmann, J,, Rutherford-Quach, S., Daro, V., Skarin, R., Weiss, S., Malamut, J. (2017). Principles for the design of mathematics curricula: Promoting language and content development. https://ell.stanford.edu/sites/default/files/u6232/ULSCALE_ToA_Principles_MLRs__Final_v2.0_030217.pdf. Accessed: 21 May 2020.


This content was created by Andrea Wilson Vazquez