Mote pairs Read Aloud, Text Prediction, and an in-context Dictionary with multilingual support to help English language learners access grade-level content, build academic vocabulary, and produce confident written and spoken English.
English language learners now make up 10.6 percent of US public school students - more than 5.3 million children, according to the National Center for Education Statistics. They are sitting in math, science, and social studies classes, learning grade-level content while still building the English they need to access it.
Mote gives teachers a practical multilingual companion that follows ELLs into any Google Doc, Slide, or web page they read. Read Aloud delivers comprehensible input. Text Prediction scaffolds writing in English. An in-context Dictionary makes academic vocabulary instantly available. Together these tools align with what reading and second-language research consistently identifies as the highest-impact ELL supports.
Mote's Read Aloud reads any selected text aloud in natural voices, with adjustable speed and dual-layer word highlighting that follows along in real time. For ELLs at WIDA Levels 1 to 3, hearing English while seeing it on the page builds the phonological-visual link that decoding alone cannot. Teachers use Read Aloud during shared reading, on assignments students take home, and as an accommodation for assessments where read-aloud is permitted.
This kind of multimodal input is what reading research calls comprehensible input - the foundation of second-language literacy development. ELLs gain access to grade-level texts they could not yet decode independently, which keeps them in the same content as classmates while their language continues to develop.
Writing in a second language carries enormous cognitive load. Every word means a decision: spelling, grammar, word choice, and sentence shape, all at once. Mote's Text Prediction suggests next words and full phrases as students type in Docs and Slides, drawing on grade-appropriate language and the topic of what they are writing.
For an ELL drafting a science explanation or a paragraph response, predictions remove the spelling roadblock and surface academic phrasing they have heard but cannot yet retrieve unprompted. Output volume goes up, frustration goes down, and teachers see the ideas underneath rather than the spelling tangles on top.
Vocabulary is the single strongest predictor of reading achievement for English language learners, according to research syntheses published by the Institute of Education Sciences. Mote's Dictionary lets students click any word in any text and get an instant student-friendly definition without leaving the page or losing their place in the reading.
That continuous access matters most with academic vocabulary - the abstract, content-area terms (analyze, evaluate, photosynthesis, denominator) that ELLs encounter daily but rarely meet in conversational English. Lookups turn from interruptions into low-friction supports, and reading momentum is preserved.
Looking up a word once is not the same as learning it. Mote lets ELLs save unfamiliar words to a personal vocabulary list as they read, then revisit them through retrieval practice and mastery tracking. Words move from passive recognition to active use through repeated retrieval - the same mechanism research links to long-term retention.
For teachers, this turns the messy reality of every ELL needing different vocabulary into something manageable. Each student builds the list that matters to their assignments, their grade level, and their current proficiency, and the practice happens in five-minute slices rather than long worksheets.
Many ELLs can express ideas orally before they can write them, but classroom routines often demand the reverse. Mote's Voice Typing lets students speak directly into Google Docs and see their words appear on the page in real time. The transcript becomes a starting point for editing, and the act of speaking gives students low-stakes practice with English pronunciation and oral fluency.
For teachers, voice typing closes the gap between what students know and what they can put on paper - a gap that can mask real understanding when written English is still developing. Students hear themselves and see their words simultaneously, which research links to gains in both speaking and writing fluency over time.
According to the National Center for Education Statistics, 5.3 million students - 10.6 percent of US public school enrollment - are classified as English learners. The number grew through the 2010s and continues to climb. In 13 states and Washington DC, ELLs make up at least 10 percent of students; in New Mexico, the figure reaches 18.8 percent. Most are in elementary grades: nearly 15 percent of US kindergarteners are ELLs.
Research synthesis points to four practices with the strongest evidence base: explicit vocabulary instruction, structured English-language interaction with peers, sheltered content instruction with built-in language scaffolds, and multimodal access to grade-level texts. The federal Office of English Language Acquisition makes the same case in its January 2025 evidence brief on instructional practices for English learners.
A 2024 meta-analysis in Language Teaching Research (Li, Tong, Irby et al.) examined the effects of scaffolding, graphic organizers, interactive read-aloud, and leveled questioning on ELL reading comprehension - and found measurable gains across all four. The Mote tools above were chosen because they map directly to these evidence-based practices: read-aloud for comprehensible input, predictive text for scaffolded output, and in-context dictionary lookup for vocabulary depth.
Last updated on
April 30, 2026
