To be prepared to teach reading, teachers must learn what makes a text complex: how text features contribute to text complexity. They must also learn how to locate and select appropriate texts for various pedagogies and know how to differentiate based on individual readers’ needs and interests.
Reading scores for the lowest-performing students have plummeted to historic lows. Misunderstandings of text complexity have contributed to this achievment gap.
Dr. Elfrieda (Freddy) Hiebert shares tips on using an AI assistant to select words from narrative text for more effective vocabulary instruction.
As we embrace AI’s strengths in educational content, we must also champion human storytelling that truly speaks to children’s hearts and minds.
Illustrations are not merely decorative elements in children’s literature. They are often powerful motivational tools that transform the reading experience.
TextProject CEO Dr. Elfrieda “Freddy” H. Hiebert, explores the opportunities to use AI to help strengthen vocabulary instruction and enhance students’ literacy skills.
Dr. Elfrieda Hiebert delivered a keynote address during the Reading Hall of Fame Mentoring session organized by the Literacy Research Association on December 5, 2024.
Unlike the strict vocabulary limits of the past, scaffolded texts use language research to create rich learning opportunities. At their core is the organization of words into morphological families – groups that share the same root. This structure comes from analyzing large collections of texts to identify the word families that occur most often at different grade levels.
Artificial intelligence (AI) offers educators a data-driven alternative to intuition-based word lists. By analyzing vast language datasets, AI tools can identify word clusters supporting text comprehension and general knowledge, as well as words with rich webs of related vocabulary.
By exploring vocabulary through the lens of story structure, we empower students to engage more deeply with texts and enrich their vocabularies.
