Text Complexity Analyser & Scaffold Designer

Analyse text complexity across quantitative, qualitative, and reader-task dimensions with scaffolding recommendations. Use when selecting texts, assessing readability, or planning reading support.

What it does

Evaluates a text across three dimensions of complexity — quantitative (sentence length, vocabulary frequency), qualitative (structure, levels of meaning, knowledge demands), and reader-task (the interaction between the text's demands and the specific readers and purpose) — and generates a tailored set of before, during, and after reading scaffolds that address the specific complexity challenges identified. Unlike readability formulas alone (which only measure quantitative features), this analysis considers whether the text has implicit meaning that requires inference, whether it assumes background knowledge students may lack, whether its structure is familiar or unfamiliar, and whether the vocabulary demands are primarily Tier 2 (academic) or Tier 3 (technical). AI is specifically valuable here because text complexity is multi-dimensional — a text can be quantitatively simple but qualitatively complex (a poem with short sentences but deep figurative meaning), and scaffolds must target the ACTUAL complexity, not just the reading level number.

The evidence behind it

Shanahan et al. (2012) analysed text complexity progression and established that effective text selection and scaffolding requires a three-dimensional model: quantitative measures (word frequency, sentence length, text length), qualitative dimensions (levels of meaning, text structure, language conventionality, knowledge demands), and reader-task considerations (the specific readers' background knowledge, motivation, and the purpose of reading). Relying on quantitative measures alone (e.g., Flesch-Kincaid) produces misleading results — Hemingway's prose scores as "easy" on readability formulas despite being qualitatively complex. Hiebert (2012) identified specific actions teachers can take to address text complexity, emphasising that scaffolding should target the specific complexity dimension that presents the greatest challenge — vocabulary scaffolding for a text whose complexity lies in structure is mismatched support. Fisher & Frey (2012) developed a practical framework for increasing rigour in reading through appropriate scaffolding: not simplifying the text, but providing the supports students need to access complex text. Beck et al. (2013) demonstrated that vocabulary instruction is most effective when it focuses on Tier 2 words (high-utility academic words that appear across subjects) rather than Tier 3 words (technical vocabulary specific to one subject), and when words are taught in context with multiple exposures. Graves & Graves (2003) established the Scaffolded Reading Experience model: before-reading activities (activating prior knowledge, building background, pre-teaching vocabulary), during-reading activities (guiding questions, think-alouds, text annotations), and after-reading activities (discussion, writing, application).

Sources

• Shanahan et al. (2012) — An analysis of text complexity progression in CCSS
• Hiebert (2012) — Seven actions that teachers can take right now: text complexity
• Fisher & Frey (2012) — Text complexity: raising rigour in reading
• Beck et al. (2013) — Bringing Words to Life: robust vocabulary instruction
• Graves & Graves (2003) — Scaffolding Reading Experiences: designs for student success

How to use it in your lesson

For the best results with EvidenceLesson, give it:

• text_description — A description of the text including genre, topic, approximate length, and source
• student_level — Age/year group and current reading level
• reading_purpose — Why students are reading this text — the task it supports
• text_extract (optional) — A short extract from the text for more precise analysis
• student_profiles (optional) — From context engine: reading levels, EAL status, background knowledge
• subject_area (optional) — The curriculum subject context
• known_challenges (optional) — Specific challenges the teacher anticipates with this text

Known limitations

1. Without a text extract, the analysis is based on the text description and genre knowledge. The complexity profile will be more accurate when an actual text extract is provided. Teachers should review the analysis against the specific text and adjust scaffolds where the analysis doesn't match.

1. The analysis identifies complexity but cannot measure individual students' reading levels. The scaffold recommendations are designed for the stated student level, but individual students within the class will have different reading capabilities, background knowledge, and engagement levels. The teacher must differentiate within the scaffold plan based on their knowledge of specific students.

1. Text complexity is context-dependent. The same text can be simple for one reading purpose and complex for another — reading a poem for enjoyment requires different comprehension demands than analysing its figurative language. The analysis is specific to the stated reading purpose; changing the purpose would change the complexity profile and scaffold recommendations.

Pairs well with