NOTE: These results are PRELIMINARY. Please DO NOT CITE or DISTRIBUTE without author’s permission.
A series of graphs in the tabs below shows overall-text complexity as well as word-level factors that contribute to text complexity for levels A to P texts in two popular guided-reading programs: A to Z and LLI.
Each dot in a graph represents a text, which is color-coded either yellow (indicating assessment/benchmark texts) or blue (indicating instructional texts). Passage title, its guided-reading level, text-characteristic score, and genre pop up if a cursor is hovered over a dot.
Lines indicate trajectories of level-specific average scores (either means or medians) across A to P levels. These lines are expected to increase as the guided reading levels go up because higher levels of texts are expected to be more complex and to include more words with challenging characteristics (e.g., longer, more abstract, learned at later years, and rarer). Also expected is little discrepancy between the lines within and across the two programs because passages placed at a same level, on average, should have similar characteristics across the two passage-types (assessment vs. instructional) as well as across the two programs.
Failing these would have serious consequences as it would indicate a guided-reading level does not have a consistent meaning across the text-types or the programs.
Graphs below show overall text complexity scores from the Early-Reader Lexile Analyzer.
Findings
Graphs below show the distributions of decoding demand scores (in percentiles) from the Early-Reader Lexile Analyzer. The first graph shows level-specific mean lines while the second graph shows median lines. Both graphs show similar patterns.
Findings
Graphs below show the distributions of scores for the cout of syllables in words across reading levels A through P. Raw scores in the first graph vary from 0 (few words with many syllables) to 8 (more words with more syllables), while scores in the second graph are percentiles.
Findings
A graph below shows the distributions of age of acquisition scores across A-P reading levels. Possible raw scores range from 1 to 25, with lower score indicating more words in the text are known by younger readers.
Findings
Graphs below show distributions of word abstractness scores across A-P reading levels. Possible raw scores range from 1 to 25 (see the first graph), with lower score indicating more words in the text are known by younger readers.
Findings
A graoh below shows the distributions of word rareness scores across A-P reading levels. Possible scores range from 0 (less rare, easier) to 6 (more rare, more difficult). It is derived as an inverse of word frequency from MetaMetrics’ 1.39 billion-words corpus with 93,000 K-16 texts, normalized to link to the frequencies in Carroll, Davies, and Richman’s frequency 5 million word list.
Key findings
| dataset | level | title |
|---|---|---|
| A-Z | A | 14 |
| A-Z | B | 14 |
| A-Z | C | 14 |
| A-Z | D | 14 |
| A-Z | E | 14 |
| A-Z | F | 14 |
| A-Z | G | 14 |
| A-Z | H | 14 |
| A-Z | I | 14 |
| A-Z | J | 14 |
| A-Z | K | 16 |
| A-Z | L | 16 |
| A-Z | M | 16 |
| A-Z | N | 16 |
| A-Z | O | 16 |
| A-Z | P | 16 |
| LLI | A | 14 |
| LLI | B | 14 |
| LLI | C | 14 |
| LLI | D | 14 |
| LLI | E | 14 |
| LLI | F | 14 |
| LLI | G | 14 |
| LLI | H | 14 |
| LLI | I | 14 |
| LLI | J | 14 |
| LLI | K | 14 |
| LLI | L | 16 |
| LLI | M | 16 |
| LLI | N | 16 |
| LLI | O | 14 |
| LLI | P | 14 |