- Difficulty of texts, as well as semantic and syntactic characteristics all determine how much inference is made (evident in Deane et al.’s study on differences in text characteristics in relation to readability and Rayner et al.’s study on eye movements)
- Text variability very important in determining how much inference can be made
- Should combine study of text characteristics and discourse analysis to better understand reading comprehension while accounting for the nature of text

Measuring reading comprehension - issues with measuring and assessing reading comprehension: nature of the text

- Importance of examining different formats of reading comprehension assessment
- Standardized tests, experimental procedures (i.e. studying regressive eye movements), discourse-level procedures (i.e. latent semantic analysis in analyzing think-alouds)
- Positive correlations found between different measurements on different reading comprehension elements
- Need to address method bias, measurement error, and other factors affecting the interpretation of such correlations 

Measuring reading comprehension - issues with measuring and assessing reading comprehension: response formats

- All papers discussed suggested diagnostic tests in first understanding the levels at which individuals are able to comprehend passages
- Diagnostic tests can improve classroom instruction on reading comprehension
- Need to continue examining different procedures on reading comprehension with larger sample sizes 
- Could also perform observational studies where teachers consistently follow up on students’ reading comprehension abilities and experiences
- Need to consider multimethod dimensions of reading comprehension using several latent variables and methods of analysis

Measuring reading comprehension - issues with measuring and assessing reading comprehension: individual differences

- Nature of the text
- Response formats
- Individual differences 

University of Michigan - Ann Arbor

Measuring reading comprehension is historically a complex process where researchers used many different mechanisms to assess outcomes. More recently, measurements have been one-dimensional and just focus on specific response formats such as multiple-choice or fill in the blank. The challenge with assessing reading comprehension is making inferences about how well the reader understands the text because researchers are not directly observing the process of the reader retaining information; they can only measure the outcomes of reading comprehension and the processes through which readers were able to reach a certain level of understanding.

Measuring reading comprehension

Fletcher, J. M. (2006). Measuring reading comprehension. Scientific studies of reading, 10(3), 323-330. https://www.tandfonline.com/doi/abs/10.1207/s1532799xssr1003_7

- Millis, K., Magliano, J., & Todaro, S. (2006). Measuring discourse-level processes with verbal protocols and latent semantic analysis. Scientific Studies of Reading, 10(3), 225-240. 
- Deane, P., Sheehan, K. M., Sabatini, J., Futagi, Y., & Kostin, I. (2006). Differences in text structure and its implications for assessment of struggling readers. Scientific Studies of Reading, 10(3), 257-275. 
- Rayner, K., Chace, K. H., Slattery, T. J., & Ashby, J. (2006). Eye movements as reflections of comprehension processes in reading. Scientific studies of reading, 10(3), 241-255. 
- Cutting, L. E., & Scarborough, H. S. (2006). Prediction of reading comprehension: Relative contributions of word recognition, language proficiency, and other cognitive skills can depend on how comprehension is measured. Scientific studies of reading, 10(3), 277-299. 
- Francis, D. J., Snow, C. E., August, D., Carlson, C. D., Miller, J., & Iglesias, A. (2006). Measures of reading comprehension: A latent variable analysis of the diagnostic assessment of reading comprehension. Scientific Studies of Reading, 10(3), 301-322. 

Measuring reading comprehension - studies discussed

- Measuring reading comprehension involves several factors that yield more precise results than latent variables currently used to minimize mono-operation bias 
- Need to address construct underrepresentation, meaning that one variable is not at all sufficient in dealing with how complex the issue is
- Further research needs to incorporate different methods to study different formats on reading comprehension and cognitive skills 

Measuring reading comprehension - conclusion

This paper explores how well variables, which contribute to reading comprehension passage and item difficulty, predict the complexity of text structure and multiple-choice items on the GRE reading test. It also seeks to disprove claims made in previous literature that question the adequacy of reading comprehension assessment through multiple-choice format. 

"The prediction of GRE reading comprehension item difficulty for expository prose passages for each of three item types: Main ideas, inferences and explicit statements"

The IMREC model shows how reading comprehension involves multiple different aspects; it also aids in determining differences in reading comprehension across individuals. Significant parts of different models related to reading comprehension are put together to form a single model, while taking into accounts the difficulties in integrating these theories into assessments.

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