REAP Study on the Correlation Between Automatically and Manually Generated Reading Comprehension Questions (Summer 2007)

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REAP Study on the Correlation Between Automatically and Manually Generated Reading Comprehension Questions (Summer 2007)

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Contents

  • <a href="# Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions">1 REAP Study on the Correlation Between Automatically and Manually Generated Reading Comprehension Questions </a>
    • <a href="#Logistical_Information">1.1 Logistical Information</a>
    • <a href="#Abstract">1.2 Abstract</a>
    • <a href="#Glossary">1.3 Glossary</a>
    • <a href="#Research_question">1.4 Research question</a>
    • <a href="#Dependent_variables">1.5 Dependent variables</a>
    • <a href="#Independent_variables">1.6 Independent variables</a>
    • <a href="#Hypotheses">1.7 Hypotheses</a>
    • <a href="#Explanation">1.8 Explanation</a>
    • <a href="#Descendents">1.9 Descendents</a>
    • <a href="#Notes">1.10 Notes</a>
    • <a href="#Annotated_bibliography">1.11 Annotated bibliography</a>
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[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions%28Summer_2007%29&action=edit&section=1" title="Edit section: REAP Study on the Correlation Between Automatically and Manually Generated Reading Comprehension Questions ">edit</a>]
<a name=" REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions "></a>

REAP Study on the Correlation Between Automatically and Manually Generated Reading Comprehension Questions

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=2" title="Edit section: Logistical Information">edit</a>]
<a name="Logistical_Information"></a>

Logistical Information

Contributors Christine M. Feeney and Michael Heilman
Study Start Date June, 2007
Study End Date July, 2007
Learnlab Courses none
Number of Students 30
Total Participant Hours (est.) 300
Data in Datashop no
[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=3" title="Edit section: Abstract">edit</a>]
<a name="Abstract"></a>

Abstract

Previous psychological research has identified two types of comprehension: shallow, in which people can reproduce information, and deep, in which people can comprehend the meaning of information. In addition, researchers have found that these two types of comprehension are separate and disparate. The PSLC currently employs an English as a Second Language vocabulary tutor, REAP, that uses shallow, automatically generated, comprehension questions to check that students are actively reading, rather than just skimming, practice reading passages. The purpose of the current study was to examine performance on the REAP-type questions with manually authored, deeper, reading comprehension questions. Participants were thirty undergraduate students (male = 11) participating in summer research programs at Carnegie Mellon University. The researcher predicted a positive correlation between the two testing types, which was supported by the data (r = .366, p < 0.0005, one-tailed t-test).

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=4" title="Edit section: Glossary">edit</a>]
<a name="Glossary"></a>

Glossary

Shallow Comprehension: Processing is directed towards reproducing the learning material without necessarily understanding it.

Deep Comprehension: Processing is directed towards comprehending the intended meaning of the learning material.

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%%28Summer_2007%29&action=edit&section=5" title="Edit section: Research question">edit</a>]
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Research question

Does performance on the shallow, automatically-generated questions correlate with performance on more sophisticated, deep reading comprehension questions?

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=6" title="Edit section: Dependent variables">edit</a>]
<a name="Dependent_variables"></a>

Dependent variables

Percentage of Shallow Comprehension Questions Answered Correctly.

Percentage of Deep Comprehension Questions Answered Correctly.

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=7" title="Edit section: Independent variables">edit</a>]
<a name="Independent_variables"></a>

Independent variable

Five reading passages, each of which was followed by four shallow reading comprehension questions and three to five deep reading comprehension questions.

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=8" title="Edit section: Hypotheses">edit</a>]
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Hypotheses

A significant positive correlation between shallow and deep reading comprehension questions will occur in this study.

[<a href="/research/wiki/index.php?title= REAP_Study_on_the_Correlation_Between_Automatically_and_Manually_Generated_Reading_Comprehension_Questions_%28Summer_2007%29&action=edit&section=9" title="Edit section: Explanation">edit</a>]
<a name="Explanation"></a>

Explanation

The study found no significant differences between the two conditions (2 or 4 words/text). This null result may be due to statistical power and mistakes in the study design. The tutor had difficulty providing high quality readings with four vocabulary words. Thus, the tutor often had to give texts with 3 or even 2 words to students in the 4-word condition. Additionally, the optimal number of words per text (the density of practice) may be higher than 4 words. There may be a threshold at which the density of practice becomes too high. This threshold may actually be at 5 or even 10 words given the average length of the texts used by the REAP tutor. Some research suggests that up to 5% of the words in a text can be unknown before comprehension is impeded (Laufer, 1992). Although the task for that study was different (reading comprehension rather than vocabulary acquisition), it suggests that the optimal level of stretch may be such that as many as 20 words may be unknown in a text with 400 word types (which is approximately the mean number of word types in REAP texts). Other research, however, suggests higher thresholds up to 98% (Nation, 2001).

Although the results for stretch from this study were inconclusive, a great deal of interesting data were gathered. Some interesting results have been found, and further analysis is possible.

Many potential variables exist that could lead to successful learning of new vocabulary: general ESL ability as measured by the MTELP, time on task, number of words looked up, pre-test scores on the academic word list. A step-wise linear regression showed that the most significant predictor of acquisition of new vocabulary was the size of the student's vocabulary scores on the academic word list prior to instruction (r= 0.77, p < .0001). However, the effect of this prior knowledge was diminished by the number of texts the students read r= -0.17). Together, in the stepwise regression, these two variable accounted for 67% of the variance (r2= .67).

This finding corroborates findings of Stanovich (1986) and James (1996) who refer to the phenomenon as the "Matthew effect" (after a Bible passage), whereby the rich get richer and the poor get poorer. In this case, it is not 'general richness' expressed in terms of higher general ESL proficiency, but specifically knowledge of words on the academic word list. In other words, the more knowledge components in the domain of acquisition a learner brings to the task, the greater the potential for future learning.

It was also found that students frequently access dictionary definitions for non-target words that are well below their expected reading level (e.g., "hitting"). This may lead to revisions of curricula for ESL vocabulary learning.

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Descendents

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Notes

Target vocabulary lists were determined by a lengthy pre-test using multiple choice cloze questions. Each question takes 30-60 seconds on average, depending on the student. In later studies, self-assessment pre-tests were preferred due to time constraints and initial impressions of the students. Lengthy pre-tests for determining target word lists leave a poor initial impression of the tutor.

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Annotated bibliography

Laufer, B. (1992). How much lexis is necessary for reading comprehension? In Vocabulary and Applied Linguistics, Pierre J. L. Arnaud and Henri Béjoint (eds.), 126–132. London: Macmillan.

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