Strategy Use on Multiple‐choice and Free‐response Items: An Analysis of Sex Differences Among High Scoring Examinees on the Sat‐m

Gallagher, Ann; Mandinach, Ellen B.

doi:10.1002/j.2333-8504.1992.tb01485.x

Cited by 6 publications

(9 citation statements)

References 17 publications

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“…Bridgeman (1992) hypothesized that examinees might solve some MC items by working backward from response options. In one of the few studies directly investigating solution strategy, Gallagher (1992) observed several means by which examinees use the response options in MC SAT-M items. For example, an examinee might reason correctly that an answer must be in a certain range and then choose the one option that falls within that range.…”

Section: Item Format and Strategy Usementioning

confidence: 99%

Effects of Response Format on Difficulty of SAT‐Mathematics Items: It's Not the Strategy

Katz

Bennett

Berger

2000

J Educational Measurement

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Problem‐solving strategy is frequently cited as mediating the effects of response format (multiple‐choice, constructed response) on item difficulty, yet there are few direct investigations of examinee solution procedures. Fifty‐five high school students solved parallel constructed response and multiple‐choice items that differed only in the presence of response options. Student performance was videotaped to assess solution strategies. Strategies were categorized as “traditional”–those associated with constructed response problem solving (e.g., writing and solving algebraic equations)–or “nontraditional”–those associated with multiple‐choice problem solving (e.g., estimating a potential solution). Surprisingly, participants sometimes adopted nontraditional strategies to solve constructed response items. Furthermore, differences in difficulty between response formats did not correspond to differences in strategy choice: some items showed a format effect on strategy but no effect on difficulty; other items showed the reverse. We interpret these results in light of the relative comprehension challenges posed by the two groups of items.

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Section: Item Format and Strategy Usementioning

confidence: 99%

Effects of Response Format on Difficulty of SAT‐Mathematics Items: It's Not the Strategy

Katz

Bennett

Berger

2000

J Educational Measurement

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“…Although there have been some intensive efforts to study the cognitive aspects of question types (e.g., Gallagher, 1992;Messick, 1993;Traub, 1993), a great deal of research could still be done to further explore the aspects of quantitative reasoning that are associated with different question types in current operational testing programs. given options (such options can also be used to check one's answers [Gallagher, 1992]).…”

Section: Question Typesmentioning

confidence: 99%

“…given options (such options can also be used to check one's answers [Gallagher, 1992]). In this way, the SPRs extend the range of the aspects of the quantitative reasoning construct that are measured.…”

Section: Question Typesmentioning

confidence: 99%

What Is Quantitative Reasoning? Defining the Construct for Assessment Purposes

Dwyer

Gallagher

Levin

et al. 2003

ETS Research Report Series

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In order to create fair and valid assessments, it is necessary to be clear about what is to be measured and how the resulting data should be interpreted. For a number of historical and practical reasons described in this paper, adequately detailed statements with both a theoretical and empirical base do not currently exist for the construct of quantitative reasoning for use in assessments. There is also no adequate explanation of the important differences between assessments that measure quantitative reasoning constructs and those that are intended to measure achievement in related mathematical content areas.The literature in psychology, psychometrics, philosophy, and education, while containing much that is relevant to the construct of quantitative reasoning, unfortunately does not provide materials that can be used in research and development to address such practical issues or to explain the basic nature of quantitative reasoning assessments. This paper briefly discusses the importance and use of constructs and the quantitative reasoning and standards literature. It then presents a statement about the construct of quantitative reasoning for assessment purposes within a construct validity framework that includes both a definition of the construct and threats to valid score interpretation. These threats are based on related but distinguishable constructs and other types of construct-irrelevant variance in the assessments.

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“…Gallagher (1991) investigated sex differences on cognitive tasks for SAT Mathematics and found that female students tend to use algorithmic strategies as test-taking skills while male students tend to use a systematic trial-and-error approach regulated by some unknown reasoning. These task variables are useful for guiding an analysis of the underlying cognitive processes.…”

Section: Introductionmentioning

confidence: 99%

Proficiency Scaling Based on Conditional Probability Functions for Attributes

Tatsuoka

Birenbaum

Lewis

et al. 1993

ETS Research Report Series

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This study introduces procedures for constructing a proficiency scale for a large‐scale test by applying Tatsuoka's Rule Space Model. The SAT Mathematics (SAT M), Section 2, is used for illustrating the process and the results. A task analysis is summarized in a mapping sentence, and then 14 processes and content attributes are identified for explaining the underlying cognitive aspects of the examinees' performance on the SAT M. Analysis results show that almost 98% of 2334 examinees are successfully classified into one of 468 cognitive states. The cognitive states are characterized by mastery or non‐mastery of the 14 attributes. Attribute Characteristic Curves, which are conditional probability functions defined on the SAT Scale, are introduced and used for interpreting an examinees' proficiency. Prototypes of a student's performance report and a group performance report are given as examples of possible ways for summarizing the analysis results.

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Strategy Use on Multiple‐choice and Free‐response Items: An Analysis of Sex Differences Among High Scoring Examinees on the Sat‐m

Cited by 6 publications

References 17 publications

Effects of Response Format on Difficulty of SAT‐Mathematics Items: It's Not the Strategy

Effects of Response Format on Difficulty of SAT‐Mathematics Items: It's Not the Strategy

What Is Quantitative Reasoning? Defining the Construct for Assessment Purposes

Proficiency Scaling Based on Conditional Probability Functions for Attributes

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