Measures of Children's Knowledge and Regulation of Cognition

Sperling, Rayne A.; Howard, Bruce C.; Miller, Lindsay; Murphy, Cheryl A.

doi:10.1006/ceps.2001.1091

Cited by 303 publications

(290 citation statements)

References 38 publications

(56 reference statements)

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“…In a review of 21 studies using self-report questionnaires, the mean variance explained by metacognition in learning performance did not exceed 3 % (r00.17) (Veenman and Van Hout-Wolters 2002). Additionally, some studies have shown the convergent validity between different questionnaires, theoretically measuring the same metacognitive processes, to be quite modest (Muis et al 2007;Sperling et al 2002). As some authors argue, off-line, generally formulated metacognitive questionnaires may be more adequate to assess metacognitive knowledge as opposed to metacognition applied during the learning process (Desoete 2007;Greene and Azevedo 2010).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Towards efficient measurement of metacognition in mathematical problem solving

Jacobse

Harskamp

2012

Metacognition Learning

112

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Metacognitive monitoring and regulation play an essential role in mathematical problem solving. Therefore, it is important for researchers and practitioners to assess students' metacognition. One proven valid, but time consuming, method to assess metacognition is by using think-aloud protocols. Although valuable, practical drawbacks of this method necessitate a search for more convenient measurement instruments. Less valid methods that are easy to use are self-report questionnaires on metacognitive activities. In an empirical study in grade five (n039), the accuracy of students' performance judgments and problem visualizations are combined into a new instrument for the assessment of metacognition in word problem solving. The instrument was administered to groups of students. The predictive validity of this instrument in problem solving is compared to a wellknown think-aloud measure and a self-report questionnaire. The results first indicate that the questionnaire has no relationship with word problem solving performance, nor the other two instruments. Further analyses show that the new instrument does overlap with the thinkaloud measure and both predict problem solving. But, both instruments also have their own unique contribution to predicting word problem solving. The results are discussed and recommendations are made to further complete the practical measurement instrument.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Towards efficient measurement of metacognition in mathematical problem solving

Jacobse

Harskamp

2012

Metacognition Learning

112

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“…Panaoura ir kiti (2003), analizuodami metakognityvaus sąmoningumo skirtumą pagal amžių tarp 4-6 klasių mokinių, nerado metakognityvaus sąmoningumo skirtumų. Temur, Kargin, Bayar ir Bayar (2010) analizavo 6-8 klasių mokinių metakognityvaus sąmonin-gumo skirtumus skaitant ir gavo rezultatą, priešingą Sperling (2002) rezultatams. Temur ir kitų (2010) teigimu, kuo aukš-tesnė klasė, tuo geresnis metakognityvus sąmoningumas.…”

Section: Raminta Seniūnaitėunclassified

“…Tyrėjų gauti prieštaringi metakognityvaus sąmoningumo raiškos pagal amžių rezultatai. Tyrimų rezultatai taip pat nevienodai vertina metakognityvaus sąmoningumo skirtumus pagal lytį, nors labiau pabrėžiama, kad nėra metakognityvaus sąmoningumo raiškos pagal lytį skirtumų (Sperling et al, 2002;Cisacai ir Haiduc, 2011).…”

Section: Raminta Seniūnaitėunclassified

“…Tyrimo rezultatai rodo, kad metakognityvių įgūdžių lavinimas turi teigiamą poveikį nuostatai dėl matematikos ir akademiniams pasiekimams. Yuksel (2013) tyrimo duomenimis, pažinimo reguliavimas ir žinios apie pažinimą leidžia prognozuoti nuostatas dėl matematikos ir akademinius pasiekimus (Yuksel, 2013) ir šie tyrimo rezultatai oponuoja kitų ty-rėjų (Sperling, et al, 2002;Countinho & Neuman, 2008;Kleitman & Gibson, 2011;Jagals & van der Walt, 2013;Nicolaidou et al, 2003;Juter, 2005;Hemmings et al, 2011) gautiems rezultatams, kad metakognityvus sąmoningumas tiesiogiai neturi įtakos akademiniams pasiekimams. Sahin, Kendir (2013), Kleitman ir Gibson (2011) įrodė, kad mokiniai, apmokyti naudotis metakognityviomis strategijomis, turėjo aukštesnę nuostatą dėl matematikos, tai nulėmė labiau teigiamos nuostatos dėl matematikos atsiradimą ir geresnius akademinius pasiekimus.…”

Section: Raminta Seniūnaitėunclassified

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10–16 Metų Mokinių Nuostatos Dėl Matematikos Ir Metakognityvaus Sąmoningumo Sąsaja

Seniūnaitė¹,

Pociūtė²

2015

ActPaed

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“…Instead of asking one to predict whether they will get an item correct, one can ask them if they got an item correct immediately after they take it, in a kind of reverse KMA (or one can be asked to do both, as in the Jr. MAI method of Sperling, Howard, Miller, & Murphy, 2002) This is also called a confidence judgment, and it has been used in cognitive psychology for many years, often as a score intensifier (examinees get more credit if they solve a problem and are confident that their solution was correct [e.g., Lohman, 1980]). Recently Stankov (1999Stankov ( , 2000 has used this technique to investigate confidence as an individual-differences construct, finding that it is a factor separate from ability per se, a claim often made of metacognition.…”

Section: Self-reportsmentioning

confidence: 99%

The Role of Noncognitive Constructs and Other Background Variables in Graduate Education

Kyllonen

Walters²,

Kaufman

2011

ETS Research Report Series

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This report reviews the literature on noncognitive and other background predictors (e.g., personality, attitudes, and interests) as it pertains to graduate education. The first section reviews measures typically used in studies of graduate school outcomes, such as attrition and time to degree. A review of qualities faculty members and administrators say they desire and cultivate in graduate programs is conducted. There appears to be a divergence between the qualities faculty members say are important and the measures researchers typically use in validity studies.The second section reviews three categories of noncognitive variables that might predict outcomes (general personality factors, quasi-cognitive factors, and attitudinal factors) and the definitions, measures, correlates, and the validity of those measures. The role of background factors, both environmental and group, is part of this review.Key words: noncognitive, personality, admissions, GRE ® , selection, assessment, new constructs ii Executive SummaryMany GRE ® studies conducted in the past several years have asked faculty members about the qualities that are important to success in graduate school. A consistent finding is that graduate faculty members believe that noncognitive factors, such as motivation, creativity, personality, interests, and attitude, ought to be considered in graduate admissions (e.g., Briel et al., 2000). Many faculty members believe that including such factors would increase both fairness and the validity of the current admissions process. At the same time there is a lack of knowledge about what the scientific literature says on what the noncognitive factors are, how important they are, how they could best be measured, and on whether it might be practical to use them in admissions decisions. The purpose of this review is to address these questions. This report reviews various noncognitive factors and definitions, measures, correlates, and the validity of those measures. Graduate School Outcomes and Their DeterminantsA notional path model illustrates the relationships between noncognitive predictor factors and graduate school outcome factors. Graduate school outcome factors are divided into traditional measures of convenience and performance factors. Traditional measures are attrition, time-to-degree, and grade point average. Performance factors are domain proficiency, general proficiency, communication, effort, discipline, teamwork, leadership, and management. The noncognitive predictor factors are divided into three main categories: personality (e.g., extroversion), quasi-cognitive (e.g., metacognition), and motivation factors (e.g., self-efficacy).In addition, there are two background categories assumed to affect the noncognitive factors:environmental (e.g., mentor support) and group factors (gender and ethnicity). The review is organized according to this model. Personality FactorsA consensus has emerged within the field that there are five major personality factors: extroversion, emotional stability, agreeableness, ...

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Measures of Children's Knowledge and Regulation of Cognition

Cited by 303 publications

References 38 publications

Towards efficient measurement of metacognition in mathematical problem solving

Towards efficient measurement of metacognition in mathematical problem solving

10–16 Metų Mokinių Nuostatos Dėl Matematikos Ir Metakognityvaus Sąmoningumo Sąsaja

The Role of Noncognitive Constructs and Other Background Variables in Graduate Education

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