Grit: Perseverance and passion for long-term goals.

Duckworth, Angela; Peterson, Christopher; Matthews, Michael D.; Kelly, Dennis R.

doi:10.1037/0022-3514.92.6.1087

Cited by 4,733 publications

(6,378 citation statements)

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“…First, we assessed participants' passion and perseverance for long-term goals using the 12-item Grit scale (Duckworth et al 2007). Items such as BI finish whatever I begin^were rated on a 5-point scale (1 = not like me at all, 5 = very much like me).…”

Section: Real-world Cognitionmentioning

confidence: 99%

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

2017

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Cognitive training interventions have become increasingly popular as a potential means to cost-efficiently stabilize or enhance cognitive functioning across the lifespan. Large training improvements have been consistently reported on the group level, with, however, large differences on the individual level. Identifying the factors contributing to these individual differences could allow for developing individually tailored interventions to boost training gains. In this study, we therefore examined a range of individual differences variables that had been discussed in the literature to potentially predict training performance. To estimate and predict individual differences in the training trajectories, we applied Latent Growth Curve models to existing data from three working memory training interventions with younger and older adults. However, we found that individual differences in demographic variables, real-world cognition, motivation, cognitionrelated beliefs, personality, leisure activities, and computer literacy and training experience were largely unrelated to change in training performance. Solely baseline cognitive performance was substantially related to change in training performance and particularly so in young adults, with individuals with higher baseline performance showing the largest gains. Thus, our results conform to magnification accounts of cognitive change.Keywords Working memory training . Individual differences . Latent growth curve modeling Over the past decade, there has been an exploding interest in computer-based commercial Bbrain training^programs and in scientific evidence relating to the effectiveness of such interventions, triggered by promising results of working memory (WM) training gains generalizing to previously untrained cognitive abilities such as intelligence in both younger (e.g., Jaeggi et al. 2008) and older adults (e.g., Borella et al. 2010). Although the idea of improving general cognitive functioning within a few weeks is enticing, there is also accumulating evidence against a generalized effect of WM training (e.g., Clark et al. 2017;De Simoni and von Bastian 2017;Guye and von Bastian 2017;Sprenger et al. 2013). Even on the meta-analytic level, evidence is mixed regarding the effectiveness of cognitive training in both younger and older adults (e.g., Au et al. 2015;Dougherty et al. 2016;Karbach and Verhaeghen 2014;Kelly et al. 2014;Lampit et al. 2014;Melby-Lervåg and Hulme 2013;Melby-Lervåg et al. 2016;Schwaighofer et al. 2015;Soveri et al. 2017). Aside from design and methodological choices potentially explaining the diverging findings (e.g., Noack et al. 2009;Shipstead et al. 2012), many authors increasingly articulated the potentially important influence of individual differences on cognitive training trajectories and outcomes (e.g., Buitenweg et al. 2012;Guye et al. 2016;Könen and Karbach 2015;Shah et al. 2012;von Bastian and Oberauer 2014 Individual differences in cognitive functioning (e.g., Ackerman and Lohman 2006) and learning potential (e.g., Stern ...

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Section: Real-world Cognitionmentioning

confidence: 99%

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

2017

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“…This idea is based on a broader literature demonstrating negative effects of extrinsic rewards (e.g., money) on intrinsic motivation (Deci, Koestner, & Ryan, 1999). Moreover, remuneration could also bias the recruitment process by preferentially attracting participants more invested in money than in selfimprovement, a quality that may preclude the type of "grit" (Duckworth, Peterson, Matthews, & Kelly, 2007) needed for successful training . We therefore hypothesized an inverse correlation between amount of payment and Gf improvement.…”

Section: Introductionmentioning

confidence: 99%

Improving Fluid Intelligence With Training on Working Memory: A Meta-Analysis

Au¹,

Sheehan²,

Tsai³

et al. 2014

PsycEXTRA Dataset

146

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Working memory (WM), the ability to store and manipulate information for short periods of time, is an important predictor of scholastic aptitude and a critical bottleneck underlying higher-order cognitive processes, including controlled attention and reasoning. Recent interventions targeting WM have suggested plasticity of the WM system by demonstrating improvements in both trained and untrained WM tasks. However, evidence on transfer of improved WM into more general cognitive domains such as fluid intelligence (Gf) has been more equivocal. Therefore, we conducted a metaanalysis focusing on one specific training program, n-back. We searched PubMed and Google Scholar for all n-back training studies with Gf outcome measures, a control group, and healthy participants between 18 and 50 years of age. In total, we included 20 studies in our analyses that met our criteria and found a small but significant positive effect of nback training on improving Gf. Several factors that moderate this transfer are identified and discussed. We conclude that short-term cognitive training on the order of weeks can result in beneficial effects in important cognitive functions as measured by laboratory tests.

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“…1 The 10-item Personality Inventory (Gosling, Rentfrow, & Swann, 2003) and the Grit Scale (Duckworth, Peterson, Matthews, & Kelly, 2007) were also used in Study 1, but were not relevant to the predictions described in this report.…”

Section: Footnotesmentioning

confidence: 99%

Judging Knowledge in the Digital Age: The Role of External‐Memory Organization

Hamilton

McIntyre

Hertel

2016

Applied Cognitive Psychology

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Two studies examined relations between features of external-memory repositories (personal computers) and confidence in knowing. Participants judged their confidence in knowledge related to their work or studies and then answered questions about the way they store and use information. Participants who maintained more organized repositories were more confident in their knowledge. Furthermore, moderation analyses showed that the participants who navigated through their files by manually clicking through folders to find documents, but not those who use an automated search feature, felt more knowledge confident if they maintained a well-organized electronic repository. These results provide evidence for relation between assessments of internally "stored" knowledge and the degree of organization of their externally stored "knowledge." When technology transforms the scope of human faculty, the distinction between features belonging to oneself and the external environment begs reconsideration. In fact, throughout history, new technologies have extended the scope of basic human faculties in ways that are pervasive-the wheel, for example, extends the scope of our feet, and clothes extend the scope of our skin. The extension of mind by technology-from stone tablets to computers-has occurred so gradually and pervasively that accurate distinctions between internally and externally held knowledge are difficult to make and sometimes seem irrelevant (Hertel, 1993;Ward, 2013).The present investigation examined the relation between confidence in knowing and features of external repositories, in this case personal computers and their memory extensions.Our primary hypothesis was that the degree to which individuals maintain organized external repositories can predict their confidence in knowledge related to their main intellectual enterprise. In essence, we propose that external memory organization operates as a heuristic, similarly to the availability heuristic (Tversky & Kahneman, 1973). The availability heuristic in judgment and decision-making tasks is a short-cut method of relying on the ease with which a few initial instances come to mind (the ease of accessibility). The unarticulated assumption is something like: If I can easily think of examples of X, X must be true (or more prevalent).Judgments of personal knowledge are also based on retrieval fluency (see Kelley & Lindsay, 1993). For example, Winkielman, Schwarz, and Belli (1998) asked participants to recall either 4 or 12 childhood memories (the easy and difficult conditions) before rating the completeness of their memories representing those childhood years. Despite recalling many fewer memories, the participants in the easy condition gave higher ratings. Retrieval difficulty in the 12-memories JUDGING KNOWLEDGE IN THE DIGITAL AGE 4 condition led participants more frequently to infer that large parts of their childhood memories were missing.The logic of an organization heuristic is similar: When individuals judge personal knowledge, they implicitly assess the ac...

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Grit: Perseverance and passion for long-term goals.

Cited by 4,733 publications

References 61 publications

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

Improving Fluid Intelligence With Training on Working Memory: A Meta-Analysis

Judging Knowledge in the Digital Age: The Role of External‐Memory Organization

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