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Furlan, Sarah (2011) Developmental and individual differences in the Ratio-Bias Phenomenon with and without time pressure. [Tesi di dottorato]

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Abstract (inglese)

The ratio bias is known as the tendency to judge a low probability event as more likely when presented as a large-numbered ratio, such as 10/100, than a smaller-numbered ratio, such as 1/10 (Kirkpatrick & Epstein, 1992). Less is known about judgments when the ratio bias frame is reversed, requiring judgments of high probability events. This frame has been scarcely investigated in adults, never in children, and results, as well as predictions, are mixed.
According to cognitive-experiential-self theory (CEST), adult participants should favor a small-numbered ratio (i.e., 9-in-10) rather than a large-numbered ratio (i.e., 90-in-100) because the former is perceived as more concrete than the latter. A correct response depends on the development and strength of analytic processing. Instead, fuzzy-trace theory (FTT) predicts the opposite: people should favor a large-numbered ratio (i.e., 90-in-100) because they have a preference for simplified rather than exact numerical information and “more is better than less”. According to FTT theory, analytic processing and intuition develop together and both of them can lead to a correct response.
Experiment 1 assessed whether the bias pattern changes with age and whether it is more visible when comparing ratios is difficult. The proportion of correct responses should increase with age and instruction. Seventh graders (N = 94), middle adolescents (N = 58) and adults (N = 30) completed three trials of a mathematical scenario. They compared a small-numbered ratio (which was always 9-in-10) to a large-numbered ratio that varied: a) 85-in-95 (smaller than 9-in-10); b) 90-in-100 (equal to 9-in-10); and c) 95-in-105 (larger than 9-in-10). Correct responses increased with age. Seventh graders, however, were 4.9 times more likely than middle adolescents to give the correct response in the comparison between 9-in-10 and 95-in-105. The analysis of the biased preference revealed that, independent of the ratios, seventh graders slightly prefer the large-numbered container, whereas, according to CEST, middle adolescents were biased toward the small-numbered container.
Experiment 2 assessed whether two different real-life scenarios activate world knowledge that triggers the bias in different directions. Participants were 157 seventh graders, 131 middle adolescents, and 69 adults. Each participant completed three trials with a single scenario. The ratios in these trials were the same three ratios used in Experiment 1. In one scenario the responses of middle adolescents were much more biased than those of seventh graders toward the less numerous option. In the other scenario the responses of seventh graders were more biased toward the less numerous option than those of middle adolescents. Adults responded correctly about 75% in every condition and showed little bias.
Experiment 3 investigated how a time-pressure condition influences the interaction between the heuristic and analytic process. Participants were 92 seventh graders, 98 middle adolescents, and 92 adults. Each participant completed the same three trials used in previous experiments with a single scenario (the same three scenarios used in Experiment 1 and 2). Results show that accuracy decreases in all age groups and that, contrary to traditional dual-process theories, time pressure inhibits both analytic and heuristic processes. In addition, time pressure, according to FTT, favors gist processing.
The present findings do not appear completely congruent with the predictions of CEST or the predictions of FTT. Biases on ratios depend on the magnitudes of the probabilities, and both age and context influence the pattern of responses. Furthermore, formal and mathematical competence is needed to overcome the influence of world knowledge. Time to decide leads to wrong decisions based on heuristics.

Abstract (italiano)

Il ratio bias viene definito come la tendenza sistematica a giudicare un evento dalle basse probabilità di accadimento (per esempio una probabilità di vincita pari al 10%) come più probabile se presentato sotto forma di ampia numerosità (per esempio 10 palline vincenti su 100) piuttosto che di bassa numerosità (1 pallina su 10), nonostante le probabilità di accadimento siano le stesse (Kirkpatrick & Epstein, 1992). Il comportamento decisionale negli eventi ad alta probabilità di accadimento è stato, invece, scarsamente indagato negli adulti e mai in ottica evolutiva. Le poche ricerche a disposizione evidenziano risultati scarsamente coerenti con le ipotesi di partenza.
Secondo la cognitive-experiential-self theory (CEST) negli eventi positivi ad alta probabilità di accadimento gli adulti preferiscono i rapporti di probabilità espressi sotto forma di bassa numerosità (ad esempio 9 su 10) rispetto che ad alta numerosità (ad esempio 90 su 100) in quanto i primi sono percepiti come più concreti e di facile visualizzazione. La risposta corretta, coerentemente con lo sviluppo, dipende dal livello di abilità legate al sistema analitico e al ragionamento formale. La fuzzy-trace theory (FFT), invece, predice l’opposto, ovvero che le persone preferiscono i rapporti di probabilità espressi sotto forma di alta numerosità (ad esempio 90 su 100 rispetto a 9 su 10) perché semplificano il confronto basandosi esclusivamente sulla quantità maggiore al numeratore: 90, rispetto a 9, offre maggiori possibilità. Secondo la FTT, la risposta corretta dipende dal ragionamento formale ma anche dal concomitante sviluppo dell’intuizione la quale rappresenta l’apice dello sviluppo.
Nell’Esperimento 1 abbiamo indagato se il ratio bias cambia con l’età e diventa più evidente laddove i rapporti di probabilità da confrontare sono caratterizzati da un’elevata difficoltà computazionale. La proporzione di risposte corrette dovrebbe aumentare al crescere dell’età e del livello di istruzione. Sono stati indagati 94 studenti italiani di seconda media, 58 adolescenti italiani e 30 studenti americani della Cornell University. Ciascun partecipante ha risolto un problema a carattere matematico presentato in tre diversi trial. Ogni trial era caratterizzato dal confronto tra due rapporti numerici: il primo, che era costante per ogni trial, era caratterizzato da un rapporto di probabilità espresso sotto forma di bassa numerosità, ovvero 9 su 10. Il secondo, espresso sotto forma di alta numerosità, era diverso per ogni trial: a) 85 su 95 (minore di 9 su 10); b) 90 su 100 (identico a 9 su 10); e c) 95 su 105 (maggiore di 9 su 10). I risultati evidenziano che le risposte corrette aumentano all’aumentare dell’età. Tuttavia, i ragazzi di seconda media rispondono 4.9 volte meglio degli adolescenti nel confronto tra 9 su 10 e 95 su 105. L’analisi delle risposte biased mostra che, indipendentemente dalla specificità del trial considerato, i ragazzi di seconda media hanno una moderata preferenza per il rapporto ad alta numerosità. Gli adolescenti, invece, coerentemente con la CEST, mostrano un chiaro bias verso il rapporto a bassa numerosità.
Nell’Esperimento 2 abbiamo indagato se due scenari tratti dalla vita quotidiana attivano rappresentazioni contestualizzate che spingono il bias verso direzioni differenti. I partecipanti erano 157 studenti italiani di seconda media, 131 adolescenti di seconda superiore e 69 studenti americani della Cornell University. Ciascun partecipante ha risolto i tre trial descritti nell’Esperimento 1. I risultati mostrano che in uno scenario le risposte degli adolescenti vanno fortemente nella direzione dei rapporto a bassa numerosità (9 su 10) rispetto alle risposte dei ragazzi di seconda media. Nell’altro scenario il pattern è opposto: i ragazzi di seconda media hanno una preferenza maggiore per il rapporto a bassa numerosità rispetto agli adolescenti. Circa il 75% degli studenti della Cornell University rispondono correttamente e non mostrano alcuna preferenza sistematica per uno dei due rapporti di probabilità.
Nell’Esperimento 3 abbiamo fatto rispondere i partecipanti in condizione di forte pressione temporale in modo tale da comprendere l’interazione tra processamento euristico e analitico. I partecipanti erano 92 studenti italiani di seconda media, 98 adolescenti di seconda superiore e 92 studenti americani della Cornell University. A ciascun partecipante è stato assegnato uno dei tre scenari descritti negli Esperimenti 1 e 2 nei tre trial. La proporzione di risposte corrette diminuisce in tutti i gruppi di età. Inoltre, la pressione temporale, coerentemente con la FTT, favorisce intuizioni corrette basate sui rapporti di probabilità.
Errori sistematici nel confronto tra rapporti di probabilità dipendono dalle quantità numeriche presentate; inoltre, sia l’età che il contesto influiscono sui pattern di risposta. L’abilità matematica e formale sono importanti per processare correttamente l’informazione numerica indipendentemente dal contesto. Allo stesso tempo, troppo tempo per decidere favorisce la creazione parallela di euristiche di ragionamento che, indipendentemente dalle abilità formali, conducono a decisioni errate.

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Tipo di EPrint:Tesi di dottorato
Relatore:Agnoli, Franca
Dottorato (corsi e scuole):Ciclo 23 > Scuole per il 23simo ciclo > SCIENZE PSICOLOGICHE > PSICOLOGIA DELLO SVILUPPO E DEI PROCESSI DI SOCIALIZZAZIONE
Data di deposito della tesi:NON SPECIFICATO
Anno di Pubblicazione:26 Gennaio 2011
Parole chiave (italiano / inglese):Teorie del doppio processo/Dual-process theories; Il fenomeno del ratio bias/The ratio-bias phenomenon; Euristiche e bias/Heuristics and biases; Ragionamento probabilistico/Probabilistic reasoning; Differenze individuali/Individual differences; Intuizione/intuition
Settori scientifico-disciplinari MIUR:Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-PSI/04 Psicologia dello sviluppo e psicologia dell'educazione
Struttura di riferimento:Dipartimenti > Dipartimento di Psicologia dello Sviluppo e della Socializzazione
Codice ID:3474
Depositato il:21 Lug 2011 08:50
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I riferimenti della bibliografia possono essere cercati con Cerca la citazione di AIRE, copiando il titolo dell'articolo (o del libro) e la rivista (se presente) nei campi appositi di "Cerca la Citazione di AIRE".
Le url contenute in alcuni riferimenti sono raggiungibili cliccando sul link alla fine della citazione (Vai!) e tramite Google (Ricerca con Google). Il risultato dipende dalla formattazione della citazione.

Acker, F. (2008). New findings on unconscious versus conscious thought in decision making: additional empirical data and meta-analysis. Judgment and Decision Making, 3, 292-303. Cerca con Google

Acredolo, C., O'Connor, J., Banks, L., & Horobin, K. (1989). Children's ability to make probability estimates: Skills revealed through application of Anderson's functional measurement methodology. Child Development, 60, 933-945. Cerca con Google

Adelson, E. H. (1995). Checker-shadow illusion. http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html. Vai! Cerca con Google

Agnoli F., Dellai, V., Furlan S., & Stragà C. (2009). The Ratio-Bias Phenomenon: Different Intuitions at Different Ages. Society for Research in Child Development, Denver, CO. Cerca con Google

Agnoli, F. (1991). Development of judgmental heuristics and logical reasoning: training counteracts the representativeness heuristic. Cognitive Development, 6, 195-217. Cerca con Google

Agnoli, F., & Krantz, D. H. (1989). Suppressing natural heuristics by formal instruction: The case of the conjunction fallacy. Cognitive Psychology, 21, 515−550. Cerca con Google

Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd ed.). New York, NY: Wiley. Cerca con Google

Aizpurua, A., & Koutstaal, W. (2010). Aging and flexible remembering: Contributions of conceptual span, fluid intelligence, and frontal functioning. Psychology and Aging, 25, 193-207. Cerca con Google

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723. Cerca con Google

Alonso, D., & Fernandez-Borrocal, P. (2003). Irrational decisions: attending to numbers rather than ratios. Personality and Individual Differences, 35, 1537-1547. Cerca con Google

Amir, G., & Williams, J. (1999). Cultural influences on children’s probabilistic thinking. Journal of Mathematical Behavior, 18, 85-107. Cerca con Google

Amsel, E., Close, J., Sandler, E., & Klaczynski, P. A.(2009). College students’ awareness of irrational judgments on gambling tasks: a dual-process account. The Journal of Psychology, 143, 293-317. Cerca con Google

Amsel, E., Klaczynski, P. A., Johnston, A., Bench, S., Close, J., Sadler, E., & Walker, R. (2008). A dual-process account of the development of scientific reasoning: the nature and development of metacognitive intercession skills. Cognitive Development, 23, 452-471. Cerca con Google

Anderson, N. H., & Schlottmann, A. (1991). Developmental study of personal probability. In N. H. Anderson (Ed.), Contributions to information integration theory. Vol. III: Developmental (pp. 110-134). Hillsdale, NJ: Erlbaum. Cerca con Google

Arkes, H. R., & Ayton, P. (1999). The sunk cost and concorde effects: are humans less rational than lower animals? Psychological Bulletin, 125, 591–600. Cerca con Google

Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost. Organizational Behavior and Human Decision Processes, 35, 124–140. Cerca con Google

Arthur, W., Jr., & Day, D. V. (1994). Development of a short form for the Raven Advanced Progressive Matrices Test. Educational and Psychological Measurement, 54, 394–403. Cerca con Google

Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390-412. Cerca con Google

Baayen, R. H., Tweedie, F. J., & Schreuder, R. (2002). The subjects as a simple random effect fallacy: subject variability and morphological family effects in the mental lexicon. Brain and Language, 81, 55–65. Cerca con Google

Babai, R., Brecher, T., Stavy, R., & Tirosh, D. (2006). Intuitive interference in probabilistic reasoning. International Journal of Science and Mathematics Education, 4, 627-639. Cerca con Google

Baddeley, A. D. (1976). The psychology of memory. New York: Basic Books. Cerca con Google

Baddeley, A. D. (1986).Working memory. Oxford: Oxford University Press. Cerca con Google

Baddeley, A. D. (1996). Exploring the central executive. Quarterly Journal of Experimental Psychology, 49A, 5-28. Cerca con Google

Baron, J. (2008). Thinking and deciding (4th ed.). New York: Cambridge University Press. Cerca con Google

Barrouillet, P. (1996). Transitive inferences from set-inclusion relations and working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 1408-1422. Cerca con Google

Bates, D. M. (2005). Fitting linear mixed models in R. R News, 5, 27-30, URL http://CRAN.R-project.org/doc/Rnews/. Vai! Cerca con Google

Bates, D. M. (2007). Linear mixed model implementation in lme4. Ms., University of Wisconsin, Madison, August 2007. Cerca con Google

Bates, D. M., & Sarkar, D. (2007). lme4: Linear mixed-effects models using S4 classes. R package version 0.9975-12. Cerca con Google

Bjorklund, D. F. (1989). Children's thinking. Forest Grove, CA: Brooks/Cole. Cerca con Google

Björklund, F., & Bäckström, M. (2008). Individual differences in processing styles: validity of the Rational–Experiential Inventory. Scandinavian Journal of Psychology, 49, 439-446. Cerca con Google

Bonner, C., & Newell, B. R. (2008). How to make a risk seem riskier: the ratio bias versus construal level theory. Judgment and Decision Making, 3, 411-416. Cerca con Google

Bos, M.W., Dijksterhuis, A., & van Baaren, R. B. (2008). On the goal-dependency of unconscious thought. Journal of Experimental Social Psychology, 44, 1114-1120. Cerca con Google

Boyd, R., & Richerson, P.J. (2005). The origin and evolution of cultures. New York: Oxford University Press. Cerca con Google

Boyer, T. W. (2007). Decision-making processes: Sensitivity to sequentially experienced outcome probabilities. Journal of Experimental Child Psychology, 97, 28–43 Cerca con Google

Braine, M. D. S. (1959). The ontogeny of certain logical operations: Piaget's formulation examined by nonverbal methods. Psychological Monographs, 73, 1-43. Cerca con Google

Brainerd, C. J. (1979). Symposium on the future of Piagetian psychology. Genetic Epistemologist. Cerca con Google

Brainerd, C. J. (1981). Working memory and the developmental analysis of probability judgment. Psychological Review, 88, 463-502. Cerca con Google

Brainerd, C. J. (1983). Young children's mental arithmetic errors: A working-memory analysis. Child Development, 54, 812-830. Cerca con Google

Brainerd, C. J. (1985). Model-based approaches to storage and retrieval development. In C. J. Brainerd & M. Pressley (Eds.), Basic processes in memory development (pp. 143–208). New York: Springer-Verlag. Cerca con Google

Brainerd, C. J. (2004). Dropping the other U: an alternative approach to U-shaped developmental functions. Journal of Cognition & Development, 5, 81-88. Cerca con Google

Brainerd, C. J., & Kingma, J. (1984). Do children have to remember to reason? A fuzzy-trace theory of transitivity development. Developmental Review, 4, 311-377. Cerca con Google

Brainerd, C. J., & Kingma, J. (1985). On the independence of short-term memory and working memory in cognitive development. Cognitive Psychology, 17, 210–247. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1988). Generic resources, reconstructive processing, and children’s mental arithmetic, Developmental Psychology, 24, 324-334. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1990a). Gist is the grist: Fuzzy-Trace Theory and the new intuitionism. Developmental Review, 10, 3-47. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1990b). Inclusion illusions: Fuzzy-trace theory and perceptual salience effects in cognitive development. Developmental Review, 10, 365-403. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1992). Explaining “memory free” reasoning. Psychological Science, 3, 332-339. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1993). Memory independence and memory interference in cognitive development. Psychological Review, 100, 42– 67. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1995). Autosuggestibility in memory development. Cognitive Psychology, 28, 65−101. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1998a). Fuzzy-trace theory and children's false memories. Journal of Experimental Child Psychology, 71, 1-78. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (1998b). When things that never happened are easier to remember than things that did. Psychological Science, 9, 484-489. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (2001). Fuzzy-trace theory: Dual processes in memory, reasoning, and cognitive neuroscience. In H. W. Reese & R. Kail (Eds.), Advances in child development and behavior (Vol. 28, pp. 41–100). San Diego: Academic Press. Cerca con Google

Brainerd, C. J., & Reyna, V. F. (2004). Fuzzy-trace theory and memory development. Developmental Review, 24, 396-439. Cerca con Google

Brainerd, C. J., Reyna, V. F., & Poole, D. A. (2000). Fuzzy-trace theory and false memory: Memory theory in the courtroom. In D. F. Bjorklund (Ed.), False memory creation in children and adults (pp. 93-128). Mahwah, NJ: Erlbaum. Cerca con Google

Breslow, N. E., & Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Society, 88, 9–25. Cerca con Google

Bull, R., & Scerif, G. (2001). Executive functioning as a predictor of children’s mathematical ability: Inhibition, switching, and working memory. Developmental Neuropsychology, 19, 273–293. Cerca con Google

Burnham, K. P., & Anderson, D. R. (2002). Model selection and multimodel inference: a practical information-theoretic approach (2nd ed.). New York, NY: Springer. Cerca con Google

Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42, 116-131. Cerca con Google

Cacioppo, J. T., Petty, R. E., Feinstein, J., & Jarvis, W. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119, 197–253. Cerca con Google

Callahan, P. (1989). Learning and development of probability concepts: Effects of computer assisted instruction and diagnosis. Unpublished doctoral dissertation, University of Arizona, College of Education, Tucson. Mentioned in Reyna & Brainerd (1994). Cerca con Google

Campitelli, G., & Labollita, M. (2010). Correlations of cognitive reflection with judgments and choices. Judgment and Decision Making, 3, 182–191. Cerca con Google

Carey, S., & Diamond, R. (1977). From piecemeal to configurational representations of faces. Science, 195, 312-314. Cerca con Google

Carlson, J. (1970). The development of probabilistic thinking in children: a comparison of two methods of assessment. Journal of Genetic Psychology, 116, 263-269. Cerca con Google

Carroll, J. B. (1993). Human cognitive abilities: a survey of factor-analytic studies. Cambridge, UK: Cambridge University Press. Cerca con Google

Case, R. (1992). The role of the frontal lobes in the regulation of cognitive development. Brain and Cognition, 20, 51–73. Cerca con Google

Chaiken, S., & Trope, Y. (1999). Dual process theories in social psychology. New York, NY: The Gilford Press. Cerca con Google

Chapman, M., & Lindenberger, U. (1988). Functions, operations, and decalage in the development of transitivity. Developmental Psychology, 24, 542–551. Cerca con Google

Chapman, R. H. (1975). The development of children's understanding of proportions. Child Development, 46, 141-148. Cerca con Google

Cohen, A. R., Scotland, E., & Wolfe, D. M. (1955). An experimental investigation of need for cognition. Journal of Abnormal and Social Psychology, 51, 291-294. Cerca con Google

Cornoldi, C., & Cazzola, C. (2003). AC-MT 11-14 - Test di valutazione delle abilità di calcolo e problem solving dagli 11 ai 14 anni. Trento, Erickson. Cerca con Google

Cornoldi, C., & Colpo, G. (1995). Nuove prove di lettura MT per la scuola media inferiore, Organizzazioni Speciali, Firenze. Cerca con Google

Cronbach, L. J. (1949). Essentials of psychological testing. New York: Harper. Cerca con Google

Dale, D., Rudski, J., Schwarz, A., & Smith, E. (2007). Innumeracy and incentives: a ratio bias experiment. Judgment and Decision Making, 2, 243-250. Cerca con Google

Daniel, D. B., & Klaczynski, P. A. (2006). Developmental and individual differences in conditional reasoning: Effects of logic instructions and alternative antecedents. Child Development, 77, 339-354. Cerca con Google

Davidson, D. (1995). The representativeness heuristic and conjunction fallacy effect in children’s decision-making. Merrill-Palmer Quarterly, 41, 328-346. Cerca con Google

Davidson, D., Suppes, P., & Siegel, S. (1957). Decision making: an experimental approach. Stanford: Stanford University Press. Cerca con Google

Davies, R. (2006). Decision making and alcohol use in adolescents: A dual process approach. Unpublished Master thesis, University of New England, Armidale, New South Wales, Australia. In Marks, Hine, Blore, & Phillips, W. J. (2008). Cerca con Google

De Neys, W. (2006a). Dual processing in reasoning—two systems but one reasoner. Psychological Science, 17, 428–433. Cerca con Google

De Neys, W. (2006b). Automatic-heuristic and executive – analytic processing during reasoning: chronometric and dual-task considerations. The Quarterly Journal of Experimental Psychology, 59, 1070-1100. Cerca con Google

De Neys, W., & Glumicic, T. (2008). Conflict monitoring in dual process theory of thinking. Cognition, 106, 1248-1299. Cerca con Google

De Neys, W., & Vanderputte, K. (in press). When less is not always more: Stereotype knowledge and reasoning development. Developmental Psychology. Cerca con Google

De Neys, W., Moyens, E., & Vansteenwegen, D. (2010). Feeling we’re biased: Autonomic arousal and reasoning conflict. Cognitive, Affective, and Behavioral Neuroscience, 10, 208-216. Cerca con Google

De Neys, W., Schaeken, W., & d’Ydewalle, G. (2005). Working memory and counterexample retrieval for causal conditionals. Thinking and Reasoning, 11, 123-150. Cerca con Google

DebRoy, S., & Bates, D. M. (2004). Linear mixed models and penalized least squares. Journal of Multivariate Analysis, 91, 1–17. Cerca con Google

Dellai, V. (2007). Sviluppo del ragionamento analitico e dell’intuizione: Il caso del Ratio Bias [The development of analytic thinking and intuition: the case of the ratio-bias]. Unpublished Thesis, University of Padua, Italy. Cerca con Google

Dempster, F. N., & Corkill, A. J. (1999). Individual differences in susceptibility to interference and general cognitive ability. Acta Psychologica, 101, 395-416. Cerca con Google

Denes-Raj, V., & Epstein, S. (1994). Conflict between intuitive and rational processing: when people behave against their better judgment. Journal of Personality and Social Psychology, 66, 819-829. Cerca con Google

Denes-Raj, V., Epstein, S., & Cole, J. (1995). The generality of the ratio-bias phenomenon. Personality and Social Psychology Bulletin, 21, 1083–1092. Cerca con Google

Dijksterhuis, A. (2004). Think different: The merits of unconscious thought in preference development and decision making. Journal of Personality and Social Psychology, 87, 586–598. Cerca con Google

Dijksterhuis, A., & Nordgren, L. F. (2006). A theory of unconscious thought. Perspectives on Psychological Science, 1, 95–109. Cerca con Google

Dijksterhuis, A., Bos, M. W., Nordgren, L. F., & van Baaren, R. B. (2006). On Making the Right Choice: the deliberation-without-attention effect. Science, 311, 1005–1007. Cerca con Google

Dixon, J. A., & Moore, C. F. (1996). The developmental role of intuitive principles in choosing mathematical strategies. Developmental Psychology, 32, 241-253. Cerca con Google

Donovan, S., & Epstein, S. (1997). The difficulty of the Linda conjunction problem can be attributed to its simultaneous concrete and unnatural presentation, and not to conversational implicature. Journal of Experimental Social Psychology, 33, 1–20. Cerca con Google

Epstein, S. (1973). The self-concept revisited, or a theory of a theory. American Psychologist, 28, 404-416. Cerca con Google

Epstein, S. (1990). Cognitive-Experiential Self-Theory, in L. Pervin (Ed.), Handbook of Personality Theory and Research (pp. 165-192). New York: Press. Cerca con Google

Epstein, S. (1991). Cognitive-experiential self-theory: an integrative theory of personality. In R. Curtis (Ed.), The relational self: convergences in psychoanalysis and social psychology (pp. 111–137). New York: Guilford. Cerca con Google

Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49, 709-724. Cerca con Google

Epstein, S. (2003). Cognitive-experiential self theory of personality. In T. Millon & M. J. Lerner (Eds.), Handbook of psychology: Vol. 5. Personality and social psychology (pp. 159–184). Hoboken, NJ: Wiley. Cerca con Google

Epstein, S., & Pacini, R. (1999). Some basic issues regarding dual-process theories from the perspective of cognitive-experiential self-theory. In S. Chaiken & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 462–482). New York, NY: The Gilford Press. Cerca con Google

Epstein, S., & Pacini, R. (2001). A comparison of the influence of imagined and unimagined verbal information on intuitive and analytical information processing. Imagination, Cognition, and Personality, 20, 195–216. Cerca con Google

Epstein, S., Denes-Raj, V., & Pacini, R. (1995). The Linda problem revisited from the perspective of Cognitive-Experiential Self-Theory. Personality and Social Psychology Bulletin, 21, 1124-1138. Cerca con Google

Epstein, S., Donovan, S., & Denes-Raj, V. (1999). The missing link in the paradox of the Linda conjunction problem: Beyond knowing and thinking of the conjunction rule, the intrinsic appeal of heuristic processing. Personality and Social Psychology Bulletin, 25, 204–214. Cerca con Google

Epstein, S., Lipson, A., Holstein, C., & Huh, E. (1992). Irrational reactions of negative outcomes: evidence for two conceptual systems. Journal of Personality and Social Psychology, 62, 328-339. Cerca con Google

Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive-experiential and analytical-rational thinking styles. Journal of Personality and Social Psychology, 71, 390-405. Cerca con Google

Estrada, C., Barnes, V., Collins, C., & Byrd, J. C. (1999). Health literacy numeracy. Journal of the American Medical Association, 282, 527. Cerca con Google

Evans J. St. B. T., Newstead, S. N., & Byrne, R. (1993). Human reasoning: the psychology of deduction. Lawrence Erlbaum Associates, Hove, UK. Cerca con Google

Evans, J. St. B. T. (1989). Bias in human reasoning: Causes and consequences. London: Erlbaum Associates. Cerca con Google

Evans, J. St. B. T. (2003). In two minds: dual-process accounts of reasoning. Trends in Cognitive Sciences, 7, 454-459. Cerca con Google

Evans, J. St. B. T. (2006). The heuristic-analytic theory of reasoning: Extension and evaluation. Psychonomic Bulletin & Review, 13, 378-395. Cerca con Google

Evans, J. St. B. T. (2007). Thinking: Dual Processes in Reasoning and Judgment. Hove: Psychology Press. Cerca con Google

Evans, J. St. B. T. (2008). Dual processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59, 255-278. Cerca con Google

Evans, J. St. B. T. (2009). How many dual process theories do we need: One, two or many? In J. St. B. T. Evans & K. Frankish (Eds.), In two minds: Dual processes and beyond (pp. 33–54). Oxford, UK: Oxford University Press. Cerca con Google

Evans, J. St. B. T., & Curtis-Holmes, J. (2005). Rapid responding increases belief bias: evidence for the dual-process theory of reasoning. Thinking & Reasoning, 11, 382-389. Cerca con Google

Evans, J. St. B. T., & Over, D. E. (1996). Rationality and reasoning. Hove, England: Psychology Press. Cerca con Google

Fagerlin, A., Ubel, P. A., Smith, D. M., & Zikmund-Fisher, B. J. (2007). Making numbers matter: Present and future research in risk communication. American Journal of Health Behavior, 31, S47–S56. Cerca con Google

Fagerlin, A., Zikmund-Fisher, B. J., Ubel, P. A., Jankovic, A., Derry, H. A., & Smith, D. M. (2007). Measuring numeracy without a math test: Development of the subjective numeracy scale. Medical Decision Making, 27, 672-680. Cerca con Google

Falk, R., & Wilkening, F. (1998). Children’s construction of fair chances: adjusting probabilities. Developmental Psychology, 34, 1240–1357. Cerca con Google

Faraway, J. J. (2006). Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Boca Raton, FL: Chapman and Hall. Cerca con Google

Ferreira, M.B., Garcia-Marques L., Sherman, S. J., & Sherman, J. W. (2006). Automatic and controlled components of judgment and decision making. Journal of Personality and Social Psychology, 91, 797–813. Cerca con Google

Fiedler, K. (1988) The dependence of the conjunction fallacy on subtle linguistic factors. Psychological Research, 50, 123–29. Cerca con Google

Fischbein, E. (1975). The intuitive sources of probabilistic thinking in children. The Netherlands: Reidel, Dordrecht. Cerca con Google

Fischbein, E. (1987). Intuition in science and mathematics. The Netherlands: Reidel, Dordrecht. Cerca con Google

Fischbein, E. (1990). Intuition and information processing in mathematical activity. International Journal of Educational Research, 14, 31-50. Cerca con Google

Fischbein, E., & Schnarch, D. (1997). The evolution with age of probabilistic, intuitively based misconceptions. Journal for Research in Mathematics Education, 28, 96-105. Cerca con Google

Fischbein, E., Pampu, I., & Manzat, I. (1970). Comparison of ratios and the chance concept in children. Child Development, 41, 377-389. Cerca con Google

Fisk, J. E., Bury, A. S., & Holden, R. (2006). Reasoning about complex probabilistic concepts in childhood. Scandinavian Journal of Psychology, 47, 497–504. Cerca con Google

Flavell, J., Miller, P., & Miller, S. (2002). Cognitive development (4th ed.). Upper Saddle River, NJ: Prentice-Hall. Cerca con Google

Fodor J. (1983). The Modularity of Mind. Scranton, PA: Crowell. Cerca con Google

Fodor J. (2001). The mind doesn't work that way. Cambridge, Mass.: MIT Press. Cerca con Google

Frank, M. J., Cohen, M. X., & Sanfey, A. G. (2009). Multiple systems in decision making: A neurocomputational perspective. Current Directions in Psychological Science, 18, 73-77. Cerca con Google

Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19, 25-42. Cerca con Google

Freud, S. (1953). The interpretation of dreams. In J. Strachey (Ed. & Trans.), The standard edition of the complete psychological works of Sigmund Freud (Vols. 4 and 5). London: Hogarth. (Original work published 1900) Cerca con Google

Freud, S. (1959). Beyond the pleasure principle. New York: Norton. (Original work published 1920) Cerca con Google

Fudenberg, D., & Levine, D. K. (2006). Superstition and Rational Learning. American Economic Review, 96, 630-651. Cerca con Google

Garavan, H., Ross, T. J., Murphy, K., Roche, R. A. P., & Stein, E. A. (2002). Dissociable executive functions in the dynamic control of behavior: Inhibition, error detection, and correction. NeuroImage, 17, 1820-1829 Cerca con Google

Gigerenzer, G. (2008). Why heuristics work. Perspective on Psychological Science, 3, 20-29. Cerca con Google

Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: models of bounded rationality. Psychological Review, 103, 650–669. Cerca con Google

Gigerenzer, G., & Goldstein, D. G. (1999). Betting on one good reason: The take the best heuristic. In G. Gigerenzer, P. M. Todd, & the ABC Research Group (Eds.), Simple Heuristics that Make Us Smart (pp. 75–95). New York: Oxford University Press. Cerca con Google

Girotto, V., & Gonzales, M. (2008). Children’s understanding of posterior probability. Cognition, 106, 325-344. Cerca con Google

Goldberg, S. (1966). Probability judgments of preschool children: Task conditions and performance. Child Development, 37, 158-167 Cerca con Google

Gopnik, A. (1996). The Post-Piaget era. Psychological Science, 7, 221-225. Cerca con Google

Hammond, K. R. (1996). Human judgment and social policy. Oxford University Press. Cerca con Google

Hertwig, R., & Gigerenzer, G. (1999). The conjunction fallacy revisited: How intelligent inferences look like reasoning errors. Journal of Behavioral Decision Making, 12, 275-305. Cerca con Google

Hertwig, R., & Pleskac, T. J. (2010). Decisions from experience: why small samples? Cognition, 115, 225-237. Cerca con Google

Hoemann, H. W., & Ross, B. M. (1971). Children's understanding of probability concepts. Child Development, 42, 221-236. Cerca con Google

Holyoak, K. J. (1978). Comparative judgments with numerical reference points. Cognitive Psychology, 10, 203-24 Cerca con Google

Houdé, O. (2007). First insights on neuropedagogy of reasoning. Thinking & Reasoning, 13, 81-89. Cerca con Google

Houdè, O., & Guichart, E. (2001). Negative priming effect after inhibition of number/ length interference in a Piaget-like task. Developmental Science, 4, 119-223. Cerca con Google

Inhelder, B., & Piaget, J. (1958). The growth of logical thinking from childhood to adolescence. New York: Basic Books. Cerca con Google

Inhelder, B., & Piaget, J. (1964). The Early Growth of Logic in the Child. New York: Routlege and Kegan (original in French, 1959). Cerca con Google

Jacobs, J. E., & Klaczynski, P. A. (2002). The development of judgment and decision making during childhood and adolescence. Current Directions in Psychological Science, 11, 145-149. Cerca con Google

Jacobs, J. E., & Potenza, M. (1991). The use of judgment heuristics to make social and object decisions: A developmental perspective. Child Development, 62, 166-178. Cerca con Google

Jaeger, F. T. (2008). Categorical data analysis: away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434-446. Cerca con Google

Janveau-Brennan, G., & Markovits, H. (1999). The development of reasoning with causal conditionals. Developmental Psychology, 35, 904–911. Cerca con Google

Jones, G. A., & Thornton, C. A. (2005). An overview of research into the teaching and learning of probability. In G. A. Jones (Ed.), Exploring Probability in School: Challenges for Teaching and Learning, (pp. 66-92). New York: Springer. Cerca con Google

Kahneman, D. (2003). A perspective on judgment and choice. Mapping bounded rationality. American Psychologist, 58, 697-720. Cerca con Google

Kahneman, D., & Frederick, S. (2002). Representativeness revisited: attribute substitution in intuitive judgment. In Gilovich, T., Griffin, D., Kahneman, D. (Eds.), Heuristics and biases: the psychology of intuitive judgment (pp. 49-81). New York: Cambridge University Press. Cerca con Google

Kahneman, D., & Miller, D. T. (1986). Norm theory: comparing reality to its alternatives. Psychological Review, 93, 136-153. Cerca con Google

Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive Psychology, 3, 430-454. Cerca con Google

Kahneman, D., & Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica, 47, 111-132. Cerca con Google

Kahneman, D., & Tversky, A. (1982). The simulation heuristic. In D. Kahneman, P. Slovic & Tversky (Eds.), Judgment under certainty: Heuristics and biases (pp. 201–208). New York, NY: Cambridge University Press. Cerca con Google

Kahneman, D., & Tversky, A. (1986). On the reality of cognitive illusions. Psychological Review, 103, 582-591. Cerca con Google

Kemmelmeier, M. (2010). Authoritarianism and its relationship with intuitive-experiential cognitive style and heuristic processing. Personality and Individual Differences, 48, 44-48. Cerca con Google

Keren, G., & Schul, Y. (2009). Two is not always better than one: a critical evaluation of two-systems theory. Perspectives on Psychological Science, 4, 533-550. Cerca con Google

Kieren, T. E. (1988). Personal knowledge of rational numbers: its intuitive and formal development. In J. Hiebert, & M. Behr (Eds.), Number concepts and operations in the middle grades (pp. 162-181). Reston, VA: NCTM; Hillsdale, NJ: Lawrence Erlbaum. Cerca con Google

Kirkpatrick, L. A., & Epstein, S. (1992). Cognitive-experiential self-theory and subjective probability: further evidence for two conceptual systems. Journal of Personality and Social Psychology, 63, 534-544. Cerca con Google

Klaczynski, P. A. (2000). Motivated scientific reasoning biases, epistemological beliefs, and theory polarization: A two-process approach to adolescent cognition. Child Development, 71, 1347-1366. Cerca con Google

Klaczynski, P. A. (2001a). Analytic and heuristic processing influences on adolescent reasoning and decision-making. Child Development, 72, 844-861. Cerca con Google

Klaczynski, P. A. (2001b). Framing effects on adolescent task representations, analytic and heuristic processing, and decision making implications for the normative/descriptive gap. Journal of Applied Developmental Psychology, 22, 289-309. Cerca con Google

Klaczynski, P. A. (2004). A dual-process model of adolescent development: Implications for decision making, reasoning, and identity. In R. V. Kail (Ed.), Advances in child development and behavior (pp. 73–123). San Diego, CA: Academic Press. Cerca con Google

Klaczynski, P. A. (2009). Cognitive and social cognitive development: Dual-process research and theory. J. B. St. T. Evans & K. Frankish (Eds.), In two minds: Psychological and philosophical theories of dual processing (pp. 265-292). Oxford, UK: Oxford University Press. Cerca con Google

Klaczynski, P. A., & Cottrell, J. E. (2004). A dual-process approach to cognitive development: the case of children’s understanding of sunk cost decisions. Thinking & Reasoning, 10, 147-174. Cerca con Google

Klaczynski, P. A., & Narasimham, G. (1998). Development of scientific reasoning biases: cognitive versus ego-protective explanations. Developmental Psychology, 34, 175–187. Cerca con Google

Klaczynski, P. A., Fauth, J. M., & Swanger, A. (1998). Adolescent identity: rational vs. experiential processing, formal operations, and critical thinking beliefs. Journal of Youth and Adolescence, 27, 185-207. Cerca con Google

Klaczynski, P. A., Gordon, D.H., & Fauth, J. (1997). Goal-oriented critical thinking biases and individual differences in reasoning biases. Journal of Educational Psychology, 89, 470-485. Cerca con Google

Kline, R. B. (2004). Beyond significance testing. Reforming data analysis methods in behavioural research. Washington, DC: American Psychological Association. Cerca con Google

Kokis, J. V., Macpherson, R., Toplak, M. E., West, R. F., & Stanovich, K. E. (2002). Heuristic and analytic processing: age trends and associations with cognitive ability and cognitive styles. Journal of Experimental Child Psychology, 83, 26-52. Cerca con Google

Kühberger, A., & Tanner, C. (2009). Risky choice framing: task versions and a comparison of prospect-theory and fuzzy-trace theory. Journal of Behavioral Decision Making, 23, 314-329. Cerca con Google

Kuhn, D. (2000). Metacognitive development. Current Directions in Psychological Science, 9, 178–181. Cerca con Google

Kuhn, D. (2009). Adolescent thinking. In R. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (3rd ed., Vol. 1, pp. 152–186). New York: Wiley. Cerca con Google

Kuhn, D., & Pearsall, S. (2000). Development of origins of scientific thinking. Journal of Cognition and Development, 1, 113–129. Cerca con Google

Kwon, Y. J., Lawson, A. E., Chung, W. H., & Kim, Y. S. (2000). Effect on development of proportional reasoning skill of physical experience and cognitive abilities associated with prefrontal lobe activity. Journal of Research in Science Teaching, 37, 1171–1182. Cerca con Google

Kyllonen, P. C., & Christal, R. E. (1990) Reasoning ability is (little more than) working memory capacity?! Intelligence, 14, 389–433. Cerca con Google

Liben, L. S., & Posnansky, C. J. (1977). Inferences on inference: the effects of age, transitive ability, memory load, and lexical factors. Child Development, 48, 1490-1497. Cerca con Google

Lieberman, M. D. (2003). Reflective and reflexive judgment processes: A social cognitive neuroscience approach. In J. P. Forgas, K. R. Williams, & W. von Hippel (Eds.), Social judgments: Implicit and explicit processes (pp. 44-67). New York: Cambridge University Press. Cerca con Google

Lindeman, M., & Aarnio, K. (2006). Paranormal beliefs: Their dimensionality and correlates. European Journal of Personality, 20, 585–602. Cerca con Google

Lipkus, I. M., & Peters, E. (2009). Understanding the role of numeracy in health: proposed theoretical framework and practical insights. Health Education and Behavior, 36, 1065-1081. Cerca con Google

Lipkus, I. M., Samsa, G., & Rimer, B. K. (2001). General performance on a numeracy scale among highly educated samples. Medical Decision Making, 21, 37–44. Cerca con Google

Mack, N. K. (1990). Learning fractions with understanding: building on informal knowledge. Journal for Research in Mathematics Education, 21, 16-32. Cerca con Google

Macpherson, R. (2001). Analytic and heuristic processing in development of statistical reasoning in children. Master Thesis, University of Toronto. Cerca con Google

Markovits, H., & Barrouillet, P. (2004). Introduction: Why is understanding the development of reasoning important? Thinking & Reasoning, 10, 113-121. Cerca con Google

Markovits, H., & Dumas, C. (1999). Developmental patterns in the understanding of social and physical transitivity. Journal of Experimental Child Psychology, 73, 95-114. Cerca con Google

Markovits, H., Doyon, C., & Simoneau, M. (2002). Individual differences in working memory and conditional reasoning with concrete and abstract content. Thinking and Reasoning, 8, 97 – 107. Cerca con Google

Marks, A. D. G., Hine, D. W., Blore, L. R., & Phillips, W. J. (2008). Assessing individual differences in adolescents’ preference for rational and experiential cognition. Personality and Individual Differences, 44, 42-52. Cerca con Google

McCullagh P., & Nelder, J. A. (1989). Generalized linear models. 2nd ed., Chapman & Hall Ltd., London. Cerca con Google

Milkman, K. L., Chugh, D., & Bazerman, M. H. (2009). How can decision making be improved? Perspectives on Psychological Science, 4, 379-383. Cerca con Google

Miller G. A. (1956). The magical number seven plus or minus two. Psychological Review, 63, 81-97. Cerca con Google

Miller, D. T, Turnbull, W, & McFarland, C. (1989). When a coincidence is suspicious: The role of mental simulation. Journal of Personality and Social Psychology, 57, 581-589. Cerca con Google

Moore, C. F., Dixon, J. A., & Haines, B. A. (1991). Components of understanding in proportional reasoning: A fuzzy set representation of developmental progressions. Child Development, 62, 441-459. Cerca con Google

Morsanyi, K., & Handley, S. J. (2008). How smart do you need to be to get it wrong? The role of cognitive capacity in the development of heuristic-based judgment. Journal of Experimental Child Psychology, 99, 18-36. Cerca con Google

Morsanyi, K., Primi, C., Chiesi, F., & Handley, S. (2009). The effects and side-effects of statistics education: psychology students’ (mis-)conceptions of probability. Contemporary Educational Psychology, 34, 210-220. Cerca con Google

Myung, I. J., Forster, M. R., & Browne, M. W. (Eds.) (2000). Model selection [Special section]. Journal of Mathematical Psychology, 44, 1-2. Cerca con Google

Nelder, J. A., & Wedderburn, R.W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society, 135, 370-384. Cerca con Google

Nelson, W., Reyna, V. F., Fagerlin, A., Lipkus, I., & Peters, E. (2008). Clinical implications of numeracy: theory and practice. Annals of Behavioral Medicine, 35, 261-274. Cerca con Google

Nisbett, R. E., Peng, K., Choi, I., & Norenzayan, A. (2001). Culture and systems of thought: Holistic vs. analytic cognition. Psychological Review, 108, 291-310. Cerca con Google

Novak, T. P., & Hoffman, D. L. (2008). The fit of thinking style and situation: new measures of situation-specific experiential and rational cognition. Journal of Consumer Research, 36, 56-72. Cerca con Google

Nunes, T., Schliemann, A.D., & Carraher, D.W. (1993). Mathematics in the Streets and in Schools. Cambridge, U.K: Cambridge University Press. Cerca con Google

Oechssler, J., Roider, A., & Schmitz, P. W. (2009). Cognitive abilities and behavioral biases. Journal of Economic Behavior and Organization, 29, 147-152. Cerca con Google

Offenbach, S. I., Gruen, G. E., & Caskey, B. J. (1984). Development of proportional response strategies. Child Development, 55, 965-972. Cerca con Google

Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic Bulletin & Review, 11, 988-1010. Cerca con Google

Osman, M., & Stavy, R. (2006). Development of intuitive rules: evaluating the application of the dual-system framework to understanding children’s intuitive reasoning. Psychonomic Bulletin & Review, 13, 935-953. Cerca con Google

Pacini, R., & Epstein, S. (1999a). The interaction of three facets of concrete thinking in a game of chance. Thinking and Reasoning, 5, 303-325. Cerca con Google

Pacini, R., & Epstein, S. (1999b). The relation of rational and experiential information processing styles to personality, basic beliefs, and the ratio-bias phenomenon. Journal of Personality and Social Psychology, 76, 972-987. Cerca con Google

Paivio, A. (1991). Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255–287. Cerca con Google

Pavan, A. (2005). Il conflitto tra istruzione formale e risposte intuitive: Il caso del Ratio Bias [Conflict between formal instruction and intuitive answers: the ratio-bias phenomenon]. Unpublished thesis, University of Padua, Italy. Cerca con Google

Pennington, N. (1990). The complexity of human responses to (apparently) simple judgment problems. Contemporary Psychology, 35, 32-33. Cerca con Google

Perner, J., & Mansbridge, D. G. (1983). Developmental differences in encoding. Child Development, 54, 710–719. Cerca con Google

Peters, E., Västfjäll, D., Slovic, P., Mertz, C., Mazzocco, K., & Dickert, S. (2006). Numeracy and decision making. Psychological Science, 17, 407–413. Cerca con Google

Peterson, J. B., Pihl, R. O., Higgins, D. M., Seguin, J. R., & Tremblay, R. E. (2003). Neuropsychological performance, IQ, personality, and grades in a longitudinal grade-school male sample. Individual Differences Research, 3, 159–172. Cerca con Google

Piaget, J. & Inhelder, B. (1975). The Origins of the Idea of Chance in Children, W. W. Norton, New York. (Original work published 1951) Cerca con Google

Piaget, J. (1930). The child’s conception of causality. London: Kegan Paul. Cerca con Google

Piaget, J. (1952). The origins of intelligence in children. New York: International University Press. (Original work published 1936) Cerca con Google

Piaget, J., & Inhelder, B. (1973). Memory and intelligence. New York: Basic Books. Cerca con Google

Pinheiro, J. C., & Bates, D. M. (2000). Mixed-effects models in S and S-PLUS. New York: Springer-Verlag. Cerca con Google

Price, P. C., & Matthews, T. V. (2009). From group diffusion to ratio bias: effects of denominator and numerator salience on intuitive risk and likelihood judgments. Judgment and Decision Making, 4, 436-446. Cerca con Google

Quené, H., & Van den Bergh, H. (2004). On Multi-Level Modeling of data from repeated measures designs: a tutorial. Speech Communication, 43, 103-12. Cerca con Google

Raidl, M.H., & Lubart, T. I. (2000-2001). An empirical study of intuition and creativity. Imagination, Cognition, and Personality, 20, 217–230. Cerca con Google

Reber, A. S. (1993). Implicit learning and tacit knowledge. New York: Oxford University Press. Cerca con Google

Reeves, T., & Lockhart, R. S. (1993). Distributional versus singular approaches to probability and errors in probabilistic reasoning. Journal of Experimental Psychology: General, 122, 207–226. Cerca con Google

Reyna, V. F. (1991) Class inclusion, the conjunction fallacy, and other cognitive illusions. Developmental Review, 11, 317–36. Cerca con Google

Reyna, V. F. (1995). Interference effects in memory and reasoning: A fuzzy-trace theory analysis. In F. N. Dempster & C. J. Brainerd (Eds.), Interference and inhibition in cognition (pp. 29–59). San Diego, CA: Academic Press. Cerca con Google

Reyna, V. F. (1996). Conceptions of memory development, with implications for reasoning and decision making. Annals of Child Development, 12, 87–118. Cerca con Google

Reyna, V. F. (2004). How people make decisions that involve risk: a dual-processes approach. Current Directions in Psychological Science, 13, 60-66. Cerca con Google

Reyna, V. F. (2008). A theory of medical decision making and health: fuzzy trace theory. Medical Decision Making, 28, 850-865. Cerca con Google

Reyna, V. F., & Adam M. B. (2003). Fuzzy-Trace Theory, risk communication, and product labelling in sexually transmitted diseases. Risk Analysis, 23, 325-342. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1990). Fuzzy processing in transitivity development. Annals of Operations Research, 23, 37-63. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1991). Fuzzy-trace theory and framing effects in choice. Gist extraction, truncation, and conversion. Journal of Behavioral Decision Making, 4, 249−262. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1992). A fuzzy-trace theory of reasoning and remembering: Paradoxes, patterns, and parallelism. In N. Hearst, S. Kosslyn, & R. Shiffrin (Eds.), From learning processes to cognitive processes: Essays in honor of William K. Estes (pp. 235−259). Hillsdale, New Jersey: Lawrence Erlbaum Associates. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1993). Fuzzy Memory and mathematics in the classroom. In G. M. Davies & R. H. Logies (Eds.), Memory in everyday life (pp.91–134). Elsevier Science Publishers B.V. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1994). The origins of probability judgment: a review of data and theories. In G. Wright & P. Ayton (Eds.), Subjective probability. New York: Wiley. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1995a). Fuzzy-trace theory: an interim synthesis. Learning and Individual Differences, 7, 1-75. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (1995b). Fuzzy-trace theory: Some foundational issues. Learning & Individual Differences, 7, 145−162. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (2007). The importance of mathematics in health and human judgment: Numeracy, risk communication, and medical decision making. Learning and Individual Differences, 17, 147-159. Cerca con Google

Reyna, V. F., & Brainerd, C. J. (2008). Numeracy, ratio bias, and denominator neglect in judgments of risk and probability. Learning and Individual Differences, 18, 89-107. Cerca con Google

Reyna, V. F., & Ellis, S. C. (1994). Fuzzy-Trace Theory and framing effects in children’s risky decision making. Psychological Science, 5, 275-279. Cerca con Google

Reyna, V. F., & Farley, F. (2006). Risk and rationality in adolescent decision making: Implications for theory, practice, and public policy. Psychological Science in the Public Interest, 7, 1–44. Cerca con Google

Reyna, V. F., & Kiernan, B. (1994). The development of gist versus verbatim memory in sentence recognition: Effects of lexical familiarity, semantic content, encoding instructions, and retention interval. Developmental Psychology, 30, 178−191. Cerca con Google

Reyna, V. F., & Kiernan, B. (1995). Children’s memory and interpretation of psychological metaphors. Metaphor and Symbolic Activity, 10, 309–331. Cerca con Google

Reyna, V. F., & Lloyd, F. J. (2006). Physician decision-making and cardiac risk: Effects of knowledge, risk perception, risk tolerance, and fuzzy processing. Journal of Experimental Psychology: Applied, 12, 179-195. Cerca con Google

Reyna, V. F., & Narter, C. (1991). Theoretical implications of children’s decision making. Presented at the 32nd Annual Meeting of the Psychonomic Society, San Francisco, CA. Cerca con Google

Reyna, V. F., Lloyd, F. J., & Brainerd, C. J. (2003). Memory, development, and rationality: An integrative theory of judgment and decision making. In S.L. Schneider & J. Shanteau (Eds.), Emerging perspectives on judgment and decision research (pp. 201–245). New York: Cambridge University Press. Cerca con Google

Reyna, V. F., Nelson, W. L., Han, P. K., & Dieckmann, N. F. (2009). How numeracy influences risk comprehension and medical decision making. Psychological Bulletin, 135, 943-973. Cerca con Google

Reyna, V.F., & Mills, B. A. (2007). Converging evidence supports fuzzy-trace theory’s nested sets hypothesis (but not the frequency hypothesis). Behavioral and Brain Sciences, 30, 278-280. Cerca con Google

Roberts, M. J., & Newton, E. J. (2002). Inspection times, the change task, and the rapid response selection task. Quarterly Journal of Experimental Psychology, 54A, 1031-1048. Cerca con Google

Rottenstreich, Y., & Kivetz, R. (2006). On decision making without likelihood judgment. Organizational Behavior and Human Decision Processes, 101, 74-88. Cerca con Google

Schlottmann, A. (2001). Children’s probability intuitions: Understanding the expected value of complex gambles. Child Development, 72, 103–122. Cerca con Google

Schlottmann, A., & Anderson, N. H. (1994). Children's judgements of expected value. Developmental Psychology, 30, 56-66. Cerca con Google

Schlottmann, A., & Christoforou, M. (2005). Why are young children so good at expected value judgment? Biennial Meetings of the Society for Research in Child Development. Atlanta, Georgia, USA. Cerca con Google

Schneider, W., Eschman, A., & Zuccolotto, A. (2002). Prime user’s guide. Pittsburgh, PA: Psychology Software Tools, Inc. Cerca con Google

Schwartz, L. M., Woloshin, S., Black, W. C., & Welch, H. G. (1997). The role of numeracy in understanding the benefit of screening mammography. Annals of Internal Medicine, 127, 966-972. Cerca con Google

Seligman, M. E. P., & Kahana, M. (2009). Unpacking intuition: a conjecture. Perspectives on Psychological Science, 4, 399–402. Cerca con Google

Shallice, T., & Burgess, P. W. (1993). Supervisory control of thought and action. In A. D. Baddeley & L. Weiskrantz (Eds.), Attention: Selection, awareness, and control: A tribute to Donald Broadbent (pp. 171 – 187). Oxford: Oxford University Press. Cerca con Google

Sheridan, S. L., & Pignone, M. (2002). Numeracy and the medical students’ ability to interpret data. Effective Clinical Practice, 5, 35–40. Cerca con Google

Shiffrin, R. M., & Schneider, W. (1977) Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84, 127–90. Cerca con Google

Shiloh, S., Salton, E., & Sharabi, D. (2002). Individual differences in rational and intuitive thinking styles as predictors of heuristic responses and framing effects. Personality and Individual Differences, 32, 415-429. Cerca con Google

Siegler, R. S. (1981). Developmental sequences within and between concepts. Society for Research in Child Development Monographs, 46. Cerca con Google

Siegler, R. S. (1996). Emerging minds: The process of change in children’s thinking. New York: Oxford University Press. Cerca con Google

Siegler, R. S., & Chen, Z. (2002). Development of rules and strategies: balancing the old and the new. Journal of Experimental Child Psychology, 81, 446-457. Cerca con Google

Singer, J. A., Kohn, A. S., & Resnick, L. B. (1997). Knowing about proportions in different contexts. In: T. Nunes, & P. Bryant. (Eds.). Learning and teaching mathematics. East Sussex, UK: Psychology Press, 115-132. Cerca con Google

Sladek, R. M., Bond, M. J., & Phillips, P. A. (2010). Age and gender differences in preferences for rational and experiential thinking. Personality and Individual Differences, 49, 907-911. Cerca con Google

Sloman S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3-22. Cerca con Google

Smith, E., & DeCoster, J. (2000). Dual-process models in social and cognitive psychology: Conceptual integration and links to underlying memory systems. Personality & Social Psychology Review, 4, 108-131. Cerca con Google

Smith, S. M., & Levin, I. P. (1996). Need for cognition and choice framing effects. Journal of Behavioral Decision Making, 9, 283–290. Cerca con Google

Stanovich, K. E, & West., R. F. (2008). On the relative independence of thinking biases and cognitive ability. Journal of Personality and Social Psychology, 94, 672-695. Cerca con Google

Stanovich, K. E. (1999). Who is rational? Studies of individual differences in reasoning. Hillsdale, NJ: Erlbaum. Cerca con Google

Stanovich, K. E. (2004). The robot’s rebellion: Finding meaning in the age of Darwin. Chicago, IL: University of Chicago Press. Cerca con Google

Stanovich, K. E., & West, R. F. (1997). Reasoning independently of prior belief and individual differences in actively open-minded thinking. Journal of Educational Psychology, 89, 342-357. Cerca con Google

Stanovich, K. E., & West, R. F. (1998a). Individual differences in rational thought. Journal of Experimental Psychology: General, 127, 161-188. Cerca con Google

Stanovich, K. E., & West, R. F. (1998b). Individual differences in framing and conjunction effects. Thinking and Reasoning, 4, 289–317. Cerca con Google

Stanovich, K. E., & West, R. F. (1999) Discrepancies between normative and descriptive models of decision making and the understanding/acceptance principle. Cognitive Psychology 38, 349–85. Cerca con Google

Stanovich, K. E., & West, R. F. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23, 645–726. Cerca con Google

Stanovich, K. E., & West, R. F. (2007). Natural myside bias is independent of cognitive ability. Thinking & Reasoning, 13, 225-247. Cerca con Google

Stanovich, K. E., Toplak, M. E., & West, R. F. (2008). The development of rational thought: a taxonomy of heuristics and biases. Advances in Child Development and Behavior, 251-285. Cerca con Google

Stavy, R., & Tirosh, D. (2000). How students (mis-)understand science and mathematics: Intuitive rules. New York: Teachers College Press. Cerca con Google

Stavy, R., Goel, V., Critchley, H., & Dolan, R. (2006). Intuitive interference in quantitative reasoning. Brain Research, 1073-1074, 383-388. Cerca con Google

Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78–106. Cerca con Google

Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personal & Social Psychology Review, 8, 220-247. Cerca con Google

Subbotsky, E. V. (1990). Phenomenal and rational perception of some object relations by preschoolers. Soviet Psychology, 28, 5–24. Cerca con Google

Swets, J. A., Dawes, R. M., & Monahan, J. (2000). Psychological science can improve diagnostic decision. Psychological Science in the Public Interest, 1, 1-26. Cerca con Google

Tirosh, D., & Stavy, R. (1999). Intuitive rules: a way to explain and predict students’ reasoning. Educational Studies in Mathematics, 38, 51-66. Cerca con Google

Toates, F. (2006). A model of the hierarchy of behaviour, cognition and consciousness. Conscious Cognition, 15, 75-118. Cerca con Google

Toplak, M., Liu, E., Macpherson, R., Toneatto, T., & Stanovich, K. E. (2007). The reasoning skills and thinking dispositions of problem gamblers: A dual-process taxonomy. Journal of Behavioral Decision Making, 20, 103–124. Cerca con Google

Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5, 207–232. Cerca con Google

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131. Cerca con Google

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453-458. Cerca con Google

Tversky, A., & Kahneman, D. (1983). Extension versus intuititve reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90, 293-315. Cerca con Google

Tversky, A., & Kahneman, D. (1986). Rational choice and the framing of decisions. Journal of Business, 59, 252-278. Cerca con Google

Wagenmakers, E.J., & Waldorp, L. (Eds.) (2006). Model selection: theoretical developments and applications [Special section]. Journal of Mathematical Psychology, 50, 99-100. Cerca con Google

Wason, P. C. (1966). Reasoning. In B. Foss (Ed.), New horizons in psychology (pp. 135–151). Harmonsworth, England: Penguin. Cerca con Google

Wason, P. C., & Evans, J. St. B. T. (1975). Dual processes in reasoning? Cognition, 3, 141–154. Cerca con Google

Weber, E. U., & Johnson, E. (2009). Mindful judgment and decision making. Annual Review of Psychology, 60, 53-85. Cerca con Google

West, R. F., Toplak, M. E., & Stanovich, K. E. (2008). Heuristics and biases as measures of critical thinking: associations with cognitive ability and thinking dispositions. Journal of Educational Psychology, 100, 930-941. Cerca con Google

Wheeler, P., & Hyland, M. E. (2005). Cognitive style predicts use of CAM and attitude to CAM. Focus on Alternative and Complementary Therapies, 10 (Suppl. 1), 56. Cerca con Google

Wilkening, E, & Anderson, N. H. ( 1991 ). Representation and diagnosis of knowledge structures in developmental psychology. In N. H. Anderson (Ed.), Contributions to information integration theory. Vol. III: Developmental (pp. 46-80). Hillsdale, NJ: Erlbaum. Cerca con Google

Wilkinson, A. C. (1982). Theoretical and methodological analysis of partial knowledge. Developmental Review, 2, 274-304. Cerca con Google

Wilson, T. D. (2002). Strangers to ourselves. Cambridge, Mass.: Belknap Press. Cerca con Google

Wilson, T. D., & Schooler, J. W. (1991). Thinking too much: introspection can reduce the quality of preferences and decisions. Journal of Personality and Social Psychology, 60, 181–192. Cerca con Google

Winer, G. A., Craig, R. K., & Weinbaum, E. (1992) Adults failure on misleading weight-conservation tests – A developmental analysis. Developmental Psychology, 28, 109–20. Cerca con Google

Wolfe, C. R., & Reyna, V. F. (2009). Semantic coherence and fallacies in estimating joint probabilities. Journal of Behavioral Decision Making, 23, 203-223. Cerca con Google

Yamigishi, K. (1997). When a 12.86% mortality is more dangerous than 24.14%: Implications for risk communication. Applied Cognitive Psychology, 11, 495–506. Cerca con Google

Yee, T. W., & Mackenzie, M. (2002). Vector generalized additive models in plant ecology. Ecological Modeling, 157, 141-146. Cerca con Google

Yost, P. A., Siegel, A. E., & Andrews, J. M. (1962). Nonverbal probability judgments by young children. Child Development, 33, 769-780. Cerca con Google

Zikmund-Fisher, B. J., Smith, D. M., Ubel, P. A., & Fagerlin, A. (2007). Validation of the Subjective Numeracy Scale (SNS): effects of low numeracy on comprehension of risk communications and utility elicitations. Medical Decision Making, 27, 663-671. Cerca con Google

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