Positive impact of sleep on recall of multiplication facts

This study tested the hypothesis that learning complex multiplication problems (e.g. 8 x 23 = 184) prior to sleep would benefit recall in adult participants compared with learning the problems prior to a period of wakefulness. Method: This study used a within-participant design where all participants learnt complex multiplication problems in two conditions separated by one week. In one condition learning was before bed (sleep learning condition) and in the other condition learning was in the morning (wake learning condition). In each condition recall was tested approximately 10.5 hours later. Data were collected online from 77 participants. Results: In the subset of the sample with ≥60% accuracy at the initial learning session (n= 37), the sleep learning condition participants had better recall compared with the wake learning condition. The equated to a moderate effect size. Regardless of initial levels of learning (n= 70) the same beneficial effect of sleep on recall was found with a small effect size. Conclusions: This study has identified a beneficial effect of learning prior to sleep on recall of complex multiplication problems compared with learning these problems during the daytime. Future research should explore whether similar effects are observed with children learning simple multiplication facts.</p

The Cost of Multiple Representations: Experiment 3 data and scripts

Raw data and analysis scripts associated with Experiment 3 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations"

The Cost of Multiple Representations: Preregistrations

Preregistration files from AsPredicted for the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations". Originals at:https://aspredicted.org/8wp6w.pdfhttps://aspredicted.org/tx92d.pdf</div

The Cost of Multiple Representations: Experiment 2 PsychoPy materials

PsychoPy scripts associated with Experiment 2 in the paper "The Cost of Multiple Representations: Learning Number Symbols with Abstract and Concrete Representations".</div

Data and stimuli for "Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement"

<p>This is the full data set and stimuli for Clayton, S., Gilmore, C., & Inglis, M. (in press). Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement. Acta Psychologica.</p> <p>The excel columns in the data file refer to the following:</p> <p>Participant: Participant identifier number</p> <p>Trialorder: The order the trials were presented for each participant (random order)</p> <p>Accuracy: 1= correct, 0 = incorrect</p> <p>Response time: Response time in milliseconds</p> <p>ImageFile: The file name of the dot array image</p> <p>GebuisImageType: This is the category of the trial in terms of convex hull congruency and cumulative surface area congruency, as generated by the Gebuis & Reynvoet (2011) script.</p> <p>1 & 8= Convex hull congruent, cumulative surface area congruent; 2 & 7= Convex hull incongruent, cumulative surface area incongruent; 3 & 6= Convex hull congruent, cumulative surface area incongruent; 4 & 5= Convex hull incongruent, cumulative surface area congruent.</p> <p>TrialNumber: The number of the trial (not in order of presentation)</p> <p>Procotol: The method used to generate the dots. Gebuis= Gebuis, T., & Reynvoet, B. (2011). Generating nonsymbolic number stimuli. Behavior Research Methods, 43, 981–986, Panamath= Panamath software, Halberda, J., Mazzocco, M., & Feigenson, L. (2008). Individual differences in nonverbal number acuity predict maths achievement. Nature, 455, 665-668.</p> <p>Time: Participants completed each trial twice. Time1= first presentation of trials, Time2= second presentation of trials.</p> <p>Numerosity1_Left: The number of dots in the left array.</p> <p>Numerosuty2_Right: The number of dots in the right array.</p> <p>Left:RightNumerosity: The ratio between the number of dots in each of the arrays in each trial (number of dots on the left / number of dots on the right)</p> <p>ConvexHull1_Left: The size of the convex hull of the left array.</p> <p>ConvexHull2_Right: The size of the convex hull of the right array,</p> <p>Left:RightConvexHull: The ratio between the convex hull of arrays in each trial (size of left convex hull / size of right convex hull)</p> <p>pixels1_Left: The number of pixels in the left array.</p> <p>pixels2_Right: The number of pixels in the right array.</p> <p>Left:RightPixels: The ratio between the number of pixels in each of the arrays in each trial (number of pixels in left array / number of pixels in right array).</p> <p>Dot size1_Left: Average size of dots in the left array (pixels / numerosity)</p> <p>Dotsize2_Right: Average size of dots in the right array (pixels / numerosity)</p> <p>Left:RightDotSize: The ratio between the average size of the dots in each array in each trial (avergae dot size of left array / average dot size of right array).</p

Full Data set for "Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement"

<p>This is the full data set for Clayton, S., Gilmore, C., & Inglis, M. (in press). Dot comparison stimuli are not all alike: The effect of different visual controls on ANS measurement. <em>Acta Psychologica. </em></p> <p><em><br></em></p> <p>The excel columns refer to the following:</p> <p>Participant: Participant identifier number</p> <p>Trialorder: The order the trials were presented for each participant (random order)</p> <p>Accuracy: 1= correct, 0 = incorrect</p> <p>Response time: Response time in milliseconds </p> <p>ImageFile: The file name of the dot array image </p> <p>GebuisImageType: This is the category of the trial in terms of convex hull congruency and cumulative surface area congruency, as generated by the Gebuis & Reynvoet (2011) script. </p> <p>1 & 8= Convex hull congruent, cumulative surface area congruent; 2 & 7= Convex hull incongruent, cumulative surface area incongruent; 3 & 6= Convex hull congruent, cumulative surface area incongruent; 4 & 5= Convex hull incongruent, cumulative surface area congruent.</p> <p>TrialNumber: The number of the trial (not in order of presentation)</p> <p>Procotol: The method used to generate the dots. Gebuis= Gebuis, T., & Reynvoet, B. (2011). Generating nonsymbolic number stimuli. Behavior Research Methods, 43, 981–986, Panamath= Panamath software, Halberda, J., Mazzocco, M., & Feigenson, L. (2008). Individual differences in nonverbal number acuity predict maths achievement. Nature, 455, 665-668.</p> <p>Time: Participants completed each trial twice. Time1= first presentation of trials, Time2= second presentation of trials.</p> <p>Numerosity1_Left: The number of dots in the left array.</p> <p>Numerosuty2_Right: The number of dots in the right array.</p> <p>Left:RightNumerosity: The ratio between the number of dots in each of the arrays in each trial (number of dots on the left / number of dots on the right)</p> <p>ConvexHull1_Left: The size of the convex hull of the left array. </p> <p>ConvexHull2_Right: The size of the convex hull of the right array,</p> <p>Left:RightConvexHull: The ratio between the convex hull of arrays in each trial (size of left convex hull / size of right convex hull)</p> <p>pixels1_Left: The number of pixels in the left array.</p> <p>pixels2_Right: The number of pixels in the right array.</p> <p>Left:RightPixels: The ratio between the number of pixels in each of the arrays in each trial (number of pixels in left array / number of pixels in right array). </p> <p>Dot size1_Left: Average size of dots in the left array (pixels / numerosity)</p> <p>Dotsize2_Right: Average size of dots in the right array (pixels / numerosity)</p> <p>Left:RightDotSize: The ratio between the average size of the dots in each array in each trial (avergae dot size of left array / average dot size of right array).</p

The ecological validity of picture SFON tasks

Research has identified that children differ in the extent to which they spontaneously focus on numerical aspects of the environment (Spontaneous Focusing on Numerosity, SFON) and that this correlates with their mathematics achievement. It is assumed that the mechanism underpinning this relationship is that children who spontaneously focus on numerical features of their environment will experience more self-initiated practice with number concepts. We explored this mechanism by investigating whether 4- to 5-year-old children’s verbal SFON scores on a picture description task related to their spontaneous focusing on number while engaged in play activities with their parent. We found that the scores derived from a picture description task were strongly correlated with the scores derived from the play sessions, rs = .638, 95% CI [.433, .781], providing evidence for this mechanism. We further investigated the role that verbal abilities may play in children’s performance on the picture description task, finding that general verbal abilities were not associated with verbal SFON scores. These results contribute to our understanding of the role played by verbal SFON tendencies in explaining differences in numerical development, and demonstrate the ecological validity of SFON picture tasks.</p

The ecological validity of picture SFON tasks

Research has identified that children differ in the extent to which they spontaneously focus on numerical aspects of the environment (Spontaneous Focusing on Numerosity, SFON) and that this correlates with their mathematics achievement. It is assumed that the mechanism underpinning this relationship is that children who spontaneously focus on numerical features of their environment will experience more self-initiated practice with number concepts. We explored this mechanism by investigating whether 4- to 5-year-old children’s verbal SFON scores on a picture description task related to their spontaneous focusing on number while engaged in play activities with their parent. We found that the scores derived from a picture description task were strongly correlated with the scores derived from the play sessions, rs = .638, 95% CI [.433, .781], providing evidence for this mechanism. We further investigated the role that verbal abilities may play in children’s performance on the picture description task, finding that general verbal abilities were not associated with verbal SFON scores. These results contribute to our understanding of the role played by verbal SFON tendencies in explaining differences in numerical development, and demonstrate the ecological validity of SFON picture tasks.</p

CongandAge_Norris_et_al.2015 – Supplemental material for The measurement of approximate number system acuity across the lifespan is compromised by congruency effects

<p>Supplemental material, CongandAge_Norris_et_al.2015 for The measurement of approximate number system acuity across the lifespan is compromised by congruency effects by Jade Eloise Norris, Sarah Clayton, Camilla Gilmore, Matthew Inglis and Julie Castronovo in Quarterly Journal of Experimental Psychology</p

Mean accuracy (%) and back-transformed mean RT data (ms) with 95% confidence intervals (CI) for the secondary task by domain, dual task load, age group and strategy.

<p>Mean accuracy (%) and back-transformed mean RT data (ms) with 95% confidence intervals (CI) for the secondary task by domain, dual task load, age group and strategy.</p