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Fig 1.

Learning schedule during 2011–2012 for all lists, where labels in bold indicate when each of the lists 1 to 10 was first learned for each retention interval.

Relearning times are not shown but can be derived by adding the retention interval (e.g., 6 days).

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Fig 1 Expand

Table 1.

Average number of repetitions until once correct.

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Table 1 Expand

Table 2.

Time spent learning (session S1) and relearning (session S2) for each list with savings (Q) by Dros.

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Table 2 Expand

Fig 2.

Four loglog graphs with savings as a function of retention interval with fitted power function curves and curves with best fitting power functions with boost at 1 day (see text for an explanation).

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Fig 2 Expand

Fig 3.

Four log graphs with savings as a function of retention interval with best-fitting Memory Chain Model retention functions (see text for an explanation).

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Fig 3 Expand

Fig 4.

Normalized savings scores as a function of retention interval on a logarithmic scale, rescaled so the first data point is 1.0 for all curves.

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Fig 4 Expand

Table 3.

Savings for Ebbinghaus ([8], p. 56, see Note 1 for the comments on the intervals 20 min, 1 hour and 9 hours), Mack and Seitz [21], and Dros (this paper).

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Table 3 Expand

Fig 5.

Learning time per list as a function of day of experiment with a fitted straight line.

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Fig 5 Expand

Fig 6.

Serial position for correct relearning scores for each retention interval and for the average of all retention intervals (see text for an explanation).

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Fig 6 Expand

Fig 7.

Proportion correct as a function of retention interval on a logarithmic scale.

(a) Proportion correct, averaged over all serial positions, shown with Dros’ savings scores for comparison. (b) Proportion correct curves for different groups of serial positions and for the average over all 13 positions.

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Fig 7 Expand

Table 4.

Fits of two equations proposed by Ebbinghaus in 1880 and 1885 to data from his own study and from three replication studies.

See text for the meaning of the parameters. SSD is the sum of squared differences between data and fitted curve, R2 is proportion variance explained, and AIC is the Akaike Information Criterion. To stay close to Ebbinghaus’ own estimates, the parameters are fitted for time expressed in minutes.

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Table 4 Expand

Table 5.

Fits of a number of equations to data from Ebbinghaus and replication studies.

See text for the meaning of the parameters. SSD is the sum of squared differences between data and fitted curve, R2 is proportion variance explained, and AIC is the Akaike Information Criterion. The parameters are fitted for time expressed in seconds.

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Table 5 Expand