The ability to prioritize learning some information over others when that information is considered important or valuable is known as value-directed remembering. In these experiments, we investigate how value influences different aspects of memory, including item memory (memory for the to-be-learned materials) and context memory (memory for peripheral details that occurred when studying items) to get a better understanding of how people prioritize learning information. In this investigation, participants encoded words associated with a range of values (binned into higher, medium, and lower value in Experiment 1, and into higher and lower value in Experiment 2) for a subsequent memory test that measured item memory (Is this item old or new?) as well as both objective context memory (memory for an objectively verifiable contextual detail: In which voice was this item spoken?) and subjective context memory (How many visual, auditory, and extraneous thoughts/feelings can you remember associated with this item?). Results indicated that value influenced item memory but had no effect on objective context memory in both Experiments. In Experiment 2, results showed better subjective context memory for multiple episodic details for higher-value relative to lower-value materials. Overall, these findings suggest that value has a strong influence over some aspects of memory, but not others. This work gives a richer understanding of how people prioritize learning more important over less important information.
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Because we were interested in examining the effects of value and order (value before, value after) on memory, we saw it as essential to include an orienting task to induce participant attention to all stimuli on a trial-by-trial basis. Without such a task, it is possible that participants could elect to simply ignore lower-value stimuli in the value before condition, as a way to improve memory for higher value items, which would impede our ability to truly measure memory effects in this experiment. Given this possibility, we chose to use an orienting task (syllable task) to make it more likely participants were attending to all trials.
In designing this experiment, we considered expanding our objective measures to include other objective contextual details (font type, font color); however, we elected against this procedure because we did not want the retrieval phase to be unduly burdensome to the participants. Given that participants were already making many retrieval judgments for each retrieval trial, we decided to focus on only one objective context measure (source memory).
Since participants were using a range of 1 (no details) to 3 (a lot of details) for MCQ ratings, the mean scores for each subjective contextual detail (visual, auditory, thoughts, and feelings) should be interpreted with this range in mind. For instance, if the mean rating for visual details is around 2, this translates into participants subjectively reporting they can retrieve a few visual details for a given trial type. In this example, this could translate to participants remembering a few visual details (like font color), but not other visual details.
Although our stimuli had a valence component (positive, negative adjectives), we did not design this experiment to look at the factor of valence in our primary ANOVA analyses, and thus Experiment 1 was not powered to run analyses including valence. However, to evaluate whether valence affected memory data, we performed a paired-samples t test comparing item memory for valence. Results showed no significance difference for positive words (M = 0.45, SD = 0.11) relative to negative words (M = 0.45, SD = 0.11), t(71) = −.33, p < .74, d = −.04.
We also calculated item memory using the signal detection measure d′, which takes into account both item hits as well as item false alarms (Snodgrass & Corwin, 1988). We entered d′ scores into a 3 (value: higher, medium, lower) × 2 (order: value before, value after) ANOVA, as in our primary analysis. Results of this analysis fully replicated our primary analysis (based on hits − false alarms): we observed a value effect, F(2, 142) = 6.37, p = .005, ηp2 = .11, but no effect of order, F(1, 71) = 0.12, p = .78, ηp2 = .00, or interaction, F(2, 142) = 0.45, p = .64, ηp2 = .01.
The model employed an effect coding scheme for order, which allowed us to set the value-before trials as the reference group with which to compare with value-after trials. This effect coding scheme allows for easier interpretation of any interaction effects, compared to dummy/treatment coding (Singmann & Kellen, 2019).
Because we had a continuous range of values (1–8) in our stimuli, we ran an additional analysis to assess whether objective context memory improved as value increased. To do so, we conducted a logistic regression. Value (1–8) and order (value before, value after) were included as predictors. Results showed that memory did not differ as a function of value, χ2(1) = .37, b = .008, p = .54, or order, χ2(1) = .09, p = .76. In a subsequent model, we included an interaction to assess whether value and order jointly affected performance. The interaction term was not significant, χ2(7) = 3.71, p = .81, and the main effects remained nonsignificant.
Because performance on our objective context measure was close to chance, we performed an analysis comparing objective context memory with chance-level performance. Results showed that only trials associated with medium-value items were significantly above chance, ts > 1.75, ps < .05.
In Experiment 2, we chose to associate items with four different values (1–4). Although past VDR studies using few values to associate with items have used values at extreme ends of a scale, such as using only a few higher values (i.e., 7 and 9) and a few lower values (i.e., 1 and 3; Elliott et al., 2020), we elected not to use values at the extreme ends of a value range, because we wanted to replicate our use a continuous range of values as we did in Experiment 1. Further, because some of our ancillary analyses treat value as a continuous variable (logistic regression), using a continuous range of values allows us to perform analogous analyses in Experiment 2, which allows for more direct comparison to the effects identified in Experiment 1.
We also performed a logistic regression on the objective context memory measure, as in Experiment 1. Results showed that memory did not differ as a function of value, χ2(1) = .04, b = −.005, p = .84, or order, χ2(1) = 1.86, p = .17. In a subsequent model, we included an interaction to assess whether value and order affected objective context memory. The interaction term was not significant, χ2(3) = .33, p = .95, and the main effects remained nonsignificant.
We performed an analysis comparing objective context memory with chance level performance. Results showed that only value before trials (higher, lower) were above chance, ts > 1.93, ps < .05.
Because we had both positive and negative stimuli in this data, we ran additional 2 (value: higher, lower) × 2 (order: value before, value after) × 2 (valence: positive, negative) ANOVAs for item, objective context, and subjective context memory (visual, auditory, thoughts and feelings). Results showed no significant effects of valence or valence interactions for item, objective context, and two of the subjective context details (visual, auditory), Fs < 2.60, ps > .11. There was a main effect of valence for thoughts and feelings, F(1, 76) = 5.66, p = .02, ηp2 = .09, however, which was driven by more subjective reported details for negative (M = 1.99, SE = .07) than positive items (M = 1.94, SE = .07).
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Villaseñor, J.J., Sklenar, A.M., Frankenstein, A.N. et al. Value-directed memory effects on item and context memory. Mem Cogn (2021). https://doi.org/10.3758/s13421-021-01153-6
- Value-directed remembering
- Item memory
- Source memory
- Context memory
- Memory characteristics questionnaire