How to allocate study time is an important decision-making problem learners face. Research on this problem can help improve the learning performance of learners and provide guidance for teaching activities. This research aimed to explore the potential of anchors (prior information that may influence individual decision-making and judgment under uncertainty) as clues for study time allocation and examine the effectiveness of study time allocation under the influence of anchors. Sixty-two Chinese university students (M_age = 21.21, SD = 1.74; 44 females) studied 20 word pairs under self-paced learning instructions. These instructions either set a high anchor (i.e., the typical participant spent 15 s learning each pair) or a low anchor (i.e., the typical participant spent 5 s learning each pair) for study time. After a brief distraction phase, participants took a cued recall test. The results showed that the higher the anchor value, the longer the corresponding study time, and the longer the study time, the better the memory performance. These results reveal that there is both an anchoring effect and a labor-and-gain effect in self-paced study time allocation. This study extends the range of observable anchoring effects and provides important information on allocating study time effectively.

Background: Although dot-probe paradigms have been widely used in previous studies to investigate the attentional bias of perfectionists, the exact characteristics of this bias are still unclear. Methods: In this study, eye-tracking technology was used to compare the attentional patterns of high perfectionists (HP) and low perfectionists (LP). The HP and LP groups (n = 39 vs 34) completed a visual attention task in which they observed perfect vs imperfect picture pairs, during which their eye movements (EMs) were recorded automatically using an EM tracking system. Results: Both the HP and LP groups showed an overall attentional bias toward imperfect pictures, as indicated by the criteria of initial visual attention orientation and attentional maintenance. There were no significant differences between the HP and LP groups during the early and middle phases of attention: both groups exhibited a longer total fixation duration on imperfect pictures than on perfect pictures. However, during the late phase of attention, the participants in the HP group diverted their attention away from the imperfect pictures and began to pay more attention to the perfect pictures. By contrast, the participants in the LP group consistently exhibited longer fixation times for imperfect pictures than the HP group during the entire duration of the stimulus. Conclusion: These findings indicate that the participants in the HP group tended to avoid imperfect stimuli during the late phase of attention; this may indicate that avoidance plays an important role in maintaining perfectionism. This study also shows that eye-tracking is a useful methodology for measuring the attentional biases of perfectionists.

Remembering to perform an action when a specific event occurs is referred to as Event-Based Prospective Memory (EBPM). This study investigated how EBPM performance is affected by task duration by having university students (n=223) perform an EBPM task that was embedded within an ongoing computer-based color-matching task. For this experiment, we separated the overall task’s duration into the filler task duration and the ongoing task duration. The filler task duration is the length of time between the intention and the beginning of the ongoing task, and the ongoing task duration is the length of time between the beginning of the ongoing task and the appearance of the first Prospective Memory (PM) cue. The filler task duration and ongoing task duration were further divided into 3 levels: 3 minutes, 6 minutes, and 9 minutes. Two factors were then orthogonally manipulated between-subjects using a Multinomial Processing Tree (MPT) model to separate the effects of different task durations on the two EBPM components. A mediation model was then created to verify whether task duration influences EBPM via self-reminding or discrimination. The results reveal three points. (1) Lengthening the duration of ongoing tasks had a negative effect on EBPM performance while lengthening the duration of the filler task had no significant effect on it. (2) As the filler task was lengthened, both the prospective and retrospective components show a decreasing and then increasing trend. Also, when the ongoing task duration was lengthened, the prospective component decreased while the retrospective component significantly increased. (3) The mediating effect of discrimination between the task duration and EBPM performance was significant. We concluded that different task durations influence EBPM performance through different components with discrimination being the mediator between task duration and EBPM performance.

Value-directed remembering involves two key mechanisms: automatic processing and strategic processing. Automatic processing relies on the brain’s reward system and is associated with midbrain dopaminergic pathways and medial temporal-lobe activity. Strategic processing, in contrast, involves conscious, effortful encoding strategies and engages semantic-processing regions and executive control systems. This article reviews the developmental trajectory of value-directed remembering from childhood to old age through the lens of a dual-process model. Children and adolescents primarily rely on automatic processing; adults are capable of flexibly switching between the two processes; older adults tend to rely more on strategic processing. These findings reflect the dynamic developmental changes in the brain’s reward and executive-control systems. Future research should further investigate the synergistic interplay between dual-processing mechanisms, the moderating role of cultural contexts, and the efficacy of intervention strategies to deepen our understanding of the developmental trajectory of value-directed memory.

This study investigated how encoding strength and consolidation shape proactive interference (PI) in associative memory. Using a Modified Modified Free Recall (MMFR) paradigm, participants studied overlapping (A-B, A-C) and non-overlapping (E-F, G-H) pairs. The encoding strength of List 1 was manipulated (one vs. three study repetitions), while List 2 was held constant. Cued recall was tested immediately and after a 24-h delay. Results showed that increasing List 1’s encoding strength enhanced overall recall for both overlapping and non-overlapping pairs, indicating more effective learning, but did not alter the magnitude of PI. Instead, PI was strongly modulated by retention interval. At immediate test, robust PI emerged across conditions, reflecting cue-based retrieval competition. After a 24-h delay, PI was reduced or absent when List 1 was weakly encoded but persisted in attenuated form when List 1 was strongly encoded, suggesting differential consolidation trajectories for overlapping and non-overlapping associations. Co-retrieval analyses further revealed reliable associative dependency between B and C across all conditions, consistent with representational linkages that promote cooperative retrieval. These findings highlight the dual influence of cue overlap: at the representational level, overlapping pairs form integrated structures that foster co-retrieval, whereas at the retrieval-processing level, cue overload induces competition and PI. Taken together, the results indicate that although initial encoding strength enhances overall recall of List 2, the persistence of proactive interference is influenced by consolidation processes.

Previous research has shown a clear self-reference effect in our memory. However, the question arises as to whether this effect could extend to higher cognitive domains such as metamemory. Thus, this study examined the effects of different encoding types on judgments of learning (JOLs) and explored the role of beliefs in this process. A one-way (encoding type: semantic, self-referential) within-participants design was employed in Experiment 1, which found no self-reference effect in JOLs. In Experiment 2, we manipulated participants’ beliefs to explore their effect on JOLs under different encoding strategies. The results showed that learners’ metamemory beliefs about encoding types influence JOLs. Learners who believed that self-referential and semantic encoding had the same memory effect tended to give equal JOLs to both words. However, learners who believed that self-referential encoding had a better memory effect than semantic encoding gave higher JOLs to self-referentially encoded words. The conclusions are as follows: There is no self-reference effect in JOLs, but learners’ metamemory beliefs about encoding types influence JOLs.