Some research with human participants has shown that the choice of a smaller-sooner reinforcer (SS) over a larger-later reinforcer (LL) is more frequent in aversive than non-aversive contexts (e.g., presence versus absence of response-independent intense noise). Although there is evidence that this effect could be reproduced in rats (e.g., response-independent noise disrupts rats’ performance on schedules of reinforcement), no explicit attempt has been reported to date. The present study tested the generality of the disruptive effect of aversive contexts in rats’ impulsive choice. To emulate the procedures implemented with humans, response-independent (Random-Time 60 s) mild-intensity footshocks (.25 mA) were incorporated into a systematic replication of Green and Estle’s (2003) task designed to study preference reversal phenomena (i.e., SS preference changes to LL with the addition of delays before both the SS and LL alternatives). In doing so, we explored the effects of an aversive context on preference reversal, which also have not been reported to date. Male Wistar rats (16) were exposed to three different conditions; eight of them experienced shocks throughout the study. During an initial delay configuration condition (SS = 2 pellets after 0.5-s; LL = 4 pellets after 6 s), responding of non-shocked rats showed an increase from indifference (∼ 50 % LL) towards preference for the LL option (∼ 75 % or higher LL responses), whereas responding of shocked rats did not deviate from indifference. Next, delays were added to the LL reinforcer until SS preference was individually established (+6 s, +9 s, +15 s, etc.). The behavior of non-shocked rats seemed more affected by the added delays, e.g., they reached SS preference with less added delays. Preference-reversal conditions consisted of adding 5-s, 15-s, and 25-s delays to both SS and LL alternatives. Shocked rats showed a more robust and consistent preference reversal effect than non-shocked rats. Research on manipulations that reduce impulsive choice suggests that similar processes could explain the disruptive effects of aversive contexts and the effects of interventions; namely, aversiveness of delays and discrimination of contingent relations between temporally distant events. The results of the present study are discussed in that framework, focusing on covariations between rats’ choice patterns across the different delay configurations and the distribution of shocks pre- and post- reinforcement delivery.
This study examined the effects of stimulus continuity and response requirements on pigeon choices between post-reinforcer delays (from 2 s to 8 s) using concurrent-chains schedules with FR 1 schedules arranged for the choice phase. In Experiment 1, using seven pigeons, the effect of stimulus continuity, the presentation of the same stimulus (background color of the computer screen) during the post-reinforcer delay period as in the pre-reinforcer delay period, was examined. In Experiment 2, the effect of stimulus continuity was examined under the conditions where a response was required (FR 1) to initiate the post-reinforcer delay using eight pigeons. The experimental results indicated that when the same stimulus as in the pre-reinforcer delay was presented continuously during the post-reinforcer delay and a response was required to start the post-reinforcer delay, the subjects showed relatively high sensitivity to differences between post-reinforcer delays. The implications of the results are discussed from a new perspective for the analysis of self-control choices.
As the main force of higher education, ensuring the learning status and quality of college students is undoubtedly an important task in the education industry. Analyzing their learning motivation can provide a good understanding of their learning status. Especially in the new educational environment supported by multimedia technology, efficient and convenient learning channels can eliminate students' concerns about educational facilities and instead strengthen the analysis of learning motivation in other aspects. As part of our comprehensive study of learning motivation, we draw on established learning theories, such as reinforcement theory, associative learning, and self-determination theory. Applying such learning theories encourages positive reinforcement, establishes constructive relationships with learning, and nurtures competence and autonomy. This article believed that using machine learning models to predict students' grades or behaviours and analyze their learning motivation is a good approach. Moreover, this article also tested the prediction accuracy by setting different improved random forest model runs, and concluded that the more runs, the higher the accuracy. Especially when the runs reached 100, the accuracy reached 99.98 %.