The effects of self‐explaining when learning with text or diagrams

Self‐explaining is an effective metacognitive strategy that can help learners develop deeper understanding of the material they study. This experiment explored if the format of material (i.e., text or diagrams) influences the self‐explanation effect. Twenty subjects were presented with information about the human circulatory system and prompted to self‐explain; 10 received this information in text and 10 in diagrams. Results showed that students given diagrams performed significantly better on post‐tests than students given text. Diagrams students also generated significantly more self‐explanations that text students. Furthermore, the benefits of self‐explaining were much greater in the diagrams condition. To discover why diagrams can promote the self‐explanation effect, results are interpreted with reference to the multiple differences in the semantic, cognitive and affective properties of the texts and diagrams studied.     

BEHAVIORAL MOMENTUM IN THE TREATMENT OF NONCOMPLIANCE

Behavioral momentum refers to the tendency for behavior to persist following a change in environmental conditions. The greater the rate of reinforcement, the greater the behavioral momentum. The intervention for noncompliance consisted of issuing a sequence of commands with which the subject was very likely to comply (i.e., high-probability commands) immediately prior to issuing a low-probability command. In each of five experiments, the high-probability command sequence resulted in a “momentum” of compliant responding that persisted when a low-probability request was issued. Results showed the antecedent high-probability command sequence increased compliance and decreased compliance latency and task duration. “Momentum-like” effects were shown to be distinct from experimenter attention and to depend on the contiguity between the high-probability command sequence and the low-probability command.     

Typical delay determines waiting time on periodic-food schedules: Static and dynamic tests

Pigeons and other animals soon learn to wait (pause) after food delivery on periodic-food schedules before resuming the food-rewarded response. Under most conditions the steady-state duration of the average waiting time, t, is a linear function of the typical interfood interval. We describe three experiments designed to explore the limits of this process. In all experiments, t was associated with one key color and the subsequent food delay, T, with another. In the first experiment, we compared the relation between t (waiting time) and T (food delay) under two conditions: when T was held constant, and when T was an inverse function of t. The pigeons could maximize the rate of food delivery under the first condition by setting t to a consistently short value; optimal behavior under the second condition required a linear relation with unit slope between t and T. Despite this difference in optimal policy, the pigeons in both cases showed the same linear relation, with slope less than one, between t and T. This result was confirmed in a second parametric experiment that added a third condition, in which T + t was held constant. Linear waiting appears to be an obligatory rule for pigeons. In a third experiment we arranged for a multiplicative relation between t and T (positive feedback), and produced either very short or very long waiting times as predicted by a quasi-dynamic model in which waiting time is strongly determined by the just-preceding food delay.     

Time-place learning by pigeons, Columba livia

In each of two experiments, 2 pigeons received discrimination training in which food reinforcement for key pecking was conditional upon both spatial and temporal cues. In Experiment 1, food was available for periods of 30 s at each of three locations (pecking keys) during trials that lasted 90 s. In Experiment 2, food was available for periods of 15 min at each of four locations (pecking keys) during a 60-min trial. In both experiments, pigeons' key pecking was jointly controlled by the spatial and temporal cues. These data, and other recent experiments, suggest that animals learn relationships between temporal and spatial cues that predict stable patterns of food availability.     

Determination of a behavioral transfer function: White-noise analysis of session-to-session response-ratio dynamics on concurrent VI VI schedules

Six pigeons were exposed to concurrent variable-interval schedules in which the programmed reinforcer ratios changed from session to session according to a pseudorandom binary sequence. This procedure corresponded to the stochastic identification paradigm (“white-noise experiment”) of systems theory and enabled the relation between log response ratios in the current session and log reinforcer ratios in all previous sessions to be determined. Such dynamic relations are called linear transfer functions. Both nonparametric and parametric representations of these, in the form of “impulse-response functions,” were determined for each bird. The session-to-session response ratios resulting from the session-to-session pseudorandom binary variations in reinforcer ratios were well predicted by the impulse-response functions identified for each pigeon. The impulse-response functions were well fitted by a second-order dynamic model involving only two parameters: a time constant and a gain. The mean time constant was 0.67 sessions, implying that the effects of abrupt changes in log reinforcer ratios should be 96% complete within about five sessions. The mean gain was 0.53, which was surprisingly low inasmuch as it should equal the sensitivity to reinforcement ratio observed under steady-state conditions. The same six pigeons were subjected to a similar experiment 10 months following the first. Despite individual differences in impulse-response functions between birds within each experiment, the impulse-response functions determined from the two experiments were essentially the same.     

Fallacies

Fallacies are things people commit, and when they commit them they do something wrong. What kind of activities are people engaged in when they commit fallacies, and in what way are they doing something wrong? Many different things are called fallacies. The diversity of the use of the concept of a fallacy suggests that we are dealing with a family of cases not related by a common essence. However, we suggest a simple account of the nature of fallacies which encompasses them all, viz., the term “fallacy” is our most general term for criticizing any general procedure used for the fixation of beliefs that has an unacceptably high tendency to generate false or unfounded beliefs, relative to that method of fixing beliefs. Very different sorts of things called fallacies are examined in the light of this account, e.g., denying the antecedent, circular arguments, so-called informal fallacies, and propositions said to be fallacies. We do not provide a theory of fallacies. Still, on our account pretty much all of those things that have been called fallacies are fallacies, and they have been called fallacies for pretty much the same reasons.     

The interaction of stimulus and reinforcer control in complex temporal discrimination.

Six pigeons were trained in a discrete-trials signal-detection procedure to discriminate between a fixed-duration stimulus (5 s or 20 s) and a set of variable durations ranging from 2.5 s to 57.5 s in steps of 5 s. For each fixed-duration stimulus, the ratio of reinforcer frequencies contingent upon reporting the fixed versus the variable stimulus was systematically manipulated. Detection performance was well controlled by both the stimulus value and the reinforcer ratio. Both the discriminability between the fixed duration and the set of variable durations, and the discriminability between the fixed duration and each of the variable durations, were independent of the reinforcer-frequency ratio when discriminability was measured as log d. The sensitivity of response bias to reinforcement-ratio changes was independent of the value of the fixed duration, but was not independent of the discriminability of the variable durations from the fixed durations. Under current models, discriminability measures in complex temporal discrimination may be independent of biasing manipulations, but bias measures are not independent of stimulus values.     

Delayed temporal discrimination in pigeons: A comparison of two procedures

A within-subjects comparison was made of pigeons' performance on two temporal discrimination procedures that were signaled by differently colored keylight samples. During stimulus trials, a peck on the key displaying a slanted line was reinforced following short keylight samples, and a peck on the key displaying a horizontal line was reinforced following long keylight samples, regardless of the location of the stimuli on those two choice keys. During position trials, a peck on the left key was reinforced following short keylight samples and a peck on the right key was reinforced following long keylight samples, regardless of which line stimulus appeared on the correct key. Thus, on stimulus trials, the correct choice key could not be discriminated prior to the presentation of the test stimuli, whereas on position trials, the correct choice key could be discriminated during the presentation of the sample stimulus. During Phase 1, with a 0-s delay between sample and choice stimuli, discrimination learning was faster on position trials than on stimulus trials for all 4 birds. During Phase 2, 0-, 0.5-, and 1.0-s delays produced differential loss of stimulus control under the two tasks for 2 birds. Response patterns during the delay intervals provided some evidence for differential mediation of the two delayed discriminations. These between-task differences suggest that the same processes may not mediate performance in each.     

Behavioral contrast in fixed-interval components: effects of extinction-component duration.

Seven albino rats were exposed to a multiple schedule of reinforcement in which the two components (fixed interval and extinction) alternated such that a presentation of the extinction component followed each fixed-interval reinforcement. In baseline sessions, the duration of the extinction component was constant and always one-third of the fixed-interval value. Probe sessions contained a probe segment in which the duration of the extinction component was increased; the response rate in fixed-interval components during the probe segment was compared with the response rate in the segments preceding and following the probe. The effect of increasing the duration of the extinction component was studied under three values of fixed interval: 30 s, 120 s, and 18 s, in three successive conditions. Response rate within fixed intervals was a direct function of duration of the extinction component. Pausing at the beginning of the fixed interval decreased as extinction duration increased. These effects were larger and more consistent for the shorter fixed-interval values (18 s and 30 s). These results indicate a functional relation between relative component duration and responding. For the component providing more frequent reinforcement, this could be stated as an inverse relationship between relative component duration and response rate. This relation is similar to findings regarding the ratio of trial and intertrial duration in Pavlovian conditioning procedures, and suggests that behavioral contrast may be related to Pavlovian contingencies underlying the multiple schedule.