Correction of a Technical Error in the Golf Swing: Error Amplification Versus Direct Instruction

Performance errors drive motor learning for many tasks. The authors' aim was to determine which of two strategies, method of amplification of error (MAE) or direct instruction (DI), would be more beneficial for error correction during a full golfing swing with a driver. Thirty-four golfers were randomly assigned to one of three training conditions (MAE, DI, and control). Participants were tested in a practice session in which each golfer performed 7 pretraining trials, 6 training-intervention trials, and 7 posttraining trials; and a retention test after 1 week. An optoeletronic motion capture system was used to measure the kinematic parameters of each golfer's performance. Results showed that MAE is an effective strategy for correcting the technical errors leading to a rapid improvement in performance. These findings could have practical implications for sport psychology and physical education because, while practice is obviously necessary for improving learning, the efficacy of the learning process is essential in enhancing learners' motivation and sport enjoyment.     

The Religious Function of Jaina Philosophy:AnekāntavādaReconsidered

This paper considers the socio-religious rationale for the Jaina theory of the non-one-sided nature of reality (anekāntavāda). In doing so it rejects the received view thatanekāntavāda's exclusive function is to promote non-violence at the intellectual level. Instead it advances a model which emphasizes the way in whichanekāntavādasustains a real connection between karmic matter and the soul (jīva) and so maintains the rationale for identity defining ascetic practice. The social and religious dangers of one-sided (ekānta) views for the Jaina tradition are demonstrated by a consideration of the Digambara teacher Kundakunda's idiosyncratic use of the two truths model of reality.     

Challenges to the four-channel model of flow: Primary assumption of flow support the moderate challenging control channel

Flow theory postulates that the psychological state of flow emerging when one engages in activities where skill level and challenge are both high, results in ‘optimal’ subjective experiences relative to other psychological states, and is intrinsically motivated. The experience sampling method was used on a sample of college students to compare daily activities associated with flow (high skill, high challenge) to the psychological state of control (high skill, moderate challenge) in relation to the subjective experiences of enjoyment, happiness, intrinsic motivation, and cognitive involvement. Contrary to flow theory, enjoyment, happiness, and intrinsic motivation were characteristic of activities associated with being in ‘control,’ as opposed to flow. Flow activities were associated with being cognitively involved in the task at hand. We believe such theoretically important findings have been masked when using the original four-channel model of flow, but are clarified with use of the revised experience fluctuation model.     

Estimating the growth of internal evidence guiding perceptual decisions

Perceptual decision-making is thought to involve a gradual accrual of noisy evidence. Temporal integration of the evidence reduces the relative contribution of dynamic internal noise to the decision variable, thereby boosting its signal-to-noise ratio. We aimed to estimate the internal evidence guiding perceptual decisions over time, using a novel combination of external noise and the response signal methods. Observers performed orientation discrimination of patterns presented in external noise. We varied the contrast of the patterns and the delay at which observers were forced to signal their decision. Each test stimulus (patterns and noise sample) was presented twice. Across two experiments we varied the availability of the visual stimulus for processing. Observer model analyses of discrimination accuracy and response consistency to two passes of the same stimulus, suggested that there was very little growth in the internal evidence. The improvement in accuracy over time characterised by the speed-accuracy trade-off function predominantly reflected a decreasing proportion of non-visual decisions, or pure guesses. There was no advantage to having the visual patterns visible for longer than 80 ms, indicating that only the visual information in a short window after display onset was used to drive the decisions. The remarkable constancy of the internal evidence over time suggests that temporal integration of the sensory information was very limited. Alternatively, more extended integration of the evidence from memory could have taken place, provided that the dominant source of internal noise limiting performance occurs between-trials, which cannot be reduced by prolonged evidence integration.     

Infants' understanding of actions performed by mechanical devices

Recent research suggests that 9-month-old infants tested in a modified version of the A-not-B search task covertly imitate actions performed by the experimenter. The current study examines whether infants also simulate actions performed by mechanical devices, and whether this varies with whether or not they have been familiarized with the devices and their function. In Experiment 1, infants observed hiding and retrieving actions performed by a pair of mechanical claws on the A-trials, and then searched for the hidden toy on the B-trial. In Experiment 2, infants were first familiarized with the experimenter and the claws but not their function. In Experiment 3, infants were familiarized with the function of the claws. The results revealed that search errors were at chance levels in Experiments 1 and 2, but a significant proportion of the infants showed the A-not-B error in Experiment 3. These results suggest that 9-month-old infants are less likely to simulate observed actions performed by mechanical devices than by human agents, unless they are familiarized with the function of the devices so that their actions are perceived as goal-directed.     

Hail the impossible: p-values, evidence, and likelihood

Significance testing based on p-values is standard in psychological research and teaching. Typically, research articles and textbooks present and use p as a measure of statistical evidence against the null hypothesis (the Fisherian interpretation), although using concepts and tools based on a completely different usage of p as a tool for controlling long-term decision errors (the Neyman-Pearson interpretation). There are four major problems with using p as a measure of evidence and these problems are often overlooked in the domain of psychology. First, p is uniformly distributed under the null hypothesis and can therefore never indicate evidence for the null. Second, p is conditioned solely on the null hypothesis and is therefore unsuited to quantify evidence, because evidence is always relative in the sense of being evidence for or against a hypothesis relative to another hypothesis. Third, p designates probability of obtaining evidence (given the null), rather than strength of evidence. Fourth, p depends on unobserved data and subjective intentions and therefore implies, given the evidential interpretation, that the evidential strength of observed data depends on things that did not happen and subjective intentions. In sum, using p in the Fisherian sense as a measure of statistical evidence is deeply problematic, both statistically and conceptually, while the Neyman-Pearson interpretation is not about evidence at all. In contrast, the likelihood ratio escapes the above problems and is recommended as a tool for psychologists to represent the statistical evidence conveyed by obtained data relative to two hypotheses.     

States of Spiritual Awareness by Time,Activity, and Social Interaction

We explore how people experience the sacred in their everyday lives using a recently developed research technique—smartphone‐based experience sampling method (S‐ESM). The primary goal of our experience‐driven approach is to explore the contours and variations of spiritual awareness within people's day‐to‐day lives. We seek to better understand when and where spiritual awareness is likely to arise, and the contexts in which it is rare. Our smartphone‐based data allow us to track the many contexts in which an awareness of the sacred occurs, as reported in real time during people's normal daily activities. We parse out how immediate contextual factors and how people's more habitual behaviors are related to their spiritual experiences. This illuminates a wide range of factors that influence spiritual experiences that have not received much scholarly attention, and enables us to connect cutting‐edge quantitative methods with qualitative scholarship on spirituality. We hope this will open the door to the development of new theories of situated spiritual experience.     

Behind the wheel: What drives the effects of error handling?

Existing research comparing error management (a strategy focusing on increasing the positive and decreasing the negative consequences of errors) to error prevention (a strategy focusing on working faultlessly), has identified error management as beneficial for multiple outcomes. Yet, due to various methodological limitations, it is unclear whether the effects previously found are due to error prevention, error management, or both. We examine this in an experimental study with a 2 (error prevention: yes vs. no) × 2 (error management: yes vs. no) factorial design. Error prevention had negative effects on cognition and adaptive transfer performance. Error management alleviated worry and boosted one’s perceived self-efficacy. Overall, the results show that error prevention and error management have unique outcomes on negative affect, self-efficacy, cognition, and performance.     

A Comparison of Population-Averaged and Cluster-Specific Approaches in the Context of Unequal Probabilities of Selection

Sampling designs of large-scale survey studies are typically complex, involving multiple design features such as clustering and unequal probabilities of selection. Single-level (i.e., population-averaged) methods that use adjusted variance estimators and multilevel (i.e., cluster-specific) methods provide two alternatives for modeling clustered data. Although the literature comparing these methods is vast, comparisons have been limited to the context in which all sampling units are selected with equal probabilities (thus circumventing the need for sampling weights). The goal of this study was to determine under what conditions single-level and multilevel estimators outperform one another in the context of a two-stage sampling design with unequal probabilities of selection. Monte Carlo simulation methods were used to evaluate the impact of several factors, including population model, informativeness of the design, distribution of the outcome variable, intraclass correlation coefficient, cluster size, and estimation method. Results indicated that the unweighted estimators performed similarly across conditions, whereas the weighted single-level estimators tended to outperform the weighted multilevel estimators, particularly under nonideal sample conditions. Multilevel weight approximation methods did not perform well when the design was informative. An empirical example is provided to demonstrate how researchers might investigate the implications of the simulation results in practice.