Christopher T. Ball

THE RELATIONSHIP BETWEEN SEARCH STRATEGY AND RISKY CHOICE

This paper describes a study of the information search patterns used by decision makers to make choices among options with unknown outcomes. The study involved 48 students from Flinders University and Melbourne University who were administered 25 decision trials on which they could win or lose money. Information search behaviour was measured by the DEAN procedure (Ball & Mann, 1991), a process-tracing package for recording and analysing information search patterns for problems presented in decision matrix format. The relationship between information search behaviour and risky choice was examined. It was found that the individuals search processes and strategies are related to the nature of subsequent choices. Individuals who searched little information were more likely to choose risky, money-losing options. The findings, which demonstrate consistency between search and choice, indicate that different parts of the decision-making process are coherent.

Decision-making abilities of intellectually gifted and non-gifted children

Abstract Samples of 61 intellectually gifted and 122 non-gifted high school students in the age range of 12-15 years were compared on four aspects of decision-making ability: metacognitive knowledge about decision making; use of efficient decision search strategies; probability “tuning”; and self-reported decision-making style and self-esteem. The study drew on Sternbergs (1985) “triarchic” theory of intelligence for an analysis of the decision-making abilities of the gifted students. It was found that intellectually gifted adolescents had superior metacognitive knowledge; were faster in making decisions; made greater use of efficient search strategies; were better at “tuning” information about probabilities; and reported a more competent decision style than non-gifted adolescents. The findings were interpreted as evidence of both quantitative and qualitative differences in die decision-making abilities of gifted and non-gifted adolescents. Similarities between the abilities of intellectually gifted adol...

Subliminal priming of autobiographical memories.

The current research examined subliminal priming of autobiographical memories. In Experiment 1 the subliminal primes consisted of affect-associated words (positive vs negative) and were presented just before the participants retrieved specific experiences to cue-words. The subliminal primes produced an inhibitory effect on autobiographical memory retrieval, with significantly lower positive ratings given to the emotional content of experiences retrieved after positive primes than given to experiences retrieved after negative primes. The subliminal primes for the second experiment consisted of words that related to specific lifetime periods (early childhood vs late childhood/early adulthood). A negative priming effect resulted again, with earlier life experiences retrieved after the presentation of late childhood/early adulthood primes. We believe the negative priming effects obtained in both experiments are consistent with predictions based on the self-memory system model of autobiographical memory. The results of this research may also explain mood-incongruent recall.

Restrained eating and memory specificity

Autobiographical memories are personal experiences that we store across our life-span. A reduced ability to retrieve specific autobiographical experiences has been reported for a number of clinical populations. Previous research has found that the size of the memory specificity effect can predict disorder occurrence, severity, and treatment success. The current research examined whether a similar relationship could be found between memory specificity and restrained eating in a female college student population. Participants retrieved autobiographical memories that related to cue-words associated with dieting and body image. Individual differences in restrained eating were measured with the Restraint Scale (RS). Participants who scored higher on the concern-with-dieting sub-scale of the RS retrieved fewer specific autobiographical memories regardless of their current dieting activity. The memory specificity effect has the potential to serve as a predictor of eating disorder occurrence and treatment success, and may also assist with the development of interventions targeting such disorders.

THE INTERACTIVE EFFECT OF VELOCITY ON COINCIDENT TIMING PERFORMANCE

For 16 men and women (18–29 years) analysis of movement coincident with a moving target showed task variables influenced each other (e.g., shorter target durations produced faster movements) and combined additively to produce marked changes in performance (e.g., fastest responses to the fastest targets resulted in the most consistent timing).

Analysis of Targeted Mouse Movements for Gender Classification

Gender is one of the essential characteristics of personal identity that is often misused by online impostors for malicious purposes. This paper proposes a naturalistic approach for identity protection with a specific focus on using mouse biometrics to ensure accurate gender identification. Our underpinning rationale lies in the fact that men and women differ in their natural aiming movements of a hand held object in twodimensional space due to anthropometric, biomechanical, and perceptual-motor control differences between the genders. Although some research has been done on classifying user by gender using biometrics, to the best of our knowledge, no research has provided a comprehensive list of which metrics (features) of movements are actually relevant to gender classification, or method by which these metrics may be chosen. This can lead to researchers making unguided decisions on which metrics to extract from the data, doing so for convenience or personal preference. Making choices this way can lead to negatively affecting the accuracy of the model by the inclusion of metrics with little relevance to the problem, and excluding metrics of high relevance. In this paper, we outline a method for choosing metrics based on empirical evidence of natural differences in the genders, and make recommendations on the choice of metrics. The efficacy of our method is then tested through the use of a logistic regression model. Received on 29 November 2017; accepted on 02 December 2017; published on 07 December 2017

A Behavioral Biometrics Based Approach to Online Gender Classification

Gender is one of the essential characteristics of personal identity but is often misused by online impostors for malicious purposes. However, men and women differ in their natural aiming movements of a hand held object in two-dimensional space due to anthropometric, biomechanical, and perceptual-motor control differences between the genders. Exploiting these natural gender differences, this paper proposes a naturalistic approach for gender classification based on mouse biometrics. Although some previous research has been done on gender classification using behavioral biometrics, most of them focuses on keystroke dynamics and, more importantly, none of them provides a comprehensive guideline for which metrics (features) of movements are actually relevant to gender classification. In this paper, we present a method for choosing metrics based on empirical evidence of natural difference in the genders. In particular, we develop a novel gender classification model and evaluate the model’s accuracy based on the data collected from a group of 94 users. Temporal, spatial, and accuracy metrics are recorded from kinematic and spatial analyses of 256 mouse movements performed by each user. A mouse signature for each user is created using least-squares regression weights determined by the influence movement target parameters (size of the target, horizontal and vertical distances moved). The efficacy of our model is validated through the use of binary logistic regressions.

The Optimal Model: Linear Programming

This is not a book on Linear Programming (LP). This is a book on decision making. It is a book on behavior, specifically resource-allocation behavior. But just as people’s decision making under choice cannot be studied in the absence of an understanding of Bayesian math, neither can people’s decisions about the allocation of resources be understood without an understanding of LP. LP is the mathematical model used in Operations Research and Management Science to find the optimal solution to resource-allocation problems when certain variables are known. This chapter will provide the reader with a very fundamental introduction to LP but it is far beyond the scope of this book (and the ability of the authors) to provide a comprehensive tutorial on all aspects of LP. Hundreds of books have been written on the topic since Dantzig’s 1963 Linear Programming and Extensions. But if the reader wishes to explore the topic in depth, one very authoritative place to start would be Linear Programming (Dantzig & Thapa, 1997).

RAB with Various Levels of Information

The first four chapters in this book introduced Linear Programming as an optimal model for calculating the optimal solution to a resource-allocation problem when certain values are known. In this chapter and the seven chapters that follow, we will view resource-allocation behavior under various conditions, structures, and environments and we will examine both normative and cognitive models for understanding how people make resource-allocation decisions. We will begin in this chapter with an examination of how people allocate resources under conditions of Certainty, Risk, and Uncertainty. We will see that participants can learn to perform a resource-allocation task with surprising success, that participants perform best under Certainty and worst under Uncertainty, that participants tend to allocate more resources early in a time period, and that participants prefer to hold some resources in reserve in case of unanticipated needs. This chapter will draw heavily on the 1993 article entitled, Resource-Allocation Behavior Under Certainty, Risk, and Uncertainty, by Langholtz, Gettys, and Foote with sections reproduced here with permission.

Conclusions and Future Areas to be Mapped

In the 11 preceding chapters we have examined how people make resource-allocation decisions. We started with some basic questions and tried to expand outwards from the beginning point in a logical and methodical manner. It was clear from the initial research that people could function surprisingly well as intuitive resource allocators, solving problems without having had any background in Linear Programming. Most participants could initially obtain approximately 80% to 85% of the optimal LP solution, and with practice, most could improve to 95% or more. This finding remained generally consistent and stable throughout all the studies we conducted under a variety of conditions.