BSc, PhD UNSW

Research Areas

I work at the intersection of three disciplines: Industrial & Organizational Psychology; Cognitive Psychology; and Human Factors. My research focuses on the motivational and cognitive determinants of performance, safety and effectiveness. My work is carried out in organizational settings and in the laboratory. I am interested in the interaction between people and the systems in which they work. My research is characterized by a concern for the temporal dynamics of complex systems, and the levels of analysis at which phenomena exist.

Current Projects

Developing and testing a dynamic model of the proximal and distal motivational processes responsible for the regulation of task-directed effort. Motivation is one of the most widely studied concepts in psychology, yet there is a mismatch between the level of analysis inherent in motivation theory, and the level at which it is studied. Theoretically, motivation is a dynamic process that operates within individuals over time. However, most studies examine variability in motivation between people rather than variability within people. This project is examining how motivation changes over time and why the rate of change varies for different people in different contexts. It aims to improve our understanding of the dynamics of motivational processes.

Development of a Computational Model for the Prediction of Mental Workload in Air Traffic Control. The aim of the project is to develop a computational model that can measure the flow of traffic through an air sector, and predict the level of workload that an air traffic controller will experience. The purpose is to develop a tool that can be used for sector redesign. The workload model has been derived empirically from data collected in both an operational environment and in high fidelity simulators based at Brisbane Centre. We have used multi-level modelling to identify the factors that produce changes in subjective workload both within and between sectors. Agent-based models have been built to simulate the tasks that the human controller carries out, allowing the workload model to run from flight plans, as well as from historical radar track data. The major focus of this modelling effort is currently on simulating how controllers detect and resolve conflicts.

Learning, transfer and adaptable expertise in fire control: The aim of this project is to develop and test innovative techniques for the development of adaptive expertise in command and control. This project is funded by the Australian Research Council, and involves the NSW Fire Brigades, the University of Sydney and the Key Centre for Human Factors and Applied Cognitive Psychology at the University of Queensland. Early research has highlighted the types of information that is used when deciding whether to use offensive or defensive strategies, while subsequent studies have provided ideas about how to use stylised examples to encourage adaptive performance in fire fighting. Studies are currently examining the effectiveness of using errors as a learning tool. Case histories are being used to show trainee fire commanders the effects of different types of errors. The effects of this training intervention on command effectiveness are being evaluated using a high fidelity command and control simulator (VectorCommand).

Motivation, Self Regulation & Temporal Dynamics

Greche, M. R., Neal, A., Yeo, G., Humphreys. M. S. & Smith, S. (in press). Workload and fatigue: An examination of the relationship within and across consecutive days of work. Journal of Occupational Health Psychology.

Yeo, G. & Neal, A. (2008). Subjective cognitive effort: A model of states, traits and time. Journal of Applied Psychology, 93(3), 617-631.

Yeo, G. & Neal, A. (2006). An examination of the dynamic relationship between self-efficacy and performance across levels of analysis and levels of specificity. Journal of Applied Psychology, 91(5), 1088-1101.

Yeo, G. & Neal, A. (2004). A multilevel analysis of effort, practice and performance: Effects of ability, conscientiousness and goal orientation. Journal of Applied Psychology, 89(2), 231-247.

Performance, Safety and Effectiveness at Work

Griffin, M. A., Parker, S.K., & Neal, A. (2008). Is behavioral engagement a distinct and useful construct? Industrial and Organizational Psychology, 1(1), 48-51.

Griffin, M. A., Neal, A. & Parker, S. K. (2007). A new model of work role performance: Positive behavior in uncertain and interdependent contexts. Academy of Management Journal, 50(2), 327-347.

Joung, W., Hesketh, B. & Neal, A. (2006). Using ‘war stories' to train for adaptive performance: Is it better to learn from error or success? Applied Psychology: An International Review, 55 (2), 282-302.

Neal, A., Godley, S. T., Kirkpatrick, T., Dewsnap, G., Joung, W. & Hesketh, B. (2006). An examination of learning processes during critical incident training: Implications for the development of adaptable trainees. Journal of Applied Psychology, 91(6), 1276-1291.

Neal, A. & Griffin, M. A. (2006). A study of the lagged relationships among safety climate, safety motivation, safety behavior, and accidents at the individual and group levels. Journal of Applied Psychology, 91(4), 946-953.

Neal, A., West, M. A. & Patterson, M. G. (2005). Do organizational climate and competitive strategy moderate the relationship between Human Resource Management and productivity? Journal of Management, 31(4), 1-21.

Griffin, M. A. & Neal, A. (2000). Perceptions of safety at work: A framework for linking safety climate to safety performance, knowledge, and motivation. Journal of Occupational Health Psychology, 5, 347-358.

Neal, A., Griffin, M. A., & Hart, P. M. (2000). The impact of organizational climate on safety climate and individual behavior. Safety Science, 34, 99-109.

Human Performance & Applied Cognition

Fothergill, S., Loft, S. & Neal, A. (in press). ATC-labAdvanced: An air traffic control simulator with realism and control. Behavior Research Methods, Instruments & Computers.

Loft, S., Bolland, S., Humphreys, M.S. & Neal, A. (2009) A theory and model of conflict detection in air traffic control. Journal of Experimental Psychology: Applied, 15, 106-124.

Neal, A. & Kwantes, P. J. (2009). An evidence accumulation model for conflict detection performance in a simulated air traffic control task. Human Factors, 51(2), 164-180.

Loft, S., Neal, A., Humphreys, M. S. (2007). The development of a general associative learning account of skill acquisition in a conflict detection task. Journal of Experimental Psychology: Human Perception & Performance, 33(4), 938-959.

Loft, S., Sanderson, P. M., Neal, A. & Mooij, M. (2007). A critical review of modelling and predicting mental workload in en-route air traffic control. Human Factors, 49(3), 376-399.

Boag, C., Neal, A., Loft, S. & Halford, G. (2006). An analysis of relational complexity in an air traffic control conflict detection task. Ergonomics, 49(14), 1508-1526.

Crawford, J. & Neal, A. (2006). A review of the perceptual and cognitive issues associated with the use of Head-Up Displays in commercial aviation. International Journal of Aviation Psychology, 16 (1) 1-19.

Kwantes, P. J. & Neal, A. (2006). Why people underestimate y when extrapolating in linear functions. Journal of Experimental Psychology: Learning, Memory & Cognition, 32(5), 1019-1030.

Loft, S., Hill, A. & Neal, A., Humphreys, M. & Yeo, G. (2004). ATC-Lab: An air traffic control simulator for the laboratory. Behavior Research Methods, Instruments & Computers , 36(2), 331-338.

Loft, S., Humphreys, M. & Neal, A. (2004). The Influence of Memory for Prior Instances on Performance in a Conflict Detection Task. Journal of Experimental Psychology: Applied, 10 (3), 173-187.

Neal, A. & Hesketh, B. (1997). Episodic knowledge and implicit learning. Psychonomic Bulletin & Review, 4, 24-37.

Neal, A., Hesketh, B. & Andrews, S. (1995). Instance-based categorisation: Intentional versus automatic forms of retrieval. Memory & Cognition, 23, 227-242.

ATC-Lab Advanced Download

Our research group has developed an Air Traffic Control simulator for use in experimental studies. The simulator is designed for use in both laboratory and field settings, and can be used by naive participants as well as expert controllers. Studies using this simulator have examined:

• Factors influencing the performance of expert and novice controllers on conflict detection tasks;
• Strategies used by expert controllers for resolving conflicts under varying levels of workload;
• Cognitive and motivational determinants of skill acquisition; and
• Prospective memory.

A paper describing the development of the simulator is now in press:

Fothergill, S., Loft, S., & Neal, A. (In Press). ATC-labAdvanced: An Air Traffic Control Simulator with Realism and Control. Behavior Research Methods, Instruments and Computers.

Downloads

 Installation Intructions (PDF)

 Spreadsheet Instructions (PDF)

 Training Manual (PDF)

 XML Instructions (PDF)

 Spreadsheet for calculating starting positions (XLS)

pact0.0.3_installer.exe

pact0.0.3_src (Zip)