Making the most of ecological interface design: the role of individual differences.

As advanced control rooms for new process control plants are being designed, the question arises as to whether operators of the future need to have a particular set of cognitive characteristics to make the most of those advanced control rooms. This issue was investigated by examining the interaction between ecological interface design (EID) and individual differences in the context of a process control microworld. A number of potential predictors of performance were investigated, including: demographic data, type of interface, type of instruction, and data from two cognitive style tests. Eight linear regression analyses were conducted to determine which variables were the strongest predictors of performance. The results indicate that the strongest and most consistent predictor of performance was the interaction between a holist cognitive style score and an interface based on the principles of EID. That is, individuals who used an EID interface and who had high holist scores were the best performers. It seems that these individuals have the relational thinking ability that is required to exploit the value of the higher-order functional information provided by an EID interface. This empirical result has practical implications for operator selection.

[1]  Lynna J. Ausburn,et al.  Cognitive styles: Some information and implications for instructional design , 1978 .

[2]  David H. Jonassen,et al.  Handbook of Individual Differences, Learning, and Instruction , 1993 .

[3]  Kim J. Vicente,et al.  Operator adaptation in process control: A three-year research program , 1997 .

[4]  Jens Rasmussen,et al.  The role of hierarchical knowledge representation in decisionmaking and system management , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Kim J. Vicente,et al.  A Longitudinal Study of the Effects of Ecological Interface Design on Skill Acquisition , 1996, Hum. Factors.

[6]  L. D. Bainbridge,et al.  Developing skills with information technology , 1989 .

[7]  Kim J. Vicente,et al.  Supporting knowledge-based behavior through ecological interface design , 1991 .

[8]  Neville A. Stanton,et al.  Human Factors in Nuclear Safety , 2007 .

[9]  Gordon Pask,et al.  Learning Strategies and Individual Competence. , 1972 .

[10]  Jens Rasmussen,et al.  The reflective expert and the prenovice: Notes on skill-, rule- and knowledge-based performance in the setting of instruction and training , 1989 .

[11]  Kim J. Vicente,et al.  Inducing effective operator control through ecological interface design , 1996, Int. J. Hum. Comput. Stud..

[12]  K. J. Vicente,et al.  Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work , 1999 .

[13]  J. Biggs.  Student Approaches to Learning and Studying , 1987 .

[14]  Jens Rasmussen,et al.  Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[15]  Kim J. Vicente,et al.  Ecological interface design: theoretical foundations , 1992, IEEE Trans. Syst. Man Cybern..

[16]  Kim J. Vicente,et al.  CRITIQUE AND RESPONSE: Response to Maddox Critique , 1996, Hum. Factors.

[17]  K. J. Vicente,et al.  The Ecology of Human-Machine Systems II: Mediating 'Direct Perception' in Complex Work Domains , 1990 .

[18]  Dianne E. Howie,et al.  Making the most of ecological interface design: the role of self-explanation , 1998, Int. J. Hum. Comput. Stud..

[19]  Michelene T. H. Chi,et al.  Eliciting Self-Explanations Improves Understanding , 1994, Cogn. Sci..

[20]  Kim J. Vicente,et al.  Attention Allocation within the Abstraction Hierarchy , 1997 .

[21]  Kim J. Vicente,et al.  A longitudinal study of the effects of ecological interface design on deep knowledge , 1998, Int. J. Hum. Comput. Stud..

[22]  Selecting personnel in the nuclear power industry , 1996 .

[23]  V. Barnett,et al.  Applied Linear Statistical Models , 1975 .

[24]  Averill M. Law,et al.  Simulation modelling and analysis , 1991 .

[25]  Jens Rasmussen,et al.  Cognitive Systems Engineering , 2022 .

[26]  E. Brunswik.  Perception and the Representative Design of Psychological Experiments , 1957 .