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Cognitive Training for Basketball Game-Intelligence: Interview with Prof. Daniel Gopher

Professor Daniel Gopher
Professor Daniel Gopher is a fellow of the U.S. Human Factors and Ergonomics Society and the International Ergonomics Association, Professor of Cognitive Psychology and Human Factors Engineering at Technion, Israel’s Institute of Science, and one of world’s leading figures in the field of Cognitive Training.

During his 40 year career, he has held a variety of scientific and academic positions, such as acting Head of the Research Unit of the Military Personnel Division, Associate Editor of the European Journal of Cognitive Psychology, member of the Editorial Boards of Acta Psychologica, the International Journal of Human-Computer Interaction, and the journal Psychology.

He published an award-winning article in 1994, Gopher, D., Weil, M. and Baraket, T. (1994), Transfer of skill from a computer game trainer to flight, Human Factors 36, 1–19., that constitutes a key milestone in the cognitive engineering field.

Prof. Gopher has also developed innovative a) medical systems, assessing the nature and causes of human error in medical work, and redesigning medical work environments to improve safety and efficiency, and b) work safety systems, developing methods and models for the analysis of human factors, ergonomic, safety and health problems at the individual, team and plant level.

Alvaro Fernandez (AF): Professor Gopher, it is an honor that you speak to us. Could you provide an overview of the projects are you working on now?

Prof. Daniel Gopher (DG): Since 1980 I have been the director of the Research Center for Work Safety and Human Engineering, an interdisciplinary research centre which involves 30 researchers from 5 Technion faculties and 80 graduate students, who work in 7 laboratories. I also act as Scientific Advisor for ACE’s Intelligym and am involved in a new integrative research project labeled “Skills – Multimodal Interfaces for the Capturing and Transfer of Skills”, directed to facilitate and improve the acquisition and transfer of skills through the development of innovative virtual-reality multimodal interfaces. This is an initiative supported by the European Commission with 15 industry and university research partners, from 9 countries.

On Cognitive Training and Cognitive Simulations

AF: Tell us a bit about your overall research interests

DG: My main interest has been how to expand the limits of human attention, information processing and response capabilities which are critical in complex, real-time decision-making, high-demand tasks such as flying a military jet or playing professional basketball. Using a tennis analogy, my goal has been, and is, how to help develop many “Wimbledon”-like champions. Each with their own styles, but performing to their maximum capacity to succeed in their environments.

What research over the last 15-20 years has shown is that cognition, or what we call thinking and performance, is really a set of skills that we can train systematically. And that computer-based cognitive trainers or “cognitive simulations” are the most effective and efficient way to do so.

This is an important point, so let me emphasize it. What we have discovered is that a key factor for an effective transfer from training environment to reality is that the training program ensures “Cognitive Fidelity”, this is, it should faithfully represent the mental demands that happen in the real world. Traditional approaches focus instead on physical fidelity, which may seem more intuitive, but less effective and harder to achieve. They are also less efficient, given costs involved in creating expensive physical simulators that faithfully replicate, let’s say, a whole military helicopter or just a significant part of it.

AF: Very interesting. In the Serious Games Summit this week we are seeing a number of simulations for military training that try to be as realistic as possible. Are you saying that they may not be the best approach for training?

DG: The need for physical fidelity is not based on research, at least for the type of high-performance training we are talking about. In fact, a simple environment may be better in that it does not create the illusion of reality. Simulations can be very expensive and complex, sometimes even costing as much as the real thing, which limits the access to training. Not only that, but the whole effort may be futile, given that some important features can not be replicated (such as gravitation free tilted or inverted flight), and even result in negative transfer, because learners pick up on specific training features or sensations that do not exist in the real situation.

Main studies and applications

AF: What are the main studies have you conducted?

DG: in this field of work, I would mention two. In one, which constituted the basis for the 1994 paper, we showed that 10 hours of training for flight cadets, in an attention trainer instantiated as a computer game-Space Fortress- resulted in 30% improvement in their flight performance. The results led the trainer to be integrated into the regular training program of the flight school. It was used in the training of hundreds of flight cadets for several years. In the other one, sponsored by NASA, we compared the results of the cognitive trainer vs. a sophisticated, pictorial and high-level-graphic and physical-fidelity-based computer simulation of a Blackhawk helicopter. The result: the Space Fortress cognitive trainer was very successful in improving performance, while the alternative was not. The study was published in the proceedings of the Human Factors and Ergonomic Society: Hart S. G and Battiste V. (1992), Flight test of a video game trainer. Proceedings of the Human Factors Society 26th Meeting (pp. 1291-1295).

AF: What have been to date the main applications of your computer-based cognitive simulations?

DG: in summary, I’d say

– Flying high-performance airplanes: in 10 hours, we showed an increase in 30% flight performance

– Flying with HMD (helmet mounted displays)

Touch-typing skills

– Teaching old adults to cope with high workload attention demands.

Developing Basketball “game-intelligence” for professional players, to improve the performance of individuals and teams

Trainer for basketball “game-intelligence”

AF: talk to us about the basketball example. I am sure many readers will find that fascinating.

DG: I served as a scientific advisor to ACE, who developed the program called Intelligym. Although the context is different, the approach and basic principles are the same of those of developing a trainer for the task of flying a high performance jet airplane. First, one needs to analyze what cognitive skills are involved in playing at top level, and then develop a computer-based cognitive simulation that trains those skills. What most people don’t realize is that top players are not born top players. We are not just talking about instincts. We are talking about skills that can be trained.

AF: what are the results of the program so far?

DG: Well, first let me say that the company has had to overcome huge cultural barriers to get adoption by a good number of university teams and some NBA players. Coaches see the value of this tool very quickly, but administrators are harder to convince in the beginning. We have seen that the teams and individuals using Intelligym have improved their performance significantly. From the cognitive training, or skill development point of view, we have seen that players improve their positional awareness-of themselves, their mates and opponents, and ability to predict what is going on in the game and to make fast and good decisions. Players quickly develop attention allocation strategies that enable them better participate in the game, and also improve their spatial orientation.

Summary of key findings

AF: Fascinating real-world experience. Can you summarize your research findings across all these examples and fields, and how you see the field evolving?

DG: In short, I’d summarize by saying that

Cognitive performance can be substantially improved with proper training.

– It is not rigidly constrained by innate, fixed abilities.

Cognitive task analysis enables us to extract major cognitive skills involved in any task.

– Attention control and attention allocation strategies are a critical determinants in performing at top level in complex, real-time decision-making environments

– Those skills, and other associated, can be improved through training

– Research shows that stand-alone, inexpensive, PC-based training is effective to transfer and generalize performance.

– The key for success is to ensure Cognitive fidelity, this is, that the cognitive demands in training resemble those of the real life task.

I can think of many other applications. Probably currency and options traders would benefit from a system like this. Now, we will need to increase awareness, and will need to find champions willing to take risks. The cognitive simulation approach is less intuitive that traditional ones.

Professor Wayne Shebilske, at Wright State University Psychology department, is conducting additional research on applications, such as outlined on the paper Shebilske, Wayne L., et al, “Revised Space Fortress: A Validation Study” (accepted for Behavior Research Methods, Instruments and computers).

(Professor Shebilske was kind enough to write a great comment below, giving us 2 detailed references:

Shebilske, W. L., Volz, R. A., Gildea, K. M., Workman, J. W., Nanjanath, M., Cao, S., & Whetzel, J. (2005). Revised Space Fortress: A validation study. Behavior Research Methods, 37, 591-601.

Volz, R.A., Johnson, J.C., Cao, S., Nanjanath, M., Whetzel, J., Ioerger, T.R., Raman, B., Shebilske, W.L., and Xu, Dianxiang (2005). Fine-Grained data acquisition and agent oriented tools for distributed training protocol research: Revised Space Fortress. Down Load Technical Supplement, Psychonomic Society Web-based Archive (see 37,591-601).

AF: are you doing something to spread the word?

DG: apart from conferences and journals, I have written the chapter Emphasis change as a training protocol for high demands tasks, in the book Applied Attention: From Theory to Practice, A. Kramer, D. Wiegman, A. Kirlik (Eds): Oxford Psychology Press, about to be released.

A more in-depth view of his cognitive simulation approach

AF: Great. For readers who may be interested in more specific details about your specific approach to cognitive training, could you give us some lessons learned?

DG: Good question. There are different types of cognitive training. The one we have specialized in focuses on the development of attention-control, attention-allocation strategies, which are bottleneck in some high-performing, high-mental-workload- environments. Our approach is called Emphasis Change Protocol, and is based on the introduction of systematic variability in training, while maintaining the overall task intact. We just change the emphasis on sub-components of a complex task during performance. In our research, this has proven to be the most effective way to train attention management skills, task switching and control processes, such as the ability to initiate, coordinate, synchronize and regulate goal-directed behavior.

This “whole task” approach increases transfer and adaptation capabilities, vs. traditional part task training, which decomposes the complex task and trains elements in isolation. However, whole task training is harder at the beginning-there is slower progress at early stages of training.

Other principles we use, based on our and others’ literature, is the need for intermittent schedules of feedback (vs. full one), to help retention and transfer (at the cost of making learning slower), and the encouragement to explore alternatives to reach a general optimum. This exploration is important: we want to help the user find a flexible, and personal best, match between his abilities and task demands, out of localized peaks. Coming back to the tennis example, we know that McEnroe and Boris Becker have different styles, but both are Wimbledon winners. We want to make sure the user increases sensitivity to real-time changes in the environment and expands his or her ability to cope with them.

AF: Professor Gopher, it has been a pleasure to talk to you. Thank you for your time.

DG: Thank you. I enjoyed very much reading your interview with Dr. Torkel Klingberg on working memory training, and appreciate your help in increasing awareness of the whole field. Btw, I will be traveling next week to Spain, for a meeting of the Skills project. The meeting will be in Bilbao.

AF: Well, that is my hometown…so please say Hi for me! Hola in Spanish, Kaixo in Basque.

DG: I will.

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21 Responses

  1. Your excellent interview with Dr. Gopher reminded me why so many of us have followed his lead in training complex skills. I hope that your interview inspires others. They will find that he is generous with his ideas, time, energy, and infectious positive spirit. Working with him to replicate experiments and extend ideas is both productive and enjoyable.
    Your interview includes a reference to an article by my colleagues and me. I want to update the reference and provide a related reference to a Web-based Archive.

    Shebilske, W. L., Volz, R. A., Gildea, K. M., Workman, J. W., Nanjanath, M., Cao, S., & Whetzel, J. (2005). Revised Space Fortress: A validation study. Behavior Research Methods, 37, 591-601.

    Volz, R.A., Johnson, J.C., Cao, S., Nanjanath, M., Whetzel, J., Ioerger, T.R., Raman, B., Shebilske, W.L., and Xu, Dianxiang (2005). Fine-Grained data acquisition and agent oriented tools for distributed training protocol research: Revised Space Fortress. Down Load Technical Supplement, Psychonomic Society Web-based Archive (see 37,591-601). .

    The journal article’s abstract describes both:

    Abstract
    We describe briefly the redevelopment of Space Fortress (SF), a research tool widely used to study training of complex tasks involving both cognitive and motor skills, to execute on current generation systems with significantly extended capabilities, and then compare the performance of human participants on an original PC version of SF with the Revised Space Fortress (RSF). Participants trained on SF or RSF for 10 sets of 8 3-min practice trials and 2 3-min test trials. They then took tests on retention, resistance to secondary task interference, and transfer to a different control system. They then switched from SF to RSF or from RSF to SF for two sets of final tests and completed rating scales comparing RSF and SF. Slight differences were predicted based on a scoring error in the original version of SF used and on slightly more precise joystick control in RSF. The predictions were supported. The SF group started better, but did worse when they transferred to RSF. Despite the disadvantage of having to be cautious in generalizing from RSF to SF, RSF has many advantages, which include accommodating new PC hardware and new training techniques. A monograph that presents the methodology used in creating RSF, details on its performance and validation, and directions on how to download free copies of the system may be downloaded from http://www.psychonomic.org/archive/.

    The extended capabilities for RSF include a) being executable on current generation platforms, b) being written in a mostly platform independent manner, c) being executable in a distributed environment, d) having hooks built in for the incorporation of intelligent agents to play various roles, such as partners and coaches e) providing a general experiment definition mechanism, f) supporting teamwork through being able to flexibly assign different input controls to different members of a team, g) maintaining all data in a central database rather than having to manually merge data sets after the fact, and h) having playback capability, which enables researchers to review all actions that occurred during an experiment and to take new measures. Experimenters can design measures before an experiment to test specific hypotheses with a rigorous laboratory task. They can also use playback to discover and explore unanticipated events. Although simpler and more complex synthetic task environments can be advantageous for some goals, Danny Gopher, our colleagues, and I believe that Space Fortress remains an important tool for scientists and trainers. Please feel free to contact me (wayne.shebilske@wright.edu) for additional help downloading and using RSF.

  2. Alvaro says:

    Dear Wayne,

    What a pleasure to see that you have enjoyed the interview and added such a great comment. I agree that the experience of working with Prof. Gopher has been all a pleasure. And, of course, very stimulating.

    I look forward to talking to you to learn more about your experiments.

    Alvaro

    PS: will add the references to the main text right away

  3. Encefalus says:

    A very nice article! I believe that cognitive training could be easily used in the educational system (and certainly video games are more interesting than books :P)

  4. jhon says:

    Your excellent interview with Dr. Gopher reminded me why so many of us have followed his lead in training complex skills. I hope that your interview inspires others. They will find that he is generous with his ideas, time, energy, and infectious positive spirit. Working with him to replicate experiments and extend ideas is both productive and enjoyable.
    Your interview includes a reference to an article by my colleagues and me. I want to update the reference and provide a related reference to a Web-based Archive.

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