Methods of Instrument Training and Effects on Pilots’ Performance With Different Types of Flight Instrument Displays - 2012

Transition Performance Operating Unfamiliar Flight Instrumentation

Lindo, Deaton, Cain and Lang (2012)1 investigated how instrument-rated pilot performance was effected when pilots transitioned to an aircraft significantly different from the instrument flight display they were accustomed to during their training. Pilots who trained in conventional steam gauge instrument aircraft were observed operating a technically enhanced glass cockpit flight simulator device, and vice versa.

The study indicated that pilots who transitioned from the conventional steam gauge instruments to glass cockpit displays had less deviations from assigned values compared with pilots who transitioned from glass cockpit to steam gauge displays. Performance differences were then determined on each of the five dependent measures, with three of the measures producing statistically significant results. This partially confirmed their alternative hypothesis.

Illustration 1: Mean No. Deviations per Participant - Entire Experiment Flight
Conventional to Glass Deviations - Mean Glass to Conventional Deviations - Mean Statistically Significant
Dependent Variables Combined 14.8 46.8 Yes
 Higher numbers equal a higher number of deviations.  

Total sample n=42

Illustration 1: shows the number of deviations made by the participants attempting to transition from glass cockpit to conventional instruments is over three times higher than those transitioning from conventional gauges to glass cockpit.

Illustration 2: Mean No. Deviations per Participant - By Dependent Variable
Variable Conventional to Glass Deviations - Mean Glass to Conventional Deviations - Mean Statistically Significant
Altitude 2.2 12.4 Yes
Airspeed 6.3 22.6 Yes
Glideslope 2.0 5.3 Yes
Heading 2.7 4.2 No
Localizer 1.6 2.3 No
 Higher numbers equal a higher number of deviations.  

Illustration 2: breaks down and summaries the data results found on each of the separate analyses of the variables by Lindo et al. into one table. To reduce the chance of type I error, a reduced alpha level of 0.002 was used. While the data showed an increase in deviations for all five of the variables, the results for heading and localizer where not considered significant by the authors of the study.

Illustration 3: % Increase in Deviations
% Increase in Deviations by those who Transitioned from Glass to Conventional
Dependent Variables Combined 316%
Altitude 564%
Airspeed 358%
Glideslope 265%
Heading 156%
Localizer 144%

Illustration 3: focus on the increase in deviations demonstrated by the participants who transitioned from glass cockpit to conventional instrumentation. For the interest of this article, the data from the study has been converted into a percentage to simplify and improve its readability.


Research approach

The scan patterns of pilots who operate one aircraft are likely to be different from those that operate an aircraft with significantly different instrumentation and without specific transition training, accurate control and navigation may be difficult.

With glass cockpits designed to simplify the scan pattern, it is thought that it may be difficult for pilots to move from a glass cockpit to a conventional steam gauge aircraft. While in contrast, it may be easier for a pilot familiar with steam gauge instrument to transition to a glass cockpit aircraft.

This is a potential safety issue, as pilots who are instrument rated using glass cockpit instrumentation, are unrestricted to fly conventional instruments (and vice versa), without the need for specific transition training. Modern aircraft often use conventional steam gauge instruments as a back up, and in an emergency situation the threat of reduced pilot performance as a result of this instrument transition could pose a danger.

The exploratory study by Lindo et al. seeks to identify any variation in pilot performance in a simplified controlled transition experiment.


  • A sample size of 42 instrument-rated pilots were selected for the study. The participants were selected randomly from a pool of volunteers and split into two equal groups depending on which type of aircraft the participant obtained their instrument rating in.
  • Group One; consisted of 21 pilots who were trained and instrument-rated using conventional steam gauge aircraft.
  • Group Two; consisted of 21 pilots who were trained and instrument-rated using glass cockpit aircraft.
  • Effort has been made to keep the groups equivalent with participants having similar variations in flight hour experience to avoid a selection bias.
  • Pilots of each group in most cases had little to no instrument flight time using the opposite method of instrument flight instrumentation.
  • It should be noted that the population size was not specified, and all participants were from a single University, which my limit the randomized selection for the sample. Participants were also volunteers, who are self selected and therefore may not represent the greater majority of the pilot body.


Using a between-group design experiment, the authors stated their null hypothesis as; pilot performance being equal between both groups of pilots across all variables. Their alternative hypothesis stated that the group of pilots who got their instrument rating using a glass cockpit aircraft and for the experiment transitioned to a conventional gauge display aircraft will perform worse (across all five variables/measures) than the group who got their instrument rating in a conventional display aircraft and for the experiment transitioned to a glass cockpit.

To evaluate the hypothesis, the authors used one-way multivariate analysis of variance (MANOVA) to determine overall performance across five dependent variables by observing deviations from set requirements.


1. Dependent Variables (DV): Flight Performance Measures

  • Airspeed
  • Heading
  • Altitude
  • Localizer
  • Glideslope

2. Independent Variable (IV): Method of Instrument Training

  • Conventional steam Gauge or,
  • Glass cockpit


  • Two certified Advanced Aviation Training Devices (AATDs)
    • Both replicated the flight performance of a Piper Archer light Aircraft, with one set as a glass cockpit and the other set up as a conventional gauge aircraft.
  • Instrument Pilot Practical Test Standard (PTS) - This is a criterion-referenced flight examiners testing guide that has a set of minimum requirements a students performance is judged against during flight tests. Similar standards were used during this study, with observed deviations from specified values recorded against the pilot.


The pilots who had trained and gained their instrument rating in a conventional steam gauge aircraft flew the glass cockpit simulator training device, and the pilots who trained in glass cockpit aircraft flew the steam gauge simulator training device.

Each pilot from group one and two performed the experimental flight in their assigned simulator. An experienced instructor verbally gave them the set flight maneuver instructions throughout the flight, and an observer monitored their deviations from the instructors assigned values.

The same series of instrument flight maneuvers were to be completed by all pilots from both groups of pilot in their assigned simulator, with the groups performance statistically compared afterwards.

Participants were graded using an error scale, based on the corresponding value of their deviation from the assigned requirement in each of the dependent measures. More frequent and extreme deviations was represented by that participant ending with more points. The higher the participants score, the worse the performance.

Pilots were given a short introduction to the new instrumentation and how to read and interpolate it. Then asked to fly the same set set of instrument flight maneuvers in the same order, in the same simulated weather conditions.

Data analysis

  • One-way between-group multivariate analysis of variance (MANOVA) was used to evaluate the instrument-rated pilots performance. Performance was determined by the scale and frequency of deviations from the given requirements the pilot made while handling an aircraft instrumented significantly different from the one they trained and obtained their rating in.
  • The alpha significance level was set at 0.01 for the initial MANOVA on the combined dependent variables.
  • The alpha significance level was set at 0.002 for individual variables.

Generalization potential

While the study partially confirms the authors alternative hypothesis, its scope is likely only relevant to pilots of light aircraft with little to no hours on the instrumentation that they are unexpectedly transitioned on to.

The pilots of this study were also not tested/observed in an aircraft similar to the one they obtained their rating in, so no base-line for individual performance was established. An underlining assumption that the pilots perform at 100% on an aircraft they are accustomed to is highly unlikely. With no base-line the results may appear exaggerated depending on the individual pilots performance.

More experienced (commercial) pilots are often provided specific aircraft type rating and transition training that should help to address the potential performance gap that might develop during instrumentation or electrical failures that require an in-flight transition. Currency of these skills will be the major question for experienced pilots.

1. Lindo, R. S., Deaton, J. E., Cain, J. H., and Lang C. (2012). Methods of instrument training and effects on pilots' performance with different types of flight instrument displays. Aviation Psychology and Applied Human Factors 2012, Vol. 2(2):62-71. doi: 10.1027/2192-0923/a000028

Want to know more?

Glass Cockpits in Aviation : Wiki page discussing the safety benefits and disadvantages for commercial and GA Aircraft

Workload in the Glass Cockpit : Published article discussing pilot workload in normal & abnormal operations, aswell as the relationship between workload & fatigue.

Original Article : Link to the database containing the full original article of this research.

Contributors to this page

  • Michael J LAMBDEN (2013). Massey University, New Zealand (lambdenmlambdenm)

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