Eye-tracking technology enables computers or other devices to identify where a user is looking while performing a task. This may provide insight into cognitive processes underlying individuals’ judgments, decisions, and behaviors in a range of laboratory and research settings.
But, can it be of benefit to accounting practitioners?
Mihaylo College Assistant Professor of Accounting Edward Lynch looks at the advantages and limitations of eye-tracking in accounting research in his 2018 study, “If Eyes Are the Window to Our Soul, What Role Does Eye-Tracking Play in Accounting Research?”.
Lynch uses eye movements as a proxy for what data a decision-maker pays attention to, including their scan path, when completing a task.
He discusses this study and its implications in the interview below.
What should the accounting industry know about eye-tracking?
Eye-tracking is a promising research tool designed to get into the black box of judgment and decision-making. Although not a new technology, improvements to both the eye-tracking hardware and the related analytic software (perhaps driven by the integration of eye-tracking into consumer electronics, like cell phones) has raised eye-tracking to a new level of functionality.
How can it be used, and what are the challenges and opportunities?
Eye-tracking technology provides a more precise understanding of which information is actually attended to when making a decision versus relying on what a theory indicates or what a decision-maker says is relevant.
Specifically, eye-tracking can be used to record eye movements and/or changes in pupil size to identify the focus of an individual’s attention (for example, a word or phrase, line item, or number) and the visual search strategy employed when performing a task, such as reading, problem-solving or decision-making.
Therefore, accounting researchers and practitioners would likely benefit from eye-tracking in areas such as information search in complex settings, including how auditors think; evaluation of financial statements and going concern decisions; comparing the cognitive processing of different groups, such as experts vs. novices; learning and training contexts; or examining the usability of accounting information systems.
However, there are limits as to how much insight eye movements can provide, the start-up cost is considerable, and data collection and analysis can be time-consuming.
Certain areas of application are likely to benefit most from eye-tracking, while others are less likely to. What would be some examples of each?
Areas that will benefit the most from eye-tracking are studies interested in information search (including big data and data analytics) and its relationship with decision-making, learning and training systems, and understanding an expert’s cognitive processes.
For example, in the context of a task, how much data/information creates cognitive overload; what specific information contributed more or less to triggering an auditor’s level of skepticism and/or was relied upon in reaching a decision; how do visuals/format influence comprehension/task performance; and finally, can we identify and “teach” an expert (for example, an audit manager) cognitive processing while performing the task?
Where do you see eye-tracking in the foreseeable future? Will it become mainstream?
I foresee eye-tracking becoming much more mainstream in the near future. The technology is becoming common at most universities (usually led by the marketing departments), and it is becoming much more affordable and easier to use and transport.
Currently, due to cost and time concerns, academic research relies heavily on student volunteers as opposed to accounting practitioners. But as eye-tracking technology advances and continues to be easier to use and transport, I think we will see more studies involving practitioners which will ultimately provide the greatest benefit.
Eye tracking could be of greatest benefit in situations where practitioners are considering new regulations, new software or tools for use on the job, how accountants think in complex situations on the job, or new approaches to training. And more specifically, in situations where practitioners are considering revisions to the audit report or financial statements, new audit or tax software packages, or how big data and information overload effects accountants.
With respect to education, I envision that someday there will be a university eye-tracking lab (either brick-and-mortar or, more likely, in the cloud). Students will have access through a desktop, laptop or smart eyeglasses where eye-tracking capability is seamlessly built in.
Students will have the option to elect to have their eye movements and changes in pupil size recorded while reading a textbook, working through a case problem or taking an exam.
From the recorded eye-tracking data, the professor could identify critical terms or phrases that the student had difficulty processing or comprehending, and which may require supplemental/additional effort on the part of the professor and the student. In a case problem (or problem-solving) context, eye-tracking can also identify the search strategy employed while performing the task, which may lead to identifying an optimal search strategy that can in turn be shared in the classroom.
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