Summary.Within the framework of the master's degree project in innovation and design, a research proposal is proposed that presents the integration of objective techniques to evaluate the cognitive load generated by the graphical user interface in an augmented reality environment, based on an experimental design unifactorial, cross-sectional, retrospective, at an explanatory level. This proposal is relevant as it will provide empirical evidence for the graphical user interface design process. It is expected, at the end of this project, to have a procedure manual for the evaluation of graphical user interfaces based on the level of external cognitive load.
With the fourth industrial revolution, technologies such as augmented reality (AR) have been
making headway in areas such as learning and skills training, given their ability to merge real and
virtual objects in practice environments and the ability to provide information in time. real to
apprentice (Akçayır & Akçayır, 2017). Several studies have shown that cognitive overload can be
an important aspect of usability
When a person is making use of an augmented environment, a series of cognitive processes are
triggered directly linked to that activity. The level of cognitive load is an indicator that could be used
to evaluate increased user-environment interaction. In the nineties, Sweller
This proposal focuses on the process of designing graphical user interfaces for augmented reality environments, specifically in the evaluation phase of design alternatives. Focused on defining a framework that allows the designer to objectively evaluate his interface from the level of extrinsic cognitive load generated by the visual stimulus. The foregoing, through a cross-technique approach of electroencephalography (EEG) and eye tracking, providing the designer with pertinent information for the redefinition of the interfaces.
The Cognitive Load (CC) can be defined as the total amount of mental activity processed,
consciously, at the moment in which the subject completes a task
The measurement of external cognitive load continues to be a challenge, since this construct
cannot be measured directly, but rather requires the evaluation of dimensions related to it, which
are: mental load, mental effort and performance
In the literature, two different approaches are generally found for such evaluation: a) requesting users to subjectively rate their perceived cognitive load or b) using objective measures, commonly physiological measures. In this proposal, an objective magnitude that is robust, continuously measurable and sensitive enough to solve the bad signal-to-noise ratio is sought.
As human-computer interaction (HCI) systems are becoming ubiquitous and used to perform critical
tasks in different domains, the need to measure the cognitive load caused by a purpose-designed
HCI system is becoming increasingly common. increasingly important in stages prior to
implementation
Current tools have allowed us to measure cognitive load from a weighted analysis; An interesting observation is that although researchers are continually trying to find or develop secondary task and physiological measures, the internal consistency of these measures requires further study. Especially to determine the extrinsic cognitive load, referring to when the learner is interacting with a material or interface whose design or execution has irrelevant elements that hinder the processes of both construction and automation of schemes, which will allow the learning of complex concepts.
To carry out the development of the project, a methodology based on the methodological approach
of
It is expected, at the end of the development of this research work, to have a procedure manual that describes the activities related to the evaluation of external cognitive load of graphical user interfaces applying crossed techniques; This manual will have a chronological narrative that systematically requires data capture, a guide for the treatment of electroencephalographic signals and a list of metrics that differentiate the levels of external cognitive load resulting from its interface, in this way, the designer will be able to evaluate objectively its design alternatives for augmented reality environments and obtain the necessary information for its redefinition, if required.
The above, based on the case study for the evaluation of external cognitive load of a prototype for learning and training activities in an augmented environment, which allows to demonstrate the significant improvement of the evaluation of cognitive load of each of the techniques separately. compared to the application of integrated techniques.
This work is framed as an investigation through design, experimental, retrospective and crosssectional at an explanatory level. The hypothesis proposed by the researcher affirms that multimodal approaches that combine data from different sensors improve the specific evaluation of external cognitive load caused by the stimulus in graphical user interfaces.
To confirm the previous hypothesis, the development of an experiment with a unifactorial design is proposed, in order to verify the values for the estimation of cognitive load from the frequency, voltage and amplitude of the waves. This information will be acquired with the EMOTIV EPOC + device, which allows us to recognize the report of performance metrics of stress, commitment and concentration. On the other hand, for the analysis of the percentage of pupil dilation, the SMI eye tracking device (SMI Eye Tracking Glasses SMI ETG) will be used; with the aim of verifying the information obtained in the literature and determining the level of reliability of the evaluation methods with respect to a subjective scale.
The test will be carried out in person in a closed room with controlled lighting. The protocol begins with the explanation of the experiment, and the signing of the informed consent. The user is directed to a hair washing area in order to meet biosafety parameters and at the same time to control the humidity of the scalp that will facilitate subsequent data collection. Once the washing is done, the subject is positioned in front of the guide marks to start with the calibration of the SMI glasses, the user must follow the marks presented; Afterwards, the EPOC + electroencephalograph will be positioned and through the EMOTIV APP application, a quality of contact of the electrodes will be established not lower than 95%, to finalize the assembly of equipment, the Hololens augmented reality glasses will be positioned.
For the analysis of results, the ordinal categorical variables will comply with a statistical analysis based on contingency tables and frequency diagrams. Likewise, a comparison of samples will be carried out to determine the significant differences between them, using the Chi-square test statistic with a p-value <0.05 to reject the null hypothesis of equality.
In the case of continuous data, once the data has been obtained and filtered, it will be analyzed descriptively through the SPSS statistical software where the internal behavior of the data is analyzed from measures of central tendency and position, such as box plots and whiskers to establish consistency in the data.
Finally, the inferential analysis will be carried out, in this case, if the data are parametric, a mean comparison study will be carried out using ANOVA as a test statistic and it will be considered that there are significant differences for p-value <0.05. For non-parametric data: The Kruskal-Wallis test would be used initially to determine if there are differences between the groups and later a Wilcoxon signed rank test to compare the two related samples.
With the analysis of the data, it is expected to accept the established hypothesis that it supposes an improvement in the specific evaluation of external cognitive load caused by the stimulus in graphical user interfaces from the use of multimodal approaches.