In the modern society, which is technologically driven, it is important to have a clear understanding of the influence of the computer malfunctions on the users. This is because there is a thin line between computers and human beings. Therefore it is important to measure the experience of users while interacting with information systems or technology. Consequently, computer interactions can lead to various malfunctions in the human brain and physiology. The malfunctions can result in measurable effects on users’ emotional, behavioral and cognitive responses. The experiment was conducted, and the participants had to wear a galvanic skin responses sensors and functional near-infrared spectroscopy.

It is a common occurrence to use surveys to gain reports on the physiological and cognitive state of humans during their interactions with computers, for example, use of semantic differentials.  According to Hirshfield, Bobko, Barelka, Hirshfield, Farrington, Gulbronson and Paverman (2014), surveys have been commonly used as a form of measurements. However, they have their drawbacks that have contributed to the development of new measurement methods.

The present study uses non-invasive brain measurement. The focus is to measure the objective and real-time changes in the user. In introducing the concept, investigators draw on the previous studies. The objective of the study is to demonstrate the feasibility associated with applying the fNIRS with the objective of measuring the state of users in real time when they either interact or work with computer systems. To achieve the objective, the author outlines the literature on the emotional, trust, workload, emotional state and suspicion. Consequently, the authors also describe the specific studies, which guide the hypothesis and experimental goals. This makes it easier for readers to identify the different variables in the study and relate them with the objective.

Investigators use an experimental design to meet the study’s objectives. Participants entailed 11 college students. The ethical considerations were adhered to. However, researchers could have defined experimental design and further explained the sampling technique employed.  The instrument used was a pre-experimental survey. It could have been ideal if they could have expounded on the reasons for the chosen instrument. The tasks and manipulations of the participants are well explained. This provides readers with a clear insight into what the entire study entails. Additionally, the pre-survey motivated participants to engage in the research. To ensure reliability, the investigators also conducted baseline, slow internet manipulation, and malware manipulation. The debriefing and suspicion exit was used with the objective of informing the participants about the nature of the study. This further assisted in testing the hypothesis and meeting the study’s objectives. The experiment survey was important for both the investigators and the participants. The collected data are well presented. However, it could have been ideal if the collected data was represented in the form of tables and charts for easy comparison, readability, and comprehension.

On the interpretation and analysis, Hirshfield, et al. (2014), stated the hypothesis. This acts as a reminder to the readers. The hypotheses are marked as H1b and H1 corollary. The objective is to prove the hypotheses using brain-based and physiological measurements. However, it could have been clearer if the investigators could have mentioned the type of data analysis used.

In conclusions, the paper is well written. The introduction gives insight into the objective of the study and makes readers identify with other sections such as methodology, literature review, data analysis technique and communication of the findings.

References

Hirshfield, L. M., Bobko, P., Barelka, A., Hirshfield, S. H., Farrington, M. T., Gulbronson, S., & Paverman, D. (2014). Using noninvasive brain measurement to explore the psychological effects of computer malfunctions on users during human-computer interactions. Advances in Human-Computer Interaction, 2014(2), 1-13.

 
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