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This paper explores whether students' learning outcomes can be improved through the use of self-assessment rubrics. Students on a computer programming module in a Higher Education Institution were required to complete a self-assessment using the same rubric as the assessors. Observing discrepancies between the grades the students were receiving, and the grades the students thought they should be receiving, the lecturers made improvements to the pedagogical approaches taken for some elements of the course by changing the format and focus of classroom activities. This resulted in both improved grades and improved self-regulation by students. The process was facilitated through a system created by the authors of the paper called SAFE (Self-Assessment Feedback and Evaluation Learner Lifecycle), which greatly enhances the learner feedback lifecycle of an assignment. The research corroborates existing studies around the importance of revisiting feedback both for assessor and student.

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Cyber security analysts use data visualizations to speed up ingestion of security data. These visualizations typically take the form of 2D graphics displayed on computer monitors. Virtual reality has the potential to improve these visualizations with immersive 3D environments and unique interaction mechanics. However, research into this newly synergised area lacks evaluation, leading to unfounded claims of effectiveness. A potential cause for these missing evaluations was identified as a lack of guidance detailing how evaluations should be conducted in this area. Additionally, the small amount of research that does include evaluation incorrectly relies on subjective participant opinions to objectively measure system effectiveness. An example of this misuse is asking participants which system they thought was quicker, rather than timing them. The objective of this paper was to propose a solution to these issues in the form of a surveyed, categorised, and analysed set of evaluation metrics. A total of 49 metrics were identified from 41 papers. The presented metrics detail which dependent variables should be considered when evaluating works in the combined fields of cyber security, data visualization, and virtual reality. These metrics can be used to produce more accurate evaluations in future works in this area.

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