Virtual reality simulations represent a much-needed effort to move beyond the shortcomings of traditional form-based assessments. Within VR, we assess competency and problem-solving skills versus the content memorization typically supported by conventional measures. This chapter explores an innovative VR simulation recently deployed at Western Governors University. The authors explored the utility of a VR simulation as an assessment tool when students engaged in more inclusive, immersive, and interactive experiences compared to conventional methods. The authors investigated students' summative assessment scores across a 2D (desktop) and 3D VR (headset) version and how additional factors like motion sickness, cognitive workload, and system usability impacted their scores. The results showed that students in the Desktop version outperformed those in the VR version on the summative assessment while feeling equally immersed in the simulation. Implications for future research are discussed, especially for optimizing learning experiences in an online competency-based higher education program.
TopIntroduction
Somewhere at the intersection between competency-based instruction and workforce demand exists an opportunity to apply what we currently know about how students learn to build competency-based credentials supported by practice scholarship. Science supports learning that builds from and inextricably links to the environment, the situations, and the working culture in which students will eventually find themselves (Schumacher, Englander, and Carpaccio, 2013). Within online competency-based higher education (OCBHE), learning is no longer viewed as a process of transmitting knowledge from instructor to student (e.g., sitting passively, listening to a lecture, taking notes, and applying concepts) but as an active process acquired through a variety of instructional and media types. As a result, students' capacity to develop a particular domain's competency and then transfer that knowledge to future job performance improves.
At a fundamental level, the term transfer refers to the influence of prior learning on later activity (Holding, 1991). Initial research began in the early 20th century, when Woodrow (1927) claimed, for example, that “improvement resulting from almost any sort of practice yields, as a rule, some transference” (p. 159). He suggested that any practice on a given task produces improvement (i.e., positive transfer) in several related functions. Today, OCBHE programs' criticality in training the next generation's workforce has become evident now that employers focus on identifying, recruiting, and retaining employers with transferable skills. Particularly in times of economic challenge, employers need a skilled, adaptable, creative, and equipped workforce for success in the global marketplace.
To meet this demand, institutions of higher learning are beginning to realize the importance of real-world, performance-based measures like virtual reality (VR) simulations, where performance demonstrations are crucial to success. Central to the development of VR simulations is the need for high-fidelity demonstrations of learner aptitudes and competencies that include a significant emphasis on cognitive abilities (i.e., knowing what) and the performance of those abilities (i.e., demonstrating how). The most important advantage of this testing mode is the real-world relevance that can be incorporated into the assessment, and technological innovations continue to expand these opportunities.
This chapter explores some fundamental principles currently being incorporated into the science of teaching at Western Governors University (WGU) and examines their effectiveness in an OCBHE program. These basic principles are summarized below:
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Skill acquisition is specific to the conditions practiced during training, and many training programs are only effective to the extent that training will transfer to new situations. Inefficiently developed training programs can interfere with developing flexible solutions to problem-solving. Programs that train students using a variety of technologies must also evaluate students using those technologies if they want to maximize training transfer.
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Training that promotes attention flexibility improves learning. Lessons from dual-task studies suggest that compared to learning single tasks alone, when tasks are practiced together, the cognitive system can coordinate task performance and minimize interference, thus, maximizing learning.
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Learning complex tasks requires variability in training to maximize learning. The most robust learning is likely to result from a combination of many experiences that allows students to engage in multiple attention processes when planning and executing solutions from memory.
A key element to each of these principles is that reviewing the same materials at different times and using reorganized contexts from other objectives and perspectives is essential for attaining advanced knowledge acquisition goals. The knowledge that will eventually be used in many ways must be represented, organized, and assessed in many ways. The alternative is knowledge only usable in situations where learners acquired the skill.