Combat vehicle identification: An adaptive computer-based training system incorporating a hybrid adult learning model and rich imagery
James Doyle Bass, Drexel University, United States
Drexel University . Awarded
The purpose of this research is to investigate the potential benefits of incorporating new Computer-Based Training (CBT) technology and implementing learning style models developed by the adult education research community to improve Combat Vehicle Identification (CVI) training. The multidisciplinary research approach chosen required the use of both qualitative and quantitative research methodologies. The investigation includes an experiment using a rapid prototype CBT CVI system. Three versions of the prototype were built to investigate three potential presentation designs (traditional military lecture, traditional lecture with rich imagery, and multiple styles with rich imagery). Subjects were evaluated using three performance tests, and they completed a systems evaluation questionnaire. Selected subjects also participated in detailed interviews.
Findings revealed that subjects training with rich imagery of combat vehicles and user selectable multiple presentation styles achieved higher scores over subjects training with a lecture presentation style without rich imagery or with a lecture style using rich imagery. Analysis of the test results and evaluation of subjects using various training modules within the prototype yielded a set of heuristics suggesting presentation design specifications and implementation strategies.
We seek to show how adopting these design heuristics and implementing a recommended change in the performance testing methodology can improve student performance in both classroom and tactical environments. This research has found evidence to support the advancement of the prototyped system to the next level of development (a high resolution prototype) and proposes to evaluate its performance in true field and garrison environments.
Bass, J.D. Combat vehicle identification: An adaptive computer-based training system incorporating a hybrid adult learning model and rich imagery. Ph.D. thesis, Drexel University.
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