The design and development of quantum algorithms present a challenge, especially for inexperienced computer science students. Despite the numerous common concepts with classical computer science, quantum computation is still considered a branch of theoretical physics not commonly used by computer scientists. Experimental research into the development of a quantum computer makes the use of quantum mechanics in organizing computation more attractive, however the physical realization of a working quantum computer may still be decades away.
This study introduces quantum computing to computer science students using a quantum algorithm animator called QuAL. QuAL's design uses features common to classical algorithm animators guided by an exploratory study but refined to animate the esoteric and interesting aspects of quantum algorithms.
In addition, this study investigates the potential for the animation of a quantum sorting algorithm to help novice computer science students understand the formidable concepts of quantum computing. The animations focus on the concepts required to understand enough about quantum algorithms to entice student interest and promote the integration of quantum computational concepts into computer science applications and curricula.
The experimental case study showed no significant improvement in student learning when using QuAL's initial prototype. Possible reasons include the animator's presentation of concepts and the study's pedagogical framework such as choice of algorithm (Wallace and Narayanan's sorting algorithm), design of pre- and post tests, and the study's small size (20 students) and brief duration (2 hours). Nonetheless, the animation system was well received by students. Future work includes enhancing this animation tool for illustrating elusive concepts in quantum computing.
| Identifer | oai:union.ndltd.org:nova.edu/oai:nsuworks.nova.edu:gscis_etd-1261 |
| Date | 01 January 2010 |
| Creators | Nicholson, Lori Eileen |
| Publisher | NSUWorks |
| Source Sets | Nova Southeastern University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CEC Theses and Dissertations |
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