An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.

DESIGN AND IMPLEMENTATION OF HOME USE PORTABLE SMART ELECTRONICS

The widespread of low cost embedded electronics makes it easier to implement the smart devices that can understand either the environment or the user behaviors. The main object of this project is to design and implement home use portable smart electronics, including the portable monitoring device for home and office security and the portable 3D mouse for convenient use. Both devices in this project use the MPU6050 which contains a 3 axis accelerometer and a 3 axis gyroscope to sense the inertial motion of the door or the human hands movement. For the portable monitoring device for home and office security, MPU6050 is used to sense the door (either home front door or cabinet door) movement through the gyroscope, and Raspberry Pi is then used to process the data it receives from MPU6050, if the data value exceeds the preset threshold, Raspberry Pi would control the USB Webcam to take a picture and then send out an alert email with the picture to the user. The advantage of this device is that it is a small size portable stand-alone device with its own power source, it is easy to implement, really cheap for residential use, and energy efficient with instantaneous alert. For the 3D mouse, the MPU6050 would use both the accelerometer and gyroscope to sense user hands movement, the data are processed by MSP430G2553 through a digital smooth filter and a complementary filter, and then the filtered data will pass to the personal computer through the serial COM port. By applying the cursor movement equation in the PC driver, this device can work great as a mouse with acceptable accuracy. Compared to the normal optical mouse we are using, this mouse does not need any working surface, with the use of the smooth and complementary filter, it has certain accuracy for normal use, and it is easy to be extended to a portable mouse as small as a finger ring.

INNOVATIVE HUMAN-COMPUTER INTERACTIONS TO SUPPORT COGNITIVE COLLABORATIVE GEOSPATIAL ENVIRONMENTS

In the current world geospatial information is being demanded in almost real time, which requires the speed at which this data is processed and made available to the user to be at an all-time high. In order to keep up with this ever increasing speed, analysts must find ways to increase their productivity. At the same time the demand for new analysts is high, and current methods of training are long and can be costly. Through the use of human computer interactions and basic networking systems, this paper explores new ways to increase efficiency in data processing and analyst training.