A study of undergraduate students’ use of educational technologies

A qualitative study was conducted to investigate the use of technology by undergraduate students at a large public research university. Forty student interviews were conducted, 20 female students and 20 male students. Students were asked questions about their technology usage, such as: How do you use technology for academic purposes, What kinds of technological devices do you use, What software and applications do you use? Students’ were also asked questions about the usage of technology in classrooms and the university’s technology resources. The findings of this study indicate that a variety of commonly available technological tools such as email, web browsers, presentation software, learning management systems, and the internet are being used by undergraduate students and their instructors. Such usage is prevalent both inside and outside the classroom. Somewhat more specialized tools are used in different disciplines. Based on the findings of the study, the authors identify a similarity between a “gear” and technology use by faculty members and students

Improving the Scalability of an Exact Approach for Frequent Item Set Hiding

Technological advances have led to the generation of large databases of organizational data recognized as an information-rich, strategic asset for internal analysis and sharing with trading partners. Data mining techniques can discover patterns in large databases including relationships considered strategically relevant to the owner of the data. The frequent item set hiding problem is an area of active research to study approaches for hiding the sensitive knowledge patterns before disclosing the data outside the organization. Several methods address hiding sensitive item sets including an exact approach that generates an extension to the original database that, when combined with the original database, limits the discovery of sensitive association rules without impacting other non-sensitive information. To generate the database extension, this method formulates a constraint optimization problem (COP). Solving the COP formulation is the dominant factor in the computational resource requirements of the exact approach. This dissertation developed heuristics that address the scalability of the exact hiding method. The heuristics are directed at improving the performance of COP solver by reducing the size of the COP formulation without significantly affecting the quality of the solutions generated. The first heuristic decomposes the COP formulation into multiple smaller problem instances that are processed separately by the COP solver to generate partial extensions of the database. The smaller database extensions are then combined to form a database extension that is close to the database extension generated with the original, larger COP formulation. The second heuristic evaluates the revised border used to formulate the COP and reduces the number of variables and constraints by selectively substituting multiple item sets with composite variables. Solving the COP with fewer variables and constraints reduces the computational cost of the processing. Results of heuristic processing were compared with an existing exact approach based on the size of the database extension, the ability to hide sensitive data, and the impact on nonsensitive data

The Internet of Things: Can a Tree Talk to You?

Farm productivity is essential for meeting the growing demand for food that is fueled by rapid population growth around the world. Farming practices can obtain the greatest optimization and profitability through “smart agriculture” which adapts farming techniques to specific conditions via enabling technologies that are often based on an Internet of Things (IoT). This paper presents a case study of an IoT innovation in an unexpected location – a rural farm in Vietnam. A practical, low-cost, and environmental friendly system was developed that help farmers manage their crops with more precision in the first IoT application for the Vietnamese agriculture industry. The pilot implementation were promising and farmer feedback was positive. After some modifications, the system has been widely deployed in different provinces in Vietnam. We believe that the system would be able to help millions of farmers to get on the IoT train and that adopting IoT to initiate smart agriculture in Vietnam has sent a strong message “To be successful, the technological innovation has to integrate into local culture”