Modeling usage of an online research community

Although online communities have been thought of as a new way for collaboration across geographic boundaries in the scientific world, they have a problem attracting people to keep visiting. The main purpose of this study is to understand how people behave in such communities, and to build and evaluate tools to stimulate engagement in a research community. These tools were designed based on a research framework of factors that influence online participation and relationship development. There are two main objectives for people to join an online community, information sharing and interpersonal relationship development, such as friends or colleagues. The tools designed in this study are to serve both information sharing and interpersonal relationship development needs. The awareness tool is designed to increase the sense of a community and increase the degree of social presence of members in the community. The recommender system is designed to help provide higher quality and personalized information to community members. It also helps to match community members into subgroups based on their interests. The designed tools were implemented in a field site - the Asynchronous Learning Networks (ALN) Research community. A longitudinal field study was used to evaluate the effectiveness of the designed tools. This research explored people\u27s behavior inside a research community by analyzing web server logs. The results show that although there are not many interactions in the community space, the WebCenter has been visited extensively by its members. There are over 2,000 hits per day on average and over 5,000 article accesses during the observation period. This research also provided a framework to identify factors that affect people\u27s engagement in an online community. The research framework was tested using the PLS modeling method with online survey responses. The results show that perceived usefulness performs a very significant role in members\u27 intention to continue using the system and their perceived preliminary networking. The results also show that the quality of the content of the system is a strong indicator for both perceived usefulness of the community space and perceived ease of use of the community system. Perceived ease of use did not show a strong correlation with intention to continue use which was consistent with other studies of Technology Acceptance Model (TAM). For the ALN research community, this online community helps its members to broaden their contacts, improve the quality and quantity of their research, and increase the dissemination of knowledge among community members

A Study Of The Effects Of Computer Animated Character Body Style On Perception Of Facial Expression

This study examined if there is a difference in viewer perception of computer animated character facial expressions based on character body style, specifically, realistic and stylized character body styles. Participants viewed twenty clips of computer animated characters expressing one of five emotions: sadness, happiness, anger, surprise and fear. They then named the emotion and rated the sincerity, intensity, and typicality of each clip. The results indicated that for recognition, participants were more slightly more likely to recognize a stylized character although it was not a significant difference. Stylized characters were on average rated higher for sincerity and intensity and realistic characters were on average rated higher for typicality. A significant difference in ratings was shown with fear (within sincerity and typicality) having realistic characters rated higher, happiness (within sincerity and intensity) having stylized characters rated higher and stylized being rated higher once for anger (stylized) and realistic (typicality) being rated once for anger. Other differences were also noted within the dependent variables. Based on the data collected in this study, overall there was not a significant difference in participant ratings between the two character styles

Techniques for grading programming labs

Techniques for manual and automated grading of programming labs are discussed. Topics investigated include: general grading of programming labs, plagiarism detection, pro gram documentation, program output, and program efficiency. This investigation led to the development of automated grading tools that report on style and point to possible instances of plagiarism. The techniques utilized will be discussed and their use demonstrated

The Influence of Software Risk Management on Software Project Success

Software development project still of high failure rates. A diversity of risk management approaches are suggested by researchers and followed by organizations in order to minimize the failure rate and ensure project success. However, does risk management do always what it is supposed to do? In this research, we survey field workers and interview project managers, to investigate the influence of risk management on project success in practice, and to explore and reveal situations where risk management could lead to failure. We also try to find if there is a relation between risk management and different software project success criteria, as well as customer satisfaction. We also give some recommendations to help field workers performing a better risk management process

Unleashing Crowd Wisdom: Leveraging Cognitive Memory Structures to Increase Quality of User-Generated Content

In recent years, online information sharing platforms have opened new opportunities for people to share information and experiences with each other and with organizations that sponsor these platforms. Increasingly, data consumers, both at the organizational and at the individual level, hope to use these User-Generated Content (UGC) in their decision making. However, recent studies uncovered significant challenges associated with the interfaces used to collect high-quality UGC. While many aspects of the information quality (IQ) of UGC have been studied, the role of data structures in gathering UGC and the nature of shared content have yet to receive attention. UGC is created on online platforms with varying degrees of data structure, ranging from unstructured (e.g., open box fields) to highly structured formats (e.g., rigid and specific forms). Despite much research on UGC, we have little understanding of the appropriate degree of data structures in data collection and its impact on the quality of information. Moreover, we know that most of the produced UGC originates in the declarative memory of the contributors. Psychology literature shows that different types of memory are stored and managed differently, and that they are retrieved accordingly. Thus, we argue that the information collection interface for retrieving and collecting each type of memory should be aligned with the way that it was stored. Therefore, we posit that designing interfaces with sensitivity to human memory structures should result in improvements of the IQ of UGC. We conducted several experiments to examine differently-designed information collection interfaces for different types of information. We evaluated both data creators’ and data consumers’ perceived quality of information collection, at the individual level. The findings support our claims of the importance of these factors for information quality. This research demonstrates a connection between information system interface design and human memory, which eventually could result in changes to best practices in interface design. This could, in turn, lead to improved interaction between participants and organizations, including enhanced data creators’ self-expression, improved users’ attitudes toward UGC systems, and increased value-add from organizations’ use of UGC