Consequences of Connection: Loneliness, Reading, and Robots

Modern communication technologies are reshaping the ways humans connect with one another as well as how we converse with machines of our own making. Our question in this essay is whether digital communication is changing the nature of conversation and, if so, what the implications may be for us as people. Our analysis identifies three sets of parameters for approaching these issues: linguistic (structure of conversations, communication medium, modulating the conversation to suit the perceived needs of our interlocutor, controlling the conversation), social (inner- or other-directed behavior, front stage or back stage behavior, strong or weak social ties, loneliness), and cognitive (level of intellectual engagement). We use these parameters to explore some of the linguistic, social, and cognitive consequences of electronically-mediated communication, of social reading onscreen, and of conversing with social robots

Spartan Daily, November 19, 2003

Volume 121, Issue 58https://scholarworks.sjsu.edu/spartandaily/9924/thumbnail.jp

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Human Factors in Agile Software Development

Through our four years experiments on students' Scrum based agile software development (ASD) process, we have gained deep understanding into the human factors of agile methodology. We designed an agile project management tool - the HASE collaboration development platform to support more than 400 students self-organized into 80 teams to practice ASD. In this thesis, Based on our experiments, simulations and analysis, we contributed a series of solutions and insights in this researches, including 1) a Goal Net based method to enhance goal and requirement management for ASD process, 2) a novel Simple Multi-Agent Real-Time (SMART) approach to enhance intelligent task allocation for ASD process, 3) a Fuzzy Cognitive Maps (FCMs) based method to enhance emotion and morale management for ASD process, 4) the first large scale in-depth empirical insights on human factors in ASD process which have not yet been well studied by existing research, and 5) the first to identify ASD process as a human-computation system that exploit human efforts to perform tasks that computers are not good at solving. On the other hand, computers can assist human decision making in the ASD process.Comment: Book Draf

TechNews digests: Jan - Mar 2010

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

Addressing Data Concerns and Usage through Law of Attraction on using Intelligent Voice Assistants in Language Classrooms

Data-mining done by data companies on ICT tools and the law of attraction comes out with a similar idea in terms of the outcome produced. In order to comprehend the idea, this paper dwells into the data rights, privacy policies and securities of the target application (Google Assistant and Amazon Alexa) that are used in the process of language teaching and learning. A lot of researches focus on the implication of ICT tools in language classrooms and so this paper reports on the ethical considerations that must be looked into before implementation of any ICT tools in language classrooms. Reasons for and against the use of Voice Assistants in terms of data privacy have been discussed with detailing on the similarities between the theory of law of attraction and the effect of data mining. The findings suggest that the constant and productive use of ICT tools in language classrooms will alter the students ’data pattern towards his/her area of study. The research suggests that it is the duty and obligation of the implementer to verify the tools to be inculcated and use it productively