BRIDGING THE GAP BETWEEN TECHNOLOGY AND SCIENCE WITH EXAMPLES FROM ECOLOGY AND BIODIVERSITY

Early informatics focused primarily on the application of technology and computer science to a specific domain; modern informatics has broadened to encompass human and knowledge dimensions. Application of technology is but one aspect of informatics. Understanding domain members’ issues, priorities, knowledge, abilities, interactions, tasks and work environments is another aspect, and one that directly impacts application success. Involving domain members in the design and development of technology in their domain is a key factor in bridging the gap between technology and science. This user-centered design (UCD) approach in informatics is presented via an ecoinformatics case study in three areas: collaboration, usability, and education and training

Information dynamics algorithm for detecting communities in networks

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network - inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.Comment: Submitted to "Communication in Nonlinear Science and Numerical Simulation

Modeling User Perception of Interaction Opportunities for Effective Teamwork

This paper presents a model of collaborative decision-making for groups that involve people and computer agents. The model distinguishes between actions relating to participantspsila commitment to the group and actions relating to their individual tasks, uses this distinction to decompose group decision making into smaller problems that can be solved efficiently. It allows computer agents to reason about the benefits of their actions on a collaboration and the ways in which human participants perceive these benefits. The model was tested in a setting in which computer agents need to decide whether to interrupt people to obtain potentially valuable information. Results show that the magnitude of the benefit of interruption to the collaboration is a major factor influencing the likelihood that people will accept interruption requests. They further establish that peoplepsilas perceived type of their partners (whether humans or computers) significantly affected their perceptions of the usefulness of interruptions when the benefit of the interruption is not clear-cut. These results imply that system designers need to consider not only the possible benefits of interruptions to collaborative human-computer teams but also the way that such benefits are perceived by people.Engineering and Applied Science

Colors Effect on Perception from Screen Layout With The View of Human Computer Interaction

This project is a research conducted on Human Computer Interaction (HCI) area. Color is one of the elements in HCI subject which will be discussed in the project research specifically. Color has becomeone of the important subjects in many fields, perhaps one of the important attributes in the study of HCI. When it comes to the designing a system or a web page, HCI also had presented some guidelines to propose color selection, perhaps there is a "why" factor on the subject to question why such color must be use or avoid. In other hand, traditionally designers tend to reflect personnel favoritism on color preferences, normally preferably choice of color or even local customs and believe over designing a system. This project will blend between color science and perception through the view ofHuman Computer Interaction. There are two objectives of the study which is to test and prove that does color effects the users and productivity. Usability testing will be performed and trough the result, this research is targeting to propose a standard of good practice color preferences on page display over a specific system. In this research, the main element to be studied is human factor and the human perception. Two areas of studies relates which is the color science and its fundamental as well as the human perception where the usability testing will be perform to structure and generate findings of the experiment. The scope of research is specifically targeted on 'sensitive system' such as banking system, aircraft, etc. The project consists of five phases of methodology which needs to be simple, and reported in sufficient detail as to be easily replicable. There are three experiments conducted for usability testing which are the video recording session with the 'think aloud method' practice, questionnaires and interview session. The data ofthe experiment will be analyzed and referred back to the fundamental of color science. At the end of the research, a standard of recommended 'Good Practice Color' will be proposed

Motivation theories and implications for teaching and learning in the biosciences

Learning is fundamental throughout the development of human life. It is also known that motivation is a key factor to successful learning. The pre-entry attributes of the student (Terenzini & Pascarella, 1980) including their own internal attitudes and motivations, are considered important for successful integration into a university system. In addition, Tinto (1975) has maintained that pre-university schooling is important for academic and social integration of students and hence their learning and motivation as deduced from successful completion rates. A pivotal goal of higher education is for students ‘to learn how to learn.’ A variety of teaching approaches encourage students to adopt a deep approach to learning by seeking a personal understanding. Within the science domain, the recent Science and Innovation White Paper (HEFCE 2008) highlighted ‘the critical role that higher education plays in the competitiveness of the nation and the productivity of its public services’. A good supply of well-trained, talented and motivated researchers is essential for research excellence and innovation. The challenge therefore, for higher education, is to skill and motivate science students to become creative and entrepreneurial ‘lifelong learners’ in a fast changing work environment that provides better health care, ensures a cleaner, safer environment, and builds on the existing science base to ensure excellence. For the Biosciences disciplines, QAA Benchmark statements specify motivating and challenging the student with the use of a ‘skilled and balanced selection of teaching and learning techniques’ (QAA website). Blended learning is recommended through a wide range of teaching methods - including laboratory sessions, self-directed study, computer-aided learning, case studies and problem-based learning, demonstrations, active learning sets, work-based learning and/or placements, reflective practice, research project work - and assessment strategies. This paper provides an overview of theories of motivation based on the work of some motivation theorists. Some key principles are identified from the literature that link cognition, motivation and learning and which could have application in the teaching of Biosciences towards the goal of lifelong learning