MACOC: a medoid-based ACO clustering algorithm

The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning have been focused on clustering, showing great potential of ACO-based techniques. This work presents an ACO-based clustering algorithm inspired by the ACO Clustering (ACOC) algorithm. The proposed approach restructures ACOC from a centroid-based technique to a medoid-based technique, where the properties of the search space are not necessarily known. Instead, it only relies on the information about the distances amongst data. The new algorithm, called MACOC, has been compared against well-known algorithms (K-means and Partition Around Medoids) and with ACOC. The experiments measure the accuracy of the algorithm for both synthetic datasets and real-world datasets extracted from the UCI Machine Learning Repository

Dimensions of situatedness for digital public displays

Public displays are often strongly situated signs deeply embedded in their physical, social, and cultural setting. Understanding how the display is coupled with on-going situations, its level of situatedness, provides a key element for the interpretation of the displays themselves but is also an element for the interpretation of place, its situated practices, and its social context. Most digital displays, however, do not achieve the same sense of situatedness that seems so natural in their nondigital counterparts. This paper investigates people’s perception of situatedness when considering the connection between public displays and their context. We have collected over 300 photos of displays and conducted a set of analysis tasks involving focus groups and structured interviews with 15 participants. The contribution is a consolidated list of situatedness dimensions that should provide a valuable resource for reasoning about situatedness in digital displays and informing the design and development of display systems

Sustaining Educational Reforms in Introductory Physics

While it is well known which curricular practices can improve student performance on measures of conceptual understanding, the sustaining of these practices and the role of faculty members in implementing these practices are less well understood. We present a study of the hand-off of Tutorials in Introductory Physics from initial adopters to other instructors at the University of Colorado, including traditional faculty not involved in physics education research. The study examines the impact of implementation of Tutorials on student conceptual learning across eight first-semester, and seven second-semester courses, for fifteen faculty over twelve semesters, and includes roughly 4000 students. It is possible to demonstrate consistently high, and statistically indistinguishable, student learning gains for different faculty members; however, such results are not the norm, and appear to rely on a variety of factors. Student performance varies by faculty background - faculty involved in, or informed by physics education research, consistently post higher student learning gains than less-informed faculty. Student performance in these courses also varies by curricula used - all semesters in which the research-based Tutorials and Learning Assistants are used have higher student learning gains than those semesters that rely on non-research based materials and do not employ Learning Assistants.Comment: 21 pages, 4 figures, and other essential inf