Team Formation for Scheduling Educational Material in Massive Online Classes

Whether teaching in a classroom or a Massive Online Open Course it is crucial to present the material in a way that benefits the audience as a whole. We identify two important tasks to solve towards this objective, 1 group students so that they can maximally benefit from peer interaction and 2 find an optimal schedule of the educational material for each group. Thus, in this paper, we solve the problem of team formation and content scheduling for education. Given a time frame d, a set of students S with their required need to learn different activities T and given k as the number of desired groups, we study the problem of finding k group of students. The goal is to teach students within time frame d such that their potential for learning is maximized and find the best schedule for each group. We show this problem to be NP-hard and develop a polynomial algorithm for it. We show our algorithm to be effective both on synthetic as well as a real data set. For our experiments, we use real data on students' grades in a Computer Science department. As part of our contribution, we release a semi-synthetic dataset that mimics the properties of the real data

The Cowl - v.81 - n.20 - Mar 23, 2017

The Cowl - student newspaper of Providence College. Volume 81, Number 20 - March 23, 2017. 24 pages

BIMing the architectural curricula: integrating Building Information Modelling (BIM) in architectural education

Building Information Modelling (BIM) reflects the current heightened transformation within the Architectural, Engineering and Construction (AEC) Industry and the Facilities and Management (FM) sector, offering a host of benefits from increased efficiency, accuracy, speed, co-ordination, consistency, energy analysis, project cost reduction etc to various stake holders from owners to architects, engineers, contractors and other built environment professionals. Many countries around the world are responding to this paradigm shift including the United Kingdom (UK). The Cabinet office took the decision in 2011 to make the use of collaborative 3D BIM technology mandatory for all public sector construction contracts by 2016 (Cabinet Office, 2011). According to Smith and Tardif, despite certain myths and misconceptions surrounding BIM, its rate of implementation has been much faster in comparison to the availability of professionals skilled in use of BIM, thus creating a skill gap in the design and construction industry (Smith and Tardif, cited in Barison and Santos, 2010a). This article aims at bridging the gap between the graduate skill sets and the changing needs of the profession. The research methodology adopted consists of thoroughly reviewing the existing literature in this subject area coupled with carrying out a survey of accredited Schools of Architecture in the UK. The analysis of the survey questionnaire results shows the extent to which BIM is currently being taught and identifies the barriers where its implementation has either been slow or not yet started. The paper highlights the fact that there has been considerable delay in the successful integration of BIM in the Schools of Architecture in the UK, thus emphasising the need for expeditiously training and preparing students in the use of BIM making them ready to effectively perform in a BIM enabled work arena

The Cowl - v.81 - n.14 - Jan 26, 2017

The Cowl - student newspaper of Providence College. Volume 81, Number 14 - January 26, 2017. 24 pages

Team formation instruments to enhance learner interactions in open learning environments

Open learning environments, such as Massive Open Online Courses (MOOCs), often lack adequate learner collaboration possibilities; they are also plagued by high levels of drop-out. Introducing project-based learning (PBL) can enhance learner collaboration and motivation, but PBL does not easily scale up into MOOCS. To support definition and staffing of projects, team formation principles and algorithms are introduced to form productive, creative, or learning teams. These use data on the project and on learner knowledge, personality and preferences. A study was carried out to validate the principles and the algorithms. The data were provided by students (n=168) and educational practitioners (n=56). The principles for learning teams and productive teams were accepted, while the principle for creative teams was not. The algorithms were validated using team classifying tasks and team ranking tasks. The practitioners classify and rank small productive, creative and learning teams in accordance with the algorithms, thereby validating the algorithms outcomes. When team size grows, for practitioners, forming teams quickly becomes complex, as demonstrated by the increased divergence in ranking and classifying accuracy. Discussion of the results, conclusions, and directions for future research are provided