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

Composite Web Services Formation Using a Social Network of Web Services: A Preliminary Investigation

A composite Web service, such as arranging a travel to a conference, can be viewed as a project team that is comprised of several members who want to collaborate in order to accomplish a specific goal. In this work, we propose an algorithm for searching a social network of Web services in order to select an effective set of Web services that can collaborate in order to attain the main goal of the composite Web service at hand. Ultimately, the selection algorithm takes into consideration the set of functions that each Web services member possesses, e.g., hotel booking, car rental, etc., and the communication cost among these members. Our goal is to secure all the functions required by the composite Web service yet minimizing the communication overhead. The preliminary design of the experiments and the future work are described. © 2011 Published by Elsevier Ltd

Capstone Teams: An Industry Based Model

Project teams, a mainstay in industry practice, are being employed in many capstone design courses. This paper examines industry models for teams and their application to a specific capstone design course. Following Katzenbach and Smith’s basics of high performing teams, teams are formed based on individuals skills. The team is made accountable and committed both as a group and as individuals through the structure and format of the course. The course structure is then planned so that teams progress through Tuckman’s development stages of forming, storming, norming and performing, during their two semester capstone design project

From Group Recommendations to Group Formation

There has been significant recent interest in the area of group recommendations, where, given groups of users of a recommender system, one wants to recommend top-k items to a group that maximize the satisfaction of the group members, according to a chosen semantics of group satisfaction. Examples semantics of satisfaction of a recommended itemset to a group include the so-called least misery (LM) and aggregate voting (AV). We consider the complementary problem of how to form groups such that the users in the formed groups are most satisfied with the suggested top-k recommendations. We assume that the recommendations will be generated according to one of the two group recommendation semantics - LM or AV. Rather than assuming groups are given, or rely on ad hoc group formation dynamics, our framework allows a strategic approach for forming groups of users in order to maximize satisfaction. We show that the problem is NP-hard to solve optimally under both semantics. Furthermore, we develop two efficient algorithms for group formation under LM and show that they achieve bounded absolute error. We develop efficient heuristic algorithms for group formation under AV. We validate our results and demonstrate the scalability and effectiveness of our group formation algorithms on two large real data sets.Comment: 14 pages, 22 figure

Crewing of Sea Vessels Taking into Account Project Risks and Technical Condition of Ship Equipment

Motivation: One of the main concepts in project management is the concept of “team†in the project, and in project management - the human resources management of the project, which includes the processes of planning, forming and creating a team, its development and support activities, transformation or disbandment of the team. Despite the great attention paid to the formation of project management teams, existing studies do not fully highlight the specifics and features of crew operations. Criteria for the quantitative optimization of the ship's crew should be consistent with the main objectives of the project.Novelty: The research paper proposes an approach that allows optimizing the quantitative composition of the crew of a ship by more accurately assessing the level of project risks and costs associated with the maintenance of ship equipment. The practical application of this approach will optimize the quantitative composition of the ship's crew, which will both satisfy the needs of managing the technical equipment and minimize the risks and costs of the shipowner.Methodology and Methods: Risk management tools were used to achieve the objective and test the hypotheses suggested in the research, namely: methodology for estimating the net present value of the project; the method of estimating internal rate of return for the project; the method of estimating the return on investment in the project; the method of estimation for the period of return on investment costs in the project; the method of estimating the discounted payback period for the project, as well as the tools of simulation modelling (Monte Carlo simulation method). The method of identification and grouping in the process of classification of project risks in the sphere of marine transportation, methods of systematization, grouping and logical generalization were also applied for systematization of information, drawing conclusions and making scientific suggestions in the research.Policy Considerations: Shipping plays an important role in the trade and tourism industry; human factor is the most important aspect that determines the efficiency of shipping development; maintaining of technical and technological processes of the ship puts certain requirements to the quantitative and qualitative composition of the team, deviation from which leads to the occurrence of certain risk events; formation of an effective model of ship's crew manning is the main link in ensuring effective shipping project management

TWO MULTI-OBJECTIVE STOCHASTIC MODELS FOR PROJECT TEAM FORMATION UNDER UNCERTAINTY IN TIME REQUIREMENTS

Team formation is one of the key stages in project management. The cost associated with the individuals who form a team and the quality of the tasks completed by the team are two of the main concerns in team formation problems. In this study, two mathematical models to optimize simultaneously cost and quality in a team formation problem are developed. Because team formation problem arises in uncertain environment, different scenarios are defined for the time requirement of the project. Two-stage stochastic programming and multi-stage stochastic programming are applied to solve the first and the second model respectively. The presented models and their solution methodology can be applied in different types of projects. In this study, a project that involves an overhaul of an aircraft is presented as a case study in which the goals are to minimize staffing costs and maximize the reliability of the aircraft by staffing workforce with high competency