A Collaborative Lecture in Information Retrieval for Students at Universities in Germany and Switzerland

K3, work in progress, is an acronym for Kollaboration (collaboration), Kommunikation (communication), and Kompetenz (competence). K3 provides a platform in the context of knowledge management to support collaborative knowledge production in learning environments. The underlying hypothesis states that collaborative discourse conciliates information as well as communication competence in learning contexts. The collaborative, communicative paradigm of K3 is implemented by asynchronous communication tools as a means of constructivist learning methodology. In this paper we will describe a K3 course. The lecture was organized and carried out at two places in two different countries (Germany and Switzerland) with students from different universities in the context of Library and Information Science. The paper informs about the management of the lecture and about the problems we had to run the lecture at two places. The circumstances in coordinating the presentations, the exercises, the examinations and evaluation, and the time schedule are presented. The conclusions of the lecturers and the results of a questionnaire for the students are explained in detail

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

Harnessing Collaborative Technologies: Helping Funders Work Together Better

This report was produced through a joint research project of the Monitor Institute and the Foundation Center. The research included an extensive literature review on collaboration in philanthropy, detailed analysis of trends from a recent Foundation Center survey of the largest U.S. foundations, interviews with 37 leading philanthropy professionals and technology experts, and a review of over 170 online tools.The report is a story about how new tools are changing the way funders collaborate. It includes three primary sections: an introduction to emerging technologies and the changing context for philanthropic collaboration; an overview of collaborative needs and tools; and recommendations for improving the collaborative technology landscapeA "Key Findings" executive summary serves as a companion piece to this full report

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Knowledge convergence in computer-supported collaborative learning

This study investigates how two types of graphical representation tools influence the way in which learners use knowledge resources in two different collaboration conditions. In addition, the study explores the extent to which learners share knowledge with respect to individual outcomes under these different conditions. The study also analyzes the relationship between the use of knowledge resources and different types of knowledge. The type of external representation (content-specific vs. content-independent) and the collaboration condition (videoconferencing vs. face-to-face) were varied. Sixty-four (64) university students participated in the study. Results showed that learning partners converged strongly with respect to their use of resources during the collaboration process. Convergence with respect to outcomes was rather low, but relatively higher for application-oriented knowledge than for factual knowledge. With content-specific external representation, learners used more appropriate knowledge resources without sharing more knowledge after collaboration. Learners in the computer-mediated collaboration used a wider range of resources. Moreover, in exploratory qualitative and quantitative analyses, the study found evidence for a relation between aspects of the collaborative process and knowledge convergence

Progressor: Personalized visual access to programming problems

This paper presents Progressor, a visualization of open student models intended to increase the student's motivation to progress on educational content. The system visualizes not only the user's own model, but also the peers' models. It allows sorting the peers' models using a number of criteria, including the overall progress and the progress on a specific topic. Also, in this paper we present results of a classroom study confirming our hypothesis that by showing a student the peers' models and ranking them by progress it is possible to increase the student's motivation to compete and progress in e-learning systems. © 2011 IEEE