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Funded by innovative programs at the National Science Foundation and the Howard Hughes Medical Institute, University of Richmond faculty in biology, chemistry, mathematics, physics, and computer science teamed up to offer first- and second-year students the opportunity to contribute to vibrant, interdisciplinary research projects. The result was not only good science but also good science that motivated and informed course development. Here, we describe four recent undergraduate research projects involving students and faculty in biology, physics, mathematics, and computer science and how each contributed in significant ways to the conception and implementation of our new Integrated Quantitative Science course, a course for first-year students that integrates the material in the first course of the major in each of biology, chemistry, mathematics, computer science, and physics. 相似文献
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Paul Şerban Agachi 《Higher Education in Europe》2006,31(3):309-315
This paper approaches the multiple employment issues in Romanian Higher Education with a special focus on “Babe?‐Bolyai” University (BBU) in Cluj‐Napoca. There are 119 higher education institutions in Romania and it is becoming increasingly common for the academic staff to have at least two to three paid teaching loads, while undertaking almost no relevant, internationally recognized, research. The paper analyses the environment in which BBU is acting; the dangers of decreasing the quality of teaching and research/services; possible types of desirable multiple employment and the measures taken to diminish the consequences of undesirable multiple employment. 相似文献
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Improving workplace-based assessment and feedback by an E-portfolio enhanced with learning analytics
Marieke van der Schaaf Jeroen Donkers Bert Slof Joyce Moonen-van Loon Jan van Tartwijk Eric Driessen Atta Badii Ovidiu Serban Olle Ten Cate 《Educational technology research and development : ETR & D》2017,65(2):359-380
Electronic portfolios (E-portfolios) are crucial means for workplace-based assessment and feedback. Although E-portfolios provide a useful approach to view each learner’s progress, so far options for personalized feedback and potential data about a learner’s performances at the workplace often remain unexploited. This paper advocates that E-portfolios enhanced with learning analytics, might increase the quality and efficiency of workplace-based feedback and assessment in professional education. Based on a 5-phased iterative design approach, an existing E-portfolio environment was enhanced with learning analytics in professional education. First, information about crucial professional activities for professional domains and suited assessment instruments were collected (phase 1). Thereafter probabilistic student models were defined (phase 2). Next, personalized feedback and visualization of the personal development over time were developed (phase 3). Then the prototype of the E-portfolio—including the student models and feedback and visualization modules—were implemented in professional training-programs (phase 4). Last, evaluation cycles took place and 121 students and 30 supervisors from five institutes for professional education evaluated the perceived usefulness of the design (phase 5). It was concluded that E-portfolios with learning analytics were perceived to assist the development of students’ professional competencies and that the design is only successful when developed and implemented through the eyes of the users. Feedback and assessment methods based upon learning analytics can stimulate learning at the workplace in the long run. Practical, technological and ethical challenges are discussed. 相似文献
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Ovidiu Șerban Nicholas Thapen Brendan Maginnis Chris Hankin Virginia Foot 《Information processing & management》2019,56(3):1166-1184
Interest in real-time syndromic surveillance based on social media data has greatly increased in recent years. The ability to detect disease outbreaks earlier than traditional methods would be highly useful for public health officials. This paper describes a software system which is built upon recent developments in machine learning and data processing to achieve this goal. The system is built from reusable modules integrated into data processing pipelines that are easily deployable and configurable. It applies deep learning to the problem of classifying health-related tweets and is able to do so with high accuracy. It has the capability to detect illness outbreaks from Twitter data and then to build up and display information about these outbreaks, including relevant news articles, to provide situational awareness. It also provides nowcasting functionality of current disease levels from previous clinical data combined with Twitter data.The preliminary results are promising, with the system being able to detect outbreaks of influenza-like illness symptoms which could then be confirmed by existing official sources. The Nowcasting module shows that using social media data can improve prediction for multiple diseases over simply using traditional data sources. 相似文献
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Anişoara Henrieta Mitrea-Şerban 《Higher Education in Europe》2000,25(2):237-241
With reference to the question of women and of socio-cultural minorities in higher education, the author examines the concept of political correctness (PC). Based on the ''principle of reversibility'', it can be a liberating factor, but if it is manipulated by dominant socio-economic forces, it can also be a force favouring divisive social and economic control. The question is, how can the liberating aspects of PC be enabled to predominate over the others. 相似文献
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