691 resultados para problem based learning
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In 2008, a collaborative partnership between Google and academia launched the Google Online Marketing Challenge (hereinafter Google Challenge), perhaps the world’s largest in-class competition for higher education students. In just two years, almost 20,000 students from 58 countries participated in the Google Challenge. The Challenge gives undergraduate and graduate students hands-on experience with the world’s fastest growing advertising mechanism, search engine advertising. Funded by Google, students develop an advertising campaign for a small to medium sized enterprise and manage the campaign over three consecutive weeks using the Google AdWords platform. This article explores the Challenge as an innovative pedagogical tool for marketing educators. Based on the experiences of three instructors in Australia, Canada and the United States, this case study discusses the opportunities and challenges of integrating this dynamic problem-based learning approach into the classroom.
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While there is evidence that science and non-science background students display small differences in performance in basic and clinical sciences, early in a 4-year, graduate entry medical program, this lessens with time. With respect to anatomy knowledge, there are no comparable data as to the impact previous anatomy experience has on the student perception of the anatomy practical learning environment. A study survey was designed to evaluate student perception of the anatomy practical program and its impact on student learning, for the initial cohort of a new medical school. The survey comprised 19 statements requiring a response using a 5-point Likert scale, in addition to a free text opportunity to provide opinion of the perceived educational value of the anatomy practical program. The response rate for a total cohort of 82 students was 89%. The anatomy practical program was highly valued by the students in aiding their learning of anatomy, as indicated by the high mean scores for all statements (range: 4.04-4.7). There was a significant difference between the students who had and had not studied a science course prior to entering medicine, with respect to statements that addressed aspects of the course related to its structure, organization, variety of resources, linkage to problem-based learning cases, and fairness of assessment. Nonscience students were more positive compared to those who had studied science before (P levels ranging from 0.004 to 0.035). Students less experienced in anatomy were more challenged in prioritizing core curricular knowledge. © 2011 Wiley-Liss, Inc.
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This paper investigates how students’ learning experience can be enhanced by participating in the Industry-Based Learning (IBL) program. In this program, the university students coming into the industry to experience how the business is run. The students’ learning media is now not coming from the textbooks or the lecturers but from learning by doing. This new learning experience could be very interesting for students but at the same time could also be challenging. The research involves interviewing a number of students from the IBL programs, the academic staff from the participated university who has experience in supervising students and the employees of the industry who supported and supervised the students in their work placements. The research findings offer useful insights and create new knowledge in the field of education and learning. The research contributes to the existing knowledge by providing a new understanding of the topic as it applied to the Indonesian context.
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The collaboration between universities and industries has become increasingly important for the development of Science and Technology. This is particularly more prominent in the Science Technology Engineering and Mathematics (STEM) disciplines. Literature suggest that the key element of University-Industry Partnership (UIP) is the exchange of knowledge that is mutually beneficial for both parties. One real example of the collaborations is Industry-Based Learning (IBL) in which university students are coming into industries to experience and learn how the skills and knowledge acquired in the classroom are implemented in work places. This paper investigate how the University-Industry Collaboration program is implemented though Industry-Based Learning (IBL) at Indonesian Universities. The research findings offer useful insights and create a new knowledge in the field of STEM education and collaborative learning. The research will contribute to existing knowledge by providing empirical understanding of this topic. The outcomes can be used to improve the quality of University-Industry Partnership programs at Indonesian Universities and inform Indonesian higher education authorities and their industrial partners of an alternative approach to enhance their IBL programs.
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The report has been produced to inform practitioners who are considering using games and simulations in their practice. Towards this end, the work includes a review of the literature and a series of case studies from practice to illustrate the range of uses of games and to synthesise key issues and themes arising from learning in immersive worlds.
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This Q and A provides an overview of copyright law and how it applies in a variety of scenarios relevant to work based learning (WBL) providers.
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2nd International Conference on Education and New Learning Technologies
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Nivel educativo: Grado. Duración (en horas): De 31 a 40 horas
The structured development of simulation-based learning tools with an example for the Taguchi method
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Over the past decade, a variety of user models have been proposed for user simulation-based reinforcement-learning of dialogue strategies. However, the strategies learned with these models are rarely evaluated in actual user trials and it remains unclear how the choice of user model affects the quality of the learned strategy. In particular, the degree to which strategies learned with a user model generalise to real user populations has not be investigated. This paper presents a series of experiments that qualitatively and quantitatively examine the effect of the user model on the learned strategy. Our results show that the performance and characteristics of the strategy are in fact highly dependent on the user model. Furthermore, a policy trained with a poor user model may appear to perform well when tested with the same model, but fail when tested with a more sophisticated user model. This raises significant doubts about the current practice of learning and evaluating strategies with the same user model. The paper further investigates a new technique for testing and comparing strategies directly on real human-machine dialogues, thereby avoiding any evaluation bias introduced by the user model. © 2005 IEEE.