255,953 research outputs found

    Teaching mathematical modelling: a research based approach

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    A collaborative, research based laboratory experiment in mathematical modelling was included in a bioprocess engineering laboratory module, taught as part of an interdisciplinary program in biotechnology. The class was divided into six groups of three students and given the task of investigating a novel diafiltration process that is currently the focus of international research. Different aspects of the problem were assigned to each group and inter-group communication via email was required to ensure that there was a coherent set of objectives for each group and for the class as a whole. The software package, Berkeley Madonna, was used for all calculations. As well as giving the students an introduction to mathematical modelling and computer programming, this approach helped to illustrate the importance of research in bioprocess engineering. In general, the experiment was well received by the students and the fact that they were discovering new knowledge generated a degree of enthusiasm. However, many students were consumed by the technical demands of computer programming, especially the attention to detail required. Thus, they did not think too deeply about the physical aspects of the system they were modelling. In future years, therefore, consideration will be given to giving the student prior instruction in the use of the software

    Values, attitudes, and goals of future Hungarian food engineers

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    Over the last few decades Hungarian higher education has been radically transformed, and this transformation was implemented to counter the backwardness that previously plagued the education system. Agricultural education in particular was part of this transformation process, which included the disciplines of food science and related technology. This attempt at transformation yielded only a partial success; student numbers shot up, but there was no subsequent general improvement in the efficiency of higher education. This article is based on two surveys carried out in 1997 and 2007. The students’ values can be characterised as pluralistic and heterogenous. Based on longitudinal research, a shift can be seen toward materialistic and hedonistic values. The motivation for choosing the Faculty of Food Science is varied in nature, mirroring the food industry’s often critical current situation. High schools’ professional orientation is weak. Although the Faculty’s Budapest location is attractive, in the long run this is not sufficient to replace carefully planned promotional work. By structural equation modelling a significant relationship can be proven between the students’ values, their types of knowledge, and their expectations for future types of work.higher education policy, human resource management, food science education, social psychology, empirical research, Agribusiness, Labor and Human Capital,

    Scaffolding learning by modelling: The effects of partially worked-out models

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    Creating executable computer models is a potentially powerful approach to science learning. Learning by modelling is also challenging because students can easily get overwhelmed by the inherent complexities of the task. This study investigated whether offering partially worked-out models can facilitate students’ modelling practices and promote learning. Partially worked-out models were expected to aid model construction by revealing the overall structure of the model, and thus enabling student to create better models and learn from the experience. This assumption was tested in high school biology classes where students modelled the human glucose-insulin regulatory system. Students either received support in the form of a partial model that outlined the basic structure of the glucose-insulin system (PM condition; n = 26), an extended partial model that also contained a set of variables students could use to complete the model (PM+ condition; n = 21), or no support (control condition; n = 23). Results showed a significant knowledge increase from pretest to posttest in all conditions. Consistent with expectations, knowledge gains were higher in the two partial model conditions than in the control condition. Students in both partial model conditions also ran their model more often to check its accuracy, and eventually built better models than students from the control condition. Comparison between the PM and PM+ conditions showed that more extensive support further increased knowledge acquisition, model quality, and model testing activities. Based on these findings, it was concluded that partial solutions can support learning by modelling, and that offering both a structure of a model and a list of variables yields the best result

    An intelligent teaching system for database modeling.

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    Database (DB) modelling, like other analysis and design tasks, can only be learnt through extensive practice. Conventionally, DB modelling is taught in a classroom environment where the instructor demonstrates the task using typical examples and students practise modelling in labs or tutorials. Although one-to-one human tutoring is the most effective mode of teaching, there will never be sufficient resources to provide individualised attention to each and every student. However, Intelligent Teaching Systems (ITS) offer bright prospects to fulfilling the goal of providing individualised pedagogical sessions to all students. Studies have shown that ITSs with problem-solving environments are ideal tools for enhancing learning in domains where extensive practice is essential. This thesis describes the design, implementation and evaluation of an ITS named KERMIT, developed for the popular database modelling technique, Entity Relationship (ER) modelling. KERMIT, the Knowledge-based Entity Relationship Modelling Intelligent Tutor, is developed as a problem-solving environment in which students can practice their ER modelling skills with the individualised assistance of the system. KERMIT presents a description of a scenario for which the student models a database using ER modelling constructs. The student can ask for guidance from the system during any stage of the problem solving process, and KERMIT evaluates the solution and presents feedback on its errors. The system adapts to each individual student by providing individualised hint messages and selecting new problems that best suit the student. The effectiveness of KERMIT was tested by three evaluations. The first was a think-aloud study to gain first-hand experience of the student's perception of the system. The second study, conducted as a classroom experiment, yielded some positive results, considering the time limitations and the instabilities of the system. The third evaluation, a similar classroom experiment, clearly demonstrated the effectiveness of KERMIT as a teaching system. Students were divided into an experimental group that interacted with KERMIT and a control group that used a conventional drawing tool to practice ER modelling. Both group's learning was monitored by pre- and post-tests, and a questionnaire recorded their perception of the system. The results of the study showed that students using KERMIT showed a significantly higher gain in their post-test. Their responses to the questionnaire reaffirmed their positive perception of KERMIT. The usefulness of feedback from the system and the amount learnt from the system was also on a significantly higher scale. Their free-form comments were also very positive

    Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

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    In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

    Introduction to Iltis: An Interactive, Web-Based System for Teaching Logic

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    Logic is a foundation for many modern areas of computer science. In artificial intelligence, as a basis of database query languages, as well as in formal software and hardware verification --- modelling scenarios using logical formalisms and inferring new knowledge are important skills for going-to-be computer scientists. The Iltis project aims at providing a web-based, interactive system that supports teaching logical methods. In particular the system shall (a) support to learn to model knowledge and to infer new knowledge using propositional logic, modal logic and first-order logic, and (b) provide immediate feedback and support to students. This article presents a prototypical system that currently supports the above tasks for propositional logic. First impressions on its use in a second year logic course for computer science students are reported

    Supporting active database learning and training through interactive multimedia

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    The learning objectives of a database course include aspects from conceptual and theoretical knowledge to practical development and implementation skills. We present an interactive educational multimedia system based on the virtual apprenticeship model for the knowledge- and skills-oriented Web-based education of database course students. Combining knowledge learning and skills training in an integrated environment is a central aspect of our system. We show that tool-mediated independent learning and training in an authentic setting is an alternative to traditional classroom-based approaches

    Genuine lab experiences for students in resource constrained environments: The RealLab with integrated intelligent assessment.

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    Laboratory activities are indispensable for developing engineering skills. Computer Aided Learning (CAL) tools can be used to enhance laboratory learning in various ways, the latest approach being the virtual laboratory technique that emulates traditional laboratory processes. This new approach makes it possible to give students complete and genuine laboratory experiences in situations constrained by limited resources in the provision of laboratory facilities and infrastructure and/or where there is need for laboratory education, for large classes, with only one laboratory stand. This may especially be the case in countries in transition. Most existing virtual laboratories are not available for purchase. Where they are, they may not be cost friendly for resource constrained environments. Also, most do not integrate any form of assessment structure. In this paper, we present a very cost friendly virtual laboratory solution for genuine laboratory experiences in resource constrained environments, with integrated intelligent assessment

    Enhancing simulation education with intelligent tutoring systems

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    The demand for education in the area of simulation is in the increase. This paper describes how education in the field of simulation can take advantage of the virtues of intelligent tutoring with respect to enhancing the educational process. For this purpose, this paper gives an overview of what constitutes the objectives and the content of a comprehensive course in discrete event simulation. The architecture of an intelligent tutoring system is presented and it is discussed how these sophisticated learning aids offer individualised student guidance and support within a learning environment. The paper then introduces a prototype intelligent tutoring system, the simulation tutor, and suggests how the system might be developed to enhance education in simulation
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