Ensuring the best teaching quality and promoting the critical thinking and hands-on experience of students are main concerns in the continuous development plan of the laboratories in the Electrical and Computer Engineering Department at the American University of Beirut. To this end, laboratory course materials are not only subject to constant updates, but also innovative teaching methods and evaluation techniques are developed. This paper outlines a new teaching methodology and novel academic Moodle-based evaluation techniques applied in a lab environment specific to Electric Circuits Laboratory which is a basic required course for all students majoring either in Computer and Communications Engineering or in Electrical and Computer Engineering in the Electrical and Computer Engineering department. The objectives of this course are to familiarize students with various circuit and electronic devices and their applications, to teach them how to use basic laboratory instruments, and to introduce them to laboratory techniques to implement and analyze electronic circuits. The motivation to implement the new changes was due to many observations and problems encountered while teaching the course for several years. The inventive teaching and evaluation approach have been applied so far for three semesters. Significant improvement in students' comprehension of the material, depicted in a considerable increase in class average of the final exam, proved the success of the adopted method. Besides, an increase in class participation and involvement was noticed and course assessment done by students scored very high.
Abstract-This paper presents an educational experience on how best engineering students can utilize their computers to tackle engineering problems. The study is matured from a long teaching experience of the Introduction to Electrical and Computer Engineering course required from all first year students majoring either in Computer and Communications Engineering (CCE) or in Electrical and Computer Engineering (ECE) at the Electrical and Computer Engineering Department of the American University of Beirut (AUB). In addition to raising awareness of the engineering topics, the course focuses on the innovative approach of using software tools in considering real-life problem solutions in order to adopt them to new educational technology. This has been achieved by carefully designed experimental sessions where software tools are introduced with an objective of illustrating the technical and analytical computing environment such as Microsoft Office, PSPICE, and MATLAB. These tools are integrated, in this setting, for students to visualize programming environment in solving and documenting engineering problems. In addition the students are introduced to different information research tools to better enhance and support their problem solving skills by using proper referencing.Index Terms-Electrical engineering, introduction to engineering, LABVIEW, MATLAB, moodle, PSPICE, undergraduate engineering studies. I. INTRODUCTIONFor so many years, the department of Electrical and Computer Engineering at the American University of Beirut introduced a new course to first year engineering students on Introduction to Electrical and Computer Engineering. Parts of the main objectives of this course were to introduce students to engineering profession and to some basic mathematical and computing tools used in electrical and computer engineering in addition to fostering communication and teamwork skills. The course contents and approaches have changed over the years based on continuous assessment and feedback obtained from senior students and faculty members.Many papers have been published on this topic including course objectives, content, teaching approach, and design project. The authors of [1], [2] addressed the need to introduce a similar course in an effort to help students in selecting a major as early as possible of their study and informing them of their educational programs and career opportunities.Others [3]-[5] addressed the need of introducing design projects at an early stage in engineering studies to help students to explore design alternatives, to learn design concepts, to solve facing challenges, and to communicate their design solutions. In other cases, the course is meant to strengthen the fundamental problem solving skills, highlight the various engineering disciplines, explore the different areas of electrical engineering with hands on approach, and prepare them to have ingenuity and creativity [6]- [8]. In other related publications, "teaching-in-context" approach is used [9] and others showed the positive backgrou...
Understanding information transfer and representation in the brain is one of the most challenging scientific endeavors since neuroscientists are still far from converging to a solution with exact description. The main challenge in deciphering the neural code is the probabilistic nature of the neural codebook which maps stimuli to neural responses and vice versa. With the advent of recording techniques from single and multiple cells, it is becoming plausible to obtain large amount of experimental data against which theoretical models can be tested. In this respect, information theory can potentially provide a powerful framework for analyzing information content and representation in neuronal network activity. In this paper, we develop a simplified neuronal firing model which is mathematically complete and scalable. The model makes use of Poisson processes' properties and queuing theory. We also derive theoretical tools to measure, quantify, and set upper limits on information coded by the proposed model based on information theory. The designed measures take into account a general coding scheme in each neuron that combines temporal and rate coding of spike train responses of neurons. The proposed model along with the tools are generalized to quantify information in a population of neurons where correlation among neurons is modeled. The model also incorporates a spatial component which allows studying the amount of information gained from the spatial pattern of responses in a neuron population. Accordingly, the developed model and tools aim at providing a unified view of measuring information quantities and hence giving a better understanding of the neural coding.
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