Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering

Do Robots Dream of Virtual Sheep: Rediscovering the "Karel the Robot" Paradigm for the "Plug&Play Generation"

We introduce ”C-Sheep”, an educational system designed to teach students the fundamentals of computer programming in a novel and exciting way. Recent studies suggest that computer science education is fast approaching a crisis - application numbers for degree courses in the area of computer programming are down, and potential candidates are put off the subject which they do not fully understand. We address this problem with our system by providing the visually rich virtual environment of ”The Meadow”, where the user writes programs to control the behaviour of a sheep using our ”CSheep” programming language. This combination of the ”Karel the Robot” paradigm with modern 3D computer graphics techniques, more commonly found in computer games, aims to help students to realise that computer programming can be an enjoyable and rewarding experience and intends to help educators with the teaching of computer science fundamentals. Our mini-language-like system for computer science education uses a state of the art rendering engine offering features more commonly found in entertainment systems. The scope of the mini-language is designed to fit in with the curriculum for the first term of an introductory computer program ming course (using the C programming language)

Challenges in Bridging Social Semantics and Formal Semantics on the Web

This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics. The approaches introduced here rely on graph-oriented knowledge representation, reasoning and operationalization to model and support actors, actions and interactions in web-based epistemic communities. The re-search results are applied to support and foster interactions in online communities and manage their resources

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

Dirichlet belief networks for topic structure learning

Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to leverage the benefits of deep structures for learning word distributions of topics has not yet been rigorously studied. Here we propose a new multi-layer generative process on word distributions of topics, where each layer consists of a set of topics and each topic is drawn from a mixture of the topics of the layer above. As the topics in all layers can be directly interpreted by words, the proposed model is able to discover interpretable topic hierarchies. As a self-contained module, our model can be flexibly adapted to different kinds of topic models to improve their modelling accuracy and interpretability. Extensive experiments on text corpora demonstrate the advantages of the proposed model.Comment: accepted in NIPS 201

It’s Not Brain Science… Or Is It? How Early Second Language Learning Can Impact Future Achievement

Capstone paper from 2015 spring MPA program. Instructed by Allen Zagoren.We live in a global economy, yet U.S. citizens lag far behind in the knowledge of other countries’ languages, cultures, customs, geographies and peoples. Equipping the next generation with foreign language skills as well as knowledge of other cultures and customs will not only provide increased career opportunities for individuals but also aid in the future success of the U.S. economy. The U.S. educational system does not stress the learning of language beyond English: K-12 curriculum is rigidly mandated, budgets are tight, class time and teacher training is limited, and language programs are often among the first to be cut during budget crises. There is a time period when a child’s brain is developing and most receptive to learning, and that is early childhood. If the seed were planted in a child before he/she enters kindergarten to learn the basics of a foreign language and culture, perhaps that knowledge could be nourished throughout the rest of their lives, preparing those children to embrace cultural differences, live and compete more successfully in an evolving and diverse world, and be better equipped for later education. Besides examining the current state of foreign language education in the U.S. and how learning occurs, the benefits of foreign language learning in relation to business and human relations are examined in this paper. Multiple solutions to solving the foreign language deficit are mentioned including a proposal for an early-learning language program

Computational Economics: Help for the Underestimated Undergraduate

Our concern in this paper is that the capability of economics undergraduates is substantially underestimated in the design of the present college curriculum and that our students are insufficiently challenged and motivated. Students enter our classrooms with substantial previous knowledge about computers and computation and we are not taking full advantage of this opportunity. We suggest a set of examples from computational economics which are challenging enough to motivate students and simple enough that they can master them within a few hours. By encouraging the students to modify the models in directions of their own interest avenues for creative endeavor are opened which deeply involve the students in their own education.teaching computational economics