In this workshop, we will describe the numerous processes and tasks involved in successfully hosting a high school programming contest. We will describe the mechanics of running the contest using PC^2, within the logistics of a college campus environment. We will talk about the logistics necessary to support the number of high schools and teams (currently we involve 15+ high schools and over 60 4-person teams). Finally, we will describe our local chapter of CSTA, which strengthens bonds and connections between ourselves and the school's coaches and advisors.

We describe a new methods of teaching computer science (CS) course tailored for mathematics education majors but also applicable to others interested in teaching CS. Goals of the course are enhancing their ability and confidence in developing and offering CS courses at high schools and starting CS courses at high schools that do not offer them. The course involves a combination of reading, programming, lesson/unit plan development, code reviews, and discussion of the various paradigms for introducing CS at the secondary level. Results indicate the course enhances the students' confidence, ability, and preparation for teaching CS in high schools.

An overview of Siena College’s participation in the Contextual Suggestion track of the Twenty-Fourth Text Retrieval Conference (TREC) is provided in this report. Our goal was to first design a search technique for complex information on specified POI’s (points of interest) from a collection set given by TREC. The second part of our task was to return a list of ranked suggestions dependent on a given context and a user’s interests. Multiple API’s were utilized for information retrieval on each particular POI including Google Places, Foursquare, and Yellow Pages. This process was repeated for not only the POI’s being suggested to the user, but for the POI’s rated by each user as well. From this information, profile preferences were created for individual users by examining the categories of the POI’s that they had rated. To build these preferences, we designed a scoring algorithm to associate a value with each individual category returned by the API’s. We finally created a ranking system that includes a unique penalty function to sort our suggestions of attractions specific to each of the users’ interests.

Abstract : As the internet dramatically changes each year, microblogs - such as Facebook and Twitter - are being used more often as a source of information exchange. Twitter users are learning about current events earlier compared to reading about it on their news feeds, as companies and celebrities continue to utilize Twitter to spread information. Information Retrieval, a topic which NIST1 (National Institute of Standards and Technology) holds a conference for every year, involves utilizing such online environments, like microblogs, to grab as much information from these sources to find if the information can be put towards a purpose. The Microblog Track was originally introduced to TREC2 (Text REtrieval Conference) in 2011, and selected Twitter3 as its microblog resource. Twitter allows its users to share short, 140 character length posts with their followers, and is often used to share anything from fashion trends to the latest terrorist attacks. Due to the short length of tweets, users often utilize other ways to share more information, such as including links or images with their tweets, which has an effect on the tweet containing relevant information. Participating groups for the track were given access to a Twitter API, provided by TREC, containing a corpus of 243 million tweets scrapped from February 1st to March 31st, 2013. Each group was given a set of test topics in which to test their system, which return results for the Adhoc and/or Tweet Timeline Generation Task (TTG). In this paper, we describe five Query Expansion modules and three Relevance modules designed for the microblog track, built within STIRS. Our precision results for our adhoc run shows STIRS' average to be at 61.91% precision, with our average TTG at 85.38% precision.

In this paper, we describe Codester, an original application developed during the summer of 2013, that teaches young students the principles of programming. The application was developed for the Android operating system, which allows for the use of tablets and smartphones as our teaching medium, instead of traditional laptops and desktops. Codester is a central part of a novel outreach program, known as the Computer Science Caravan (CSC). The CSC consists of members of the Siena College community, who travel to local K-6 schools equipped with tablets and other materials to reach out to students who do not usually have the opportunity to learn about programming or computer science.

While many software engineering programs focus on the theoretical aspects of that discipline, the capstone course [2] at Siena College has evolved into hybrid course that emphasizes "life-lessons" as well as the traditional software engineering materials. The capstone course still retains the basic structure of a typical software engineering course, with a yearlong team project that adheres to the waterfall model. However, team members' communication skills are tested throughout the year; a client relays his or her problem to the team in a fashion similar to real world interactions. At the end of each stage in the waterfall model (five stages in all), the team must make a powerpoint presentation where every member must speak in front of the class, clients, and other guests. Other communication exercises occur throughout the year, including resume creation, mock interviews, etiquette lessons, and mandatory classroom discussions.

In this paper, we describe Codester, an original application developed during the summer of 2013, that teaches young students the principles of programming. The application was developed for the An...

: As the internet dramatically changes each year, microblogs - such as Facebook and Twitter - are being used more often as a source of information exchange. Twitter users are learning about current events earlier compared to reading about it on their news feeds, as companies and celebrities continue to utilize Twitter to spread information. Information Retrieval, a topic which NIST1 (National Institute of Standards and Technology) holds a conference for every year, involves utilizing such online environments, like microblogs, to grab as much information from these sources to find if the information can be put towards a purpose. The Microblog Track was originally introduced to TREC2 (Text REtrieval Conference) in 2011, and selected Twitter3 as its microblog resource. Twitter allows its users to share short, 140 character length posts with their followers, and is often used to share anything from fashion trends to the latest terrorist attacks. Due to the short length of tweets, users often utilize other ways to share more information, such as including links or images with their tweets, which has an effect on the tweet containing relevant information. Participating groups for the track were given access to a Twitter API, provided by TREC, containing a corpus of 243 million tweets scrapped from February 1st to March 31st, 2013. Each group was given a set of test topics in which to test their system, which return results for the Adhoc and/or Tweet Timeline Generation Task (TTG). In this paper, we describe five Query Expansion modules and three Relevance modules designed for the microblog track, built within STIRS. Our precision results for our adhoc run shows STIRS' average to be at 61.91% precision, with our average TTG at 85.38% precision.

There has been an increasing interest, both of the research community and federal funding agencies in microblogs as a source of viable information for a variety of tasks. NIST (National Institute of Standards and Technology) has added a microblog retrieval track to TREC (Text REtrieval Conference) for the first time in 2011. NIST has selected Twitter as the source of microblog data. Twitter is a dynamic social website that allows users to post tweets which are short posts to share news with friends and followers across the world. While some tweets provide useful information, this information is very limited by the restriction on length to 140 characters or less. Participating teams were provided with the code necessary to download the Twitter Corpus, consisting of 16,141,812 tweets from a 2-week time period, January 24, 2011 to February 8, 2011, inclusive. Teams were also provided with a training set of 12 example topics, and later the test set of 50 topics. In this paper, we describe three modules designed for this track, built within a system called STIRS, Siena’s Twitter Information Retrieval System. After submitting three user-defined runs and a Lucene baseline run, the NIST judging showed our best run to be at 30.83% precision. The reported median from all runs of all 58 participating teams was 25.9%. We also describe our process of developing a new and complete end-to-end system in just 10 weeks time with six undergraduate researchers.

This paper describes a one-credit film course featuring movies that involve many aspects of computer science. This course was designed to introduce computer science to non-major students in an unconventional fashion. Using films, as well as a selection of inclass viewings, discussions and activities, students were exposed to diverse areas of computer science, such as computer animation, computer security, artificial intelligence, bioinformatics, and gender issues.

This paper describes the use of a board game as a device for introducing graph theory to computer science students. By experiencing a hands-on demonstration of graphs, students can better understand the basic principles of graph theory and can better design algorithms and programs which manipulate graph data. The programming assignment tied to the game forces the students to come to grips with the algorithmic aspects of graph theory, including the proper choice of data structures and the implementation of graph algorithms.

This paper describes the use of a board game as a device for introducing graph theory to computer science students. By experiencing a hands-on demonstration of graphs, students can better understan...

This paper presents a novel method of introducing bioinformatics to students in a Programming Languages class. The study and use of the scripting language Ruby allowed the instructor to introduce basic string manipulation concepts that are fundamental to sequence analysis. Student interest in this language and in bioinformatics led to the formation of a research group, who presented results formulated using Ruby at an undergraduate mathematics conference in the Spring of 2005.

In this paper, we describe the supervised learning approach to optimization problems in the spirit of the PAC learning model. By this approach, we discover domain-specific algorithms by learning from an oracle, which is also an optimization algorithm for the problem in question. We describe examples of learning backtracking-based algorithms and algorithms that implement the dynamic programming paradigm.

Infrastructure can be unreliable and administration subject to corruption in Asia's rapidly developing economies. Foreign investment is thus drawn to privileged investment enclaves, as well as in and around centers of international infrastructure. This context provides opportunity for Singapore-styled industrial parks, through the provision of superior infrastructure, the ability to negotiate investment concessions at inter-government level and, where existing, through the links to influential Chinese business groups in the investment location. Batamindo Industrial Park and Bintan Industrial Estate in Indonesia were the prototypes. This paper revisits the Parks, and offers a stock-take on the challenges confronting these flagship projects. Evidence from on-site surveys and interviews are presented. This paper concludes that the raison d'etre for the projects has overestimated the attractiveness of the low-cost investment enclaves for multinational companies, and the projects' potential has been largely overshadowed by socio-political uncertainties in the host environment.