Keep it rich, keep it simple.

Novel researchers often look for help to analyze data collected during their first research projects. They have usually collected a huge, chaotic collection of data and seek an appropriate statistical test that fulfills their needs &nbsp

Information Literacy Assessment: Keep It Simple, Keep It Going

Is it possible to administer an information literacy assessment in only a few classes that would provide essential, adequate, data from semester to semester? In a college with a student body of about 2,000, would it be possible to obtain actionable assessment results if only 150 to 200 students were assessed each semester? This article is the result of the creation and implementation of the information literacy assessment that was launched in the fall of 2009 by Savage Library at Western State College of Colorado (WSC). WSC changed its name to Western State Colorado University on August 1, 2012. The authors of this article, a librarian and a lecturer in English, collaborated closely to embed the information literacy assessment into multiple sections of the second-year writing class required for all Western students. This article presents an overview of the information literacy (IL) assessment and an analysis of the data obtained from the assessment. The article also provides an overview of how to embed IL instruction and IL assessment into the classroom to improve student skills in critical thinking, IL, public speaking, and research and persuasive writing. Through a specific case study in which IL instruction and assessment was used in multiple sections of the same second year required writing course (COTH 202: Academic Writing and Inquiry), a broader set of implications is suggested for the usefulness and relevancy of the IL assessment in almost any academic course, regardless of the discipline. One model for how librarians and faculty might collaborate by incorporating IL instruction and assessment in a classroom setting is presented. This particular collaboration resulted in a substantial improvement in student learning outcomes as well as an easy-to-use formative method of assessing and then adjusting IL instruction as it is situated in a required writing course

Keep it simple: three indicators to deal with overfishing

Three simple fisheries indicators are presented: (i) percentage of mature fish in catch, with 100% as target; (ii) percent of specimens with optimum length in catch, with 100% as target; and (iii) percentage of ‘mega-spawners‘ in catch, with 0% as target, and 30–40% as representative of reasonable stock structure if no upper size limit exists. Application of these indicators to stocks of Gadus morhua, Sardinella aurita and Epinephelus aeneus demonstrate their usefulness. It is argued that such simple indicators have the potential to allow more stakeholders such as fishers, fish dealers, supermarket managers, consumers and politicians to participate in fisheries management and eventually hold and reverse the global pattern of convenience overfishing, which is defined here as deliberate overfishing sanctioned by official bodies who find it more convenient to risk eventual collapse of fish stocks than to risk social and political conflicts

Keep It Simple Sheffield – a KISS approach to the Arabic track

Sheffield’s participation in the inaugural Arabic cross language track is described here. Our goal was to examine how well one could achieve retrieval of Arabic text with the minimum of resources and adaptation of existing retrieval systems. To this end the public translators used for query translation and the minimal changes to our retrieval system are described. While the effectiveness of our resulting system is not as high as one might desire, it nevertheless provides reasonable performance particularly in the monolingual track: on average, just under four relevant documents were found in the 10 top ranked documents

ICML Exploration & Exploitation challenge: Keep it simple!

International audienceRecommendation has become a key feature in the economy of a lot of companies (online shopping, search engines...). There is a lot of work going on regarding recommender systems and there is still a lot to do to improve them. Indeed nowadays in many companies most of the job is done by hand. Moreover even when a supposedly smart recommender system is designed, it is hard to evaluate it without using real audience which obviously involves economic issues. The ICML Exploration & Exploitation challenge is an attempt to make people propose efficient recommendation techniques and particularly focuses on limited computational resources. The challenge also proposes a framework to address the problem of evaluating a recommendation algorithm with real data. We took part in this challenge and achieved the best performances; this paper aims at reporting on this achievement; we also discuss the evaluation process and propose a better one for future challenges of the same kind