7,240 research outputs found

    A Path to Alignment: Connecting K-12 and Higher Education via the Common Core and the Degree Qualifications Profile

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    The Common Core State Standards (CCSS), which aim to assure competency in English/language arts and mathematics through the K-12 curriculum, define necessary but not sufficient preparedness for success in college. The Degree Qualifications Profile (DQP), which describes what a college degree should signify, regardless of major, offers useful but not sufficient guidance to high school students preparing for college study. A coordinated strategy to prepare students to succeed in college would align these two undertakings and thus bridge an unfortunate and harmful cultural chasm between the K-12 world and that of higher education. Chasms call for bridges, and the bridge proposed by this white paper could create a vital thoroughfare. The white paper begins with a description of the CCSS and an assessment of their significance. A following analysis then explains why the CCSS, while necessary, are not sufficient as a platform for college success. A corresponding explanation of the DQP clarifies the prompts that led to its development, describes its structure, and offers some guidance for interpreting the outcomes that it defines. Again, a following analysis considers the potential of the DQP and the limitations that must be addressed if that potential is to be more fully realized. The heart of the white paper lies in sections 5 and 6, which provide a crosswalk between the CCSS and the DQP. These sections show how alignments and differences between the two may point to a comprehensive preparedness strategy. They also offer a proposal for a multifaceted strategy to realize the potential synergy of the CCSS and the DQP for the benefit of high school and college educators and their students -- and the nation

    Teaching Discrete Structures: A systematic review of the literature

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    This survey paper reviews a large sample of publications on the teaching of discrete structures and discrete mathematics in computer science curricula. The approach is systematic, in that a structured search of electronic resources has been conducted, and the results are presented and quantitatively analysed. A number of broad themes in discrete structures education are identified relating to course content, teaching strategies and the means of evaluating the success of a course

    Teaching Discrete Structures: A systematic review of the literature

    Get PDF
    This survey paper reviews a large sample of publications on the teaching of discrete structures and discrete mathematics in computer science curricula. The approach is systematic, in that a structured search of electronic resources has been conducted, and the results are presented and quantitatively analysed. A number of broad themes in discrete structures education are identified relating to course content, teaching strategies and the means of evaluating the success of a course

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

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    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

    Cross-Paced Representation Learning with Partial Curricula for Sketch-based Image Retrieval

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    In this paper we address the problem of learning robust cross-domain representations for sketch-based image retrieval (SBIR). While most SBIR approaches focus on extracting low- and mid-level descriptors for direct feature matching, recent works have shown the benefit of learning coupled feature representations to describe data from two related sources. However, cross-domain representation learning methods are typically cast into non-convex minimization problems that are difficult to optimize, leading to unsatisfactory performance. Inspired by self-paced learning, a learning methodology designed to overcome convergence issues related to local optima by exploiting the samples in a meaningful order (i.e. easy to hard), we introduce the cross-paced partial curriculum learning (CPPCL) framework. Compared with existing self-paced learning methods which only consider a single modality and cannot deal with prior knowledge, CPPCL is specifically designed to assess the learning pace by jointly handling data from dual sources and modality-specific prior information provided in the form of partial curricula. Additionally, thanks to the learned dictionaries, we demonstrate that the proposed CPPCL embeds robust coupled representations for SBIR. Our approach is extensively evaluated on four publicly available datasets (i.e. CUFS, Flickr15K, QueenMary SBIR and TU-Berlin Extension datasets), showing superior performance over competing SBIR methods

    Challenges to Teaching Credibility Assessment in Contemporary Schooling

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    Part of the Volume on Digital Media, Youth, and CredibilityThis chapter explores several challenges that exist to teaching credibility assessment in the school environment. Challenges range from institutional barriers such as government regulation and school policies and procedures to dynamic challenges related to young people's cognitive development and the consequent difficulties of navigating a complex web environment. The chapter includes a critique of current practices for teaching kids credibility assessment and highlights some best practices for credibility education

    Complete Issue 24, 2001

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