Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

A review of the research literature relating to ICT and attainment

Summary of the main report, which examined current research and evidence for the impact of ICT on pupil attainment and learning in school settings and the strengths and limitations of the methodologies used in the research literature

Multinational perspectives on information technology from academia and industry

As the term \u27information technology\u27 has many meanings for various stakeholders and continues to evolve, this work presents a comprehensive approach for developing curriculum guidelines for rigorous, high quality, bachelor\u27s degree programs in information technology (IT) to prepare successful graduates for a future global technological society. The aim is to address three research questions in the context of IT concerning (1) the educational frameworks relevant for academics and students of IT, (2) the pathways into IT programs, and (3) graduates\u27 preparation for meeting future technologies. The analysis of current trends comes from survey data of IT faculty members and professional IT industry leaders. With these analyses, the IT Model Curricula of CC2005, IT2008, IT2017, extensive literature review, and the multinational insights of the authors into the status of IT, this paper presents a comprehensive overview and discussion of future directions of global IT education toward 2025

Introduction to location-based mobile learning

[About the book] The report follows on from a 2-day workshop funded by the STELLAR Network of Excellence as part of their 2009 Alpine Rendez-Vous workshop series and is edited by Elizabeth Brown with a foreword from Mike Sharples. Contributors have provided examples of innovative and exciting research projects and practical applications for mobile learning in a location-sensitive setting, including the sharing of good practice and the key findings that have resulted from this work. There is also a debate about whether location-based and contextual learning results in shallower learning strategies and a section detailing the future challenges for location-based learning