A Data Science Course for Undergraduates: Thinking with Data

Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be non-traditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students with a variety of techniques to analyze small, neat, and clean data sets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that is considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms.Comment: 21 pages total including supplementary material

Reviews

Sally Brown, Steve Armstrong and Gail Thompson (eds.), Motivating Students, London: Kogan Page, 1998. ISBN: 0–7494–2494‐X. Paperback, 214 pages. £18.99

ICT skills acquisition by older people: motivations for learning and barriers to progression

This paper reports findings from one strand of an extensive research project investigating digital engagement of older people and the risks to sustained usage of information and communication technologies (ICTs). The factors that motivate older people to learn about ICTs, the barriers they face in the learning process and with on-going ICT use are examined. Research methods included focus groups (28 ICT learners aged 50+); questionnaires and interviews with seven 50+ learners; three interviews with ICT tutors; and observation sessions in three different ICT learning and support environments in England and Scotland. Findings show that while learning to use ICTs to ease the mechanics of daily life (e.g. on-line shopping) was a motivating factor for some, the more powerful drivers tended to be those applications seen as enriching quality of life e.g. using ICTs to keeping in contact with family and friends and using ICTs in pursuit of passions and interests. The key barriers relate to fear of using a computer; learning suppo rt ; quality and provision of ICT training; cost of training and technology; memory problems, and technology barriers. Implications of these findings for service providers, ICT designers and policy makers are identified and discussed

Harnessing Technology: new modes of technology-enhanced learning: action research, March 2009

5 action research studie

Reviews

Brian Clegg, Mining The Internet — Information Gathering and Research on the Net, Kogan Page: London, 1999. ISBN: 0–7494–3025–7. Paperback, 147 pages, £9.99

The Evolution of Student Engagement: Writing Improves Teaching in Introductory Biology

In response to calls for pedagogical reforms in undergraduate biology courses to decrease student attrition rates and increase active learning, this article describes one faculty member’s conversion from traditional teaching methods to more engaging forms of practice. Partially told as a narrative, this article illustrates a.) the way many faculty initially learn to teach by modeling the pedagogy from their own undergraduate programs; b.) the kind of support biology faculty may need to break out of traditional molds; c.) how writing can promote active learning; and d.) the impact of reformed pedagogy on student levels of engagement. The latter will be demonstrated through assessment results gathered from student surveys, reflective writing, and focus group interview. Ultimately, the study challenges misunderstandings some faculty might have regarding the value of writing in science classes and offers inspiration, urging critical reflection and persistence

Block-Based Development of Mobile Learning Experiences for the Internet of Things

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor's standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.Spanish National Research Agency (AEI) - ERDF fund