Overview and Status of the CMS Silicon Strip Tracker

The CMS experiment at the LHC features the largest Silicon Strip Detector ever built. The impact of the operating conditions and physics requirements on the design choices of the CMS Silicon Tracker is reviewed. The readiness of the Silicon Strip Tracker for the tentatively scheduled CMS commissioning in Summer 2008 is briefly described.Comment: 3 pages, 2 figures, conference proceedings for the 2007 Europhysics Conference on High Energy Physics, Manchester, England, 19-25 July 200

Teaching Tip: A Scalable Hybrid Introductory Analytics Course

We report on the design and development of an introductory analytics course delivered to almost 10,000 undergraduate business students to date. One novel aspect of the course is its orientation to add analytics capabilities to a business student’s toolbox, resulting in significant design and implementation implications. We anchored the course on three fundamental principles: maximizing learning, operating at scale, and a consistent experience for all learners. To enable a rigorous and valuable learning experience, the underlying course curriculum is based on the modified CRISP-DM (CRoss Industry Standard Process for Data Mining) framework. Bloom’s taxonomy is applied to the course assessments to evaluate the depth of learning. The course is delivered in a hybrid mode, arguably the best combination of online and face-to-face delivery modes. In a naturally occurring experimental setting, the COVID-19 pandemic accelerated the evolution of the course and generated additional reinforcing lessons. We explore those lessons and suggest directions for further research

Location Analytics in Information Systems: Innovative Applications & Research Opportunities

Some organizations have found competitive advantages through location analytics, yet such methods are rarely taught, applied, or researched within the information systems discipline. Instead, questions about location or analysis of location data are frequently treated as an afterthought or special case rather than an integral part of most business processes. Hence, organizations rarely adopt location analytics as a core enabler for remaining competitive or gaining a competitive advantage. Location analytics is an exciting opportunity for information systems programs to discover innovative industry applications, expand research approaches, and meet a critical workforce need through curricular enhancements. Many industries have yet to discover the capabilities of practical analyses of location-based data to drive decisions and inform strategy. Similarly, most information systems research (analytical, organizational, and behavioral) does not include spatial methodologies and theories. Finally, industries that hire information systems majors expect them to be able to work with a variety of data, including spatial data. Therefore, exposing information systems students to advanced spatial problem solving and analysis is critical. Our panel will share ideas for implementing innovative spatial analysis within industries, present examples of how spatial dimensions can inform richer and more rigorous research methodologies, and discuss how to best ensure that information systems students are exposed to spatial analysis. We invite those curious about bringing innovation to the IS curriculum to join us on an exploratory journey about location analytics in industry, research, and the classroom

Opportunities and Challenges of Remote Learning in the COVID Era – A Study Based on Sentiment Analysis of Geotagged Tweets

With the onset of COVID-19, remote learning has become a new standard and is slowly being embraced by students and teachers. This research article deduces positive and negative sentiment towards remote learning during the COVID-19 era by conducting sentiment analysis on Tweets geolocated in New York City (NYC), NY, USA. Furthermore, we explore potential associations between local geospatial information (such as demographic and psychographic data) and Twitter sentiment. In our preliminary analysis, we articulate a model that describes how these sentiments are correlated with individuals’ demographic information, socioeconomic status, and psychographic traits. Finally, based on our findings, we plan to explore the opportunities and challenges of remote learning in this community

A Hybrid Introductory Analytics Course: Lessons Learned During The COVID-19 Pandemic

We report on the design & development of an introductory analytics course delivered to over 6,000 students undergraduate business students thus far. The course is delivered in a hybrid mode, arguably the best combination of online and face to face delivery modes. The Pandemic reinforced that lesson, among others. We explore those lessons and suggest directions for further research