Teaching Analytics in Colleges of Business

Business Analytics has become a common term in all businesses. The importance of analytics in the modern business environment has made it necessary to include analytics as a foundational course for all business majors. There is much debate on what content should be taught in analytics courses and what is the role of computational skills versus the skills needed to interpret and communicate the results that are needed as part of the analytics process? These problems point to the essential difference between analytics and statistics. As we discuss in this paper, analytics is a process that employs statistical tools. We first discuss the business analytics process which we feel should be taught in all business analytics courses. We then propose a two-course sequence, Business Analytics I and Business Analytics II, to be taught as required courses in colleges of business

Business Intelligence in the Business Curriculum

There has been widespread investment in business intelligence/business analytics within industry because of the potential for improved managerial decision-making through mining the vast quantities of data collected by modern corporations; however, despite major recent curriculum changes in business schools, there has been very little attention given to this field. This has been true of both research and teaching and is compounded by inadequate quantitative literacy possessed by U.S. students and antipathy towards quantitative literacy among faculty. This paper documents the importance of business intelligence within business and the programs offered by the 50 leading business schools. A pioneering minor in the field offered by one school is described

Teaching Social Media Analytics: An Assessment Based on Natural Disaster Postings

Unstructured data in social media is as part of the “big data” spectrum. Unstructured data in Social media can provide useful insights into social phenomena and citizen opinions, both of which are critical to government policy and businesses decisions. Teachers of business intelligence and analytics commonly use quantitative data from sales, marketing, finance and manufacturing to demonstrate various analytics concepts in a business context. However, researchers have seldom used social media data to analyze social behavior and communication. In this study we aim to demonstrate an assessment structure for teaching social media analytics concepts with the goal of analyzing and interpreting social media content. We base this assessment on forum postings regarding two recent events: the Christchurch earthquake in New Zealand, and the Japanese earthquake and tsunami. The aim of the assessment is to discover social insights. We base the assessment structure on Cooper’s Analytics Framework to cover such concepts as term frequency (TF), term frequency–inverse document frequency (TFIDF), data visualization, sentiments and opinions analysis, the Nearest Neighbor K-NN classification algorithm, and Information Diffusion theory. We review how the students performed on the assignment that used this assessment, and we make recommendations for future studies

Analytics and complexity: learning and leading for the future

There is growing interest in the application of learning analytics to manage, inform and improve learning and teaching within higher education. In particular, learning analytics is seen as enabling data-driven decision making as universities are seeking to respond a range of significant challenges that are reshaping the higher education landscape. Experience over four years with a project exploring the use of learning analytics to improve learning and teaching at a particular university has, however, revealed a much more complex reality that potentially limits the value of some analytics-based strategies. This paper uses this experience with over 80,000 students across three learning management systems, combined with literature from complex adaptive systems and learning analytics to identify the source and nature of these limitations along with a suggested path forward

Selecting Undergraduate Business Majors

The paper begins with a brief review of the literature and how business students choose their major in the U.S. and we list the most popular majors in the U.S. Universities. We also talk about the factors that influenced student’s choice. In our next research project, we will not only use a larger sample size but also the sample will come from a few universities to reduce the sampling bias. In this paper, we also talk about changing trends in international students. We talk about the large group of Chinese, Indian, and Arabic students, and we show that with literature and graphical support. In the next section, we analyze one of the up and coming new business majors ―Business Analytics‖ We finish the paper with a discussion of growth of international students both at graduate and undergraduate level, and how we will address the shortcomings of this paper with our next project

Assessing collaborative learning: big data, analytics and university futures

Traditionally, assessment in higher education has focused on the performance of individual students. This focus has been a practical as well as an epistemic one: methods of assessment are constrained by the technology of the day, and in the past they required the completion by individuals under controlled conditions, of set-piece academic exercises. Recent advances in learning analytics, drawing upon vast sets of digitally-stored student activity data, open new practical and epistemic possibilities for assessment and carry the potential to transform higher education. It is becoming practicable to assess the individual and collective performance of team members working on complex projects that closely simulate the professional contexts that graduates will encounter. In addition to academic knowledge this authentic assessment can include a diverse range of personal qualities and dispositions that are key to the computer-supported cooperative working of professionals in the knowledge economy. This paper explores the implications of such opportunities for the purpose and practices of assessment in higher education, as universities adapt their institutional missions to address 21st Century needs. The paper concludes with a strong recommendation for university leaders to deploy analytics to support and evaluate the collaborative learning of students working in realistic contexts