The arts have played a major role in the development of management theory, practice, and education; and artists’ competencies like creativity, inventiveness, aesthetic appreciation, and a design mindset are increasingly vital for individual and organizational success in a competitive global world. The arts have long been used in teaching to: (a) explore human nature and social structures; (b) facilitate cognitive, socioemotional, and behavioral growth; (c) translate theory into action; (d) provide opportunities for professional development; and (e) enhance individual and systemic creativity and capacities for change. Use of literature and films are curricular mainstays. A review of the history of the arts in management teaching and learning illustrates how the arts have expanded our ways of knowing and defining managerial and leadership effectiveness—and the competencies and training necessary for them.
The scholarship of management teaching is large, primarily ‘how-to’ teaching designs and the assessments of them. There is a clear need to expand the research on how and why the arts are and can be used more effectively to educate professionals, enable business growth and new product development, facilitate collaboration and team building, and bring innovative solutions to complex ideas. Research priorities include: the systematic assessments of the state of arts-based management teaching and learning; explorations of stakeholder attitudes and of environmental forces contributing to current educational models and practices; analyses of the learning impact of various pedagogical methods and designs; examining the unique role of the arts in professional education and, especially, in teaching for effective action; mining critical research from education, psychology, creativity studies, and other relevant disciplines to strengthen management teaching and learning; and probing how to teach complex skills like innovative thinking and creativity. Research on new roles and uses for the arts provide a foundation for a creative revisiting of 21st-century management education and training.
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The Arts and the Art and Science of Management Teaching
Joan V. Gallos
Article
Content and Text Analysis Methods for Organizational Research
Rhonda K. Reger and Paula A. Kincaid
Content analysis is to words (and other unstructured data) as statistics is to numbers (also called structured data)—an umbrella term encompassing a range of analytic techniques. Content analyses range from purely qualitative analyses, often used in grounded theorizing and case-based research to reduce interview data into theoretically meaningful categories, to highly quantitative analyses that use concept dictionaries to convert words and phrases into numerical tables for further quantitative analysis. Common specialized types of qualitative content analysis include methods associated with grounded theorizing, narrative analysis, discourse analysis, rhetorical analysis, semiotic analysis, interpretative phenomenological analysis, and conversation analysis. Major quantitative content analyses include dictionary-based approaches, topic modeling, and natural language processing. Though specific steps for specific types of content analysis vary, a prototypical content analysis requires eight steps beginning with defining coding units and ending with assessing the trustworthiness, reliability, and validity of the overall coding. Furthermore, while most content analysis evaluates textual data, some studies also analyze visual data such as gestures, videos and pictures, and verbal data such as tone.
Content analysis has several advantages over other data collection and analysis methods. Content analysis provides a flexible set of tools that are suitable for many research questions where quantitative data are unavailable. Many forms of content analysis provide a replicable methodology to access individual and collective structures and processes. Moreover, content analysis of documents and videos that organizational actors produce in the normal course of their work provides unobtrusive ways to study sociocognitive concepts and processes in context, and thus avoids some of the most serious concerns associated with other commonly used methods. Content analysis requires significant researcher judgment such that inadvertent biasing of results is a common concern. On balance, content analysis is a promising activity for the rigorous exploration of many important but difficult-to-study issues that are not easily studied via other methods. For these reasons, content analysis is burgeoning in business and management research as researchers seek to study complex and subtle phenomena.
