2018 AEJMC Teaching Panel Brief

There is growing consensus among educators and media practitioners that digital analytics is becoming a central point in journalism, public relations and advertising. However, how digital analytics can be integrated into these concentrations as a way of knowing and teaching is less studied. The difficulty of finding experts who can help or teaching ourselves this fast-changing subject adds even more challenge. About 3 years ago, I started to look into digital analytics for our students and only found that there are many digital analytics tools with no clear winner. That is why I started to ask my fellow educators who started their search earlier than me. They know of my frustration for the lack of resources and practices. Speaking to fellow educators helped me more than attending very expensive professional digital analytics conferences. The teaching panel that took place in Washington D.C. this year was almost a reunion of my support group in teaching digital analytics.

This panel explored challenges and different strategies used by journalism schools in teaching digital analytics, such as issues ranging from how a journalism school builds support for new analytics components within and across a campus, to opportunities and challenges at an instructor-level especially in the areas of concepts, pedagogy, and ethics.

Especially for educators with limited knowledge in digital analytics, this session aimed to start or enhance their current program beyond the traditional undergraduate curriculum by learning about successful cases.

Future directions and challenges (Lance Porter, LSU)
Lance introduced the most current trends in the digital environment, such as analyzing data from wearables and convergence, as well as the fast shift to clouds-based media which only enhance the importance of digital analytics. The explosive growth of data from digital media consumption behaviors like second screening, multitasking, digital videos and ephemeral media were also discussed. In sum, the volume and characteristics of digital data has and is changing and the best approach toward teaching and doing digital analytics.

Conceptual and practical challenges (Itai Himelboim, UGA)
Itai presented the primary conceptual challenges that educators encounter: difficulty in teaching digital analytics concepts that match with real data; understanding different types of data including owned data, earned data, network data, user-to-user vs. user-to-content. At an instructor level, he emphasized the importance of the data collection procedure using valid search terms based on Boolean search while screening Bots and other fake accounts’ data. Also, learning new tools, infographics and excel was recommended.

Practical challenges and project-based teaching (Robin Blom, BSU)
Media analytics is an interdisciplinary field, which results in media analytics courses with a wide variety of majors (journalism, public relations, advertising, telecommunications, marketing, and even biology). That means that the students also have a wide variety of knowledge and skills, as well as experiences with analytics. However, they may not have much experience working with students who possess such different skills. Therefore, it is important to have students better understand the specific skills they bring to the table and how those skills fit in with the expertise of others. Media analytics courses need to facilitate that exploration process early on. This could be combined with other group building exercises. In our courses, we split students in smaller groups of 5 or 6 members. The smaller sizes allows for better group coordination to meet outside the classroom, encourages students to take ownership of important aspects of the projects, and it allows for a gamification aspect in which smaller group compete against each other to create the most insightful data analysis and most useful recommendations to a real-world client.

Ethical challenges (Laeeq Khan, OU)
In the age of big data, vast amounts of user data are being constantly generated. Advances in technologies have enabled collection and storage of large datasets from multiple sources. Such data is a gold mine for marketers, researchers, and businesses vying to extract meaning and thereby gain competitive advantage. Digital analytics may be understood as the science and art of making sense of big data can be described as. Digital analytics involves “the measurement, collection, analysis and reporting of Internet data” (Digital Analytics Association 2008, 3), encompassing web analytics, social media analytics, and mobile analytics.

Challenges associated with ethical use of data extend into the academic world. Research scholars in analytics are often from diverse and interdisciplinary fields such as Communication, Education, Informatics, Business, and Computer Science. This begs the need to understand and keep updated with the regulations of ethical research. At all stages of analytics—data collection, analysis, and visualization, ethical decisions need to be made. Instructors and research scholars teaching analytics need to impart understanding of ethical dilemmas and challenges. For example, in the United States, Institutional Review Boards (IRB), often treat publicly available online social data as exempt from review. In other international contexts, even in locations where there is widespread social media use, there is an absence of, or a lack of laws governing data use and privacy protections. A pressing ethical dilemma in such scenarios is whether identifiable data can be collected and analyzed without consent.

Teaching digital analytics requires institutional understanding of the complexities of big data, which should lead to clear and actionable strategies of dealing with analytics challenges. Ensuring transparency in research practices especially in terms of big data collection and analysis will ensure that digital analytics techniques are standardized leading to a lessening of gray areas, and equal opportunities for all researchers in terms of data access.

Contacts and resources
Dr. Lance Porter (lporter@lsu.edu) is the Doris Westmoreland Darden Distinguished Professor and the Director of the Social Media Analysis and Creation (SMAC) Lab at Louisiana State University. He recommends Deen Freelon’s social media analytics wiki for gaining most up-to-date resource about social media analytics: http://socialmediadata.wikidot.com/

Dr. Itai Himelboim is the Director of the SEE Suite – Social Media Engagement and Evaluation at the Grady College of Journalism and Mass Communication of the University of Georgia. He has developed and teaching the social media analytics class.
Website: http://seesuite.uga.edu (Syllabi, sample analytics reports, professional mentors, etc.)
Twitter: @SEESuiteUGA

Dr. Robin Blom is a graduate director and assistant professor of journalism at Ball State University, where he teaches media theory, media law and ethics, media analytics, and data journalism.

Dr. Laeeq Khan is an Assistant Professor and Director of SMART Lab in the Scripps College of Communication at Ohio University. Here is the lab website link: https://smartlabohiou.com/

Dr. YoungAh Lee is an Assistant Professor and Graduate Studies Director in Public Relations at Ball State University where she teaches mass communication research methods, public relations case studies, and media analytics measurement. She recommends starting with the following links in order to gain basic knowledge about social network analysis and analytics specific pedagogy principles at https://netlytic.org/home/?page_id=10849 and http://learning-analytics.info/.


YoungAh Lee, Ph.D.
Ball State University

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