Abstract:

Advertising has traditionally been viewed as the component of marketing focused on creative communication, and numeracy skills have not been a requisite for career success. The Big Data revolution’s unprecedented volume of primary consumer data now provides actionable insights to devise persuasive messages. Big Data allows creative strategists to target increasing specific niche audience segments and even personalize messages to particular individuals. This new emphasis on data analytics has advertising educators asking, “What do we want our students to know about big data?” (Broyles & Slater, 2014). Knowing that advertising students are math averse compared to peers enrolled in business programs (Fullerton & Umprey, 2018) forces us to first consider how to help students overcome basic math anxiety and embrace critical data analysis as an act of creativity. Mann & Enderson (2017) explored using a more holistic approach to curriculum development to address these issues. They combined procedural (formula-driven) and conceptual instructional approaches to first teach the foundational math skills underlying Big Data. Not surprisingly, the marketing students in Mann & Enderson’s study preferred application of procedural approaches (“Give me a formula, not a concept”) over conceptual instruction. This signals that students are perhaps even more averse to critical, conceptual applications of data analytics than they are to basic mathematics.

This paper describes how one advertising program developed an entry-level data analytics literacy course by applying transformative learning theory (Mezirow, 1991) to build upon Mann & Enderson’s holistic model. Problem-and-task based learning is used to establish student self-confidence by starting with familiar, straightforward scenarios that allow students to experience success. Course content then builds upon that foundation with gradual introduction of higher-level tasks that require critical connections to be made to develop communication strategies. Emphasis on achieving the one “right” computational answer is reduced as students are encouraged to glean creative insights through analysis of numerical audience data. The desired learning outcome is for students to undergo a change in perspective to recognize that in Big Data analysis for advertising, there is never just one “right” answer that can lead to a creative, effective message strategy.

Keywords:

Transformative learning, data analytics, data literacy, critical thinking, marketing, advertising, pedagogy.