Technical communicators in the workplace are tasked with maintaining digital assets like websites and social media platforms on behalf of their employers. While technical and professional communication (TPC) classrooms prepare students for user-centered research and design, these preparations focus on developing new artifacts or completing major revisions. Less often addressed in TPC classrooms is the regular maintenance of digital artifacts with user metrics from data analytics tools. In the workplace, technical communicators are asked to interpret and use insights captured in data analytics tools to provide actionable, routine updates based on user behavior. Data analytics tools provide aggregated reports of user behavior on and around such digital properties. This proposal seeks funding to develop and share ethical, user-centered instructional materials that TPC instructors can utilize to teach critical use of data analytics for user research, and routine maintenance of digital assets. Our project positions data analytics as a critical digital literacy that TPC students need to study, understand, and practice in classroom settings as preparation for workplace experience. We consider using data analytics as problematic but necessary methods that TPC classrooms should cover, and hope to use grant funds to develop tools that TPC instructors can use to teach these critical skills.
The always-active online presence of organizations through websites and social media accounts has made it easier to understand audience needs. But the broad variety of needs makes the audience analysis process complex. To understand audience behavior by triangulating findings on information consumption, technical communicators pull abstract data and extract knowledge using different data analytics tools. As such tools provide an overwhelming amount of data about users, synthesizing the data to make strong correlations between audiences based on data characteristics and organizational goals is challenging. While learning about audiences and user experience, technical and professional communication (TPC) instructors and students need to consider various questions that lie at the intersections of collaboration, statistics, data analysis, and organizational communication. How do analytics influence audience analysis methods? How does data marginalize audiences and how do these tools reinforce algorithmic biases? Most importantly, how can we develop innovative instructional materials for TPC instructors that will help students derive valuable insights from data analytics while also being conscious about the various algorithmic influences on decision making? In this research, we seek to address these questions by leading a training program for TPC instructors to help them include audience analysis (through data analytics) methods in classrooms, and also by developing materials that can be included in TPC curricula.
TPC’s audience-focused approach to composing results in natural affinity to usability studies and user experience in web development and social media platform management. Since the turn of the 21st century, but especially in the last several years, the preferred methodological approach to user experience has been participatory (Johnson, 1997; Johnson, 1998; Spinuzzi, 2005), focusing squarely on the imperative to engage users in communication design (Albers, 2005; Verhulsdonck & Shalamova, 2020; Yu, 2020), in community-based research and service (Brizee, Pascual-Ferrá & Caranante, 2020; Carlson, 2020; Rose, 2016), in social justice work (Walton, Moore & Jones, 2019; Jones, 2016), in code development (Beck, 2016; Brock, 2019), and in user-centered design (Tham, 2021; Zachry & Spyridakis, 2016). These approaches use TPC methods to engage users in the iterative stages of creating communication artifacts and activities, ensuring that user needs are anticipated and fully represented in finished products. On the other hand, maintaining existing web sites and social media accounts, once launched, is seldom addressed in these approaches and in the programs that prepare technical communicators for the workforce. When addressed, these approaches may produce user-centered redesigns, site-wide accessibility updates, and other relatively major revisions; they tend to gloss over the mundane activities of daily maintenance and improvement using metrics captured through data analytics. Yet technical communicators in the workforce may only rarely be asked to redesign a website, to rework an existing information architecture, develop a new website, or launch a new social media platform. They are more likely to be asked to collect user data and to develop actionable, user-centered tweaks to existing content, information architectures, designs, and platforms. These mundane, everyday activities require knowledge and experience with collecting user metrics using data analytics. Most technical communication classrooms, however, seldom have access to data analytics collected for an active website that can be used to generate concrete, actionable recommendations for developers to implement. Our research project seeks to research and develop an instructional tool and accompanying curriculum that TPC instructors can implement to provide real-time access to Google Analytics from the Fabric of Digital Life (fabricofdigitallife.com, FoDL) digital archive to their students. Using this tool and curriculum, we envision TPC instructors teaching students the routine skills of digital artifact maintenance by studying analytics data collection and aggregation processes, interpreting user metrics critically, and developing actionable recommendations that FoDL web developers will consider and possibly implement. We believe this project will help fill knowledge and experience gaps that recent TPC graduates may encounter when asked to use data analytics tools for website analysis and maintenance. This project follows up on the “Building Digital Literacy through Exploration and Curation” initiative funded in a 2019 CPTSC Research Grant. The PIs have participated in the Building Digital Literacy (BDL) team and contributed to its advancement, and have recently been invited to join the Building Digital Literacy cluster in the Digital Life Institute (digitallife.org). We position data analytics — the process of extracting intelligence from raw data, often the realm of data scientists and information technologists — as a critical digital literacy, one often overlooked in technical communication classrooms.
The goal of this research is increased awareness about the opportunities and limitations of data analytics approaches for the field of technical and professional communication. We aim to provide a methodological framework for TPC instructors to include data analytics in classrooms as a critical literacy method to conduct audience analysis, and to publish materials that can be directly included in curriculum designing. In the first stage, we will prepare training methods and develop the pedagogical framework to be shared with instructors. In the second phase, TPC instructors across CPTSC institutions will be invited to participate in a training workshop. In the third phase, participants’ feedback will be used to develop models that aim at evaluating data analytics approaches more critically for the TPC field.
Phase 1 (June-August 2021): We have secured a partnership with FoDL to help us develop materials using their website as a sample case. Using current literature on data analytics in TPC, information science, and machine learning fields, we will develop a methodological framework that will include step-by-step tutorials on deploying data analytics projects in three steps: planning, implementation, and testing.
Phase 2 (September-December 2021): We will invite TPC instructors from across CPTSC institutions to participate in the study and use the instructional materials, and to lead similar training sessions or workshops in classrooms and other academic and professional environments. We will hold periodic meetings for training and discussion. We will use discussion notes to iteratively improve existing resources, and we’ll share the improved materials with participants to include in their Spring 2022 classes.
Phase 3 (January-May 2022): Collaborative group discussions with other CPTSC instructors will lead to qualitative insights about the training and learning process, critical questions about the affordances of data, limitations of the tools, and ways to improve data analytics models in user experience research. As part of continuing discussions and research, we plan to create and support a community of scholars that can contribute insights and solutions to data and algorithm-based problems in technical communication spaces.