Purpose: This study examined immigrants’ perceptions of their interactions with financial institutions and asked if U.S. immigrants are considered in these institutions??? formal statements on diversity, equity, and inclusion (DEI).Method: We interviewed 13 participants and also conducted a content analysis of the DEI statements of the top nine U.S. banks. In addition to content analysis, we also used text mining to gain further information on the key themes prevalent in the diversity statements of the financial institutions.Results: Our findings show a clear disconnect between the top U.S. banks’ DEI statements and the lived experiences of immigrants. For instance, banks had oppressive banking processes that makes it difficult for immigrants to open accounts. We also identified lack of communication channels.Conclusion: As calls for diversity, equity, and inclusion in our field grow, we must pay attention to material conditions of immigrant students/scholars in Technical and Professional Communication (TPC) academic programs. Immigrants interviewed in this study wanted clarity about which documents they need to submit to banks, accurate translation of bank-related documents, and detailed explanations of banking industry jargon.
Purpose: This study examined immigrants’ perceptions of their interactions with financial institutions and asked if U.S. immigrants are considered in these institutions??? formal statements on diversity, equity, and inclusion (DEI). Method: We interviewed 13 participants and also conducted a content analysis of the DEI statements of the top nine U.S. banks. In addition to content analysis, we also used text mining to gain further information on the key themes prevalent in the diversity statements of the financial institutions. Results: Our findings show a clear disconnect between the top U.S. banks’ DEI statements and the lived experiences of immigrants. For instance, banks had oppressive banking processes that makes it difficult for immigrants to open accounts. We also identified lack of communication channels. Conclusion: As calls for diversity, equity, and inclusion in our field grow, we must pay attention to material conditions of immigrant students/scholars in Technical and Professional Communication (TPC) academic programs. Immigrants interviewed in this study wanted clarity about which documents they need to submit to banks, accurate translation of bank-related documents, and detailed explanations of banking industry jargon.
Purpose: This project contributes a rhetorical approach to search engine optimization (SEO) as algorithmic audience analysis. It positions SEO as an activity that requires strategists to compose website content that is optimized to both human search engine users and the algorithmic audience (Gallagher, 2017) of a search engine???s indexed content. Method: Actor-Network Theory (Latour, 2005), with its focus on the agency of non-human entities combined with human agency in social activity, provides the theoretical framework for this approach. The project combines usability testing with web development methods to trace rhetorical agency during online search activities (Hocutt, 2019). Doing so demonstrates the role search algorithms play as receptive audiences of SEO strategies. Results: Approaches to teaching SEO within the framework of technical and professional communication (TPC) rhetorical foundations require understanding the algorithmic audiences of SEO practices. By matching timestamp data from videorecorded usability tests and HTTP archive (HAR) files produced during usability testing sessions, content strategists can overlay the chronological recordings with their SEO strategies to better understand how successfully SEO met human and algorithmic audience expectations. When SEO practice identifies human audience expectations effectively and develops content signals attractive to its technological audiences, both audiences succeed in an assembled meaning-making exercise. By applying existing methods of audience analysis to search algorithms, content strategists can improve SEO and help surface relevant content for their human users. Conclusion: The results of this project provide a framework for practicing SEO as rhetorical activity built upon audience analysis of both human and non-human users.
Purpose: As technical and professional communicators (TPCs) use AI to develop content, inaccuracies due to AI limitations are introduced; it is vital TPCs evaluate AI-generated content to improve accuracy and human-centeredness. In this article, we present a human-in-the-loop AI content heuristic (HEAT: Human experience, Expertise, Accuracy, and Trust) as a rating mechanism. Method: This exploratory case study evaluated the quality of content generated by ChatGPT from the perspective of beginner TPC students. We used multiple prompting strategies asking ChatGPT to create documentation on personas using two Darwin Information Type Architecture (DITA) information types namely, concept topics and task instructions, and we evaluated the results with HEAT. Results: HEAT had good intraclass correlation coefficient (ICC) reliability (.743 pilot; .825 for scenarios) indicating its fitness as a heuristic for evaluating generative AI output. The findings indicate that ChatGPT was generally good at writing concept topics; however, it performed less well creating step-by-step task instructions. Expert TPC input helped develop a better prompt for improved output. We also found that tokenization in ChatGPT (the way it breaks up text) has a large role in terms of noncompliance with format specifications. Conclusion: There is a need for TPCs to (1) develop new models for AI-assisted content creation, (2) recognize the impact of different prompting strategies on developing specific structured authoring units such as concept and task topics, and (3) be aware of the limitations of AI such as ChatGPT. Human-in-the-loop quality check mechanisms, such as HEAT, can help validate and modify AI-generated content to better serve end users.
Purpose: This research paper explores the following phenomena that impact content strategy in technical communication (TC): 1) understudied user analysis methods that reveal users’ information seeking behavior, 2) changes in infrastructure design for innovative user research practices, 3) skill sets required by technical communicators to carry out content strategy tasks. Methods: Methodologically, the article reports findings from 19 interviews conducted with TC practitioners who hold titles such as technical writer, content strategist, information developer, information architect, and documentation manager. Results: The interviews revealed more than 13 practices/methods in which users’ interactions resulted in data that provided more information about them which impacted the design of content platforms. I classified the findings into 4 main categories of users’ interactions that hold valuable insights about users’ information consumption behavior. These insights that can be used to make informed content strategy decisions are lost if the data is not carefully processed. Conclusion: This paper demonstrates how user interactions can inform research on content strategy in TC and how it impacts the processes of users, as well as the impacts on existing roles of technical communicators. I argue that we need to be more purposeful about analyzing users’ interactions that produce data and design infrastructures to support interactions as part of an organization’s content strategy goals. My future work will focus on how issues such as privacy, surveillance, and incentivization can be handled in situations where users’ information is used for audience analysis purposes.
