Get the Story Straight: Comparing Narrative and Logical-Scientific Communication to Capture Gen Z’s Interest in Science Podcasts

Opat, Kelsi; Irlbeck, Erica; Cummins, R. Glenn; Li, Nan; Boren-Alpízar, Amy

doi:10.1080/19376529.2022.2145481

Cited by 2 publications

(1 citation statement)

References 28 publications

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“…CRM technologies allow for measurement in self-reported shifts in message processes using electronic technologies (Biocca et al, 1994). CRM has been used in public speaking, advertising, film and television, political and health communication (Biocca et al, 1994), and agricultural communication (LaGrande et al, 2021;Opat et al, 2022;Tarpley et al, 2020). Research designs within this method can use experimental, survey and quasi-experimental, time-series, focus groups, and coding content and behavior designs (Biocca et al, 1994).…”

Section: Resultsmentioning

confidence: 99%

All in a moment: Continuous response measurement method for analyzing dynamic science communication content

Baker,

McLeod-Morin,

Mattox

2024

Adv Ag Dev

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Science communication strategy plays a crucial role in effectively conveying scientific information to target audiences. While various models exist for developing communication strategies, many focus on measuring the effectiveness of communication efforts and adjusting these based on audience feedback. However, traditional methods of evaluating communication effectiveness often measure one component at a time and do not consider how people make decisions in real-life situations. This paper proposes the use of continuous response measurement (CRM) as a method to evaluate science communication in agricultural social science research. CRM allows for real-time measurement of how individuals make decisions in response to dynamic communication content. This paper compares different types of CRM, including in-person and virtual dial CRM, and provides resources for researchers interested in implementing this methodology. The paper also discusses various research designs that can be used with CRM, such as experimental designs, survey designs, time-series designs, focus groups, and coding content and behavior. The benefits and limitations of CRM are outlined, highlighting the need for immediate feedback and real-time response in science communication campaigns. In-person CRM is discussed, including the selection of stimuli, response prompts, data collection procedures, and data analysis. Virtual CRM is also examined, highlighting its advantages in terms of flexibility and cost-effectiveness. The paper concludes by discussing data output and analysis methods for CRM data. Overall, this paper serves as a methodological proposal for the use of CRM in agricultural social science research, emphasizing the importance of real-time measurement and response in science communication.

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Section: Resultsmentioning

confidence: 99%