Fostering a Community of Care in Online Graduate Education: Leveraging the Affective Filter Hypothesis

Abstract

Online graduate students often face heightened stress due to isolation, the demands of self-directed learning, and balancing academic responsibilities with personal life. These challenges can raise the affective filter, resulting in increased anxiety and lower academic performance. When students feel supported, their affective filter lowers, allowing them to absorb content more effectively. To counter these effects, institutions can foster a community of care that incorporates strategies for offsetting the affective filter. These offsetting strategies are grounded in relationships between faculty and students, supported by the institution that addresses academic and emotional needs. The affective filter model for online graduate education can facilitate lowering stress for students through purposeful attention to how the philosophies of a community of care and the affective filter intersect. Targeted instructional strategies, acknowledging accomplishments, and flexible, caring faculty alleviate cognitive overload and contribute to students' self-efficacy and motivation, which are key components in reducing the affective filter. Within the broader implications of community care in online education, the affective filter model for online graduate education is a holistic approach to teaching and learning online, where physical distance can exacerbate feelings of isolation. By addressing students’ emotional needs, online programs can create an inclusive and engaging learning environment, ultimately leading to better academic outcomes.