Poster Session
Reviving Wonder: How a Sense of Awe Enhances Digital Learning View Digital Media
Poster Session
Jason Waldow,
Lindsey J.
This study explores the transformative power of awe in nurturing lifelong learning and curiosity among students, with a particular focus on its application in both traditional and digital learning environments. In educational contexts often constrained by routine and rigid curricula, incorporating awe-inspiring experiences—such as marveling at natural phenomena, engaging with profound art, or delving into significant historical sites—can spark a sense of wonder that enriches and deepens the learning process. This approach is especially relevant in online learning, where the digital environment offers unique opportunities to simulate awe-inspiring moments through virtual explorations, interactive media, and immersive storytelling. Drawing on Maxwell’s (2017) findings, which highlight awe’s ability to elevate emotions and enhance well-being, and Prade and Saroglou’s (2016) research demonstrating its potential to boost prosocial behaviors like generosity and altruism, this session advocates for the intentional integration of awe into educational practices across all platforms. Furthermore, McGlynn (2023) emphasizes how awe fosters a sense of connectedness and respect for diverse forms of life, promoting a holistic educational approach that cultivates empathy and respect—values that resonate powerfully in collaborative online settings. This presentation seeks to motivate educators to design both physical and virtual learning spaces where awe and wonder are not fleeting occurrences but core components of the educational experience, thereby boosting student engagement, creativity, and a sustained passion for learning throughout their lives.
Culturally Responsive Artificial Intelligence Pedagogy (CRAIP): Addressing Algorithmic Bias and Equity in AI-Driven Education
Poster Session
Benjamin Boison
Artificial intelligence (AI) is transforming education through adaptive learning, predictive analytics, and automated assessments, reshaping how students learn and how teachers engage with instructional content. However, AI-driven technologies also introduce challenges such as algorithmic bias (the systematic reinforcement of inequities through AI decision-making), data privacy concerns, and the erosion of teacher agency (the ability of educators to make informed instructional decisions). These challenges reveal the limitations of Culturally Responsive Teaching (CRT), a pedagogical framework designed to incorporate students’ cultural backgrounds into curriculum and instruction but not explicitly developed to address the ethical complexities of AI integration. This paper introduces Culturally Responsive AI Pedagogy (CRAIP) as an expansion of CRT, integrating insights from Critical Algorithm Studies (CAS), which critiques how AI systems perpetuate biases, and Data Justice, which advocates for the fair and ethical use of data in education. CRAIP’s five core principles—Algorithmic Fairness, Culturally Responsive AI Curriculum, Teacher Agency, Student AI Literacy, and Ethical AI Governance—provide a structured approach to ensuring that AI-powered education remains equitable, transparent, and culturally inclusive. By analyzing real-world cases where CRT does not adequately address AI-driven challenges, this paper highlights the urgent need for CRAIP as an essential framework for ethical and inclusive AI integration in education.
