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Lindenwood Digest, February 26, 2025
Get PDFThe Lindenwood Digest has been a digital employee newsletter since 2009
Personalizing and decolonizing general education: A case study in gamifying global art history curriculum
Get PDFThis study explores the transformation of general education art history courses at a liberal arts college, shifting from Eurocentric surveys to a decolonized, gamified, and student-centered curriculum. Through a longitudinal mixed-methods design, the research evaluates the integration of global narratives and innovative teaching strategies to enhance student engagement and global competencies. Data from pre- and post-implementation surveys with faculty, students, and instructional designers demonstrate significant improvements in student satisfaction, cultural openness, and engagement with global art. Challenges include navigating demographic skews, addressing the complexity of gamified structures, and refining assignment instructions. Findings highlight the value of curriculum redesigns that promote inclusivity, flexibility, and active learning, offering a framework for advancing general education in a globalized academic landscape
Novice School Prinicpals\u27 Culturally Responsive Leadership Practices
Get PDFThis paper investigates the perspectives of three novice school leaders who explore ways to accommodate new instructional practices at their campuses by setting high expectations and getting to know students and their educational needs. The three novice school leaders who participated in this investigation emphasized the importance of communication and relationships with all the stakeholders, including: teachers, staff, students, parents, office personnel, and community members. Additionally, all three novice school leaders expressed gaining trust and proactively providing support to teachers at all times. Moreover, they concurred that the key skills required for success as a novice school leader are: communication, building relationships, establishing trust, continuous improvement, data-driven decisions, and innovation
Lindenwood Digest, April 2, 2025
Get PDFThe Lindenwood Digest has been a digital employee newsletter since 2009
Lindenwood Digest, November 5, 2025
Get PDFThe Lindenwood Digest has been a digital employee newsletter since 2009
Lindenwood Digest, November 12, 2025
Get PDFThe Lindenwood Digest has been a digital employee newsletter since 2009
Faculty Development Update, October 2025
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Resonant Body Communication for Neurodivergent Contexts: A Multimodal, Temporally Elastic Blueprint for Inclusive Biometric Systems
Get PDFPrevailing emotion-sensing systems privilege a facial-and-gaze paradigm that encodes neurotypical tempo, channel priority, and expression classes, thereby mischaracterizing or erasing neurodivergent communication. This article advances a design-oriented framework for biometric sensing that centers resonant body communication: temporally extended, multimodal, and environmentally situated patterns of posture, gesture, rhythm, and interoception that carry affective meaning. Through an integrative methodology that synthesizes cognitive neuroscience, embodied arts practices, and human–computer interaction, the study formalizes a theoretical model with four pillars: temporal elasticity, multimodal sensory hierarchies, resonant gestures and rhythmic entrainment, and environmental attunement. Building on this model, the article specifies technical requirements for next-generation systems, including whole-body pose capture, wearable inertial and physiological sensing, ambient context instrumentation, and crosschannel fusion pipelines aligned to individual baselines. Temporal analytics—windowed sequence modeling, rhythm extraction, and state trajectory inference—are proposed to recover slow affective dynamics that escape frame-level classifiers. Illustrative design patterns are presented for clinical diagnostics, affective interfaces, extended reality environments, and learning technologies, emphasizing participatory co-design and neurodiversity-affirming outcomes. A parallel ethics program addresses consent, privacy, representational harm, and the risk of normative enforcement, recommending local control, transparent inference, and disability-led governance for deployment settings. The contribution is twofold: a unifying vocabulary for neurodivergent affect as embodied resonance, and a concrete technical blueprint for inclusive biometric architectures. By rebalancing attention from faces toward bodies in context, affective technology can move from narrow detection toward attuned interpretation, improving accuracy, dignity, and usefulness for a broader range of minds. Future work outlines validation protocols and cross-domain deployment benchmarks
Large Language Models as Machines of Beauty: Cognitive Averaging, Latent Space Geometry, and the Entropic Foundations of Aesthetic Preference
Get PDFThis study advances the position that large language models (LLMs) and human perceptual systems are governed by a shared computational drive toward prototypicality, entropy reduction, and aesthetic coherence. Drawing on developmental evidence that infants exhibit early preferences for facial symmetry and averageness, the analysis situates aesthetic preference within broader research on processing fluency and predictive coding, emphasizing that biological perception rewards stimuli that reduce uncertainty and support efficient information compression. This foundation is used to examine how LLMs, through cross-entropy optimization, perplexity minimization, and latent space clustering, converge on high-density representational regions that operate as statistical prototypes of linguistic and conceptual categories. The examination shows that centroids within latent space function as computational counterparts to psychological prototypes, while attention mechanisms act as filters that amplify structured regularity and suppress idiosyncratic variation. Through the integration of perspectives from cognitive psychology, computational neuroscience, and machine learning, the study reframes aesthetic qualities as emergent properties of systems optimized to stabilize input and maximize predictive coherence. This perspective also clarifies phenomena such as mode collapse and embedding drift as consequences of excessive convergence toward prototypical structure, paralleling aesthetic degradation observed when biological systems over-attenuate variability. The significance of this argument lies in demonstrating that beauty can be modeled as a measurable outcome of intelligent information processing, linking infant cognition, neural prediction dynamics, and the generative capacities of artificial systems through the common logic of prototype formation and entropy minimization
