This study critically examines the Hierarchical Model of Inspirational Teaching (Rowcliffe, 2022), a conceptual framework proposing that pedagogical competence, student-teacher relationships, and teacher passion are associated with student intrinsic motivation. Although the model has previously been presented conceptually, it has not been subjected to quantitative scrutiny.

Data were collected from 369 students and 33 teachers across two international post-16 schools. Student questionnaires assessed perceptions of student-teacher relationships, teacher passion, and intrinsic motivation, while teacher questionnaires examined burnout. Exploratory and confirmatory factor analyses were used to examine construct structure, followed by correlation, regression, and mediation analyses to explore relationships among variables. …

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Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design, Delante Clark Jun 2026

Expanding The Cognitive Attentional Standards Platform Through Artificial Influence Assessment (Aia): Rationale, Development, And Measurement Design, Delante Clark

Graduate Scholarship and Creative Works

Artificial intelligence is increasingly shaping how individuals access information, make decisions, and interact with digital environments. The Cognitive Attentional Standards Platform (C.A.S.) was developed to assess attention related harms, cognitive safety, digital autonomy, and platform influence across digital systems (Clark, 2026). However, the growth of generative AI, conversational agents, and algorithmic decision support technologies has introduced new forms of influence that may not be fully captured by existing assessment domains. This paper proposes the Artificial Influence Assessment (AIA) as an expansion of the C.A.S. framework designed to measure AI mediated influence on cognition, behavior, autonomy, and information processing. Drawing on …

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Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence, Delante Clark Jun 2026

Governing Algorithmic Attention: Attention Safeguard Models And The Cognitive Attentional Standard As System Level Interventions In Human Computer Interaction, Behavioral Economics, And Artificial Intelligence, Delante Clark

Graduate Scholarship and Creative Works

Algorithmic recommendation systems and interface designs shape attention by combining visually salient cues with uncertain reward timing and low friction interaction. These conditions can sustain anticipatory checking, extend time on task, and reduce natural disengagement points through patterns such as infinite scrolling and autoplay. This paper synthesizes research across neuroscience, human computer interaction, behavioral economics, and artificial intelligence to argue that attention capture is a predictable outcome of incentive driven design rather than an individual failure of self regulation. It advances the Attention Safeguard Models and the Cognitive Attentional Standard as system level interventions that regulate exposure conditions, pacing, and …

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