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The rapid growth of online learning has mandated the development of faculty evaluation models geared specifically toward the unique demands of the online classroom. With a foundation in the best practices of online learning, adapted to meet the dynamics of a growing online program, the Online Instructor Evaluation System created at Park University serves the dual purpose of mentoring and faculty evaluation. As such, the model contains two distinct phases of interaction: formative reviews and a summative evaluation. Beyond its critical role in instructor retention, program assessment, and accreditation, this faculty evaluation system signals the University's commitment to ongoing professional development. The Online Instructor Evaluation System maximizes the potential of faculty evaluation to inspire reflection and growth; encourages the persistent professional development needs of online instructors; emphasizes the process of teaching as well as product; incorporates multiple perspectives to capture a comprehensive view of instructor performance; and educates key on-ground university constituents about online learning. In the infancy of online instruction, considerable emphasis was given to demonstrating equivalence between online and traditional face-to-face instruction. This movement extended from pedagogy to evaluation as many online programs mirrored established face-to-face processes for faculty evaluation when creating models for the virtual classroom. With the rapid growth of online learning, these early evaluation models have revealed limited relevance to the online environment both in content and implementation. To address the ineffectiveness of traditional faculty evaluation models for use with online faculty, as well as to contribute to the growth of online learning as a field (and not simply a practice), innovative faculty evaluation models that are geared specifically to the unique demands, expectations and requirements of modern online learning must be developed.
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Stored only when both papers are in the corpus — 65 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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