Evaluations
The Evaluate phase closes the loop on the instructional design process, ensuring that what was built actually works — for learners, for facilitators, and for the business. This phase focuses on the course itself: Is it technologically sound? Is the pedagogy effective? Is the content accurate and aligned? Quality assurance for online and blended courses is grounded in the TPCK framework — evaluating how well Technology, Pedagogy, and Content Knowledge are integrated within the learning experience. Evaluation data comes from multiple sources: student satisfaction surveys, outcomes data from assessments built during earlier phases, technical issue reports, and structured rubric-based quality reviews. Additionally, learner evaluations may include 30, 60, or 90-day retention checks to measure knowledge transfer and on-the-job application, in order to connect learning outcomes to business requirements. Artifacts in this section demonstrate how these methods work in practice — from detailed course reviews and scoring rubrics to real student feedback analysis and actionable improvement recommendations.
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Comprehensive QA — A collection of detailed quality reviews conducted across multiple technical training courses, each scored on two dimensions: a Quality Score assessing the learner experience, and an ADDIE Score evaluating adherence to instructional design standards. Reviews cover courses ranging from cloud data products and monitoring tools to customer communication and team collaboration, with scores ranging from 56% to 99%. Each review includes specific, constructive feedback on objectives alignment, activity design, assessment strategy, course length, and delivery readiness — demonstrating a consistent, rubric-driven evaluation methodology applied across a diverse portfolio of technical training content.
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Quality Review — Software Development Course — A three-part written evaluation that translates the student feedback data into a structured improvement plan. Part one synthesizes the major themes from the survey — pacing, pre-work alignment, depth calibration, after-hours availability, and instructor experience — and recommends specific interventions for each. Part two proposes a professional development workshop for the teaching team, including a detailed session outline covering classroom management, expectation-setting, confidence-building for new instructors, and a capstone teaching practice activity. Part three addresses an instructor recruitment strategy for a new course launch, demonstrating how evaluation thinking extends beyond the current course into organizational planning. Together, this document shows the full arc from data to diagnosis to action.
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Student Feedback (Data) — Software Development Course (General Assembly) — A multi-tab spreadsheet capturing anonymized student feedback for a software development bootcamp, organized across four dimensions: overall class experience, and individual evaluations of two lead instructors and an instructional associate. Each tab includes Likert-scale ratings on engagement, clarity, approachability, and feedback quality, along with NPS scores and open-ended student comments. The "IM Comments" column contains the instructional manager's real-time annotations — identifying emerging themes like pacing concerns, prerequisite gaps, and instructor experience levels, and flagging items for follow-up. This artifact demonstrates how raw feedback data is systematically organized and interpreted to surface actionable patterns rather than isolated complaints.
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TPACK Framework — The Technological Pedagogical Content Knowledge framework, developed by Punya Mishra and Matthew Koehler (2006), provides the lens through which courses in this portfolio were evaluated. TPACK identifies effective teaching as the intersection of three knowledge domains — technology, pedagogy, and content — and serves as the guiding model for assessing whether a learning experience integrates all three in a way that actually works for learners.