UNIV- AI Education Innovation and Implementation Lead - ESL Center for the Advancement of Teaching and Learning (CATL)

Job Description Summary

MUSC Education Innovation and Student Life (EISL) is seeking a faculty member to serve as the AI Education Innovation and Implementation Lead, advancing the institution’s strategic vision for transforming health professions education through the responsible integration of artificial intelligence. This position provides leadership in faculty development, educational innovation, AI-enabled educational technology implementation, and Scholarship of Teaching and Learning (SoTL). Working collaboratively with faculty, academic leaders, and institutional partners, the successful candidate will help evaluate, implement, and scale AI-driven educational solutions that enhance teaching, learning, assessment, and academic program operations while preparing future healthcare professionals to thrive in an AI-enabled healthcare environment.

Entity

Medical University of South Carolina (MUSC - Univ)

Worker Type

Employee

Worker Sub-Type​

Faculty

Cost Center

CC001359 ESL Center for the Advancement of Teaching and Learning (CATL)

Pay Rate Type

Salary

Pay Grade

• University-00
• Pay Range

0.00 - 0.00 - 0.000

Scheduled Weekly Hours

40

Work Shift

Job Description

Faculty Innovation, Professional Learning, and Scholarship Support (25%)

Design and facilitate professional learning experiences focused on AI readiness, responsible AI integration, and AI-enhanced teaching practices. Provide consultations to faculty and academic programs on AI-enhanced teaching, learning, assessment, feedback, course design, and academic integrity. Support faculty in redesigning courses and assessments to promote meaningful learning, competency development, learner effort, and professional judgment in AI-enabled environments. Assist faculty in designing, developing, implementing, and evaluating AI-enhanced educational innovations. Partner with faculty to translate educational challenges and innovations into Scholarship of Teaching and Learning (SoTL) and educational research projects. Support faculty with educational research design, project planning, implementation, evaluation, dissemination, and continuous improvement activities. Develop exemplars, toolkits, implementation guides, case studies, and faculty-facing resources that support effective AI integration. Contribute to communities of practice, faculty learning networks, and institutional AI champion initiatives.

Educational Technology Implementation and Adoption (25%)

Lead implementation efforts for approved AI-enabled educational technologies across MUSC colleges and academic programs. Partner with Information Solutions, vendors, and institutional stakeholders to support successful implementation and adoption. Develop implementation resources including onboarding materials, readiness checklists, communication plans, support documentation, and faculty guidance. Monitor implementation progress and identify barriers to successful adoption. Coordinate training, communication, support, and change management activities associated with approved technologies. Develop implementation strategies that support sustainable use and adoption across colleges, programs, and courses. Contribute to continuous improvement efforts that strengthen the effectiveness and scalability of AI-enabled educational technologies.

AI Education Innovation and Pilot Initiatives (20%)

Identify emerging AI-enabled educational technologies, practices, and use cases that may improve teaching, learning, assessment, feedback, advising, and academic operations. Design and coordinate educational innovation pilots focused on meaningful educational challenges and opportunities. Develop pilot objectives, success criteria, evaluation plans, implementation requirements, participant support strategies, and communication plans. Coordinate pilot implementation activities including onboarding, faculty support, feedback collection, troubleshooting, and continuous improvement. Collaborate with faculty, academic programs, vendors, and institutional partners to implement and evaluate pilot initiatives in authentic educational settings. Analyze pilot findings and develop recommendations regarding adoption, scaling, modification, continuation, or retirement of solutions. Maintain awareness of developments in AI, educational technology, health professions education, and higher education innovation.

AI-Enabled Educational Technology Portfolio Management and Evaluation (15%)

Maintain an inventory of approved, emerging, and pilot AI-enabled educational technologies, including educational use cases, implementation status, vendor information, integrations, adoption trends, support requirements, evaluation findings, and recommendations. Monitor the AI educational technology landscape to identify emerging solutions that address unmet teaching, learning, assessment, feedback, learner support, and academic operations needs. Evaluate AI-enabled educational technologies for alignment with desired learning outcomes, educational goals, program needs, and institutional priorities. Assess the strength of available evidence regarding educational effectiveness, learner outcomes, faculty value, and appropriateness for health professions education. Evaluate technologies for usability, accessibility, implementation complexity, faculty and learner experience, sustainability, and readiness for scale. Conduct comparative reviews of technologies with similar capabilities to identify overlap, differentiation, redundancy, and strategic fit within MUSC's educational technology ecosystem. Develop recommendations regarding technology selection, adoption, consolidation, expansion, or retirement based on educational value, implementation feasibility, integration requirements, user needs, and institutional priorities. Partner with Information Solutions, vendors, and institutional stakeholders to evaluate AI technology capabilities, educational use cases, implementation requirements, integrations, learner data considerations, security requirements, governance implications, and adoption readiness. Assess compatibility of AI-enabled educational technologies with D2L Brightspace, Microsoft 365, assessment platforms, learner support systems, and other approved enterprise technologies. Support educational technology pilot initiatives by contributing technology evaluations, implementation recommendations, integration reviews, educational use cases, and adoption analyses. Develop educational technology evaluation frameworks, implementation recommendations, and faculty-facing support resources that inform institutional decision-making. Document implementation findings, lessons learned, and institutional best practices to support continuous improvement and future technology decisions.

Evaluation, Scholarship, and Dissemination (15%)

Evaluate educational innovations and implementation efforts through collection and interpretation of evidence related to adoption, effectiveness, learner experience, support needs, and scalability. Collaborate with faculty and academic programs to evaluate AI-enhanced educational interventions and innovations. Support faculty in developing, conducting, and disseminating Scholarship of Teaching and Learning (SoTL) projects related to AI in education. Contribute to conference presentations, scholarly publications, implementation reports, educational research studies, and grant proposals. Collaborate on projects that advance evidence-based and responsible AI integration in health professions education. Assist in disseminating institutional lessons learned, promising practices, and implementation findings within and beyond MUSC.

Additional Job Description

Required Qualifications

Master's degree in educational technology, instructional design, curriculum and instruction, educational development, higher education, learning design and technology, or a related field. Three or more years of progressively responsible experience in curriculum development, faculty develo