自动化新生课程分级与注册：一个案例研究
Automating Freshman Course Placement and Registration: A Case Study
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中文总结 AI 辅助
罗文大学针对新生入学人数激增导致手动课程流程不可持续的问题，开发了整合Banner等数据的自动化系统，处理超3500名新生，年节省超350小时，减少人为错误并释放人员精力。
中文摘要 AI 辅助
这份实施报告探讨了罗文大学（Rowan University）在自动化新生课程分级与注册流程方面的工作。历史上，罗文大学的新生教学指南（FIGS）是手动执行的，需要测试服务部、大学咨询部和注册办公室投入大量时间评估分级需求并为学生分配课程。鉴于十年间首次攻读学位的学生入学人数激增57%，手动流程变得越来越不可持续。作为应对，一个跨部门团队开发了一套全面的自动化流程，以整合来自Banner（学生信息系统）、咨询部维护的Google Sheets及其他来源的数据。该自动化流程基于项目分组对学生进行分类，确定主要和次要课程分级，检查Banner中的实时可用性和约束条件，并批量完成新生的课程注册。该系统处理了超过3500名新生，每年节省超过350小时的时间，减少了人为错误的可能性，并使工作人员能够将重点从行政工作转移到战略咨询上。本报告概述了实施背景、设计架构、技术集成、评估方法、经验教训以及面临类似挑战的院校的实践意义。
英文摘要
This implementation report explores Rowan University's effort to automate the process of freshman course placement and registration. Historically, Freshman Instructional Guides (FIGS) at Rowan was manually executed, requiring significant time from Testing Services, University Advising, and the Registrar's Office to evaluate placement needs and assign students to courses. Given the 57% surge in first-time degree-seeking student enrollment over a decade, the manual processes became increasingly unsustainable. In response, a cross-departmental team developed a comprehensive automated process to integrate data from Banner (Student Information System), Google Sheets maintained by Advising, and other sources. This automated process classifies students based on program groupings, determines primary and secondary course placements, checks for real-time availability and constraints in Banner, and completes course registration for freshmen in bulk. The resulting system processed over 3500 incoming students with over 350 hours in annual time savings, reduced the potential for human error, and enabled staff to shift focus from administrative work to strategic advising. This report outlines the implementation context, design architecture, technical integration, assessment methods, lessons learned, and practical implications for institutions with similar challenges.
