UAGC Integrates Industry AI Tools to Bridge Graduate Skills Gap

UAGC引入行业AI工具以弥补毕业生技能差距 高等教育必须以战略性行业合作取代事务性软件采购，帮助学生为应对AI驱动的职场做好准备。 Karen Ivy博士概述了高等教育如何超越基础的事务性软件应用、迈向变革性AI整合的策略。她强调AI整合并非可有可无，并详细阐述了三种跨领域合作模式：产学合作、政研合作以及社区与非营利组织合作。通过与CompTIA等伙伴开展合作，并引入UAGC品牌AI机器人“Jazz”等工具，高校可以为学生提供实操经验，简化指导老师的行政工作，并共同构建一个具有包容性且面向未来的AI生态系统。 高校必须转变思维，从简单的交易型软件采购迈向深度的变革性 AI 整合，打破孤立闭门造车的局限，树立积极拥抱 AI 的机构文化。 (0:04) UAGC 积极推进学术与行业合作模式（如携手 CompTIA），将实际行业工具直接融入学位课程，切实弥合学生的实践技能差距。 (4:30) 通过部署专属命名的内部 AI 工具“Jazz”，UAGC 简化了学业顾问的前期准备流程，使其能够专注于提供更深入、个性化的高触感学生支持。 (18:15) 总结指出“合作是全新竞争优势”，机构必须通过跨界协同共创并充分激活内部人才潜力，共同塑造面向未来的 AI 生态。 (18:50)

Dr. Karen Ivy and colleagues from the University of Arizona Global Campus (UAGC) argue that higher education institutions must move beyond transactional software adoption to transformative AI partnerships across industry, government, and community sectors. Moving from Transactional Deployment to Strategic Collaboration (0:04) Higher education institutions often struggle with viewing artificial intelligence primarily through the lens of academic dishonesty or treating adoption as an isolated purchasing decision. Dr. Karen Ivy argues that AI integration is an unavoidable reality that cannot be handled effectively in silos. Instead of transactional vendor relationships that stop at deploying isolated tools, institutions must pursue transformative integration, which requires aligning partner technologies with institutional mission, shared strategies, and long-term capability building. Closing Workforce Gaps via Academic-Industry Collaborations (4:30) To prevent students from graduating without familiarity with actual workplace technologies, UAGC integrates industry-standard platforms directly into degree curricula. For example, collaborating with organizations like CompTIA provides hands-on technical labs within technology coursework. Dr. Ivy notes that direct exposure to applied tools resolves a recurring employer critique—such as cybersecurity graduates lacking experience with real-world security platforms—thereby equipping students to speak concretely about applied technical skills during employment interviews. Extending Reach Through Research and Community Initiatives (8:19) Beyond commercial industry, institutions can leverage government-backed research and nonprofit channels to build AI competency. Drawing from her work as a Fulbright Specialist in Croatia, Dr. Ivy cites partnerships with local universities to incorporate human-centric AI concepts into cognitive science and human-centered academic programs. Complementary initiatives, such as collaborations with organizations like Shades of Blue, extend AI curricula into specialized fields such as aviation and aerospace. Empowering Academic Staff with Internal AI Tools Internal AI deployments can automate routine administrative overhead to enhance high-touch operational functions. At UAGC, an internally branded AI bot named 'Jazz' was deployed to prepare academic advisors ahead of student calls by gathering background data into an accessible interface. This automated preliminary prep time allows advisors to redirect their attention toward evaluating complex student needs and designing tailored support interventions. Ivy concludes that successful institutional AI adoption relies on co-creation, internal inclusion of staff expertise, and active cross-sector partnerships rather than solo execution, leaving higher education leaders with an explicit directive to pursue continuous collaboration.

亚利桑那全球校园大学（UAGC）技术研究助理院长Karen Ivy博士指出，高等教育机构必须摆脱将人工智能仅视为防范作弊手段或外包采购工具的事务性思维，转而通过深度战略合作建立变革性的AI整合生态。 超越事务性采购：构建变革性AI整合文化 (0:04) Ivy博士基于高等教育圆桌会议的讨论指出，高校管理者普遍面临如何引导全体教职员工理解AI的挑战，亟需扭转将AI窄化为“学生作弊手段”的防御性视角。她强调，AI技术的深度融合已成为不可逆转的必然趋势，机构不应再将其视为可有可无的选配方案，更不能在孤立封闭的环境中独自摸索。 在传统事务性模式下，高校往往局限于向外部供应商购买单一产品并做一次性部署，执行过程容易陷入部门孤岛。相比之下，Ivy博士倡导的变革性整合要求合作双方围绕长远使命与战略目标深度绑定，推动持续性的制度变革。她主张高校通过同行经验共享与跨机构协作，将外部资源转化为内部持续演进的战略能力。 三维合作模型：产学研与非营利机构的协同落地 (4:30) 针对如何落实战略合作，Ivy博士提出了三种跨领域模式：学术与产业合作、政府资助研究合作，以及社区与非营利组织合作。在产学合作方面，UAGC技术研究系已在其所有技术学位课程中系统化融入AI，例如引入CompTIA等行业标准工具搭建实操实验平台。Ivy博士援引圆桌会议上医疗行业代表的观察指出，许多网络安全毕业生在离校时缺乏实际业务工具操作经验，而产学直接对接能精准填补这一技能缺口，使学生在求职面试中具备切实的实践话语权。 在后两种模式中，Ivy博士结合自身作为富布赖特专家（Fulbright Specialist）在克罗地亚的履职经历，展示了高校如何与海外大学联合开展由政府支持的研究，将“以人为本的AI”理念嵌入认知科学等前沿学科。此外，UAGC还与聚焦航空航天领域的社区非营利组织Shades of Blue建立合作，共同开发针对性AI课程，进一步拓展了技术的社会应用维度。 内部运营赋能：专属AI工具“Jazz”的实践探索 除了课程维度的创新，UAGC还将AI自动化技术直接应用于学生支持与学术顾问工作流中。根据团队成员Melissa等人的实践反馈，AI工具能够在学术顾问拨通学生电话之前，自动完成背景信息的调取、整理与预审，大幅削减了人工处理行政杂务所需的时间成本。 这一效率提升使顾问能够从机械的数据准备工作中解脱出来，将核心精力转向针对学生个体需求的高黏性深度沟通，进而制定定制化的长期学业支持策略。项目团队还为该AI机器人确立了专属品牌名称“Jazz”，通过定制化的机构标识赋予技术工具鲜明的人格化属性，以增进内部协同认同感。 协同共创与包容性驱动：构建机构战略新优势 Ivy博士在总结中明确提出，“合作是当下的全新优势”，单打独斗难以支撑深层次的AI技术转型。真正的变革依赖于多元团队间的协同创新与方案共创，单向的技术引进无法催生持久的机构活力。 为此，Ivy博士建议机构领导层在推进数字化转型时必须坚持包容性原则，主动识别并赋能内部具有独特见解、实战经验和开拓意愿的骨干人才。通过激发内部人才引擎并与外部伙伴协同发力，高校才能在适应技术变革的同时，塑造出具备可持续演进能力的AI应用生态。 Ivy博士在演讲尾声发出“合作、合作、再合作”的行动呼吁，主张跨界共创是塑造负责任AI未来的唯一路径；不过由于现场问答环节未出现提问，关于该模式在不同办学规模院校中推广的具体成本分配与长期效果评估指标等问题仍有待进一步厘清。

## Background 本内容由 Ai4 于 2025 年 8 月 28 日在 YouTube 平台发布，记录了亚利桑那大学全球校区（UAGC）技术研究助理院长 Karen Ivy 博士等人的演讲。视频简介指出，演讲聚焦于高校与产业合作在推动 AI 创新及满足未来劳动力需求方面的变革潜力，并分享了成功合作模式与实践策略。 ## TL;DR 演讲围绕“协作是 AI 时代的全新竞争优势”展开，深入辨析了事务性采购与变革性整合的本质区别。Ivy 博士通过 UAGC 融合 CompTIA 实训平台、富布赖特克罗埃西亚跨境研究以及赋能 Shades of Blue 航空航天人才等实践，展示了产学、政研与非营利机构的三维合作范式。随后，UAGC 团队联合 EdSights 介绍了专属 AI 助手“Jazz”，该系统通过 SMS 结合 AI 主动倾听两万名非传统学生的心声，并赋能学术顾问实现精准干预。最后，演讲总结了以共创、包容与深度协同塑造可持续 AI 未来的核心行动准则。 ## Atmosphere & style 整场演讲氛围热情洋溢、务实而充满感染力，Ivy 博士以极具号召力的互动开场，迅速打破教育界对 AI 的“作弊防范”偏见。多位讲者之间的无缝接力与幽默互动展现了高度默契的团队协作，尤其在坦诚剖析以往学生服务脱节的痛点时既真诚又接地气。观众在聆听过程中能清晰感受到从战略高度到底层落地细节的层层推进，最终在“合作、合作、再合作”的激昂口号中激发起强烈的跨界共创共鸣。 ## Key takeaways - [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) AI 整合已是不可逆转的必然趋势，教育界应摆脱将其仅视作“学生作弊工具”的狭隘认知，通过全员拥抱与跨机构协作破除孤岛心态。 - [03:08](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=188s) 变革性 AI 整合与传统事务性采购存在本质区别，前者要求合作伙伴深度理解并对齐机构的战略使命、当前痛点与长期业务目标。 - [05:36](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=336s) UAGC 在全部科技学位中深度融入 AI 实践，并携手 CompTIA 等行业伙伴引入实操平台，有效解决毕业生“懂理论但脱离实际工具”的就业痛点。 - [08:19](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=499s) 借助富布赖特（Fulbright）等政府与科研跨境合作项目，在认知科学等跨学科领域构建“以人为本的 AI”与伦理道德框架。 - [10:07](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=607s) 深挖非营利组织与社区合作潜力，例如为航空航天公益组织 Shades of Blue 开发 AI 融合课程，赋能未来多元专业人才。 - [10:07](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=607s) 成功推进跨界 AI 合作的三大准则：建立共享语言与指标、共创 AI 实践实验室、维持长效的技能迭代与构建机制。 - [12:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=770s) 针对 2 万名非传统在线学生的庞大支持需求，UAGC 推动学生服务从传统的“被动救火”转向基于双向交互的主动预警与倾听机制。 - [15:17](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=917s) EdSights 方案通过 SMS 结合 AI 形成双轨机制：提供 24/7 基础问答，并从身心健康、财务、社交、学业四大维度主动评估学生在读留存风险。 - [15:17](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=917s) 短信聊天机器人为学生提供了极高的“心理安全感”，促使学生更坦诚地袒露困境，从而让顾问在掌握前置数据的前提下展开精准关怀。 - [18:15](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1095s) UAGC 推出专属 AI 助手“Jazz”，在通话前全面整合学生画像与背景信息，赋能学术顾问聚焦于高价值的深度辅导。 - [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) 组织推进 AI 变革的四大核心支柱：将合作视作竞争优势、以共创推动转型、以包容激发内部人才潜能，以及携手共塑负责任的 AI 未来。 ## Detailed walkthrough ### [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) 破除作弊偏見：AI 整合已非可選項，唯有合作才能突圍 演講在亞利桑那大學全球校區（UAGC）技術研究助理院長 Karen Ivy 博士熱情洋溢的問候中展開。Ivy 博士首先向台下觀眾提出互動問題：“現場有多少人曾與合作夥伴一起進行過 AI 整合？”在看到熱烈的舉手回應後，她笑稱“大家今天都來對了地方”。她強調，本次分享的核心在於如何跨越單純的技術導入，邁向深度的“變革性 AI 整合”（transformative AI integration）。 Ivy 博士回顧了前一天主持的高等教育圓桌論壇，當時有與會者提出關鍵焦慮：如何讓全體教職員工理解 AI 的演進步驟，並擺脫將 AI 僅僅視為“學生作弊工具”的狹隘視角。Ivy 博士明確指出，“AI 不是可選項，它已經到來且絕不會離開”，最好的應對姿態是全員擁抱並尋求合作。她特別告誡機構切勿陷入“閉門造車”的孤島心態，因為不論是先行者還是後發者，共享實踐經驗才是關鍵。 - **核心洞察**：“AI 的真正優勢全在於協作，而不在於單打獨鬥。”（"The real edge in AI is all about collaboration. It is not about doing it by yourself."） - **文化建構**：推動教育界超越“作弊防範”思維，將 AI 視為不可或缺的教學與業務整合動能。 ```mermaid flowchart LR accTitle: 事務性與變革性合作模式對比 subgraph 事務性合作 ["事務性模式 (Transactional)"] A1["尋找單一供應商"] --> A2["交付技術/產品"] --> A3["流程終止於集成"] end subgraph 變革性合作 ["變革性模式 (Transformative)"] B1["對齊使命與戰略"] --> B2["掌握現狀與未來變革"] --> B3["持續共創與指標共享"] end ``` --- ### [03:08](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=188s) 事務性採購與變革性整合的本質區別 Ivy 博士深入剖析了“事務性”（Transactional）與“變革性”（Transformative）兩種合作路徑的根本差異。事務性合作本質上只是傳統的採購行為——選定供應商、安裝產品、完成驗收，關係隨即停止；而變革性整合則要求雙方擁有高度契合的使命感。合作夥伴必須透徹理解高校或企業的戰略定位、當前處境、未來願景以及即將面臨的各類外部變革。 變革性合作不會在系統上線那一刻劃下句點，而是一個伴隨業務發展持續演進的動態過程。Ivy 博士指出，當機構推動 AI 整合時，背後必然有著具體的業務或教育目標，因此確保合作夥伴完全理解並對齊這些目標至關重要。隨後，她梳理了將在演講中詳細展示的三種商業合作範式：產學合作（Academia & Industry）、政研合作（Government & Research），以及學術與社群/非營利組織合作（Academia & Nonprofit/Community）。 --- ### [05:36](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=336s) 產學深度合作：以 CompTIA 實訓平台弭平技能鴻溝 在產學合作板塊，Ivy 博士以 UAGC 科技研究學院的實踐為例，自豪地宣布其所有科技學位項目均已在課程體系中深度融入了 AI 內容。雖然具體的實施方式會根據學科主任、特定課程及研究課題靈活調整，但整體戰略高度一致：通過與產業先鋒合作，為學生提供直觀的實操平台，使其在求學階段就能掌握業界實際需求的工具與技術方向。 Ivy 博士分享了圓桌論壇上的一段共鳴時刻：現場一位醫師和另一位網絡安全專家均強烈指出，許多畢業生在走上工作崗位後，對產業實際使用的方法、規範和工具一無所知，這對用人單位而言極其低效。為了縮小這一象牙塔與職場之間的鴻溝，UAGC 與 CompTIA 等機構展開合作，引入前沿開發平台。學生得以在求職面試時自信地證明自己具備實操經驗，從而無縫融入產業環境。 - **課程覆蓋**：UAGC 科技學系全體項目均主動規劃並融入 AI 實訓模組。 - **產業銜接**：引入 CompTIA 等行業標準平台，解決畢業生“理論充足但實操脫節”的痛點。 --- ### [08:19](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=499s) 政府與研究項目聯動：富布賴特克羅埃西亞“以人為本的 AI”實踐 談及政府與學術研究的結合，身為富布賴特專家的 Ivy 博士分享了她近期前往克羅埃西亞的學術交流經歷。她受邀與克羅埃西亞的高校合作，共同探索如何在認知科學及相關學科中融入“以人為本的 AI”（human-centric AI）架構。這與大會主講嘉賓反覆提及的倫理與人文維度不謀而合。 在克羅埃西亞期間，Ivy 博士深入學生與教職員群體，開展規劃研討，確定課程體系應如何兼顧算法能力與倫理考量。這種政府資助的跨境研究合作，確保了未來的畢業生不僅能開發 AI 工具，更能引導企業在部署技術時遵循道德框架與以人為本的原則。她熱情地鼓勵現場與會者，若對富布賴特（Fulbright）等國際科研合作項目感興趣，隨時可以與她交流探討。 --- ### [10:07](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=607s) 社群與非營利生態：賦能 Shades of Blue 航空航天人才培養 第三種模式聚焦於常被忽視的社群與非營利組織合作。Ivy 博士強調，開拓合作視野能帶來意想不到的雙向價值。她以自身支持的非營利組織“Shades of Blue”為例——該組織致力於為渴望投身航空與航天領域的人才提供教育與職涯通道。 Ivy 博士與大會現場的一位同事共同為 Shades of Blue 開發了融合 AI 技術的航空航天專屬課程體系，為未來的飛行員、機械工程師等各類航空專業人員提供實用的人工智能輔助培訓。總結這三種合作模型，Ivy 博士提出了三大行動準則： 1. **建立共享語言與成功指標**：確保雙方戰略目標同頻。 2. **跨領域共創與實驗室建設**：打造供學生、社區與產業開展實踐與技能提升的 AI 實驗室。 3. **長期技能構建機制**：維持連續性的學習與實操迭代。 --- ### [12:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=770s) UAGC 學生服務的痛點轉折：從被動追趕到主動傾聽學生心聲 隨後，演講麥克風交給了 UAGC 學生服務副總裁 Eric Piepenbrink。Piepenbrink 介紹了他帶領的“百人學業顧問軍團”，這支團隊承擔著為約 20,000 名非傳統學生（non-traditional students）提供全方位學業支持的重任。在帶來成就感的同時，龐大的學生基數也帶來了巨大的運營挑戰。 Piepenbrink 坦誠地透露了一個內部痛點：UAGC 學生服務此前竟然一直未支持與學生進行雙向短信溝通（two-way texting），他自嘲道“這簡直落後了行業 15 年”。過去，學校曾構建過機器學習模型來預測哪些學生最需要幫助，但整體工作模式依然深陷於“被動救火”——往往是學生缺課、作業出錯或陷入困境後，顧問才打電話介入。然而實踐證明，學生其實渴望主動傾訴，學校迫切需要一種機制在學生“跌落懸崖邊緣”之前提前感知其心聲，正是在此背景下，UAGC 選擇與教育科技公司 EdSights 攜手合作。 - **規模與挑戰**：100 位學業顧問服務 20,000 名非傳統在職/在線學生。 - **轉型核心**：由被動追蹤（Reactive Chasing）轉向基於學生原聲的主動預警（Proactive Student Voice Integration）。 --- ### [15:17](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=917s) EdSights 雙軌機制：結合 SMS 與 AI 打造高安全感的主動對話 EdSights 代表 Melissa Crowley 隨後詳細拆解了雙方合作落地的人工智能短信聊天機器人方案。該方案旨在通過 SMS 結合 AI 技術，為 Piepenbrink 的顧問團隊實現規模化的主動觸達（proactive outreach）。該聊天機器人具備清晰的雙重功能定位： 1. **24/7 被動響應功能**：學生可隨時主動詢問第一層級（Tier 1）的日常問題（如學期開始時間、選課流程、寫作中心資源等），所有回答均精準對接 UAGC 內部官方資源。 2. **四維度主動式觸發框架**：系統沿著四大核心維度向在讀學生定期發送對話式問候，並據此評估學生的持續在讀率（persistence likelihood）。 - **身心健康（Wellness）** - **財務狀況（Financial）** - **社交融入（Social Engagement）** - **學業進展（Academics）** Crowley 分享了試點項目的顯著成果：學生展現出了極高的留存率（opt-in rate）與活躍度。更為關鍵的是，機器人為學生創造了一種極高的“心理安全感”（psychological safety）。許多不願或羞於直接向人類顧問開口的學生，願意向聊天機器人如實傾訴面臨的困境；系統在捕捉到風險信號後，第一時間將結構化洞察推送給學業顧問，讓顧問能夠帶著對學生背景的深度理解精準介入，實現了 AI 資源自動化匹配與人工溫情關懷的最佳平衡。 ### [18:15](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1095s) 赋能学术顾问与 UAGC 专属 AI 助手“Jazz” 在针对学生支持系统的讨论中，演讲者阐明了 AI 工具如何通过在通话前为顾问整合并呈现完整的学生背景信息，大幅提升沟通效率。顾问无需再耗费精力在杂乱的数据中检索信息，而是能够将全部时间投入到深入理解学生真实需求、规划后续支持方案的高价值工作中。 正当讨论告一段落时，Ivy 博士幽默地提醒搭档 Melissa 漏掉了一个关键细节，并追问：“我们的机器人叫什么名字？”Melissa 笑着回答道：“哦对，叫 Jazz。”该团队为亚利桑那大学全球校区（UAGC）打造了具有专属品牌特色的定制化 AI 机器人，并将其正式命名为“Jazz”。 - **通话前信息整合**：AI 助手为学术顾问提前梳理好所有必要的学生背景数据，使顾问能专注于个性化关怀与长期支持策略。 - **专属品牌打造**：UAGC 团队为学校定制并命名了名为“Jazz”的 AI 助手。 ```mermaid flowchart LR accTitle: AI 助手 Jazz 赋能学术顾问流程 subgraph DataPrep["数据与准备"] A["学生全景数据"] --> B["AI 助手 Jazz 整合分析"] end subgraph AdvisorAction["顾问深度服务"] B --> C["通话前准备就绪"] C --> D["深挖学生真实需求"] D --> E["制定长期支持策略"] end ``` --- ### [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) 核心总结：以合作、共创与包容驱动 AI 转型 在演讲的收尾阶段，Karen Ivy 博士提炼了四项推动组织进行 AI 变革的核心原则，强调在这个快速发展的时代中，协同合作至关重要： 1. **合作是全新的竞争优势（Partnership is the new edge）**：切勿孤军奋战。组织在推进 AI 集成时完全没有必要闭门造车，寻求外部与内部的合作才是破局关键。 2. **转型需要共创（Transformation demands co-creation）**：保持创新活力的同时，各方必须携手共创，共同明确并推进组织在 AI 驱动下的转型方向。 3. **以包容为引领（Lead with inclusion）**：组织内部潜藏着大量兼具专业知识、丰富经验与敏锐洞察的人才。更重要的是，他们拥有推动组织迈向新高度的强烈意愿。管理者应主动发掘并充分赋能这些内部力量。 4. **携手合作塑造 AI 的未来（Together partnership shapes the future of AI）**：唯有通过广泛的跨界协作，才能真正定义并引领负责任、可持续的 AI 未来。 在结束演讲时，Ivy 博士抓紧最后的一分钟时间向现场参会者征询提问，并在掌声中以热情坚定的口号“合作、合作、再合作（Partner, partner, partner）”为整场分享画上了圆满句号。 ## Notable quotes > [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) 現場有多少人曾與合作夥伴一起進行過 AI 整合？ — Karen Ivy > [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) 大家今天都來對了地方 — Karen Ivy > [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) AI 不是可選項，它已經到來且絕不會離開 — Karen Ivy > [00:04](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=4s) The real edge in AI is all about collaboration. It is not about doing it by yourself. — Karen Ivy > [12:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=770s) 這簡直落後了行業 15 年 — Eric Piepenbrink > [18:15](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1095s) 我們的機器人叫什麼名字？ — Karen Ivy > [18:15](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1095s) 哦對，叫 Jazz。 — Melissa Crowley > [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) Partnership is the new edge — Karen Ivy > [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) Transformation demands co-creation — Karen Ivy > [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) Lead with inclusion — Karen Ivy > [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) Together partnership shapes the future of AI — Karen Ivy > [18:50](https://www.youtube.com/watch?v=aKJ3IOCISgk&t=1130s) 合作、合作、再合作 — Karen Ivy ## Mentioned Karen Ivy, Eric Piepenbrink, Melissa Crowley, University of Arizona Global Campus (UAGC), EdSights, Jazz, CompTIA, Shades of Blue, Fulbright (富布賴特項目), Ai4 ## Video description Karen Ivy, Assistant Dean, Technology Studies, University of Arizona Global Campus Abstracts Dr. Karen Ivy will emphasize the transformative potential of partnerships between industry and higher education in advancing AI innovation and addressing the workforce demands of the future. The talk will highlight successful collaboration models and actionable strategies to align educational outcomes with industry needs. Objectives for Attendees: - Understand Workforce Demands: Gain insight into the evolving skill sets required for AI-driven industries and the challenges businesses face in recruiting AI-literate professionals. - Explore Collaborative Opportunities: Learn about successful partnership models between higher education and industry, including joint research initiatives, internship programs, and AI-focused boot camps. - Develop Actionable Strategies: Identify practical steps for fostering partnerships, such as creating AI-focused advisory boards, designing agile curricula, and leveraging industry resources to enhance student and faculty innovation. - Foster Ethical and Inclusive Innovation: Recognize the role of universities in promoting ethical AI practices and driving inclusive innovation to prepare a diverse and responsible AI-ready workforce. [Source](https://www.youtube.com/watch?v=aKJ3IOCISgk)

[0:04] Karen Ivy: 現場有多少人曾與合作夥伴一起進行過 AI 整合？ [0:04] Karen Ivy: 大家今天都來對了地方 [0:04] Karen Ivy: AI 不是可選項，它已經到來且絕不會離開 [0:04] Karen Ivy: The real edge in AI is all about collaboration. It is not about doing it by yourself. [12:50] Eric Piepenbrink: 這簡直落後了行業 15 年 [18:15] Karen Ivy: 我們的機器人叫什麼名字？ [18:15] Melissa Crowley: 哦對，叫 Jazz。 [18:50] Karen Ivy: Partnership is the new edge [18:50] Karen Ivy: Transformation demands co-creation [18:50] Karen Ivy: Lead with inclusion [18:50] Karen Ivy: Together partnership shapes the future of AI [18:50] Karen Ivy: 合作、合作、再合作

[0:04] Dr. Karen Ivy: not optional [18:15] Melissa: Jazz [18:50] Dr. Karen Ivy: partnership is the new edge [18:50] Dr. Karen Ivy: together partnership shapes the future of AI [18:50] Dr. Karen Ivy: partner, partner, partner

[0:04] Good morning everyone. I'm Dr. Karen [0:07] Ivy. I am so excited to see you this [0:10] morning and to be here with my [0:12] colleagues to present to you the session [0:14] that we have today. The importance the [0:17] importance of partnering with [0:19] individuals as you go through your AI [0:22] integration directions. So before we [0:25] start and for those coming in I do have [0:28] a question just by raise of your hands. [0:30] How many people have gone through AI [0:33] integration with partners? [0:36] Raise of hands. Okay. Very good. Very [0:39] good. Okay. Everyone is in the correct [0:41] place. So we're talking about moving [0:44] beyond just AI integration into [0:47] transformative [0:48] AI integration and the difference [0:52] between that is very important. And so [0:53] you can see we're going to step through [0:56] some of the ideas of how to be [0:58] transformative, what that really means. [1:00] We're going to step through some models [1:02] when it comes to partnering and [1:04] different types of partnerships. We're [1:06] going to share some examples of what [1:07] we've been involved in as well. And we [1:10] would love to have time after that to [1:12] entertain your questions and hear some [1:14] of your examples as well of what you are [1:17] into also. So are you ready? All right. [1:21] Okay. framing the culture. [1:25] When we think about AI, um myself and my [1:28] partners from my technology operations [1:31] organization, we are with the University [1:32] of Arizona global campus. Some of us, we [1:36] led the higher education round table [1:38] yesterday and one individual asked that [1:41] question as far as how do we engage all [1:44] faculty into understanding AI, [1:47] understanding the steps of AI and even [1:49] as Eric mentioned today and also one of [1:51] our keynote speakers, how to move beyond [1:54] considering AI just as a way to cheat, [1:57] right, for students. How do you do that? [1:59] AI is not optional. It is here is not [2:03] leaving and the best position for all of [2:06] us is to get engaged in it and also to [2:09] work with partners to help to integrate [2:12] your AI direction as well. It's not [2:14] optional. And then when we talk about [2:17] innovation, what some of us may want to [2:20] do is move forward and integrate by [2:22] ourselves. That was the other very [2:24] important point that came out from [2:26] yesterday. Don't try to do it by [2:28] yourself. You don't have to. We have [2:31] other organizations who have moved [2:33] forward and have practices in helping [2:36] with integration. We have other peers [2:39] who are maybe steps ahead or steps [2:41] behind us. Group together what are you [2:44] doing the purpose of this conference? [2:46] How are you doing it? What can you share [2:47] out? Right? Don't do it in silos at all [2:51] and then definitely definitely seek out [2:53] partners to work with as you integrate. [2:56] Um the real edge in AI is all about [2:58] collaboration. It is not about doing it [3:01] by yourself. And the goal is to move [3:03] forward in adopting AI in building [3:06] partnerships. [3:08] So when we think about transformative [3:12] AI integration, why is that different [3:14] than transactional? Right? So [3:16] transactional is just that process of [3:18] okay, I'm going to identify a vendor [3:20] who's going to give me a product and [3:23] then we'll integrate it and that's it. [3:26] Transformative integration is working [3:29] with that partner, making sure you have [3:31] likeminded missions. The partner [3:34] understands your strategy. The partner [3:36] even understands where you are today, [3:38] where you want to go and the changes [3:40] that may be coming forward that you as [3:43] your business, university, etc. may need [3:45] to deal with. Transformative is making [3:48] sure you are working with a partner who [3:50] understands all of that, connects with [3:53] you on the mission and then works with [3:55] you even through the changes. It doesn't [3:58] stop at integration. It goes beyond [4:01] that. That's transformative AI [4:03] integration. When you are integrating [4:06] artificial intelligence in your [4:07] university, in your business, you have [4:10] goals that you are trying to meet. What [4:12] are those goals? and make sure your [4:14] partner is aware of what those goals [4:17] are. Right, Melissa and Eric? Is that [4:19] right? [4:20] >> Yes. And they're going to give us a very [4:22] good example of how at our university we [4:25] did just that. [4:30] So, we're going to talk about three [4:32] examples of business partnering when it [4:35] comes to AI integration. I'll share some [4:38] examples of what I've been up to and [4:39] what I've been involved in. Eric and [4:42] Melissa will share some good examples of [4:44] what our university as a whole has been [4:47] involved in as well. We're going to talk [4:48] about academia and industry partnership. [4:52] We'll talk about government and research [4:54] partnerships. And we'll talk about [4:56] academia and nonprofit or community [5:00] partnerships as well. And just thinking [5:03] about those examples of what we're going [5:04] to step through through just remember [5:07] your partner who can be very effective [5:09] with you comes in all different shapes, [5:12] sizes, and forms. Be sure you know that [5:14] and look out to see who has information, [5:17] experience, examples um that would be [5:21] beneficial to me and my organization. [5:24] You may be able to partner with more [5:26] than who you may think about and there [5:28] could be a willingness for others to [5:30] partner with you and your organization [5:32] that you haven't even considered before. [5:35] All right. So, let's talk about the [5:37] academic and industry partnership [5:40] example and step through that model as [5:43] far as what we have integrated at the [5:45] University of Arizona global campus. So [5:47] I'm in front of our technology studies [5:49] organization and I'm very proud to say [5:52] that our technology programs all each [5:55] program has integrated AI within the [5:59] curriculum. Finding out exactly how [6:01] we've done that it could vary based on [6:04] the program chair in front of the [6:06] program based on the course and the [6:09] topic of study as well. But we have [6:12] intentionally planned to do that. In so [6:15] doing that we have partnered with [6:18] organizations who bring forward to us [6:20] platforms that our students then can [6:23] use. Those platforms provide handson [6:27] industry demanded tools for our students [6:32] as they learn that various topic as they [6:35] use those handson equipments as well and [6:39] they learn the industry directions and [6:41] targets. In our session yesterday in the [6:45] round table, we had a very passionate [6:47] attendee who may be with us this [6:49] morning. He was a physician and he [6:52] talked about individuals finishing their [6:54] degree path. We actually had two. One [6:57] was in cyber security and now they're on [7:00] the job and they are not familiar with a [7:03] lot of the industry methods and ways and [7:05] practices and tools that is not [7:08] effective for that business. and he [7:11] really asks how can we as higher [7:14] education tighten that gap and make sure [7:17] that students who are going through [7:19] programs are actually getting the skills [7:21] that they need to get. So in our case, [7:23] we have partnered with businesses, [7:25] CompTIA is one example, to make sure [7:28] we're providing those handson [7:30] development platform tools our students [7:33] can use where they are learning the [7:35] skills, they are learning the techniques [7:38] and the and the technology that they [7:40] then will use in industry. And you can [7:43] see on there the different types of [7:45] skills that they learn as well where [7:48] when they are even interviewing they can [7:50] say yes I have used those tools I have [7:52] developed with those tools I'm familiar [7:54] with those practices as well and they [7:57] then can be very productive as they step [8:00] into industry. And so there are various [8:03] different ways that academics can [8:05] partner with industry. Just think about [8:08] your environment and how if you're not [8:11] using industry partners, how you can [8:15] enhance the learning for your students [8:17] in doing just that. [8:19] So talking through the example of um [8:22] government and research, you know, if [8:25] you're not thinking of how government [8:27] can really assist with research within [8:30] your university, your college, your [8:32] place of learning, I am a fullbrite [8:36] specialist and I just returned from [8:38] Croatia where I provided a partnering [8:41] direction with the university in Croatia [8:44] as we looked at the integration of AI to [8:48] support the human centric side of AI. [8:52] And for those in their um human centric [8:56] programs that they have, they're [8:57] basically their cognitive science areas [8:59] and programs in the university. Our [9:02] keynote speaker talked again about that [9:05] human centric side of AI. And so I was [9:08] hauled there to make sure I was working [9:10] with them as they looked at what should [9:12] be in our programs, what should be in [9:14] our curriculum, what should be in our [9:16] courses, what should our students know. [9:18] I met with the students and met with the [9:20] faculty and we did planning and we [9:22] talked through what was important to [9:24] make sure that the training that they're [9:26] providing to their students has the [9:28] human centric side. That means it's [9:31] ethical. That means we're looking at all [9:33] the factors of integrating AI that's [9:35] important that the student should be [9:37] aware of as they graduated and then they [9:41] are now in industry they will assist [9:43] companies and making sure that their AI [9:46] directions indeed are human centric [9:50] related and aligned and so that's just [9:52] one example of partnering with [9:54] government to extend your research and [9:57] your research directions and if anyone [9:59] wants to know anything more about [10:01] forbrite just tap me on the shoulder. I [10:03] would love to share that with you as [10:05] well. [10:07] And the last example of the model that [10:09] we'll share before turning it over to my [10:11] colleagues here is partnering with [10:13] community. Again, expand our minds when [10:17] we think about who would be good [10:19] individuals to partner with. There could [10:22] be partners out there that we're not [10:24] thinking of who bring a lot of value [10:26] into the table and vice versa. we [10:29] provide a lot of value back to them as [10:31] well. So here is another example. Myself [10:34] and others in this crowd actually [10:36] support a nonprofit organization called [10:39] Shades of Blue. Shades of Blue is an [10:41] organization there to educate [10:43] individuals interested in stepping into [10:46] aviation and aerospace positions. I have [10:49] worked with them for a while. I provide [10:51] the technical input and insights to [10:54] them. myself and a colleague who's in [10:57] attendance to this conference are [10:59] actually working with them to develop [11:01] curriculum that goes into their [11:03] curriculum package to support aviation [11:07] in um artificial intelligence in [11:10] aviation and aerospace. So we are [11:12] helping them to develop out their [11:14] curriculum that they will provide to [11:16] those who are going through their [11:18] program to prepare our pilots, our [11:21] mechanics, everyone who's working in [11:23] aviation and aerospace as well, [11:26] especially when it comes to integrating [11:29] AI to assist in those directions. So [11:33] those are just three examples of how [11:36] partnering in business is so so [11:38] effective and so so essential. And once [11:41] again, a takeaway and we're going to [11:43] talk about a call to action once we [11:44] leave is when you are thinking of what [11:48] type of partnering should we have. Think [11:51] about this. Make sure that your [11:53] partnering has a shared language and [11:55] success metrics between you and your [11:57] partner speak the same language. What [11:59] are your goals? Right? Our strategy [12:01] should be similar. Cross- sector in AI [12:05] labs or co-creation with your partner. [12:08] There are partners who are here to help [12:11] especially higher education institutions [12:13] to develop out those labs so that [12:16] students can go and community and [12:18] industry can go to get that hands-on [12:20] exposure and then also to have a place [12:23] for continuous skill building as well. [12:27] Does that sound good? [12:29] All right. So now we are going to get up [12:31] close and personal to an example of what [12:33] we have and what we've moved into place [12:36] at the University of Arizona Global [12:38] Campus. I'm going to ask if Eric [12:40] Peepenbrink can come to the mic and take [12:42] control as well. Thank you. [12:44] >> And they will share the example. [12:46] >> Want me to next? [12:48] >> Okay. [12:50] >> Good morning. Uh my name is Eric [12:52] Peepenbrink and I represent I serve as [12:55] the vice president of student services [12:57] at University of Arizona Global Campus. [12:58] So, I represent our team of 100 mighty [13:02] ac academic adviserss and uh they serve [13:06] approximately 20,000 non-traditional [13:09] students. So, um with that is a lot of [13:13] joy but also a lot some inherent issues [13:15] and we were trying to figure out how to [13:17] solve one of our issues recently. Um, if [13:20] you look on the screen, you can [13:22] basically see like one of the biggest [13:24] things that we are not doing at UAGC in [13:26] student services is using two-way [13:28] texting with students, which is crazy [13:30] cuz we're probably like 15 years behind [13:32] in getting there. Uh, but we're not [13:34] there yet. So, we're working on that. Um [13:36] but the other um kind of primary things [13:39] that we wanted to figure out was how to [13:41] use some kind of technology, some kind [13:44] of AI, whatever it may be to more [13:46] effectively put our adviserss in the [13:48] right place at the right time with the [13:50] right students. Many years ago, we did [13:52] build a machine learning model that put [13:54] a lot of information in front of [13:56] adviserss to give them um the [13:58] opportunity to have a little bit more [14:00] narrow focus on who probably needs them [14:02] the most right now. Um, but more [14:05] recently we realized we just really [14:07] needed to implement the student voice in [14:10] our work and a lot of our work is [14:13] reactive to whatever the situation may [14:15] be. Students do this, we find out about [14:17] it, we call them, we talk to them about [14:19] what's going on. Um, sometimes it's [14:22] things they didn't do, but it's usually [14:23] what they did. What we know is that [14:26] students want to tell us what's going on [14:29] in most cases. Um, and we wanted to do a [14:31] better job of learning about those [14:34] things from the student voice prior to [14:36] them making the mistakes in the class or [14:38] them not showing up for class or [14:40] whatever it may be. We've done a lot of [14:42] chasing our students over the years to [14:44] try to make sure that they know what we [14:46] have to provide for them, all the many [14:48] resources, all the many different ways [14:49] that we can help them. Um, so we're [14:51] looking for a way to more effectively [14:54] connect with them in advance of getting [14:56] to that edge of the cliff, if you will. [14:58] Um, and in our search to do so, we found [15:02] Edsites, which to Karen's point earlier [15:04] is all about uh creating a partnership [15:06] to solve a problem. So, I'd love to turn [15:09] it over to Melissa who can talk a little [15:10] bit about the product that we are now [15:12] using um to do that for our students. [15:17] >> Morning everyone. Melissa Crowley. I'm [15:19] with Edsite. Um, if you're not familiar [15:21] with us, we're an edtech company. And so [15:24] we partner with institutions like [15:26] University of Arizona Global Campus. Um, [15:28] and what our focus is on scaling [15:31] proactive outreach strategies for [15:33] outreach teams like Eric's advising [15:35] team. And so what we actually do is [15:38] we'll leverage SMS and AI together to [15:41] bring our partners a chatbot that will [15:44] engage with their students as they're [15:46] enrolled in their courses. And so we [15:48] have two functionalities to that chatbot [15:50] that we've been leveraging for UAGC. And [15:53] so we have a reactive. So that chatbot's [15:55] available 24/7. Students can proactively [15:58] outreach, answer any get any questions [16:00] they have answered, like when's the next [16:02] term start, how do I get courses or if [16:04] they need writing resources. And so all [16:07] of the responses are built off of the [16:10] partners' internal resources. So, we're [16:12] connecting them to what's available um [16:15] that they should be familiar with [16:16] already. The other part that we really [16:19] um lean into is a proactive messaging [16:21] framework. And so, we build that off of [16:24] four areas of focus. Um wellness, [16:26] financial, uh social engagement, and [16:29] academics. So every proactive message [16:31] we're sending to students as they're in [16:33] their courses is designed to tie into [16:36] one of those areas of focus that then [16:38] turns around and tells Eric's team the [16:40] likelihood of a student to persist. So [16:43] the goal for us is to let that chatbot [16:46] answer a lot of the tier one questions [16:48] that students have get them a resource [16:51] in real time while also identifying the [16:53] students who are at risk of not [16:55] persisting and then let the advising [16:57] team spend their efforts there and [16:59] calling the students cuz we know it's a [17:01] combination of getting them a resource [17:03] but there are students at this point who [17:04] need a human to support them. We're [17:08] giving them additional insights through [17:09] their dashboard dashboard um to give [17:12] them more highle understanding of their [17:14] student demographic and how they are [17:16] moving through their courses. [17:19] So as oh did I go backwards? I think so. [17:24] Oh go back on here we go. So as we move [17:27] through the pilot um edtech and I can't [17:30] figure out a clicker. Uh so as we moved [17:33] through the pilot what we really saw is [17:35] a high level engagement from students. [17:37] We always looked at how often um what's [17:40] our percentage of students remaining [17:41] opted in and then um really how they're [17:44] engaging throughout their courses. And [17:47] we saw a really active population and [17:49] we're able to see also a high level of [17:51] psychological safety with these students [17:53] and the information they shared. um [17:56] knowing that for some of these students [17:58] they may not have engaged with their [17:59] adviser yet or they may have felt [18:01] challenged in how do I share exactly [18:03] what I'm going through with someone. So [18:05] they shared it with the chatbot so that [18:07] the chatbot knowing this would tell the [18:10] adviser and the adviser is going to call [18:11] me and they what we've done for the [18:13] adviser is also shared with them that [18:15] conversation with the student so they [18:17] have all that information readily [18:19] available to them to prep for what that [18:21] phone call will look like. And so it [18:24] really allows the adviserss to spend [18:26] more time digging into those students [18:28] needs um and thinking about how to [18:31] support them in the future. [18:33] >> Very good. [18:35] >> Now I think Melissa, I think you left [18:37] out one thing. What's the name of our [18:38] bot? [18:39] >> Oh yeah, Jazz. [18:41] >> Yes. Yes. [18:43] >> This group got to brand the bot. So it's [18:45] all branded to um University of Arizona [18:48] Global Campus and they selected Jazz. [18:50] >> Yes. Fantastic. And so some takeaways [18:53] guys as we wrap up. Partnership is the [18:55] new edge. Do not try to do your AI [18:58] integration by yourself. You don't have [19:00] to. Transformation demands cocreation. [19:03] Be innovative, right? But work together [19:07] as you work on your transformative AI [19:10] directions of what your organization is [19:12] doing. Lead with inclusion. You have [19:15] individuals within your organization who [19:18] have expertise, who have experience, who [19:21] have insight, but most important within [19:24] with AI, they have the urge to move and [19:26] help the organization get to the next [19:28] level. Seek out those individuals in [19:31] your organization and guess what? Use [19:33] them, right? And then the fourth is [19:36] together partnership shapes the future [19:39] of AI. That's our presentation for [19:42] today. Do we have one minute? We have [19:44] exactly one minute. Is there one [19:46] question? [19:50] If not, we'd like to say thank you for [19:52] attending with us today. Partner, [19:54] partner, partner. Okay, take care.