人工智能可以加强您本学年教学的5种方式

原文标题: 5 ways AI can strengthen your teaching this school year
来源: eSchoolNews | 发布时间: 2026-08-17
原文链接: 点击阅读原文

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Key points:

• The future of education is not defined by AI, but by educators who use it wisely

• Schools are building AI rules before they know the destination

• Leading with AI and technology in the age of personalized learning

• For more news on AI and teaching, visit eSN’sDigital Learninghub

A year ago, many educators were still asking whether artificial intelligence belonged in the classroom. Some were cautiously experimenting with AI-generated lesson plans, while others were focused on preventing students from using it altogether.

Today, the conversation has evolved.

Across the country, school districts are developing AI guidance, investing in educator-specific platforms, and providing professional learning around responsible implementation. Teachers are moving beyond asking,“Can AI write a lesson plan?”and beginning to ask a much more meaningful question:“How can AI help me become a more effective teacher?”

That’s an important distinction.

The best educators aren’t using AI to replace their expertise. They’re using it to amplify it.

But the real promise of AI isn’t that it helps teachers produce more. It’s that it helps educators protect more time for the human work of teaching. When technology reduces the hours spent formatting materials, rewriting directions, or completing repetitive administrative tasks, teachers gain more opportunities to greet students at the door, confer with them about their learning, notice when something feels off, and build the trust that makes meaningful learning possible.

AI should never create greater distance between teachers and students. Used thoughtfully, it should do the opposite. It should give educators more capacity to create belonging—because before students respond to instruction, feedback, or expectations, they need to know they are seen, supported, and valued.

As you prepare for the 2026–27 school year, here are five ways AI can strengthen your teaching while keeping relationships—and learning—at the center.

1. Build an AI workflow, not just an AI toolbox

One of the biggest shifts over the past year is that AI is no longer a single tool or website.

Today’s educators are using different AI platforms for different purposes:

• Brainstorming lesson ideas

• Creating differentiated instructional materials

• Developing formative assessments

• Translating family communication

• Designing visuals and presentations

• Analyzing student work

• Summarizing research

• Organizing instructional resources

Rather than asking,“What’s the best AI tool?”begin asking,“What’s the best AI tool for this task?”

Just as we don’t rely on one program for grading, email, presentations, and data analysis, we shouldn’t expect one AI platform to meet every instructional need.

The goal isn’t mastering every new tool that appears. It’s building a workflow that helps you teach more intentionally and efficiently.

2. Differentiate faster—without lowering expectations

Differentiation has always been one of the most rewarding—and time-intensive—parts of teaching.

AI can now help teachers quickly create:

• Multiple reading levels of the same text

• Vocabulary supports

• Sentence stems

• Graphic organizers

• Extension activities

• Accommodations for diverse learners

• Multilingual resources

The objective isn’t to make learning easier.

It’s to make learning more accessible.

When teachers spend less time recreating the same lesson five different ways, they gain more time to meet with students individually, facilitate meaningful discussions, and provide targeted support.

Technology shouldn’t replace high expectations. It should remove unnecessary barriers so every student has an opportunity to meet them.

3. Let AI support student thinking—not replace it

Perhaps the most important evolution in AI has been the shift from simply generating answers to supporting the learning process itself.

Instead of asking students to use AI to complete assignments, encourage them to use it to deepen their thinking.

Students can ask AI to:

• Explain a difficult concept in another way

• Identify gaps in their reasoning

• Practice academic conversations

• Revise their writing

• Generate practice questions before an assessment

• Reflect on their own learning

The most powerful AI doesn’t think for students.

It helps students think more deeply.

That subtle shift changes AI from a shortcut into a learning partner.

4. Make AI literacy part of every classroom

Today’s students don’t simply need rules about AI.

They need instruction.

Just as we teach digital citizenship and media literacy, AI literacy has become an essential skill.

Students should learn how to:

• Write thoughtful prompts

• Recognize inaccurate or fabricated information

• Identify bias in AI-generated responses

• Verify information using reliable sources

• Acknowledge when AI has been used appropriately

• Decide when AI is helpful—and when independent thinking is the better choice

Teaching students how to think critically about AI may prove more valuable than teaching them how to use any single platform.

Technology will continue to evolve.

Critical thinking will always matter.

5. Use AI to create more time for belonging before behavior

Teachers didn’t choose this profession because they enjoy formatting documents, rewriting directions, or drafting routine emails.

They chose it because they wanted to make a difference in the lives of young people.

AI can help educators reclaim valuable time by assisting with tasks such as:

• Drafting family communication

• Creating rubrics and instructional materials

• Summarizing formative assessment data

• Organizing meeting notes

• Brainstorming intervention and enrichment ideas

• Developing first drafts of newsletters or classroom updates

But saving time isn’t the goal.

The real question is:What will you do with the time you get back?

If we believe that belonging comes before engagement, before motivation, and yes, before behavior, then every minute AI gives back to us is another opportunity to strengthen the relationships that make everything else possible.

Use that time to greet students at the door.

Sit beside a reluctant reader.

Conference with a writer.

Celebrate a student’s growth.

Call home with good news.

Check in with the student whose behavior has suddenly changed.

Laugh with your class.

Listen before you redirect.

Those moments will never be generated by artificial intelligence.

They can only be created by a caring educator.

Technology should never make teaching less human. It should create more opportunities for the relationships that make learning possible. Before students engage with curriculum, feedback, or expectations, they need to experience belonging.

AI is at its best when it helps educators become more present—not simply more productive.

Final thoughts

The biggest change over the past year isn’t the technology.

It’s our mindset.

The conversation is no longer about whether AI belongs in education.

It’s about ensuring educators lead its implementation with purpose, ethics, and sound instructional practice.

The future of education is not AI replacing the teacher at the center of the classroom. It is thoughtful educators using AI to protect what technology cannot replicate: professional judgment, empathy, trust, and human connection.

The most meaningful measure of AI’s value will not be how much more work educators produce. It will be whether the time it saves allows them to know students more deeply, respond more thoughtfully, and build classrooms where every learner feels seen and supported.

As the 2026–27 school year begins, let’s embrace AI not as a replacement for great teaching, but as a tool that allows us to do more of what has always mattered most.

Because the future of education isn’t defined by artificial intelligence.

It’s defined by the educators who use it wisely.

And the best use of AI may simply be this: helping us spend more time being the teachers our students need us to be.

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Timothy Montalvo is a middle school educator and leader passionate about leveraging technology to enhance student learning. He serves as Assistant Principal at Fox Lane Middle School in Westchester, NY, and teaches education courses as an adjunct professor at Iona University and the College of Westchester. Montalvo focuses on preparing students to be informed, active citizens in a digital world and shares insights on Twitter/X @MrMontalvoEDU or on BlueSky @montalvoedu.bsky.social.

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• Today’s classroom isn’t broken–but it wasn’t built for today’s top students- August 18, 2026

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本报道由 AI 助手自动抓取、翻译并发布。

学校在知道目的地之前就开始构建人工智能规则

原文标题: Schools are building AI rules before they know the destination
来源: eCampusNews | 发布时间: 2026-08-17
原文链接: 点击阅读原文

Key points:

• Career durability depends on fundamentally human skills that give students the flexibility and adaptability to adjust to changes

• Higher education needs better AI experiences, not more AI tools

• A strategic roadmap for AI in higher education

• For more news on schools and AI pathways, visit eCN’sAI in Educationhub

America’s schools are moving quickly to respond to the rise of artificial intelligence, with parents, teachers, administrators, and lawmakers working to wrap their arms around what this means for student education.

But regulation that comes ahead of a clear definition of preparedness may set students back in the AI race. For the future of America’s students — and economy — leaders need to first define what the future of career preparedness looks like.

The speed at which education leaders have moved to respond to AI has been nothing short of remarkable. Just a few years ago, there were no states with formal guidance on AI in K-12 education. Today,34 states and Puerto Ricohave issued some sort of AI guidance for schools. More than 70 bills about AI in the classroom have been introduced across 27 statesthis year alone,as policymakers debate every aspect of AI, from classroom restrictions and student privacy, to graduation requirements and teacher training.

Yet as schools debate every part of AI policy, including who is and isn’t allowed to use it, how they’re allowed to use it, and when they’re allowed to use it, they’re skipping over a more fundamental issue. What do students actuallyneedto learn in order to be successful for the rest of their lives post-graduation?

It’s a question that should fundamentally drive most education policy decisions, especially when it comes to students in the final years of high school and in college. Before schools can determine what students should avoid, they need to first understand what needs to be encouraged based on the demands of employers and the changing business landscape.

This isn’t about letting businesses dictate education policy. We’ve seen industry lead students astray before. The bootcamps and computer science degrees students not long ago were told would lead to higher paying jobs have nowfizzled out— a short-term need now rendered obsolete by the advancement of AI.

The mistake we made then was over-indexing on short-term signals. Several years ago, there was high demand for computer engineers, so education leaders gave students one set of skills needed for one defined future.

Then things changed.

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Scott Laband is the President and CEO of Colorado Succeeds, a nonprofit, nonpartisan coalition of business leaders committed to improving the state’s education and workforce system.

• Schools are building AI rules before they know the destination- August 17, 2026

• Cohort connections matter: Strategies to help graduate students persist and succeed- August 14, 2026

• Higher education needs better AI experiences, not more AI tools- August 12, 2026

本报道由 AI 助手自动抓取、翻译并发布。

AI教育，一边狂奔一边刹车——本周智能教育大事札记

这周智能教育领域最值得咂摸的，不是又发布了什么大模型，而是一边有人在狂奔，一边有人在喊”慢一点”。世界银行把 AI 称作发展中国家的”生命线”，地方高校忙着建行业大模型，教育科技公司连夜接入新模型；与此同时，李飞飞和肖仰华两位学者不约而同地提醒：别让工具夺走孩子学习的动力。快与慢的拉扯，构成了本周最真实的底色。

一、世界银行：AI 是发展中国家的”生命线”

8 月 4 日，世界银行发布《世界发展报告 2026：人工智能》，首席经济学家吉尔说了一句很重的话：”AI 为发展中经济体提供了一条生命线，应该抓住它。”报告建议发展中国家不要盲目建大模型、大算力，而是把小型、低成本的 AI 工具做本地化适配，用在教育、医疗、农业上——“10 年内完成原本可能需要一个世纪才能做到的事”。

我的看法：这份报告最打动我的，是它把 AI 教育从”富国的玩具”拉回到”穷国的机会”。它提醒我们，AI 教育的价值不在参数规模，而在能不能让一个没电、没网、缺老师的乡村学校，也享受到优质教学资源。报告里有个细节很扎心：撒哈拉以南非洲，三成乡村学校没有稳定的电力，89% 的 10 岁孩子读不懂基本文字——“老师想用 AI 备课，可灯都亮不起来”。技术再先进，也绕不开基础设施这道坎。这让我想到国内正在做的事：科大讯飞的 AI 黑板已经走进超 10 万间教室，其中不少在偏远地区；阿里巴巴少年云用轻量化 AI 工具把村落变成课堂。世界银行说的”本地化适配”，中国其实已经在用脚投票了。

二、高校实践：行业特色大模型开始冒头

8 月 12 日，大连海事大学发布航海教育大模型 1.0，聚焦航海技术、轮机工程、船舶电子电气工程三个专业，搭建专业知识库和结构化专业图谱，部署智能体集群，为师生提供智能备课、学情分析、全天候学伴等服务。

我的看法：通用大模型之外，垂直行业的教育大模型开始冒头了。航海教育高度专业化，通用模型答不好”船舶避碰规则”，但行业大模型可以。这种”专业图谱+智能体集群”的模式，可能是高校 AI 教育的一条新路——不追求大而全，而是把某个行业的知识体系吃透。对职业教育和行业特色高校来说，这比追逐通用大模型更务实。想想看，如果每个行业都有自己”懂行”的教育大模型，AI 教育才算真正长在了产业的土壤里。

三、地方协同：AI 教育研究中心落地黑龙江

8 月 14 日，黑龙江省”1+13”人工智能教育教学研究中心启动建设，省教育厅支持哈工大牵头建设省级中心，哈尔滨工程大学、东北林业大学、东北农业大学等高校围绕船海核、生态、农业、医学、智能制造等领域成立分中心，覆盖理工农医文各学科。

我的看法：地方政策从”要不要做”进入”怎么做”的阶段了。黑龙江的亮点在于”AI+龙江优势领域”——航天科技、海洋工程、智慧农业、冰雪经济，都是黑龙江的看家本领。把 AI 教育研究中心建在产业需求上，比空喊”培养 AI 人才”实在得多。这种”一省一策”的差异化，和宁波的”产业适配型 AI 教育”异曲同工：AI 教育正在从无差别的通识课，变成和本地产业咬合在一起的”定制课”。

四、产业动态：教育科技公司紧跟模型迭代

8 月 13 日，网易有道宣布全线产品接入 DeepSeek-V4-Pro，从词典、翻译到 AI 答疑笔、口语陪练 Hi Echo，全部换上新模型。有道词典面对数万字的合同、白皮书能整体承接、连贯译出；Hi Echo 能基于对话历史做多维度口语评测，对话结束后自动生成评测报告。

我的看法：国内教育科技公司跟着模型迭代的速度，肉眼可见地加快了。距离月初接入 V4-Flash 仅十余天，有道又完成了一次升级。这背后是一个趋势：教育 AI 产品的竞争，正在从”谁的模型强”转向”谁把模型用得好”。模型是公共的，但把模型能力变成用户体验，才是各家真正的护城河。对用户来说，这是好事——不用换 App，就能用上最新的模型能力。

五、出海实践：中国 AI 教育走向世界

本周，中国 AI 教育出海有两件事值得记一笔。8 月 12 日，科大讯飞宣布星火大模型落地海外教育场景，主动适配多国教育数据安全与 AI 治理规范，AI 中文智慧教学、AI 黑板、智能批阅机等产品已获多国教育主管部门认可。8 月 3 日，阿里巴巴少年云”村落即课堂：轻量化 AI 工具赋能乡村遗产教育”案例，从全球 90 多个项目中脱颖而出，获联合国教科文组织 2026 全球世界遗产教育创新案例最高奖”卓越之星”。

我的看法：过去我们习惯”引进来”，现在开始”走出去”了。科大讯飞的出海，难点不在技术，而在合规——每个国家的数据安全法规都不一样，能主动适配，说明中国 AI 教育企业开始认真对待海外市场。阿里少年云拿奖，则是一个更柔软的故事：用 AI 把村落变成课堂，让山区的孩子用语音识别转写老人的口述、用图像识别留存传统建筑。技术出海之外，还有”温度出海”——这可能是中国 AI 教育最独特的竞争力。

六、反思声音：AI 进校园，快还是慢？

本周最有价值的声音，来自两位学者。8 月 12 日，斯坦福大学教授李飞飞警告：AI 进校园的最大风险不是作弊，而是削弱年轻一代的自主性和学习动力。”最糟糕的结果是，我们年轻一代的自主性和人类水平的学习和生活动力被工具夺走了。”8 月 9 日，复旦大学教授肖仰华更直接：AI 进中小学校园，可以慢一点！基础教育应该成为”AI 不可染指的保护区”。他做了一次实验，让 51 名学生出题”考倒”AI，结果发现 AI 正在放大马太效应——强的更强，弱的更弱。

我的看法：这两段话，是本周最该被反复咀嚼的。当所有人都在比谁跑得快时，有人站出来问”我们是不是跑得太快了”，这本身就是进步。李飞飞和肖仰华都不是反对 AI，而是反对”把思维训练外包给 AI”。肖仰华那句”AI 不会自动让人变强，它只会放大你原有的能力”，尤其值得琢磨——如果你本来就有扎实的判断力，AI 是杠杆；如果连基础都没打好，AI 只会让你更快地放弃思考。这提醒我们：AI 教育的终点，不是让机器替人思考，而是让人学会和机器一起思考。

七、青少年赛事：首届全国青少年 AI 大赛落幕

8 月 3 日，首届全国青少年人工智能大赛决赛在上海黄浦落幕，由中国福利会和中国妇女发展基金会共同主办，1200 余人参加。大赛设置”智星·拔尖人才专项奖””智蕴·女性学生专项奖””智惠·普及普惠专项奖”，还启动了”青少年人工智能沃土计划”，面向偏远地区开展普及普惠活动。

我的看法：这个赛事最打动我的，是它把”拔尖”和”普惠”放在了一起。一方面选拔专才，另一方面专门设了”普及普惠专项奖”，让偏远地区的孩子也有机会触摸科技前沿。联合国儿基会驻华代表桑爱玲说了一句话：”人工智能已不再是属于未来的技术，它正在塑造当今的童年。”赛事的意义，不只是比出谁更厉害，而是让更多孩子知道：AI 不是别人的玩具，你也可以用它创造点什么。

写在最后

回看这一周，智能教育像一条奔涌的河：世界银行在喊”抓住生命线”，高校在埋头建行业大模型，企业在连夜迭代，而学者在喊”慢一点”。快与慢，其实不矛盾——快的是技术迭代，慢的是教育规律。技术可以一夜之间更新，但人的成长、思维的形成，从来急不得。本周最大的启发或许是：AI 教育的关键，从来不是快慢，而是方向——我们到底想让 AI 成为孩子的”外置大脑”，还是”学习伙伴”？答案，决定了教育的未来。

素材来源清单

1. 世界银行《世界发展报告 2026：人工智能》——中国青年报（2026-08-05）https://www.toutiao.com/article/7670471616983368198
2. 大连海事大学发布航海教育大模型 1.0——信德海事/新浪财经（2026-08-12）https://www.toutiao.com/article/7673153007295463936/
3. 黑龙江”1+13”人工智能教育教学研究中心启动——人民网（2026-08-14）https://www.toutiao.com/article/7673803487091769899/
4. 网易有道全线产品接入 DeepSeek-V4-Pro——企鹅号（2026-08-13）https://so.html5.qq.com/page/real/search_news?docid=70000021_1326a7d9a2a48852
5. 科大讯飞星火大模型落地海外教育场景——微博/2026 全球智慧教育大会（2026-08-12）https://weibo.com/3194153385/5331225675568192
6. 阿里巴巴少年云获 2026 全球世界遗产教育创新案例最高奖——企鹅号（2026-08-04）https://so.html5.qq.com/page/real/search_news?docid=70000021_5516a71b20e17552
7. 李飞飞警示 AI 进校园风险——环球网（2026-08-12）https://www.toutiao.com/article/7672981086892327433/
8. 肖仰华：AI 进校园可以慢一点——上观新闻（2026-08-09）https://www.toutiao.com/article/7671946465194803739/
9. 首届全国青少年人工智能大赛决赛落幕——上海市人民政府（2026-08-05）https://www.shanghai.gov.cn/nw15343/20260806/6c7cd021cb224e76a44fc8634227df99.html
   （内容由 AI 生成，仅供参考）
   （内容由AI生成，仅供参考）

AI正在改写课堂的“默认设置”：智能教育一周观察

这周最让我心头一紧的新闻，不是哪家大模型又刷了分，而是谷歌把 Gemini 直接塞进了 1.7 亿学生的课堂。8 月 10 日起，Google Classroom 里的 AI 学习功能向全年龄段学生开放，不再有年龄门槛。AI 第一次以“默认配置”的身份，出现在全球最大教育平台的日常流程里。回看本周的智能教育大事，几乎都绕着同一个主题打转：AI 正在从“可选插件”变成“默认设置”——有人主动拥抱，有人被迫适应，也有人悄悄把 AI 带去了最偏远的乡村。

一、谷歌把 AI 变成课堂的“默认配置”

8 月 10 日，谷歌宣布 Google Classroom 中的 Gemini 功能向全年龄段 K-12 及高等教育学生开放（需学校管理员授权）。学生可以把课程资料一键转成抽认卡、练习测验、学习指南，还能结合作业要求进行“情境化引导”——把作业要求直接喂给 AI，让它帮忙理出写作框架。Google Workspace for Education 全球有超过 1.7 亿用户，这意味着这是历史上单日触达规模最大的 AI 教育部署之一。

我的看法：这件事的分量不在功能本身，而在“默认”二字。过去两年，教育科技公司都在讲“AI 进课堂”，但几乎都要单独采购、单独注册、单独培训。谷歌这次什么都没要——它把 AI 嵌进了学生本来就在用的界面里。对 Quizlet、Chegg 这些靠“学习工具”吃饭的公司来说，这是釜底抽薪；对学校来说，这是“零门槛”的诱惑。但我也在想：当 AI 成为默认配置，学生还会主动思考吗？谷歌的产品里没有强制“主动回忆”的机制，抽认卡一键生成，会不会让记忆变成“看过即忘”？技术越方便，越考验人的自觉。

二、OpenAI 给教师和学生发了三张“工作流卡片”

8 月 4 日，OpenAI 发布三款面向教育工作者的预配置插件：K-12 Educator（K-12 教师）、College Educator（大学教师）、College Student（大学生）。教师插件能生成差异化教学资源、更新课程大纲、打包学习管理系统内容；学生插件能围绕课程资料生成学习指南、测验、闪卡，还能制定学习计划同步到日程。

我的看法：OpenAI 这次没有做“更聪明的 AI”，而是把 AI 打包成了“即插即用”的角色。这背后是一个很务实的判断：学校里真正缺的不是大模型，而是“知道怎么用大模型的人”。把角色、技能、指令和工作流打包好，让老师不用从零写提示词——这是把 AI 从“玩具”推向“工具”的关键一步。不过，插件再好，也替代不了老师对“教什么、为什么教”的判断。工具越顺手，越要警惕用 AI 的勤奋掩盖思考的懒惰。

三、新加坡国立大学：不会用 AI，毕不了业

8 月 11 日，新加坡国立大学（NUS）宣布，从今年 8 月入学的新生开始，所有本科生必须完成至少两门 AI 必修课才能毕业。所有学生、教师和员工还将获得 ChatGPT Edu 的免费访问权限。教务长 Aaron Thean 说了一句很戳人的话：“大学的核心业务是培养人，不是培养 AI。”

我的看法：这是亚洲顶尖大学第一次把“AI 素养”写进毕业的硬性门槛。注意它的设计：不是让所有学生都去学编程，而是让每个专业都有一门“AI 如何改变本专业”的课——商科学生学“用 AI 做决策分析”，政治学学生学“AI 与公共政策”。这比“人人学 Python”高明得多。它承认了一个现实：AI 素养不是一门课，而是所有学科的底色。相比之下，国内高校的 AI 通识课大多还在“要不要开”的讨论里打转，NUS 已经把它变成了毕业证的一部分。差距不在技术，在决心。

四、宁波：一座城市把 AI 教育写进三年行动方案

8 月 10 日，《中国教育报》报道，宁波市教育局发布《宁波市中小学人工智能教育行动方案（2026—2028 年）》，提出开展“智能助教”试点、推广人机协同教学，还首创“AI 虚拟教研员”，把港口物流、智能制造、海洋经济等本地产业嵌入课程开发。

我的看法：宁波这份方案最打动我的，是“产业适配型 AI 教育”这个提法。很多地方的 AI 教育是“为 AI 而 AI”，学完就忘；宁波却把 AI 教育跟本地产业绑在一起——港口物流、智能制造、海洋经济，都是宁波的看家本领。这其实回答了 AI 教育一个根本问题：学了到底有什么用？当孩子能用 AI 解决身边真实的问题，AI 教育才算真正落地。另外，“AI 虚拟教研员”这个细节也很有意思——教研从“经验驱动”转向“数据+智能双驱动”，这可能是教师专业发展里最被低估的变革点。

五、一块会思考的黑板，让外国网友惊呼“教育的未来”

本周，一段中国 AI 黑板的视频在海外社交媒体刷屏：老师在黑板上手写公式，内容实时同步大屏；圈定函数算式，系统即刻生成动态曲线；随手画个立方体，瞬间变成可旋转的 3D 模型。加拿大博主感叹“这就是教育的未来”，不少美国网友以为是 AI 特效。据中国青年报报道，在安徽、江苏、广东等地，超过 10 万间教室已经用上了这种“会思考”的黑板。

我的看法：这条新闻让我有点复杂。一方面，中国 AI 教育硬件确实走在了前面——10 万间教室不是 PPT 里的数字，是真实存在的课堂。另一方面，海外网友的惊叹也提醒我们：技术领先不等于教育领先。黑板会思考了，但坐在黑板前的孩子，有没有学会思考？科大讯飞说“不是通过拉平差异，而是尊重每个孩子的个性化成长节奏”，这句话很漂亮，但真正的考验在课堂之外——AI 黑板录下的每一堂课，能不能真正变成老师改进教学的依据，而不是又一块“更贵的显示屏”。

六、AI 教育往乡村走：从“送设备”到“长本事”

本周还有两条关于乡村 AI 教育的消息。一是华东师大联合华为发布“科技小学堂”AI 课程资源包，用农田、果园、蔬菜大棚当“天然实验室”，项目已覆盖 7 个省区 100 余所乡村学校、惠及 1.5 万名学生；二是海尔希望小学教师 AI 训练营在青岛开营，未来三年将覆盖近万名乡村教师。

我的看法：这两条新闻放在一起看特别有味道。过去乡村教育信息化，最常见的是“送设备”——捐一批电脑，装个样子，然后吃灰。但“科技小学堂”和海尔训练营都在做同一件事：把能力留给乡村。前者让孩子用 AI 解决乡土问题，后者让老师学会用 AI 设计课程。设备会过时，但长在老师和学生身上的能力不会。这大概就是“从输血到造血”的真正含义——AI 教育公平，不是让乡村孩子用上和城里一样的设备，而是让他们拥有和城里孩子一样的能力。

写在最后

回看这一周，AI 教育的关键词从“要不要用”变成了“怎么用、为谁用”。谷歌把 AI 变成默认配置，NUS 把 AI 写进毕业要求，宁波把 AI 绑上产业，乡村把 AI 种进土地——四个方向，指向同一个判断：AI 不再是教育的选修课，而是必修课。但必修课不等于好课。技术越普及，越要回答“人往哪里去”的问题。这周我最喜欢的一句话，来自 NUS 教务长：“大学的核心业务是培养人，不是培养 AI。”这句话，值得所有做智能教育的人贴在墙上。

素材来源清单

1. 谷歌 Classroom 全年龄段开放 Gemini：Google Workspace Updates（2026-08-10）；钛媒体《谷歌把 Gemini 塞进课堂，教育科技公司还有活路吗？》https://www.tmtpost.com/agent/ai-article/19667
2. OpenAI 三款教育插件：36氪（2026-08-07）https://www.36kr.com/p/3929351267712386
3. 新加坡国立大学 AI 必修课：The Vibes / The Straits Times（2026-08-11）https://www.thevibes.com/articles/education/126064/singapores-nus-to-make-ai-courses-compulsory-for-all-undergraduates-from-august
4. 宁波中小学 AI 教育行动方案：《中国教育报》2026-08-10 第 01 版（网易转载）https://c.m.163.com/news/a/L3V76AJS0550CBNY.html
5. 科大讯飞 AI 黑板：《中国青年报》2026-08-07（淮北新闻网转载）https://www.hbnews.net/gngj/2026/08-08/xDLgewgr.html；环球网/央视财经 2026-08-05（今日头条转载）https://www.toutiao.com/article/7670340228296606214/
6. 华东师大×华为“科技小学堂”：上海教育传媒网（2026-08-01）https://www.shedunews.net/detailArticle/28407786_30597_dyjy.html
7. 海尔希望小学教师 AI 训练营：中国质量新闻（2026-08-04，今日头条转载）https://www.toutiao.com/article/7670046691705274895/
   （内容由AI生成，仅供参考）

队列连接很重要：帮助研究生坚持和成功的策略

原文标题: Cohort connections matter: Strategies to help graduate students persist and succeed
来源: eCampusNews | 发布时间: 2026-08-14
原文链接: 点击阅读原文

Key points:

• Graduate students often need flexible, low-pressure ways to stay connected

• Archiving your academic journey: Preserving coursework and program artifacts

• How we connect incoming students to the university resources they need

• For more news on student support, visit eCN’sStudent Successhub

Graduate education is demanding and isolating, especially for adult learners balancing coursework, research, employment, and family responsibilities.National data showhalf of doctoral students leave their programs before earning their degree.While many factors influence persistence,one studypoints to peer relationships for reducing isolation, increasing motivation, strengthening confidence, and helping students complete their programs.

To examine this connection, a pilot study was conducted with doctoral students at Winona State University during an academic residency. The study explored how cohort connection, belonging, and peer interaction may support persistence and degree completion. This article summarizes the findings and offers practical strategies for strengthening cohort connections while respecting adult learners’ busy lives.

What the pilot study found

This pilot study surveyed two doctoral cohorts and gathered 20 responses about cohort connection, belonging, and interaction patterns. Students most often stayed connected through texting and group messaging, followed by email, suggesting a preference for informal, accessible communication while balancing doctoral work with professional and personal responsibilities.

Connection outside of residency sessions varied. Forty percent of respondents connected with cohort members six or more times during the week, while 35 percent connected only once or twice. Despite this variation, 90 percent agreed they received peer support when needed, and most reported that cohort interactions strengthened confidence and supported academic success.

Overall, the findings suggest that cohort connection may depend less on frequency and more on whether support feels meaningful, accessible, and available when needed. Because this was a small pilot study conducted in one doctoral program during an in-person residency, the findings are exploratory rather than generalizable. Still, they offer useful insights into how doctoral programs can support belonging, confidence, and persistence.

Strategies to strengthen cohort connection

For adult learners, effective cohort-building should be intentional, flexible, accessible, and low-pressure. Rather than adding more requirements to an already full schedule, cohort connection can be woven into the learning experience in ways that make peer support easier to access and sustain.

What educators can do:

• Strengthen peer relationshipsby making peer interaction a regular, purposeful part of the program’s norms rather than assuming relationships will develop on their own. This can help eradicate large variations of frequency of connection as noted in the study. Small, consistent practices can help students feel seen, supported, and connected without adding unnecessary requirements.

• Begin with brief peer check-ins.For example, instructors can invite students to respond to brief prompts such as, “What is one goal you have for residency this week?”. Students may share aloud, write a response on a sticky note, or post in a digital space, allowing connection without lengthy discussion.

• Create low-pressure accountability opportunities.Offer optional writing sessions, research or study groups, or goal-setting check-ins during demanding points in the program. For example, students might use the time to map out their most pressing educational goals. This supports student confidence, encouraging both new and returning students to participate.

• Normalize help-seeking and peer support.Faculty could invite students to bring “sticking points” to a small group discussion. For example, “sticking points” could be uncertainty about APA formatting, survey wording, or theoretical framework alignment. Peers can offer suggestions, examples, or encouragement.

• Establish optional communication spaces.Program directors can help each doctoral cohort create or encourage cohort-based channels such as Teams, GroupMe, or email groups where students can connect informally before residency begins. The space can be used for informal questions, reminders, resource sharing, dinner plans, or quick encouragement throughout the doctoral program.

• Support cross-cohort mentoring.For example, during residency, pair first-year doctoral students with more advanced students for an informal mentoring conversation. Discussion prompts might include, “What do you wish you had known during your first residency?” or “What helped you stay organized during dissertation work?” This allows new students to receive practical guidance from peers who have recently navigated similar milestones.

• Reduce logistical barriers.Offer asynchronous options, virtual discussion groups, regional meetups, and flexible participation opportunities for students with competing responsibilities.

• Create a culture of belonging.Ensure that the learning atmosphere is supportive and safe for students of all backgrounds, needs, and cultures. For example: Offering accommodations for students with specific accessibility needs, utilizing inclusive language, and formatting presentations and materials to be easily accessible to all students.

What students can do: Stay connected in small ways

Students also contribute to the strength of their learning community. Connection does not require frequent or time-intensive interaction; small, consistent gestures can help peers feel supported and reduce isolation throughout the program.

• Check in with classmates or study buddies.Use a cohort chat to ask questions, share reminders, post resources, or celebrate progress. For example: Students can send a brief message to a classmate such as “Thinking of you today. You’re ready for this,” or “Do you want to do a quick goal check before tomorrow’s writing block?”. These small gestures can help classmates feel seen and supported.

• Share useful resources.Post articles, templates, writing tools, or examples that may help others move forward. For example, students may share tools that helped them move forward in their doctoral work, such as an article on methodology or a dissertation organization template. During residency, these resources could be placed in a shared digital folder for the cohort.

• Form accountability partnerships.Pair with a peer or small group to discuss goals, deadlines, motivation, and progress. For example, two or three students can agree to check in during residency and continue after residency with brief weekly or monthly updates. Each person might share their current goals and barriers, keeping each other supported, accountable, and motivated.

• Engage in low-pressure ways.For example: reacting to a peer update, answering a question, or joining an optional virtual coffee chat when time allows. This reinforces the idea that meaningful cohort connection does not require constant participation.

• Celebrate one another’s wins.Recognize milestones and encourage classmates through the challenging parts of doctoral work. Students can celebrate wins in the cohort group chat or text message group. A short message such as “Congratulations on your topic approval” or “Great job presenting today” can help motivate and reinforce belonging during demanding stages of doctoral work.

The bottom line

Effective cohorts are built through intentional, flexible, and accessible opportunities for peer support. For educators and program leaders, the goal is not to add more required meetings or activities, but to create structures that make connections easier. For students, the goal is to engage in small but meaningful ways that help peers feel supported. When programs make connections visible, optional, and easy to access, cohorts can become an important source of motivation, encouragement, and persistence.

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Kate Glogowski, Ed. D candidate, Speech-Language Pathologist, Workforce Simulation Director, and a Certified Healthcare Simulation Educator (CHSE) at Minnesota State University, Mankato, where she supports workforce simulation-based education with clinical and community partners. She is a doctoral candidate at Winona State University, where her research focuses on simulation-based education and healthcare workforce development.Tinotenda Mupambo, M.S. CCC-SLP, is a Clinical Instructor and Speech-Language Pathologist at Minnesota State University, Mankato in the Master’s of Speech-Language Pathology program where she supervises and teaches graduate students in the on-campus speech therapy clinic. She is also a doctoral student in the Doctor of Education program at Winona State University.Stacy Schilling, M.S. Communication Studied & Journalism, is a Communication Studies Professor at Winona State University in Winona, MN, specializing in effective communication and public speaking. She is also a doctoral candidate at Winona State University, where her research focuses on relationship rich education and academic self-efficacy among first-generation college students.Jody Shong, M.S. is a professor at the University of Wisconsin–Stout in Menomonie, Wisconsin, specializing in early childhood special education. She is also a doctoral candidate at Winona State University. Her research focuses on preparing the next generation of early childhood special education teachers with the knowledge and skills needed to build meaningful relationships with students and families and promote academic growth.Kari Sween, M.S. Ed., SLPI: Superior Plus, is an American Sign Language Assistant Professor and Coordinator at Minnesota State University, Mankato, where she leads the ASL certificate program, including ASL Levels 1–4, Conversational ASL, and Deaf Studies courses. She is a doctoral student in the Doctor of Education program at Winona State University, where her research explores communication access and barriers for Deaf and Hard of Hearing patients in healthcare settings

• Schools are building AI rules before they know the destination- August 17, 2026

• Cohort connections matter: Strategies to help graduate students persist and succeed- August 14, 2026

• Higher education needs better AI experiences, not more AI tools- August 12, 2026

本报道由 AI 助手自动抓取、翻译并发布。

最大的返校挑战

原文标题: The biggest back-to-school challenge
来源: eSchoolNews | 发布时间: 2026-08-12
原文链接: 点击阅读原文

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Key points:

• When students aren’t listening effectively, they aren’t fully learning

• 3 steps to build belonging in the classroom

• The untaught lesson: Prioritizing behavior as essential learning

• For more on classroom management, visit eSN’sInnovative Teachinghub

As students return to classrooms across America this fall, parents are focused on school supplies, class schedules, and academic expectations. Teachers are preparing lesson plans, organizing classrooms, and hoping for a successful year.

Yet one of the biggest obstacles to student success won’t be found in a math textbook or reading assignment.

It is listening.

Every day, teachers ask students to “listen carefully,” “pay attention,” or “focus.” Yet almost no one ever teaches childrenhowto listen.

That assumption comes with a tremendous cost.

Teachers across the country consistently report that one of their greatest daily challenges is simply getting students to stop, focus, and truly understand what is being said. Between smartphones, tablets, social media, shorter attention spans, and constant digital stimulation, gaining and maintaining students’ attention has become one of education’s biggest battles. Technology may amplify the problem, but it didn’t create it. We’ve spent generations assuming listening simply happens naturally.

It doesn’t.

Listening is a learned cognitive skill, not an automatic behavior. Hearing words and understanding them are two very different things.

Research shows that students spend roughly 70 percent of their classroom time listening to teachers or classmates. Yet listening is rarely taught as a structured skill, despite being the primary way children receive instruction.

The result is predictable.

Teachers often spend valuable instructional time redirecting distracted students, repeating directions, clarifying assignments, and trying to regain the attention of classrooms that have drifted off task. Classroom interruptions and the effort required to refocus students can cost the equivalent of days—or even weeks—of instructional time over the course of a school year.

When students aren’t listening effectively, they aren’t fully learning.

Poor listening directly affects curriculum retention. Students miss important details, misunderstand instructions, struggle to connect ideas, and retain less of what they are taught. Teachers then find themselves reteaching concepts instead of moving forward. The learning gap widens—not because students lack intelligence, but because they never truly processed the information in the first place.

Ironically, we spend enormous amounts of time teaching children how to read, write, solve equations, and conduct scientific experiments, yet the very skill that allows them to absorb those lessons is often left to chance.

Imagine trying to teach reading without first teaching the alphabet.

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Christine Miles, M.S. Ed., is the founder of The Listening Path® and author of What Is It Costing You Not to Listen?

• What it really takes to accelerate adolescent literacy across our district- August 20, 2026

• Uncovering the college and career readiness shifts that exceptional school systems are making- August 19, 2026

• Today’s classroom isn’t broken–but it wasn’t built for today’s top students- August 18, 2026

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Want to share a great resource? Let us know atsubmissions@eschoolmedia.com.

本报道由 AI 助手自动抓取、翻译并发布。