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How to Save Thousands of Grading Hours with Automation of Fusion 360 Learning and Assessment

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说明

The assessment of CAD is extremely resource intensive. Dr. Tom Peach of University College London (UCL) estimates that marking Fusion 360 submissions for a single cohort takes two months of man hours, without even considering the time spent delivering content and supporting students. The session will outline how this entire process was completely automated by Fabrio this year, turning around 1500 submissions within a day. Grades were ready for students 50 times faster, while also improving accuracy. Integrating Fabrio into UCL's teaching plans addressed a number of key pain points faced by institutions across the world, including developing content, low staff-to-student ratios, and general limitations in assessment styles. This session will also highlight how the same learning paradigms can be applied in the corporate space (e.g., onboarding, upskilling, or preparing for certification).

主要学习内容

  • Discover the key pain points faced by educators and students learning Fusion 360.
  • Learn about integrating automated assessment into your teaching plans.
  • Collaborate with other educators and external Fusion 360 learning.

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      Transcript

      JAY SAHNAN: Hey, everyone. I'm Jay, and I'm here with my co-founder Anirudh. Together we co-founded Fabrio. And today we're here to tell you about a new learning paradigm we've developed for engineering. It saves thousands of hours for students, educators, and engineers, and we believe it's the future of learning CAD.

      Now, to give you a little bit of background about me, I studied aerospace engineering here in the UK and I graduated around about a couple of years ago now. During my degree, I absolutely loved 3D printing and I've been making things since I was a child. Through 3D printing and making things I picked up CAD on the side, but found it really difficult during my degree to learn it the way they taught us. I also didn't enjoy my degree as much as I thought I did and that was because it was still mostly taught in a bog standard kind of way.

      ANIRUDH VADIYAMPETA: And to be honest, it's the same with me. I've always enjoyed making things and the practical side of things and experimenting with things around the house since as long as I can remember. And we had a topic or a subject in school called design and technology, and it was one of my favorites. But the way it was taught formally at higher levels isn't something that appealed to me and why I didn't decide to pursue it further and I just kept it as a hobby.

      JAY SAHNAN: Let's start by setting the scene. University College London is a global top 10 institution with a renowned engineering department. They've won numerous awards, such as Innovation of the Year, and are hugely successful in student-led competitions, like Formula Student. Overall, it's a fantastic institution with a highly motivated and committed staff and student body.

      ANIRUDH VADIYAMPETA: It's quite surprising, then, that some aspects of student satisfaction are surprisingly low, especially with regard to feedback. Just 42% of students say that they receive feedback on a timely basis and only 45% of those students actually finding that feedback helpful. Overall, only about 50% of students can confidently say that they feel like the course runs smoothly and is well organized.

      To be fair, this isn't just isolated to UCL, with the average for universities across the UK to be uncharacteristically low and not really up to scratch compared to the other criteria. Clearly, there are similar challenges faced across all universities and they're difficult to overcome, regardless of the educators' best intentions.

      JAY SAHNAN: To break it down, let's look at the current process followed by UCL and many other universities across the world and the problems that come with the way they teach CAD. First, learning materials, such as presentations, PDF handouts, or videos, need to be prepared ahead of time. Now, of course, a previous professor might have already prepared this, but there's no guarantee that it's up to date, especially given how quickly software updates nowadays.

      Then it's up to the students to follow the material. It's either delivered to them verbally in a lecture theater or computer cluster, or simply assigned for homework. Students are mostly left to their own devices to get through the CAD work and produce the results.

      Now, both of these solutions come with their own problems, namely the lack of contact between students and educators. Due to the low staff to student ratios at most universities, it's extremely difficult for students to get the help quickly. This leads to barrages of emails, congested office hours, or in the worst case scenario, the students simply disengages from the course completely.

      ANIRUDH VADIYAMPETA: Of course, after all of this, it comes time for the students to submit their work. Currently, this is a pretty tedious process with students saving and uploading individual files to a Learning Management System, or an LMS, which isn't really designed for this type of job. In many cases, students are just emailing their files to the professor and it's up to them to sort between them.

      However, this mess is still nothing compared to the actual marking process. Take Dr. Tom Peach's experience, for example. He's an associate professor at UCL in the mechanical engineering department. For one part of a single assessment within one individual modules, students submit 1,500 individual files to him.

      To mark them, he needs to open each of them one by one, import in the correct file, and overlay it. Then he needs to compare and visually inspect the two of them and note down the differences, and then record these marks in a separate LMS again. And then once he's done all of this, he gets to do it again 1,499 more times.

      JAY SAHNAN: So this whole process isn't great. It's hard to keep learning materials up to date. There's not enough contact time between students and educators, and marking takes forever.

      And as I mentioned, I've experienced this problem myself. So when I was at university we learnt CAD through sitting in a computer cluster with 149 other students and maybe one professor and a couple of TAs. If I had a problem, I'd have to put my hand up and ask for help. Great, but it would take 10 minutes for someone to come and help me. It would then take them another 10 minutes to figure out where I'd gone wrong, help me, and then move on to the next student.

      By me following that PDF document and going step by step and following the instructions, I came across a lot of problems. I was always making mistakes and I didn't know where I was going wrong. And also, because it took so long for me to get feedback, I was getting very disengaged with CAD in general. And CAD is such a huge skill that every engineer should know and understand.

      Then at the end of the session, I would need to send an email. I would send an email with my CAD files to the professor for him to mark it. Great, right? But no, it would take two weeks for me to get any feedback and my next CAD session was a week after the first one. So I didn't know what to do for the next session and I wasn't prepared [? again. ?]

      All of this is a massive burden on staff. Educators have actually told us they've been forced to limit the complexity of their curriculums simply to keep up. Many of them are just not teaching the CAD skills that they would like to.

      ANIRUDH VADIYAMPETA: This is what we're solving at Fabrio. For the past three years, we've been deeply focused on the problems in CAD learning, from schools to universities, all the way up to the workplace. And as recent graduates ourselves, we've experienced the problems firsthand and were extremely passionate about solving them. We firmly believe that there's one thing that will change the way engineering is taught. It's called embedded learning.

      JAY SAHNAN: Embedded learning is the integration of learning resources and activities directly into the software, allowing users to learn whilst they use it. Now, embedded learning has existed at some level for some while now, included everything from tooltips to introductory product tours. However, here at Fabrio, we've taken it to a completely new level. And with UCL being one of the first ones to try it out, here's a quick video outlining how it went.

      [VIDEO PLAYBACK]

      [MUSIC PLAYING]

      - Hi. I'm Tom Peach. I'm an Associate Professor of Mechanical Engineering here at UCL, and Fabrio has completely changed the way that we teach CAD.

      - We're Fabrio, and we provide interactive CAD courses designed from the ground up to reduce teacher intervention and promote independent learning.

      - I'm normally teaching about 50 or 60 at a time. In a 2-hour session, I might only have 2 or 3 minutes with each student, so often they're then coming to me in my office hours.

      - All students need to do is log in to the web platform with credentials provided by their professor and install the Fabrio add-in for Fusion 360. From there, they simply open the course assigned to them and work through them. Throughout, we ask them questions to test their understanding whilst the add-in checks their work directly in Fusion 360 to make sure they're on the right track. The platform and add-in combined take care of most questions and issues, getting students to help they need instantly without overwhelming the professor.

      - I would normally be teaching about three classes a year. Each class is 200 students. They're going to be submitting files to me for assessment, and in total, I'm probably going to mark something like 2,000 individual files in one year. Each assessment that one class of students submits to me takes me about 100 hours to mark.

      My normal process would be to go and download that file from our submission portal. Then I'd need to import that into Fusion. I'd open it up and at the same time I'd open up an ideal version, a correct version of the file. I'd compare them one to one, and then I'd have to give a mark and write down that feedback into a portal and upload that mark as well.

      I'm pretty good at marking them, but I'm obviously not 100% accurate. Marking that many files is obviously exhausting, very boring, and I don't get to spend any time actually teaching students. Instead, I'm just stuck in front of a screen. Really, I'm rarely getting my feedback in on time and they're not getting the vital feedback they need before their next assessment.

      I used Fabrio for the first time this year. Using Fabrio in the new system was amazing because it actually let me concentrate on talking to the students 1 to 1 with their more kind of detailed problems.

      - Students this year used Fabrio for their assessments. All they had to do was log on and follow the assessment that was assigned to them.

      - They were provided with all of the assessment prompts and all they had to do was click submit once they were ready. Fabrio marked their work instantly and turned around weeks' worth of marking within the same day.

      - We're the only edtech platform to integrate into industry-level software and assess students as they work through our courses to give them helpful feedback and build their confidence.

      - Fabrio made it very easy for me to submit my CAD files. I just had to click one button and the Fabrio did the rest for me.

      - The website was really well made. It was very visual, so it was really easy to understand as well. They took me step by step through all the design, so it was really helpful. Fabrio definitely accelerated the process of grading, which was very helpful because knowing how well I did on that assignment fast enough helped me with the rest of the course.

      - Fabrio was really easy to install. Using it with the CAD, it's a really simple extension that's really natural to use on the interface. It's just there and helps you create CADs.

      - As you can see, we've completely transformed the entire learning experience at UCL, saving Dr. Peach hours of time, bearing in mind, all of that was still only for one part of one module. And over the course of three years across all the modules, we'd estimate that we'd save nearly 3,000 hours of time at a six-figure cost. The amount of time we can save for universities and the value that we can bring to students is immeasurable. Now let's show you how Fabrio works.

      [END PLAYBACK]

      JAY SAHNAN: So this is Fabrio. Students will come to the home page and they'll click Explore Courses. As you can see, we have a range of courses that students can attempt, or they can be assigned to the students by the professors or the teachers. For today's demo, we're going to go into the Brick Project.

      As you can see, the students will be able to see what they're going to be taught and the necessary prerequisites, if they need any. Within the Brick Project, students will get instructions on the left-hand side and on the right-hand side they will also see a video. This can also be played picture in picture alongside Fusion 360 so the students can be doing the actions, viewing the actions at the same time.

      Let's go back to the tab. And if I press Next Step now, students will get the next instruction. This one, OK, we need to create a sketch. Here are the dimensions and here's the sketch. Every so often as well, students will randomly get asked a question to make sure that they're-- to check their understanding. We want to make sure that they know what they're doing and they're not just clicking through.

      Every so often, when we see a Fabrio ball, we know there's a check step. And this is where the true benefit of Fabrio comes into play. You can not only see a 3D file-- and obviously, this is the basic of a cube, so it's quite simple right now. But also you can see a logo. This says, make sure you check your work using the Fabrio CAD Assist in Fusion 360.

      So I'm just going to jump to a different step here and I'm going to go to this replicating step. This is where you've got now a little bit more complex brick and the students can really interact with it. So say, if they're sitting on their computer and they're trying to make a CAD model of the brick, they're like, I don't know where this fits or I can't see where this is going. They can now interact with that 3D file.

      Let's go into Fusion 360 and let's check our work. In Fusion 360, you can see the brick. At the top, we have developed an add-in that just sits in the toolbar. I'm just going to click Open. And once the student logs into it for the first time, they're logged in on the add-in and they're logged in on the platform.

      I'm going to press Check My Model and Fabrio is going to check if they've done it correctly or incorrectly. As you can see, for this brick I've done it correctly. Great, I've constructed it correctly. OK, I'm going to press OK and there's going to be no changes to the model. As a student, I can continue to work on the model and follow the next step.

      But what happens if the student did it incorrectly? Now, let's just extrude this up. Let's extrude this one down. Let's take this one up a little bit, and I'm going to press Check Again. Fabrio is going to go through the exact same process.

      OK, now we can see there's an error. Please check the marked model for corrections. If I press OK, we can see exactly where we've gone wrong.

      Now, as a student going back to that computer cluster that [? has ?] a 150 students, imagine all the students instantly knowing if they're going right or wrong without having to stick their hand up. A student can interact with it and see, OK, I've gone wrong here, I've made a mistake here, and they can make those changes instantly. It's not like they're going to get to the end of the model and realize they've made a huge mistake and they need to start again.

      Also, for professors, they're going to receive this feedback instantly. So they'll be able to see a breakdown where all the students are going through at the same time, and they'll be able to see who's getting it right and who's getting it wrong.

      Now, if I press Clear My Markings, I'm taken back to my LEGO brick. Press CTRL-Z, CTRL-Z, and as a student, I can go and I can check again. I can make the correct model.

      How this works is essentially we will take a reference file on our side, on our system, and we're able to compare the students work to it. For example, if the student works in the wrong orientation, we know. We know if they've worked in the wrong orientation. We can give them that feedback. Hey, you started the sketch in the wrong orientation. You need to fix it.

      Or for example, if the features are wrong, looking at a fillet, if they've missed a fillet, we can say, hey, you haven't got a fillet here. You need to add a fillet.

      This level of detail has never been able to be done before. And even with professors marking it, they can't spend that much time giving those in-depth responses to the students. As the student continues to work through, they work through the courses, work through the check steps, at the end of the course, they'll also come to a course quiz.

      So I'm going to press Start [? Up, ?] and what we have are 7 to 10 random questions that every student will have to sit through and the complexity depends on the level of course they're going through. So for this one, we can see, what's the name of the navigation tool in the top right corner of the workspace in Fusion 360. But we all know it's the ViewCube but for a first-time student who's opened Fusion for the first time, they wouldn't.

      As the courses increase in complexity, so do the quizzes. So Generative Design course will have a lot harder questions. What we're really trying to do is to check that the students are understanding as they go through, and all this is reported to the teachers [? in the ?] dashboard.

      One thing we didn't talk about earlier when we spoke about the marking process is accuracy.

      One thing we didn't talk about earlier when we spoke about the marking process is the accuracy. It's extremely difficult to maintain standards when you've been staring at the same model for hours on end. To illustrate our point, we actually sat down and marked all of Dr. Peach's 1,500 files ourselves. And I can officially say that I understand the pain of marking.

      Unsurprisingly, we found a number of cases where we missed things ourselves. In fact, there are multiple cases where we actually thought the files were correct, but only until CAD Assist flagged it up did we go back and realize that we were wrong.

      ANIRUDH VADIYAMPETA: We've designed CAD Assist to be as easy to integrate into existing curriculums as possible and we're working with a number of universities already. We've taken the effort of designing a completely custom curriculum, keeping embedded learning in mind. However, everything is still mapped against Autodesk's own criteria for their certifications, so we can guarantee the students are still meeting the industry standard. We take care of all of the heavy lifting and professors can simply assign one of our learning pathways instead of making their own material.

      Educators can choose how deeply they'd like to integrate Fabrio. On one end, we have some professors using it just as an optional learning aid, and on the other end, we have some professors using Fabrio to deliver their entire curriculum and also handle summative assessments. If professors want to keep using their existing material, we can help to transfer it onto Fabrio's platform so they can still get the benefits of our automated marking features whilst using a curriculum that they're already familiar with.

      JAY SAHNAN: We've worked extremely hard on our dashboard to take care of all the professor's needs, giving them a comprehensive overview at a glance, whilst also allowing them to deep dive into specific students' progress to see exactly where those students need the support. Every single step and question is tagged against a particular skill from Autodesk criteria. And educators can use these to assign specific courses to develop targeted skills. However, this is only the start of how we see embedded learning changing CAD.

      ANIRUDH VADIYAMPETA: We've poured all of our knowledge, data, and experience into developing this tool. We've analyzed tons of CAD files and user data from our courses to build something that can really understand user intentions and help everyone, whether you're a complete beginner or a seasoned engineer. Introducing CAD Assist AI.

      JAY SAHNAN: Right now, CAD Assist AI is designed to work seamlessly with Fusion 360. So what does that mean? Well, it can give you contextual answers to your questions much faster than if you were to search Google or watch a YouTube video.

      Take this example. If you're working on adding threads to a bolt, CAD Assist AI doesn't just add the threads, it advises you on the most appropriate design choice. Or in this case, simply explaining the difference between a fillet and a chamfer, and when each is appropriate.

      Or another example is when we've asked CAD Assist AI how to make this circle bigger. And now, as a student, this might be a hugely difficult task. But CAD Assist AI provides the students instructions on exactly how to do it.

      Now, this is huge. It can bring value to students at any level. It's not just about answering questions. It's about understanding the user's intentions and providing the right guidance and suggestions to help them with their work.

      Many professors are already trying it out with their students and the feedback has been positive. And of course, as students become more experienced and go into industry, CAD Assist AI will grow with them, speeding up their workflow and guiding them through their designs.

      ANIRUDH VADIYAMPETA: We believe that embedded learning is paving the way forward for learning any specialized software. And we at Fabrio are excited to be at the forefront. We're not stopping here. We're continuously exploring new ways to enhance and expand our solutions to meet the evolving needs of learners and educators alike.

      You can keep up with what we're doing by visiting our website to understand more of the amazing skills that Fabrio has. You can also check out our social media to see more case studies and examples of how professors and students are using Fabrio. Thanks for taking the time to listen.

      ______
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      我们通过 Upsellit 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Upsellit 隐私政策
      CJ Affiliates
      我们通过 CJ Affiliates 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. CJ Affiliates 隐私政策
      Commission Factory
      我们通过 Commission Factory 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Commission Factory 隐私政策
      Google Analytics (Strictly Necessary)
      我们通过 Google Analytics (Strictly Necessary) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Strictly Necessary) 隐私政策
      Typepad Stats
      我们通过 Typepad Stats 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Typepad Stats 隐私政策
      Geo Targetly
      我们使用 Geo Targetly 将网站访问者引导至最合适的网页并/或根据他们的位置提供量身定制的内容。 Geo Targetly 使用网站访问者的 IP 地址确定访问者设备的大致位置。 这有助于确保访问者以其(最有可能的)本地语言浏览内容。Geo Targetly 隐私政策
      SpeedCurve
      我们使用 SpeedCurve 来监控和衡量您的网站体验的性能,具体因素为网页加载时间以及后续元素(如图像、脚本和文本)的响应能力。SpeedCurve 隐私政策
      Qualified
      Qualified is the Autodesk Live Chat agent platform. This platform provides services to allow our customers to communicate in real-time with Autodesk support. We may collect unique ID for specific browser sessions during a chat. Qualified Privacy Policy

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      改善您的体验 – 使我们能够为您展示与您相关的内容

      Google Optimize
      我们通过 Google Optimize 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Google Optimize 隐私政策
      ClickTale
      我们通过 ClickTale 更好地了解您可能会在站点的哪些方面遇到困难。我们通过会话记录来帮助了解您与站点的交互方式,包括页面上的各种元素。将隐藏可能会识别个人身份的信息,而不会收集此信息。. ClickTale 隐私政策
      OneSignal
      我们通过 OneSignal 在 OneSignal 提供支持的站点上投放数字广告。根据 OneSignal 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 OneSignal 收集的与您相关的数据相整合。我们利用发送给 OneSignal 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. OneSignal 隐私政策
      Optimizely
      我们通过 Optimizely 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Optimizely 隐私政策
      Amplitude
      我们通过 Amplitude 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Amplitude 隐私政策
      Snowplow
      我们通过 Snowplow 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Snowplow 隐私政策
      UserVoice
      我们通过 UserVoice 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. UserVoice 隐私政策
      Clearbit
      Clearbit 允许实时数据扩充,为客户提供个性化且相关的体验。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。Clearbit 隐私政策
      YouTube
      YouTube 是一个视频共享平台,允许用户在我们的网站上查看和共享嵌入视频。YouTube 提供关于视频性能的观看指标。 YouTube 隐私政策

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      定制您的广告 – 允许我们为您提供针对性的广告

      Adobe Analytics
      我们通过 Adobe Analytics 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Adobe Analytics 隐私政策
      Google Analytics (Web Analytics)
      我们通过 Google Analytics (Web Analytics) 收集与您在我们站点中的活动相关的数据。这可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。我们使用此数据来衡量我们站点的性能并评估联机体验的难易程度,以便我们改进相关功能。此外,我们还将使用高级分析方法来优化电子邮件体验、客户支持体验和销售体验。. Google Analytics (Web Analytics) 隐私政策
      AdWords
      我们通过 AdWords 在 AdWords 提供支持的站点上投放数字广告。根据 AdWords 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AdWords 收集的与您相关的数据相整合。我们利用发送给 AdWords 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AdWords 隐私政策
      Marketo
      我们通过 Marketo 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。我们可能会将此数据与从其他信息源收集的数据相整合,以根据高级分析处理方法向您提供改进的销售体验或客户服务体验以及更相关的内容。. Marketo 隐私政策
      Doubleclick
      我们通过 Doubleclick 在 Doubleclick 提供支持的站点上投放数字广告。根据 Doubleclick 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Doubleclick 收集的与您相关的数据相整合。我们利用发送给 Doubleclick 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Doubleclick 隐私政策
      HubSpot
      我们通过 HubSpot 更及时地向您发送相关电子邮件内容。为此,我们收集与以下各项相关的数据:您的网络活动,您对我们所发送电子邮件的响应。收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、电子邮件打开率、单击的链接等。. HubSpot 隐私政策
      Twitter
      我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
      Facebook
      我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
      LinkedIn
      我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
      Yahoo! Japan
      我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
      Naver
      我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
      Quantcast
      我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
      Call Tracking
      我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
      Wunderkind
      我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
      ADC Media
      我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
      AgrantSEM
      我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
      Bidtellect
      我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
      Bing
      我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
      G2Crowd
      我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
      NMPI Display
      我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
      VK
      我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
      Adobe Target
      我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
      Google Analytics (Advertising)
      我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
      Trendkite
      我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
      Hotjar
      我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
      6 Sense
      我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
      Terminus
      我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
      StackAdapt
      我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
      The Trade Desk
      我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
      RollWorks
      We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

      是否确定要简化联机体验?

      我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

      个性化您的体验,选择由您来做。

      我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

      我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

      通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。