See the learning status value of the shared learning component (SCO) in the SCORM standard.
Learning status value of the shared component
According to SCORM's definition of learning components, learning assets simply point to
SCORMAnd Internet education
Written by nius: 2011-10-22
Blog: http://nius.me
The last simple translation of the SCORM protocol (portal), from the complexity of the protocol, we can roughly understand why this standard is still, at least in China, obscure. We can use SCORM to discuss Internet-based education.The instructor is a user
SCORM aims to develop a comple
relevant course content;
Publish notices, course materials, tasks, links to teaching resources, Professor and student profiles, and other information;
Upload course files over the Internet and manage course content conveniently;
Supports uploading and sending various format files, including:
Microsoft Office
Adobe Acrobat PDF
Html
Digital Image
Digital audio files
Digital Video Files
Multimedia (such as flash, Shockwave, and Authorware)
IMS, SCORM, a
opened in the grading view.
When each frame page is saved, the latest computing points and final points are stored on the server.
When saving the score table, the final points currently displayed in the table are stored.
The calculated points can only be modified by the content score, but cannot be modified in the score table. This makes it a good "primary score" reference when the final points cannot be synchronized and must be updated by the instructor.
Default Value
Where to store
Lrm
Default Value in index. xml
Assignmentitem. pointspossible
SCORM 2004
100
Assignmentitem. pointspossible
SCORM 1.2
Null
Assignmentitem. pointspossible
Non-eLearning
Null
Assignmentitem. pointspossible
In the alwp and SLK assignment process interface, the number of possible po
that the application has positive feedback. It can be formally incorporated into the experience library. Limitations of e-Learning
After recognizing the above analysis method, we can find that e-learning systems are more likeCommunityWebsite. User behavior is more valuable than data in the system. However, the current e-learning system, from system design to da
, anywhere. By integrating Oracle Certified Partners BackWeb technology, PeopleSoft Enterprise Learning Management software further expands the ability to learn anytime, anywhere. Now, without connecting to the network, employees can interact with learning software and course content regardless of which writing tool they use. As they reconnect to the network, their lear
Drawing a learning curve is useful, for example, if you want to check your learning algorithm and run normally. Or you want to improve the performance or effect of the algorithm. Then the learning curve is a good tool. The learning curve can judge a learning algorithm, which
Objective
Machine learning is divided into: supervised learning, unsupervised learning, semi-supervised learning (can also be used Hinton said reinforcement learning) and so on.
Here, the main understanding of supervision and unsupervised
Earlier, we mentioned supervised learning, which corresponds to non-supervised learning in machine learning. The problem with unsupervised learning is that in untagged data, you try to find a hidden structure. Because the examples provided to learners arenot marked, so there is no error or reward signal to evaluate the
unrestrictedLet students all over the world freely decide how they want to access the course.Almost all devices are optionalProvide more ways for students to access the course. The course can be published as a single click in the HTML5 format supported by the mobile browser, the Flash format supported by desktop and laptop computers, and the formats supported by the IPAD and Android user Articulate Mobile player.Localized contentEasily translate courses for students from all over the world. Sto
[Introduction to machine learning] Li Hongyi Machine Learning notes-9 ("Hello World" of deep learning; exploring deep learning)
PDF
Video
Keras
Example application-handwriting Digit recognition
Step 1:define A set of function
Step 2:goodness of function
Step 3:pick the best function
X_t
Deep Learning notes finishing (very good)
Http://www.sigvc.org/bbs/thread-2187-1-3.html
Affirmation: This article is not the author original, reproduced from: http://www.sigvc.org/bbs/thread-2187-1-3.html
4.2, the primary (shallow layer) feature representation
Since the pixel-level feature indicates that the method has no effect, then what kind of representation is useful.
Around 1995, Bruno Olshausen and David Field two scholars, Cornell Unive
As we all know, when Alphago defeated the world go champion Li Shishi, the whole industry is excited, more and more scholars realize that reinforcement learning is a very exciting in the field of artificial intelligence. Here I will share my intensive learning and learning notes. The basic concept of reinforcement learning
Original address: http://www.cnblogs.com/cyruszhu/p/5496913.htmlDo not use for commercial use without permission! For related requests, please contact the author: [Email protected]Reproduced please attach the original link, thank you.1 BasicsL Andrew NG's machine learning video.Connection: homepage, material.L 2.2008-year Andrew Ng CS229 machine LearningOf course, the basic method does not change much, so the courseware PDF downloadable is the advanta
In machine learning, supervised learning (supervised learning) by defining a model and estimating the optimal parameters based on the data on the training set. The gradient descent method (Gradient descent) is a parametric optimization algorithm widely used to minimize model errors. The gradient descent method uses multiple iterations and minimizes the cost funct
Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and the machine
For the performance of four different algorithms in different size data, it can be seen that with the increase of data volume, the performance of the algorithm tends to be close. That is, no matter how bad the algorithm, the amount of data is very large, the algorithm can perform well.When the amount of data is large, the learning algorithm behaves better:Using a larger set of training (which means that it is impossible to fit), the variance will be l
Transferred from: http://blog.csdn.net/zouxy09/article/details/8775518
Well, to this step, finally can talk to deep learning. Above we talk about why there are deep learning (let the machine automatically learn good features, and eliminate the manual selection process. As well as a hierarchical visual processing system for reference people, we get a conclusion that deep
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