We found 142 results that contain "ai"

The educator scores student work reliably by using protocols to engage in collaborative, structured discussions. These discussions will focus on accurately and consistently documenting evidence within the student work of achievement of the learning target(s).

Method Components
The Advanced Performance Assessment for Learning Design stack is designed so that, if all three credentials are taken together, they will become more than the sum of their parts. Each micro-credential is intended to be able to stand on its own; however, the ideas and activities of each of these credentials support and expand on the others, allowing a fuller appreciation of performance assessment and its implications. Even more value will be gained by engaging in all three Performance Assessment for Learning stacks together.

The educator scores student work reliably by using protocols to engage in collaborative, structured discussions. These discussions will focus on accurately and consistently documenting evidence within the student work of achievement of the learning target(s).

Method Components
The Advanced Performance Assessment for Learning Design stack is designed so that, if all three credentials are taken together, they will become more than the sum of their parts. Each micro-credential is intended to be able to stand on its own; however, the ideas and activities of each of these credentials support and expand on the others, allowing a fuller appreciation of performance assessment and its implications. Even more value will be gained by engaging in all three Performance Assessment for Learning stacks together.

School interventions should include a team approach across multiple settings, consisting of both
preventive and intervention strategies.

Interventions must be based upon assessment data that includes information about the student’s strengths and needs as well as the environmental conditions in which her characteristics of ADHD occur.

Progress monitoring and strategy adjustments are critical to the success of any intervention plan (Wolraich & DuPaul, 2010).

The first step in creating classroom supports for students with ADHD is understanding the
students’ strengths and needs. This involves formal and informal assessment, as well as
collaboration among educational professionals and the students’ families.

If a student is not responsive to behavioral strategies and interventions, more intensive interventions, such as functional behavior assessment and behavior intervention plans, should be considered (see Practical FBA).

No one intervention is universally effective for all students with ADHD. A combination of research-based and promising practices is recommended.

Here are several of these practices:

Neural networks, or artificial neural networks (ANNs), are comprised of a node layers, containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold. If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network. The “deep” in deep learning is just referring to the depth of layers in a neural network. A neural network that consists of more than three layers—which would be inclusive of the inputs and the output—can be considered a deep learning algorithm or a deep neural network. A neural network that only has two or three layers is just a basic neural network.

Lorem Ipsum, sometimes referred to as 'lipsum', is the placeholder text used in design when creating content. It helps designers plan out where the content will sit, without needing to wait for the content to be written and approved. It originally comes from a Latin text, but to today's reader, it's seen as gibberish

In the global Internet environment processing of information in multiple languages has a great importance. Intellexer Language Recognizer identifies the language and character encoding of incoming documents. It supports more than 30 languages, covering major European and Asian languages. Intellexer Language Recognizer can be successfully used: - as a pre-filtering step to improve the quality of input text data (because of most natural processing algorithms deal with monolingual texts and inclusion of other languages can decrease the performance of document management systems); - in mining bilingual texts for machine translation from online resources; - for retrieval, grouping and understanding relevant information (user’s texts, emails and etc.) in multilingual environment.Language Recognizer

Contrary to popular belief, Lorem Ipsum is not simply random text. It has roots in a piece of classical Latin literature from 45 BC, making it over 2000 years old. Richard McClintock, a Latin professor at Hampden-Sydney College in Virginia, looked up one of the more obscure Latin words, consectetur, from a Lorem Ipsum passage, and going through the cites of the word in classical literature, discovered the undoubtable source. Lorem Ipsum comes from sections 1.10.32 and 1.10.33 of "de Finibus Bonorum et Malorum" (The Extremes of Good and Evil) by Cicero, written in 45 BC. This book is a treatise on the theory of ethics, very popular during the Renaissance. The first line of Lorem Ipsum, "Lorem ipsum dolor sit amet..", comes from a line in section 1.10.32.

qTest is a test management tool used for Project Management, Bug Tracking, and Test Management. It follows the centralized test management concept that helps to communicate easily and assists in rapid development of task across QA team and other stakeholders.

qTest is a cloud based tool and was developed by QASymphony. It supports all browsers especially Chrome, Firefox, IE, etc. and also supports different windows OS versions – Windows XP, Vista, 7, etc. QTest provides a 14-days trial period for Business email id with access to 4 users. qTest can be integrated with many other tools – JIRA, Bugzilla, FogBugz, Version One, etc.