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  2. ADDIE model - Wikipedia

    en.wikipedia.org/wiki/ADDIE_Model

    Florida State University initially developed the ADDIE framework in 1975 [3] to explain, “...the processes involved in the formulation of an instructional systems development (ISD) program for military interservice training that will adequately train individuals to do a particular job and which can also be applied to any interservice curriculum development activity.” [4] The model ...

  3. 360-degree feedback - Wikipedia

    en.wikipedia.org/wiki/360-degree_feedback

    360-degree feedback (also known as multi-rater feedback, multi-source feedback, or multi-source assessment) is a process through which feedback from an employee's colleagues and associates is gathered, in addition to a self-evaluation by the employee.

  4. Wikipedia:Training/For students/Training feedback - Wikipedia

    en.wikipedia.org/.../For_students/Training_feedback

    For detailed feedback after 21 January 2015, see Wikipedia:Training/For students/Leave feedback. Entries to this page are added via MediaWiki:Guidedtour-tour-StudentTrainingComplete.js, a guided tour launched at the end of the student training.

  5. Wikipedia:Training/For educators/Training feedback - Wikipedia

    en.wikipedia.org/.../For_educators/Training_feedback

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Donate; Help; Learn to edit; Community portal; Recent changes; Upload file

  6. Wikipedia:Training/For students/Leave feedback - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Training/For...

    192 Training feedback: The training is lengthy... It's difficult for a student to set aside time to go through all the slides at once. It was a lot of reading especially for the editing portions that were best communicated visually anyway.

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

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