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Supplemental instruction (SI) is an academic support model that uses peer learning to improve university student retention and student success in high-attrition courses. [1] [2] Supplemental Instruction is used worldwide by institutions of higher learning.
Example checklist. While the check sheets discussed above are all for capturing and categorizing observations, the checklist is intended as a mistake-proofing aid when carrying out multi-step procedures, particularly during the checking and finishing of process outputs. This type of check sheet consists of the following:
Both free and paid versions are available. It can handle Microsoft Excel .xls and .xlsx files, and also produce other file formats such as .et, .txt, .csv, .pdf, and .dbf. It supports multiple tabs, VBA macro and PDF converting. [10] Lotus SmartSuite Lotus 123 – for MS Windows. In its MS-DOS (character cell) version, widely considered to be ...
Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).
Fact – unique data (e.g. symbols for Excel formula, or the parts that make up a learning objective) Concept – a category that includes multiple examples (e.g. Excel formulas, or the various types/theories of instructional design) Process – a flow of events or activities (e.g. how a spreadsheet works, or the five phases in ADDIE)
Analyse-it is a statistical analysis add-in for Microsoft Excel. Analyse-it is the successor to Astute, developed in 1992 for Excel 4 and the first statistical analysis add-in for Microsoft Excel. Analyse-it is the successor to Astute, developed in 1992 for Excel 4 and the first statistical analysis add-in for Microsoft Excel.
The main approaches for stepwise regression are: Forward selection, which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically significant improvement of the fit, and repeating this process until none improves the model to a statistically significant ...
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