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Notebooks 2.2

Notebooks 2.2 ===>

Notebooks 2.2

Please forgive my dragging up ancient history: I have been using Mathematica from version 2.2 through 7.0. I remember at least one (maybe two) format conversions that were necessary to update old notebooks to the newer formats. I also remember at least one batch-notebook-conversion command. Unfortunately I cannot remember the details:

There was only the one switch from 2.2 .ma/.mb files to 3.0 .nb files. Possibly, you might be remembering v6 when pre-v6 notebooks were opened with an compatibility tool added to the top, but the tool had nothing to do with the file was merely an aid to updating some of the code inside the notebook.

Also, .nb files are not wholly backward compatible. They'll always open in older versions, but as new features get added to Mathematica, inputs/outputs depending upon those features may not render or function correctly in older versions. The most radical such change would be in v6, when we switched from using PostScript for graphics to more native constructs in the notebooks. Which means that pretty much any v6 or later notebook is going to produce graphics which are wholly unusable by v5 or earlier (but the notebooks do open, and textual content comes through just fine).

Project Jupyter is three things: a collection of standards, acommunity, and a set of software tools. Jupyter Notebook, one part ofJupyter, is software that creates a Jupyter notebook.A Jupyter notebook is a document that supports mixing executable code, equations,visualizations, and narrative text. Specifically, Jupyter notebooks allowthe user to bring together data, code, and prose, to tell aninteractive, computational story. Whether analyzing a corpus of AmericanLiterature, creating music and art, or illustrating the engineering conceptsbehind Digital Signal Processing, the notebooks can combine explanationstraditionally found in textbooks with the interactivity of an application.

Read on to find out how we have used Jupyter notebooks for teaching and learningto benefit both our students and ourselves. Jupyter notebooks support a widerange of learning goals, including learning to program, learning domainknowledge, and practicing communication skills like storytelling. The authors ofthis book have used Jupyter notebooks to teach:

As teachers we routinely struggle to engage our students, especially when we areconstrained by the format of the course (e.g., online, 50-minute lecture),available technologies, students distractions, and/or other factors.Nevertheless, it is substantially our responsibility to create environments andexperiences within these limits that engage students in our courses. This iswhere notebooks can give you another tool to break out of the mundane, and getstudents engaged in their learning.

Engaging students in your courses requires their participation and interactionwith you, their peers, and/or the content (Moore, 1989). How, when, andwhy you use student participation in yours will, of course, depend on yourgoals, the specific objectives for teaching the content within your course, yourstudents, and other factors. Using notebooks, however, encourages participationand gives you more tools for promoting participation. Notebooks can connectstudents to authentic external audiences as well. Students can, for example,consume notebooks from other classes, and publish notebooks where others canread them.

The goal of learning is often actualized through the performance of students.This is routinely most visible by what we attempt to assess during and at theend of instruction. Using notebooks we can create a variety of a performanceopportunities for students, thereby giving them more opportunities for practiceand feedback, as well as more opportunities for us, as instructors, toassess their ability to perform.