Best MathML 1.01 content code for multi-step solutions/derivations/proofs?

What is the best way to write MathML 1.01 content code for multi-step 
solutions/derivations/proofs? I need to be able to programmatically 
distinguish between the steps. I also want MathML code that displays 
well using IBM's TechExplorer.

For example let say you want to code the simple multi-step solution:
4*x = x + 6
3*x = 6
x = 2

I could just just have a list of <reln> nodes like this:
<math>
   <reln>
   <eq/>
     <apply>
     <times/>
       <cn>4</cn>
       <ci>x</ci>
     </apply>
     <apply>
     <plus/>
       <ci>x</ci>
       <cn>6</cn>
     </apply>
   </reln>
   <reln>
   <eq/>
     <apply>
     <times/>
       <cn>3</cn>
       <ci>x</ci>
     </apply>
     <cn>6</cn>
   </reln>
   <reln>
   <eq/>
     <ci>x</ci>
     <cn>2</cn>
   </reln>
</math>

But TechExplorer will just scrunch each step together on one line so 
it ends up looking like:
4*x = x + 63*x = 6x = 2

That way is also problematic in determining which step is what, 
especially in more complicated examples.

I could use <semantics> nodes like this:
...
   <semantics>
     <reln>
     ...
     </reln>
     <annotation-xml encoding="MySpecialCode">
       <step ID="1"/>
     </annotation-xml>
   </semantics>
...
Now while I process the MathML code I will definitely know which step 
is which, but TechExplorer will still scrunch each step together on 
one line. To solve that problem I could use the <tendsto> operator so 
TechExplorer's presentation is like this:
4*x = x + 6 -> 3*x = 6 -> x = 2

Still on one line, but less misleading. However since <tendsto> is a 
binary relational operator, I would have to nest allot of <reln> 
nodes (each associated with a <tendto> node) inside each other.

I could avoid using <tendsto> by using my second option internally, 
and displaying to users HTML code with MathML embedded in it, each 
step is displayed on one line.

I hoping the MathML community can suggest a simpler solution that 
only requires the use of MathML 1.01 that TechExplorer would be happy 
with.

Kofi Weusi-Puryear
Learning Sciences Ph.D. Student
Northwestern University
mailto:puryear@ils.northwestern.edu
http://www.ils.northwestern.edu/~puryear

Received on Monday, 18 September 2000 12:24:24 UTC