Texts:1986 Into the Starting Gate: Difference between revisions

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Let us roughly estimate the vast quantities of information enclosed within such study trees.<ref>these estimates I am assuming that a byte is a byte is a byte. This is not an entirely fair assumption. Generally, if software is designed well, a quantity of executable program code will usually occupy a student longer than reading an equal amount of American Standard Code for Information Interchange (ASCII) text code. All the same, treating all code as if it were text code gives an adequate approximation of the information content of software. The following estimates are in the number of bytes that would be required to code the information pointed to by various study trees. For text each character is counted as a byte. Representing the amount of information in this way should not obscure the fact that currently most of the information in print-based courses is obviously not coded in binary form. My basic assumption is simply that for a course to be genuinely computerbased the full information content within its study tree should be accessible through computers. When we have gotten the information into such a form, then computing is in the starting gate.</ref> For instance, most reading these remarks will have once been undergraduates at quality colleges and they will recall struggling with the knowledge structure of a tough liberal arts course: a book a week, that is, 1-2 megabytes, or a total of about 20 megabytes of required reading, plus a serious term paper, which would require careful study of another 5 megabytes, two or three further books, along with more cursory perusal of a good deal more data, all different from one student to the next. Let us say there were twenty students in the course. The information capacity of the study tree would be the following:

<ul class="sl"><li>20 meg—Required materials worked with by each of the twenty students</li>

<ul class="numsoff"><li>20 meg—Required materials worked with by each of the twenty students</li>

<li>100 meg—Primary materials drawn on in writing papers, 5 meg per student</li>

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Be that as it may, the point here is not to find the exact quantity of information included in either the teaching tree or the study tree of the typical course, whether high school, college, or graduate school. In all cases the structure encompasses a very large amont of information, especially relative to the storage capacities of available academic computing systems. One might imagine a not terribly demanding high school course generating a study tree comprising the following amounts of information:

<ul class="sl"><li>2 meg—Required materials worked with by each of thirty students</li>

<ul class="numsoff"><li>2 meg—Required materials worked with by each of thirty students</li>

<li>45 meg—Primary materials drawn on in writing papers, 1.5 meg per student</li>

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 <p>Let us roughly estimate the vast quantities of information enclosed within such study trees.<span class="cite"></span><ref>these estimates I am assuming that a byte is a byte is a byte. This is not an entirely fair assumption. Generally, if software is designed well, a quantity of executable program code will usually occupy a student longer than reading an equal amount of American Standard Code for Information Interchange (ASCII) text code. All the same, treating all code as if it were text code gives an adequate approximation of the information content of software. The following estimates are in the number of bytes that would be required to code the information pointed to by various study trees. For text each character is counted as a byte. Representing the amount of information in this way should not obscure the fact that currently most of the information in print-based courses is obviously not coded in binary form. My basic assumption is simply that for a course to be genuinely <i>computerbased</i> the full information content within its study tree should be accessible through computers. When we have gotten the information into such a form, then computing is in the starting gate.</ref> For instance, most reading these remarks will have once been undergraduates at quality colleges and they will recall struggling with the knowledge structure of a tough liberal arts course: a book a week, that is, 1-2 megabytes, or a total of about 20 megabytes of required reading, plus a serious term paper, which would require careful study of another 5 megabytes, two or three further books, along with more cursory perusal of a good deal more data, all different from one student to the next. Let us say there were twenty students in the course. The information capacity of the study tree would be the following:</p>
-<ul class="sl"><li>20 meg—Required materials worked with by each of the twenty students</li>
+<ul class="numsoff"><li>20 meg—Required materials worked with by each of the twenty students</li>
 <li>100 meg—Primary materials drawn on in writing papers, 5 meg per student</li>
@@ Line 55: / Line 55: @@
 <p>Be that as it may, the point here is not to find the exact quantity of information included in either the teaching tree or the study tree of the typical course, whether high school, college, or graduate school. In all cases the structure encompasses a very large amont of information, especially relative to the storage capacities of available academic computing systems. One might imagine a not terribly demanding high school course generating a study tree comprising the following amounts of information:</p>
-<ul class="sl"><li>2 meg—Required materials worked with by each of thirty students</li>
+<ul class="numsoff"><li>2 meg—Required materials worked with by each of thirty students</li>
 <li>45 meg—Primary materials drawn on in writing papers, 1.5 meg per student</li>