Grade Prediction in Blended Learning Using Multisource Data

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Semester/grade</td><td class="align_center">Data dimensions</td><td class="align_center">Number of pieces of data</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Fall semester 2017-2018 (grade 1)</td><td class="align_center">119</td><td class="align_center">82</td></tr><tr><td class="align_left">Fall semester 2018-2019 (grade 2)</td><td class="align_center">130</td><td class="align_center">117</td></tr><tr><td class="align_left">Fall semester 2019-2020 (grade 3)</td><td class="align_center">130</td><td class="align_center">115</td></tr><tr><td class="align_left">Fall semester 2020-2021 (grade 4)</td><td class="align_center">131</td><td class="align_center">119</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Description of integration data summary.</div>

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Table 4

Table 4: Grade Prediction in Blended Learning Using Multisource Data 