A Proposal of Blank Phrase Selection Algorithm for Phrase Fill-in-Blank Problems in Web-Client Programming Learning Assistant System

In today's digital landscape, web applications play a central role in information systems across the Internet. Therefore, mastering web-client programming using HTML, CSS, and ]avaScript is essential for novice students. Previously, we have introduced the phrase fill-in-blank problem (PFP) as a self-study tool, where students are required to fill in missing phrases (sets of elements) in given source code by referring to the screenshots of the corresponding web page. The correctness of submitted answers is evaluated through string matching. However, the selection of blank phrases was made manually in previous, based on the importance of elements and the uniqueness of correct answers, which was time-consuming and less scalable. In this paper, we propose a blank phrase selection algorithm to automatically generate a new PFP instance from a given source code for web-client programming. We define nine rules for selecting blank phrases and implement the procedure in Python using open-source regular expressions. For evaluations, we generated 10 PFP instances using the proposed algorithm and assigned them to 20 students in Okayama University. Their solution results confirmed the validity of the proposal.