TY - GEN
T1 - A Generative-AI Approach to Validating Blank Selections for Phrase Fill-in-Blank Problems in Web-Client Programming Learning Assistant System
AU - Li, Zhikang
AU - Qi, Huiyu
AU - Funabiki, Nobuo
AU - Kyaw, Htoo Htoo Sandi
AU - Kao, Wen Chung
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Dynamic web-client programming with HTML, CSS, and JavaScript has become dominant in web application system. To assist its study by novices, we have developed a Phrase Fill-in-Blank Problem (PFP) in the Web-client Programming Learning Assistant System (Web-PLAS). Any answer is marked through string matching with the correct one. However, the current blank phrase selection algorithm implemented for helping a teacher to make a new PFP instance may not select blanks having unique answers. In this paper, we investigate a generative-AI approach to validating the selected blank phrases by the algorithm. In this approach, we first change the name of any user-defined identifier in a code so that the AI cannot use a memorized code for the answer. Then, we check the validity of the selected blanks by asking the AI to find their correct answers. After that, we repeat selecting a new phrase for blank and validating it by asking the AI to find the correct answer, until no new phrase can be selected. In either case, if the AI cannot find the correct answer, the blank is discarded. For preliminary evaluations, we manually apply this approach to the 10 PFP instances for basic topics in our previous study, using MS Copilot. The results show that several blanks in existing instances are not correct and additional blanks can be selected. The implementation of a program to automate the approach and its comprehensive evaluations with various codes will be in our next study.
AB - Dynamic web-client programming with HTML, CSS, and JavaScript has become dominant in web application system. To assist its study by novices, we have developed a Phrase Fill-in-Blank Problem (PFP) in the Web-client Programming Learning Assistant System (Web-PLAS). Any answer is marked through string matching with the correct one. However, the current blank phrase selection algorithm implemented for helping a teacher to make a new PFP instance may not select blanks having unique answers. In this paper, we investigate a generative-AI approach to validating the selected blank phrases by the algorithm. In this approach, we first change the name of any user-defined identifier in a code so that the AI cannot use a memorized code for the answer. Then, we check the validity of the selected blanks by asking the AI to find their correct answers. After that, we repeat selecting a new phrase for blank and validating it by asking the AI to find the correct answer, until no new phrase can be selected. In either case, if the AI cannot find the correct answer, the blank is discarded. For preliminary evaluations, we manually apply this approach to the 10 PFP instances for basic topics in our previous study, using MS Copilot. The results show that several blanks in existing instances are not correct and additional blanks can be selected. The implementation of a program to automate the approach and its comprehensive evaluations with various codes will be in our next study.
KW - blank phrase selection algorithm
KW - Copilot
KW - generative AI
KW - phrase fill-in-blank problem
KW - web-client programming
UR - https://www.scopus.com/pages/publications/105037402752
UR - https://www.scopus.com/pages/publications/105037402752#tab=citedBy
U2 - 10.1109/ICCE67443.2026.11449623
DO - 10.1109/ICCE67443.2026.11449623
M3 - Conference contribution
AN - SCOPUS:105037402752
T3 - Digest of Technical Papers - IEEE International Conference on Consumer Electronics
BT - 2026 IEEE International Conference on Consumer Electronics, ICCE 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2026 IEEE International Conference on Consumer Electronics, ICCE 2026
Y2 - 3 February 2026 through 5 February 2026
ER -