GOOGLE FORM VA QR KOD ASOSIDA XAVFSIZ KOGNITIV BAHOLASH ALGORITMI

Yusupova Shohida Botirboevna; Khujaev Otabek Kadamboyevich

Authors

Yusupova Shohida Botirboevna Abu Rayhon Beruniy nomidagi Urganch davlat universiteti
Khujaev Otabek Kadamboyevich Abu Rayhon Beruniy nomidagi Urganch davlat universiteti

Keywords:

QR kod, kognitiv baholash, Google Form, Item Response Theory (IRT), Kompyuter-adaptiv test (CAT), anomaliya deteksiyasi, raqamli ta’lim

Abstract

Ushbu maqolada onlayn kognitiv baholashda QR kodga asoslangan autentifikatsiyani Google Form platformasi bilan integratsiyalash imkoniyatlari tahlil qilinadi. Taklif etilgan algoritm QR token yaratish va verifikatsiya qilish jarayonini Item Response Theory (IRT) modellari (Rasch, 2PL, 3PL) bilan uyg‘unlashtirgan bo‘lib, bu test topshiriqlarini kalibrlash va talabalar qobiliyatini aniqroq baholashga xizmat qiladi. Shuningdek, tizimda Kompyuter-adaptiv test (CAT) mexanizmi joriy etilib, savollar test axborot funksiyasi asosida tanlanadi. Bu yondashuv test uzunligini qisqartirish bilan birga baholash ishonchliligini saqlab qoladi. Akademik halollikni ta’minlash maqsadida vaqt va xulqiy anomaliyalarni aniqlash (Z-score va izolatsiyaga asoslangan modellar) mexanizmlari ham kiritilgan. An’anaviy va onlayn baholash tizimlari natijalari taqqoslanganda, QR-kod integratsiyalangan yondashuv o‘lchash aniqligi, xavfsizlik va adaptivlik bo‘yicha ustunliklarga ega ekanligi ko‘rsatildi. Natijalar shuni tasdiqlaydiki, mazkur yondashuv raqamli ta’lim muhitida shaxsiylashtirilgan, shaffof va samarali baholash tizimlarini joriy etish uchun ishonchli asosdir.

References

2. Anderson, J. R. Cognitive Psychology and Its Implications. – 7th ed. – New York: Worth Publishers, 2010. – 497 p.

3. Siemens G. Connectivism: A Learning Theory for the Digital Age // International Journal of Instructional Technology & Distance Learning. – 2005. – №2(1). – С. 3–10.

4. S. B. Yusupova and B. Faxriddin, "Dynamic Data Transfer with Color QR Codes," 2024 IEEE 3rd International Conference on Problems of Informatics, Electronics and Radio Engineering (PIERE), Novosibirsk, Russian Federation, 2024, pp. 1440-1444, doi: 10.1109/PIERE62470.2024.10805033.

6. Krathwohl D. R. A Revision of Bloom’s Taxonomy of Educational Objectives. – Theory into Practice, 2002. – Vol. 41(4). – P. 212–218.

7. Bloom B. S. Taxonomy of Educational Objectives: The Classification of Educational Goals. – New York: Longman, 1956. – 207 p.

8. Narayanan S. QR Codes in Education: A New Tool for Teaching and Learning // International Journal of Educational Technology. – 2019. – Vol. 16(2). – P. 45–56.

10. Yusupova S. B., Ishmetov B. Y., Davletboyev S. Z. O. G. L. LMS MOODLE elektron ta’lim tizimida adaptiv testlarni yaratish va ularni baholash modelini ishlab chiqish //Academic research in educational sciences. – 2023. – Т. 4. – №. 3. – С. 128-138.