Mining students{u2019} performance Indicators from student response systems / (Record no. 74393)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03092cam a2200337 a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | EG-GiCUC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250223032414.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 191010s2019 ua f m 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | EG-GiCUC |
| Language of cataloging | eng |
| Transcribing agency | EG-GiCUC |
| 041 0# - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 049 ## - LOCAL HOLDINGS (OCLC) | |
| Holding library | Deposite |
| 097 ## - Thesis Degree | |
| Thesis Level | M.Sc |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | Cai01.20.03.M.Sc.2019.Sa.M |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Sarah Hassan Sayed |
| 245 10 - TITLE STATEMENT | |
| Title | Mining students{u2019} performance Indicators from student response systems / |
| Statement of responsibility, etc. | Sarah Hassan Sayed ; Supervised Aly Fahmy , Mohammad Elramly |
| 246 15 - VARYING FORM OF TITLE | |
| Title proper/short title | التنقيب عن مؤشرات أداء الطلاب من نظم الإجابة الإلكترونية |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Cairo : |
| Name of publisher, distributor, etc. | Sarah Hassan Sayed , |
| Date of publication, distribution, etc. | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 122 Leaves ; |
| Dimensions | 30cm |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Computer Science |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Improving the quality of education is always a desired goal in educational institutions, and involving technology in the educational process can improve education by supporting teachers with variety of tools to facilitate their job. One supporting solution is automatic scoring systems for students{u2019} short answers. This system can eliminate from teachers the burden of grading a large number of test questions and facilitate performing even more assessments either during lectures or via quizzes especially when the number of students is large. This research presents a learning model for short answers clustering and automatic scoring without using reference answers. The model is divided into three phases: (1) an embedding model for short answers representation, (2) a clustering model to cluster answers into groups based on their similarities, and (3) a regression model for predicting students{u2019} scores. For the embedding phase, a comprehensive evaluation of multiple state-of-the-art embedding models was applied to choose the best technique for text representation. Seven models were tested and evaluated separately by training a regression model to predict students{u2019} scores based on the cosine similarity between embeddings of students{u2019} answers and reference answers as a training feature. The study shows that using pre-trained models achieved comparable results for the task of automatic short answer scoring. The model that achieved the best results is doc2vec model which was trained on answers - students{u2019} answers and reference answers - from the benchmark dataset in order to learn vector representations of answers. The model achieved 0.569 correlation coefficient value measured based on the correlation between actual grades and predicted scores. The model achieved 0.797 root mean square error (RMSE) value for correctness of predictions |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE | |
| Additional physical form available note | Issued also as CD |
| 653 #4 - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | Automatic scoring |
| 653 #4 - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | Short answer grading |
| 653 #4 - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | Word embedding |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Aly Fahmy , |
| Relator term | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mohammad Elramly , |
| Relator term | |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://172.23.153.220/th.pdf">http://172.23.153.220/th.pdf</a> |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) | |
| Cataloger | Nazla |
| Reviser | Revisor |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) | |
| Cataloger | Samia |
| Reviser | Cataloger |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Thesis |
| Source of classification or shelving scheme | Not for loan | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Koha item type | Copy number |
|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | المكتبة المركزبة الجديدة - جامعة القاهرة | قاعة الرسائل الجامعية - الدور الاول | 11.02.2024 | Cai01.20.03.M.Sc.2019.Sa.M | 01010110079543000 | 22.09.2023 | Thesis | ||
| Dewey Decimal Classification | المكتبة المركزبة الجديدة - جامعة القاهرة | مخـــزن الرســائل الجـــامعية - البدروم | 11.02.2024 | Cai01.20.03.M.Sc.2019.Sa.M | 01020110079543000 | 22.09.2023 | CD - Rom | 79543.CD |