STUDENT PERFORMANCE PREDICTION FROM ONLINE HANDWRITING BIOMETRICS / (Kayıt no. 290931)
[ düz görünüm ]
| 000 -BAŞLIK | |
|---|---|
| Sabit Uzunluktaki Kontrol Alanı | 02704nam a22002777a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ | |
| Kontrol Alanı | KOHA |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI | |
| Kontrol Alanı | 20230905091438.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ | |
| Sabit Alan | 230905d2023 cy ||||| m||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI | |
| Özgün Kataloglama Kurumu | CY-NiCIU |
| Kataloglama Dili | eng |
| Çeviri Kurumu | CY-NiCIU |
| Açıklama Kuralları | rda |
| 041 ## - DİL KODU | |
| Metin ya da ses kaydının dil kodu | eng |
| 090 ## - Yerel Tasnif No | |
| tasnif no | YL 3070 |
| Cutter no | O46 2023 |
| 100 1# - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Omolafe, Olamideji Michael |
| 245 10 - ESER ADI BİLDİRİMİ | |
| Başlık | STUDENT PERFORMANCE PREDICTION FROM ONLINE HANDWRITING BIOMETRICS / |
| Sorumluluk Bildirimi | OLADIMEJI MICHEAL OMOLAFE; SUPERVISOR: ASST. PROF. DR. YASEMIN BAY |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - FİZİKSEL TANIMLAMA | |
| Sayfa, Cilt vb. | vii, 68 sheets; |
| Boyutları | 31 cm. |
| Birlikteki Materyal | Includes CD |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| Content type code | txt |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| Media type code | n |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| Carrier type code | nc |
| 502 ## - TEZ NOTU | |
| Tez Notu | Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems Department |
| 504 ## - BİBLİYOGRAFİ NOTU | |
| Bibliyografi Notu | Includes bibliography (sheets 54-62) |
| 520 ## - ÖZET NOTU | |
| Özet notu | ABSTRACT<br/>Traditionally, biometrics has been associated with fingerprint mapping, facial <br/>recognition, and retina scans. However, the recognition of individuals merely based <br/>on their handwriting has drawn the interest of researchers in the subject of handwriting <br/>biometrics. This new discipline has promising prospects for predicting student <br/>academic performance from their online handwriting biometrics. The available <br/>handwriting biometric database for this research is the CIU handwritten database, <br/>which includes student performance in addition to their identification labels. 804 <br/>handwriting samples collected from 134 students are contained in the database.<br/>This research investigates the potential of handwriting biometric features in predicting <br/>academic performance. Two datasets were extracted from the CIU handwritten <br/>database, with the first consisting of 134 participants and the second consisting of 97 <br/>participants. Success scores were classified as good, average, or poor in the first <br/>dataset, and as good or poor in the second dataset. NaiveBayes, J48 decision tree, <br/>RandomForest, and KNN models were used to classify the success scores based on <br/>handwriting biometric features. Results showed that the RandomForest model <br/>outperformed the other models in both datasets, with the highest accuracy achieved <br/>after feature selection. The results of the empirical analysis based on the online <br/>handwriting biometrics show that it is possible to predict student academic <br/>performance from their online handwriting biometrics.<br/>Keywords: Biometric Features, Handwriting Biometrics, Performance Prediction, <br/>Students Performance |
| 650 ## - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Biometry |
| Alt başlık biçimi | Dissertations, Academic |
| 650 ## - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Performance |
| Alt başlık biçimi | Dissertations, Academic |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Bay, Yasemim |
| İlişkili Terim | supervisor |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) | |
| Sınıflama Kaynağı | Dewey Onlu Sınıflama Sistemi |
| Materyal Türü | Thesis |
| Geri Çekilme Durumu | Kayıp Durumu | Sınıflandırma Kaynağı | Kredi için değil | Koleksiyon Kodu | Kalıcı Konum | Mevcut Konum | Raf Yeri | Kayıt Tarih | Source of acquisition | Yer Numarası | Demirbaş Numarası | Son Görülme Tarihi | Fatura Tarihi | Materyal Türü | Genel / Bağış Notu | Toplam Ödünçverme |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Tez Koleksiyonu | 05.09.2023 | Bağış | YL 3070 O46 2023 | T3451 | 05.09.2023 | 05.09.2023 | Thesis | Management Information Systems Department | ||||
| Dewey Onlu Sınıflama Sistemi | CIU LIBRARY | CIU LIBRARY | Görsel İşitsel | 05.09.2023 | Bağış | YL 3070 O46 2023 | CDT3451 | 05.09.2023 | 05.09.2023 | Suppl. CD | Management Information Systems Department |