الصفحة الرئيسية

كلية العلوم \ الرياضيات

محمد الشاذلي سر الختم عبد الوهاب زيدان

السيرة الذاتية
نسبة اكتمال الملف الشخصي
الجنسية السودانية
التخصص العام الإحصاء
التخصص الدقيق الإحصاء الحيوي
المسمى الوظيفي أستاذ مساعد
الدرجة العلمية (المرتبة) دكتوراه

نبذه مختصرة

My research interests encompass a diverse range of subjects, including dynamical systems modeling, perturbation theory, and machine learning

المؤهلات العلمية

PhD in Applied Mathematics

الاهتمامات البحثية

Applied Mathematics, and computer science

الخبرات والمناصب الإدارية

Assistant Professor at Tabuk University Head of the Quality Assurance Committee at the Mathematics Department

الجدول الدراسي
اليوم المادة الوقت
من إلى
الأحد office hours 10:00 12:00
الأحد STAT 1101-Sec:537 12:30 14:00
الإثنين office hours 08:30 09:30
الإثنين MATH1102-Sec3741 09:30 11:00
الأربعاء office hours 08:30 09:30
الأربعاء MATH1102-Sec3741 09:30 11:00
الأربعاء MATH1102-Sec3734 11:00 12:30
الخميس office hours 10:00 12:00
الأبحاث والمؤلفات
  • Understanding the Dynamic Characteristics of Student Cohort Progression Using Dynamic Mode Decomposition
  • A wavelet time-frequency analysis of pandemic dynamics and impacts - COVID19 case study
  • Wavelet dynamic mode decomposition diagnosis some marketing time series and economic impact
  • Forecasting Students Progression rates: A case study at Tabuk University
  • Constraining the gravitational action with CMB anisotropies
  • Cosmological tensor perturbations in theories beyond Lamda-CDM
  • Cosmological dynamics of fourth order gravity: A compact view
  • Covariant gauge-invariant perturbations in multi-fluid f(R)-gravity
  • Unifying the study of background dynamics and perturbations in f(R)-gravity
  • Cosmological dynamics of exponential gravity
جوائز التميز
  • NA
المشاريع البحثية
اسم المشروع وصف المشروع
Predicting Student Progression in a Four-Year University Program Using Time Series Data In higher education, understanding and predicting student progress is crucial to enhancing academic success and increasing program completion rates This research aims to analyze student progress using time series data containing student grades across all courses and levels The primary goal is to predict the likelihood of future progress, academic status (withdrawal, suspension, graduation), and performance in higher-level courses based on first-year student grades The core idea behind this research proposal is to harness the potential of advanced data analysis techniques to predict and improve student progress by analyzing time series data of student groups, which include detailed records of grades across all courses and levels The study aims to uncover hidden patterns affecting academic paths The main goal is to develop a predictive model using first-year grades to forecast future academic outcomes such as withdrawal, suspension, graduation, and performance in advanced courses The motivation for this project stems from the urgent need to enhance student retention rates and success in higher education institutions Understanding the factors leading to different academic outcomes can enable universities to implement early interventions, design academic support, and improve resource allocation For program leaders, the benefits of this research are multifaceted The predictive model will provide actionable insights, allowing for the early identification of at-risk students This facilitates targeted support strategies, which can be crucial in preventing dropout and improving overall graduation rates Additionally, by predicting future performance in advanced courses, programs can design personalized educational pathways that meet individual student needs, thereby enhancing educational quality and student satisfaction Implementing an easy-to-use code that provides these predictive insights based on first-year student grades will serve as a powerful tool for academic advisors and administrators, facilitating data-driven decision-making Ultimately, the results of this research will contribute to creating a more supportive and responsive educational environment, enhancing high academic achievement and improving program completion rates
معلومات التواصل
البريد الإلكتروني : mabdelwahab@ut.edu.sa
1805

الخصوصية وملفات تعريف الارتباط
هذا الموقع يستخدم ملفات تعريف الارتباط الخاصة للتأكد من سهولة الاستخدام وضمان تحسين تجربتك أثناء التصفح. من خلال الاستمرار في تصفح هذا الموقع، فإنك تقر بقبول استخدامنا لملفات تعريف الارتباط. الشروط والأحكام.