DOI: 10.5281/zenodo.17459528
title: Architectural Visualization Student Performance Dataset-(Summer 2025 Semester)

description: Architectural Visualization Student Performance Dataset – Summer 2025

1. Overview

The Architectural Visualization Student Performance Dataset (Summer 2025) presents a detailed record of student performance in two sections of the Architectural Visualization course offered at Daffodil International University (DIU), Bangladesh.

Although the sections were conducted under different academic programs, both followed the same syllabus, course structure, and evaluation process. The course was taught and coordinated by S. M. Monowar Kayser, Lecturer, Department of Multimedia and Creative Technology (MCT), DIU.

The dataset combines the results of students enrolled in:



B.Sc. (Hons) in Environmental Science and Disaster Management (ESDM)

B.Sc. in Multimedia and Creative Technology (MCT)


Its purpose is to support comparative studies, institutional research, curriculum evaluation, and broader educational data analysis.

 

2. Dataset Composition






Attribute



Description





Total Records



76 student entries





Departments Included



Environmental Science and Disaster Management (ESDM) and Multimedia and Creative Technology (MCT)





Course Title



Architectural Visualization





Course Codes



ESDM 409, 0212-323





Semester



Summer 2025





Credit Hours



3.00





Instructor



S. M. Monowar Kayser, Lecturer, Department of MCT, DIU





Institution



Daffodil International University, Bangladesh





Each record provides a complete academic profile, including attendance, class tests, project-based work, midterm and final exam marks, and the final course grade.

 

3. Data Structure and Variable Description






Column Name



Description



Type / Format





SL



Serial number (1–76)



Integer





Department



Student’s department (ESDM / MCT)



Text





Course Code



Course identification code



Text





Student ID



Unique registration number



Text





Name of Student



Full name of the student



Text





Attendance (out of 7)



Attendance marks



Numeric





CT-1 / CT-2 / CT-3 (out of 15)



Class-test scores



Numeric





Class Test (out of 15)



Average score from class tests



Numeric





Presentation / Viva (out of 8)



Marks for presentation or viva



Numeric





Assignment (out of 5)



Assignment marks



Numeric





Mid Term (out of 25)



Midterm exam marks



Numeric





Final Exam (out of 40)



Final exam marks



Numeric





Grand Total (out of 100)



Combined total marks



Numeric





Final Grade



Letter grade following DIU grading system



Text





Performance Category



Performance level: High, Moderate, Low, or Very Low / Incomplete



Text





 

4. Performance Categories






Grade Range



Category



Description





A+, A, A−



High Performance



Excellent mastery of course objectives





B+, B, B−



Moderate Performance



Consistent and satisfactory progress





C+, C, D



Low Performance



Limited achievement; improvement needed





I, F



Very Low / Incomplete Performance



Incomplete or failing outcome





This classification enables consistent comparison across departments and helps identify areas where students may need additional support.

 

5. Applications

The dataset can be used for:



Analyzing patterns of student performance

Evaluating curriculum effectiveness

Educational data mining and predictive modeling

Institutional benchmarking and policy design

Visualization and academic research projects


 

Keywords

Architectural Visualization, Student Performance, Educational Data, Academic Analytics, Daffodil International University, Bangladesh, Higher Education, Assessment