A dataset of the senior high students.  


The dataset contains :

1_teacher.csv contains the corresponding information of the teachers;

2_student.csv contains the corresponding information of the students;

3_kaoqin.csv contains the attendance information of the students;

4_kaoqintype.csv contains the type of attendance. 

5_chengji.csv contains the grades of the students. 

6_exam_type.csv contains the type of examinations. 





The dataset links to the survey performed on students and professors of Biological Engineering introductory course, as the Department of Biological Engineering, University of the Republic, Uruguay.


The dataset is meant for pure academic and non-commerical use.

For queries, please consult the corresponding author (Parag Chatterjee, paragc@ieee.org).


This dataset represents the main different unique learning behaviors that may be found in any group of learners in e-learning/educational systems. It represents 20 learners through 17 OERs.


The dataset consists of two files:

1.OER Tracked Behavior.CSV

2.Course Tracked Behavior.CSV


E-learning is a type of learning by using electronic technologies to access an educational program outside of a traditional classroom. As conventional classrooms continue to be transformed into digital, teachers must deliver lectures through multiple learning modes. Digitally enriched content and personalized learning, should be the primary way of teaching, as well as collaborative and interactive learning.


Dataset is intended for studying how student programming styles and usage of IDE differs between students who plagiarise their homework and students who solve them honestly.Dataset includes homeworks submitted by students during two introductory programming courses (A and B) delivered during two years (2016 and 2017). A is delivered in C programming language, while B is delivered in C++. In addition to homeworks, dataset includes full traces of all student activity and keystrokes during homework development.


The archive provided consists of three parts:SOURCE CODES:Actual submitted homeworks by students (i.e. their source codes) are stored in folder "src". Subfolders of this folder are named after courses: A2016, A2017, B2016 and B2017. This further contain subfolders for individual assignments. On each course students were required to solve 16-22 assignments labeled "Z1/Z1", "Z1/Z2", "Z2/Z1" etc. Finally, in each folder are actual C or C++ files named after student (anonymized, so actual student names were replaced by strings in form "student1393").TRACES:IDE usage traces are stored in folder named "stats". Again, this folder is organized into subfolders named after courses. These folders contain files named after student (anonymized) with extension .stats and are in JSON format. Format of JSON files is described in readme.txt file.GROUND TRUTH:Ground truth lists students and groups of students that are considered to have involved in plagiarism due to code similarity and failure to deliver an "oral defense". There are three ground truth files. ground-truth-anon.txt contains full list of plagiarisms, ground-truth-static-anon.txt only those based on source code similarity, and ground-truth-dynamic-anon.txt only those based on failure to do an "oral defense". There is some overlap between the last two files. The format of the file is: homework assignment in the format:- A2016/Z1/Z1(dash, space, course name, slash, assignment name), followed by lists of anonymized names of students (such as "student3241") or groups of students who are mutually plagiarised separated by comma.


The project is conceptualized to 'Geo Web-Based Facility Mapping for Zone-2 in Greater Visakhapatnam Municipal Corporation- GVMC in Visakhapatnam, India'. The main objective is to share the spatial data to the public to help them find the information about the nearest Hospital, ATM, Educational institutions, petrol filling stations, and supermarkets by providing both web map services and web coverage services using QGIS Cloud.


Accurate information about crop rotation is essential for administrators, managers and various government departments for assessment, monitoring, and management of various resources for crop escalation. Radar remote sensing, because of its all-weather capability and assured uninterrupted data supply can show a substantial part in the evaluation of crop rotation.


This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time". M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.


The code is written for MATLAB. We used transfer learning using AlexNet and GoogLeNet as convolutional neural network (CNN) backbones.

In MATLAB, replace the directory path with yours. If you want to recognize other classes, just add the images from different classes on labeled folders.


In this paper, the influencing factors of university teachers' intention to flow in Hebei Province are taken as the research object. The universities in the province are divided into public undergraduates, private undergraduates, public colleges, and private colleges. Questionnaires are sent to 39 colleges.


The correlation matrix and the survey items are provided for the design and validation of an instrument to evaluate the implementation of six sigma critical success factors during the realization of improvement projects in higher education institutions.