Assessing students self-awareness on career choice is an important element in career guidance. This dataset is assessed during pre-treatment of career guidance programme involcing three Holland's constructs, i.e. occupational knowledge, realism, and attitude.

Categories:
72 Views

Psychometric Data

Categories:
151 Views

Description:

This repository contains the datasets used as part of the OC2 lab's work on Student Performance prediction and student engagement prediction in eLearning environments using machine learning methods.

Categories:
228 Views

An overview of a real-world Chinese mathematics dataset removed duplicated questions and simple questions.

Categories:
54 Views

A dataset of senior high student. 

Instructions: 

A dataset of senior high student. That can be used to verify student performance prediction method such as graph neural network for grade prediction

Categories:
132 Views

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.

Instructions: 

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

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

Categories:
206 Views

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.

Instructions: 

The dataset consists of two files:

1.OER Tracked Behavior.CSV

2.Course Tracked Behavior.CSV

Categories:
242 Views

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.

Categories:
156 Views

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.

Instructions: 

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.

Categories:
947 Views

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.

Categories:
139 Views

Pages