Project Exploratory Learning Analytics toolkit for Student (ELAS)
The goal of the project "Exploratory Learning Analytics toolkit for Students" is to develop a platform for students of the University of Duisburg-Essen to support their learning activities. The platform provides a collection of Learning Analytics applications developed by students for students. ELAS includes the best projects from the previous iterations of the Learning Analytic (LA), Advanced Web Technologies (AWT), Learning Analytics and Visual Analytics (LAVA), and Interactive Data Exploration and Analytics (IDEA) courses offered at the Social Computing Group, where different Learning Analytics applications were developed as part of student projects.
E3Selector is an application in ELAS that provides insights into the E3 module catalog to help students choose interesting courses that fit their needs. This project consists of power filtering, searching, and sorting capabilities to make it easy for students to search for suitable E3 courses. Furthermore, E3Selector keeps track of all the selections that can be easily shared in social media applications.
StudyCompass is an application in ELAS that supports UDE students in selecting suitable university’s courses in a few easy steps. Furthermore, the platform lets students easily make a schedule by observing various details such as overlapping course schedules, ratings of the courses, and links to LSF.
CourseRecommender is an application in ELAS that aims to provide course and study program recommendations to potential new students at the UDE. The engineering courses and study programs of the UDE are collected from LSF and VDB (Veranstaltungsdatenbank für Ingenieure). The collected data is used to generate personalized recommendation of courses, study programs, and related interests. CourseRecommender leverages Knowledge Graphs (KG), NLP, and word/sentence embedding techniques to generate the recommendations.
The idea of the project is to develop a user-friendly web application that provides various functionalities, including the organization and categorization of notes and the ability to search for notes shared by other students. Additionally, the application incorporates an AI-powered chatbot, which can offer study guidance and support to users. This feature enhances the learning experience by providing personalized assistance and recommendations.
ProjectFinder simplifies the process of finding projects and group members for Bachelor's/Master's projects. It provides a centralized platform for students to discover projects and connect with like-minded peers. Students can search for projects based on their field of study and preferences, and create their own projects to find collaborators. ProjectFinder streamlines the project-finding process, allowing students to focus on their research and academic goals without the stress of searching for projects and group members.
Intogen is an application in ELAS that aims to identify and improve students’ learning styles based on David Kolb’s learning cycle (Kolb’s 40-item questionnaire), and suggest courses according to their preferred learning styles. In addition, this application allows students to get an overview of the learning styles present in other courses, study programs, and countries.
DataCampus Conference - IDEA Poster
The event was organized by the - an interdisciplinary association to promote data skills at the UDE. During the conference, impressions of the development of the field of data literacy and data science were given, practical examples for the promotion of data skills in the subjects were presented, and perspectives for the development and expansion of data literacy and data science offered at the UDE were jointly developed.