DABAI: A data driven project for e-Learning in Denmark

TY - GEN

T1 - DABAI

T2 - 16th European Conference on e-Learning, ECEL 2017

AU - Alstrup, S.

AU - Hansen, Casper

AU - Hansen, Christian

AU - Hjuler, Niklas

AU - Lorenzen, Stephan

AU - Pham, Ninh

PY - 2017/1/1

Y1 - 2017/1/1

N2 - A new Big Data research team called DABAI have been launched in Denmark, which aims at integrating cutting edge computer science research from machine learning, algorithms and visualization into the education sector. The educational part of the DABAI project is a cooperation between Danish universities and multiple enterprises providing e-Learning solutions for the Danish market. The companies' services cover over 90% of the Danish schools, with more than one million students, who on a daily basis do millions of exercises and interactions using the involved companies' solutions. The study presented in this paper is an initial investigation of the needs of the three largest companies in e-Education in Denmark directly involved in DABAI, with the goal being to continue providing novel and high-demand features for their customers. The three companies are MaCom, Clio Online, and EduLab. Clio Online and EduLab provide an online platform for teaching material and exercises for the primary school level covering all subjects. MaCom provides a lecture management system used by most Danish high schools. Overall the study shows that the problems encountered at the different companies are varied, but can be categorized into three general sub categories: Student Profiling, Content Profiling, and Content Recommendation. Some problem types fall into multiple sub categories, and in general to accomplish the goal of providing e-Learning of the highest quality, research into all of them is necessary. This paper presents the fundamental problems these companies are facing in e-Learning. For each encountered problem, we describe its objectives and challenges in detail, followed by the current state of the art for solving it.

AB - A new Big Data research team called DABAI have been launched in Denmark, which aims at integrating cutting edge computer science research from machine learning, algorithms and visualization into the education sector. The educational part of the DABAI project is a cooperation between Danish universities and multiple enterprises providing e-Learning solutions for the Danish market. The companies' services cover over 90% of the Danish schools, with more than one million students, who on a daily basis do millions of exercises and interactions using the involved companies' solutions. The study presented in this paper is an initial investigation of the needs of the three largest companies in e-Education in Denmark directly involved in DABAI, with the goal being to continue providing novel and high-demand features for their customers. The three companies are MaCom, Clio Online, and EduLab. Clio Online and EduLab provide an online platform for teaching material and exercises for the primary school level covering all subjects. MaCom provides a lecture management system used by most Danish high schools. Overall the study shows that the problems encountered at the different companies are varied, but can be categorized into three general sub categories: Student Profiling, Content Profiling, and Content Recommendation. Some problem types fall into multiple sub categories, and in general to accomplish the goal of providing e-Learning of the highest quality, research into all of them is necessary. This paper presents the fundamental problems these companies are facing in e-Learning. For each encountered problem, we describe its objectives and challenges in detail, followed by the current state of the art for solving it.

KW - Big Data

KW - E-Learning

KW - E-Learning challenge categorization

UR - http://www.scopus.com/inward/record.url?scp=85037543232&partnerID=8YFLogxK

M3 - Article in proceedings

AN - SCOPUS:85037543232

SP - 18

EP - 24

BT - ECEL17 - Proceedings of the 16th European Conference on e-Learning

A2 - Peres, Paula

A2 - Mesquita, Anabela

PB - Academic Conferences and Publishing International

Y2 - 26 October 2017 through 27 October 2017

ER -