Analysis and Evaluation of a Learning Platform

Student Project (1-3 participants)

Career advancement requires employees to continuously update their skills and, in many cases, to document their up-to-date knowledge with a certificate. In Germany, the Chamber of Crafts provides numerous vocational trainings that lead to the obtainment of a certificate. Trainees are full-time working professionals. Till now most of the trainings are fully face-to-face.

The aim of the project “Smart Learning in Vocational Training" is to introduce a blended-learning approach in the energy consultant training. Learning material is being currently structured and developed using different digital media: texts, animations, screencasts, videos, etc. During face-to-face phases trainees learn hands-on with a professional. To prepare and to review face-to-face learning, they can access online what they need when they need it with the help of a novel mobile web application called the Learning Companion App (LCA).

Your tasks:

You will analyze a learning platform and different components in its architecture in different quantitative and qualitative evaluations in order to:

  • Identify strength and weaknesses of the platform
  • Measure accuracy of predictions
  • Make suggestions for new features and functions
  • Improve the usability for learning
  • Implement new algorithms


Required skills:


  • Interest in different evaluation techniques
  • Understanding of programming/ prototyping in web technologies, such as HTML, JS, CSS 
  • Optional: High-Level Understanding of Data Mining/ Recommendation Engines
  • Creative ideas, analytical skills and autonomous acting


Related Technologies:

  • Recommendation Engines
  • Predictive Data Mining

Related FAME Projects:



Contact:


Developing Linked Data Applications

Student Project

The nature of the World Wide Web has evolved from a web of linked documents to a web including Linked Data. Traditionally, we were able to publish documents on the Web and create links between them. Those links however, allowed us only to traverse the document space without understanding the relationships between the documents and without linking to particular pieces of information.

Linked Data allows us to create meaningful links between pieces of data on the Web. The adoption of Linked Data technologies has shifted the Web from a space connecting documents to a global space where pieces of data from different domains are semantically linked and integrated to create a global Web of Data. Linked Data enables operations to deliver integrated results as new data is added to the global space. This opens new opportunities for applications such as search engines, data browsers, and various domain-specific applications.

Over the course of this project the students will develop a system leveraging or supporting the field Linked Data. All details of the project will be defined together with the students depending on the size of the group, shared interests, technical skills, and the background. The group will go through the entire process of developing a working solution, from understanding and defining a problem, trough designing a solution, to developing, and finally testing a system. Students will be assisted by a supervisor at all stages of the project. 

Contact:

Marcin Wylot

Gamification for Leveraging Recommendation Engines in Digital Learning Environments

Student Project (1-3 participants)

Considering the faster technical improvement and the more extensive guidelines, standards and laws employed persons have to study further continuously from the time of graduation to the beginning age of retirement. The educational offer requires a strict schedule and learning discipline by the employed half-time students. A straight consequence of the lack of time is a short-time, exam-oriented learning strategy.

Our recommender system predicts learning objects and thus, extends Learning Management Systems (LMS). It focuses on a blended-learning approach for universities, chamber of crafts and adult education centers. Thereby, students can keep track of their individual predicted knowledge level on different learning objects at every point in time and get personalized learning recommendations based on the determined learning need value.


Your tasks:

In order to leverage the learner's intrinsic and extrinsic motivation, you shall choose specific Gamification elements for the integration into an existing Learning Companion Application. Thereby, each element shall be analyzed in theory and evaluated with real participants.

Required skills:
  • Good programming/ prototyping skills in web technologies, such as HTML, JS, CSS
  • Knowledge of server-side programming languages, such as Java, and common relational and/ or NoSQL database technologies
  • Optional: High-Level Understanding of Data Mining/ Recommendation Engines
  • Creative ideas, analytical skills and autonomous acting


Related technologies:

  • Gamification
  • Recommendation Engines
  • Predictive Data Mining


Related FAME Projects:


Contact: