Summersemester 2024/25

Intelligent Learning Environments (ILE)

Computers and ‘machine-intelligence’ are frequently discussed as the means for addressing today’s critical educational challenges: learning remotely, learning at one’s own pace, learning according to one’s needs and background, providing quality education to all and for all. In this course, we welcome all master-level students with technical or non-technical backgrounds. Through the semester, we will cover topics on the intersection of Artificial Intelligence in Education, Educational Technologies, and Human-Computer Interaction and we will carry out hands-on exercises to deepen our understanding of intelligent learning technologies.

Teaching Form: Blended learning: Face-to-face lectures and practical sessions with online learning modules, and group work. 


Investigating the effect of tactile perception on the working memory

Learning can be perceived as the storage of information in Long-term memory:

  • Information is first assimilated through our senses, visual, auditory etc. as perception(Multi store model of information processing)
  • Knowledge (factual & procedural) stored in long-term memory

Tactile perception, i.e, information through touch, should play or plays a huge role in learning (embodied cognition)

We use ‘attention’ to filter out irrelevant stimuli to improve learning. Given this, amplification of a stimuli should support the attention process leading to improved learning. Dual-coding theory assumes that auditory and visual information is processed in separated channels which lowers the demand on working memory. Similarly, tactile perceptions should also be processed separately in the working memory.

In this project we aim:

  • To investigate how sensory modalities influence the retrieval of motor skills for handwriting skill development
  • To learn how to design and carry out small-scale research, including:
  • Designing studies to explore your hypothesis
  • Developing tools, for example using sensors, for collecting handwriting data
  • Conducting data analysis and reporting your findings

Teaching Form: Blended learning


Implementation of an Intelligent Tutor for Programming with Personalised Feedback

This project aims to explore the design, use and impact of Intelligent Tutoring Systems for programming.

In particular, we aim to: 

  1. We will be using CTAT – the Cognitive Tutor Authoring Tools – that support the creation of flexible tutors
  2. We will look at the different levels of feedback and how to give appropriate feedback for a variety of programming tasks
  3. Eventually, we will combine this and pass our feedback to the intelligent tutors

For this project, we will work in groups of 4 students on a predefined topic (each group will be assigned a different topic). During the first weeks, we will provide an overview of the project, its goals, and related theoretical and practical concepts. Then, the groups will work towards three milestones:
a. An initial presentation of their ideas, strategies and workplans to address the project’s topic;
b. A mid-term presentation of the work-progress up to that point
c. A final presentation of the finished project and a written project report in the form of a scientific article.

Teaching Form: Blended learning (in person meetings, real-time webinars, video recordings, group consultation sessions).


"What do we mean when we talk about AI Literacy?" Exploring the research landscape

In this seminar, we will explore aspects of Artificial Intelligence (AI) Literacy: What do we mean when we talk about AI Literacy, what are the competencies and skills to help us prepare for and live with AI and what is the current state of the art. To do so, we will review research works and literature on the topic of AI Literacy with an emphasis on competence frameworks that are used in formal and informal education.

Teaching Form: Blended learning: face-to-face and online meetings.