PhD Defense: A Bridge between Learning Analytics and Learning Design

PhD Defense: A Bridge between Learning Analytics and Learning Design

Book, Event, Higher Education, Learning Analytics, Learning Design, Multimodal Learning Analytics, PhD defense, Publication, School
We warmly congratulate our esteemed associate partner, DR. Marcel Schmitz, on successfully defending his PhD thesis on November 29, 2024. Marcel is a senior lecturer and researcher in Data Intelligence and the Applied Data Science & Artificial Intelligence program at Zuyd University of Applied Sciences. In his dissertation, titled “Towards Learning Analytics-Supported Learning Design”, he focused on how education can be better personalized by incorporating learning analytics already in the design and course planning. His dissertation was supervised by Prof. Dr. Hendrik Drachsler (DIPF | Leibniz Institute & Goethe University Frankfurt), with co-supervisors Prof. Dr. Maren Scheffel (Ruhr University Bochum) and Dr. Roger Bemelmans (Zuyd University of Applied Sciences). Marcel's dissertation provides actionable strategies not only for higher education but also for other educational sectors. His work envisions a future…
Read More
New Pub: Understanding Learning Engagement in Asynchronous Online Settings

New Pub: Understanding Learning Engagement in Asynchronous Online Settings

Higher Education, Journal, Learning Analytics, Publication
A newly published study illustrates the complexities of learning engagement (LE) in asynchronous online settings (AOSs) for university students. For university students it can be difficult to learn in such environments since these lack real-time interactions. This also makes it difficult for teachers to measure how engaged students actually are with their study materials. Through trace data, learning analytics can be used as a foundation to analyze students’ learning methods and LE. The study investigates whether LE can be characterized by the sub-dimensions: effort, attention and content interest. The study also explores the question of which trace data from student behavior within AOSs can best represent these factors of LE in self-reports. The research involved 764 university students and utilized best-subset regression analysis to determine which indicators most reliably represent…
Read More
New Pub: Learning At and From a Virtual Conference

New Pub: Learning At and From a Virtual Conference

Higher Education, Journal, New Pub
In light of the COVID pandemic and the climate crisis, many academic conferences have switched from face-to-face to virtual or hybrid conferences. The advantages of completely virtual conferences are clear. The organizers don’t need to look for physical rooms to book or need to organize food or drinks for participants. For the participants, this form of conferences can also be advantageous because there are no travel expenses and no travel time. Those participating from other countries can even take part in the conference despite being in different time zones or continents. The advantages go hand in hand with the disadvantages of limited personal interaction: no scientific (or leisurely) discussions during a coffee break or a chance to get to know fellow researchers seated nearby before a session begins. With all…
Read More
PhD Defense: A Deep Dive into Visual Learning Analytics

PhD Defense: A Deep Dive into Visual Learning Analytics

Award, Higher Education, Learning Analytics, PhD defense, School
On September 13th, Hendrik Drachsler took on the esteemed role of opponent in the PhD defense of Artemis Mohseni at Linnaeus University, Sweden. The defense, which marked a pivotal moment in Artemis’s academic journey, centered around her innovative doctoral thesis titled "Development of Visual Learning Analytics Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education." The evaluation commission was formed by: Associate professor Olga Viberg, Royal Institute of Technolgy, Sweden Associate professor Linnéa Stenliden, Linköpings University, Sweden Professor Johan Lundin, University of Gothenburg, Sweden Associate professor Fisnik Dalipi, Linnaeus University, Sweden Associate professor Arianit Kurti, Linnaeus University, Sweden It was an exciting defense that showcased Artemis’s research, which focuses on the potential of Visual Learning Analytics (VLA) to enhance teaching and learning by providing actionable…
Read More
Keynote at #LearningAID24, Bochum Germany

Keynote at #LearningAID24, Bochum Germany

Artificial Intelligence, Conference, Event, Higher Education, Keynote, Learning Analytics, Learning Design
At the recent #LearningAID24 conference in Bochum, Germany, Hendrik Drachsler delivered a keynote that challenged conventional perspectives on Learning Analytics and AI in education. He opened the discussion by examining the often ambiguous boundary between Learning Analytics and AI in education, posing a thought-provoking question: are these two areas truly distinct, or do they converge into one shared domain? Beyond theoretical discussions, Hendrik presented early empirical findings from the research program on Highly-Informative Learning Analytics (HILA), advocating for a more evidence-based approach to integrating Learning Analytics and AI into education. The goal, he argued, should be to ensure that these technologies effectively meet the informational needs of learners, providing meaningful and actionable insights. He framed the 2nd conference day around the theme: INFORMED PRECISION -  This concept captures the need…
Read More
New Pub: Revolutionizing Essay Scoring with Hierarchical Rater Models

New Pub: Revolutionizing Essay Scoring with Hierarchical Rater Models

Artificial Intelligence, Assessment, Higher Education, Journal, New Pub
For a special issue on Natural Language Processing in Psychology we proposed a hierarchical rater model-based approach to address the challenges in automatic essay scoring. Essay writing tests are an integral part of educational systems, essential for assessing students' critical thinking, articulation and understanding. Since the manual scoring process requires significant resources and time, teachers are beginning to use Automated Essay Scoring (AES), which is potentially capable of alleviating the manual effort involved. #AutomatedEssayScoring #NaturalLanguageProcessing #FormativeAssessment #EducationalTechnology #MachineLearning #AIinEducation #HierarchicalRaterModel #EdTech #ScoringAutomation #AI #AssessmentTools #MeasurementInvariance #TransformerModels #EducationResearch #UniversityTesting #AIModels #TechInEducation There are an abundance of available models and each one has its own unique features and scoring methods. Thus, selecting the optimal model is complex and challenging, especially when different aspects of content have to be assessed over a number…
Read More
Advancing Automated Analysis of Concept Maps at AIED24

Advancing Automated Analysis of Concept Maps at AIED24

Artificial Intelligence, Feedback, Higher Education, Learning Analytics, Publication, School, Workshop, Workshop
The 25th International Conference on Artificial Intelligence in Education (AIED 2024), held from July 8-12 in Recife, Brazil, was a significant event for the Highly Informative Learning Analytics Research Programme. This year marked the first Brazilian-German cooperation in this field, supported by the Alexander Humboldt Foundation, the DIPF in Frankfurt and IPN in Kiel under the ALICE project. Two workshop papers presented at the conference showcased innovative approaches to automatically analyze concept maps, promising to automate the way educators assess and understand the student-created context. #AIED24 #LearningAnalytics #ConceptMaps #AIinEducation #EducationalTechnology #MachineLearning #CulturalDiversity #RealTimeFeedback #EdTech #AI #Education #CrossCulturalCollaboration Paper 1: The Influence of Diverse Educational Contexts on Concept Map Structures Authors: Laís P. Van Vossen, Isabela Gasparini, Elaine H. T. Oliveira, Berrit Czinczel, Ute Harms, Lukas Menzel, Sebastian Gombert, Knut Neumann,…
Read More
New pub: Predicting Item Difficulty and Item Response Time with Scalar-mixed Transformer Encoder Models and Rational Network Regression Heads

New pub: Predicting Item Difficulty and Item Response Time with Scalar-mixed Transformer Encoder Models and Rational Network Regression Heads

Artificial Intelligence, Assessment, Computational Psychometrics, Conference, Higher Education, Publication, Workshop
In a contribution to the BEA 2024 Shared Task, we addressed the challenge of predicting the difficulty and response time of multiple-choice questions from the United States Medical Licensing Examination® (USMLE®). This exam is an important assessment for medical professionals. To predict these variables, we evaluated various BERT-like pre-trained transformer models. We combined these models with Scalar Mixing and two custom 2-layer classification heads, using learnable Rational Activations as the activation function. This multi-task setup allowed us to predict both item difficulty and response time. The results were noteworthy. Our models placed first out of 43 participants in predicting item difficulty and fifth out of 34 participants in predicting item response time. This demonstrates the potential of advanced AI techniques in improving the evaluation processes of critical exams like the…
Read More
New Pub: Emotional and motivational effects of automated and personalized feedback

New Pub: Emotional and motivational effects of automated and personalized feedback

Computer-supported collaborative learning, Empirical Study, Feedback, Higher Education, Journal, Learning Analytics, New Pub, Open access
With increasingly large student numbers, providing personalized teacher feedback becomes untenable. On the other hand, providing students feedback about their work is an integral part of ensuring student support throughout their learning trajectory. Fortunately, Learning Analytics now makes it feasible to automatically deploy feedback to many students at once. However, the design of effective feedback still remains an area of investigation Joshua Weidlich, Aron Fink, Ioana Jivet, Jane Yau, Tornike Giorgashvili, Hendrik Drachsler, and Andreas Frey's recently published paper in the Journal of Computer-Assisted Learning focused on one key design feature: the reference frame. Any feedback content must be formulated in reference to some performance level, be it the average of the student group (social comparison), the desired performance level (criterion-referenced comparison), or past performance. A longstanding literature on this…
Read More
JTEL workshop: Making Presentable Research

JTEL workshop: Making Presentable Research

Higher Education, Multimodal Learning Analytics, Workshop
[caption id="attachment_6515" align="aligncenter" width="640"] Photo of Nina and Stefan presenting in the worskhop[/caption] On May 14th, a workshop titled "Making Presentable Research" was held at the JTEL Summer School 2024, led by Stefan Hummel, Nina Mouhammad, Daniele Di Mitri, and Jan Schneider. The session was designed to equip PhD candidates with the skills necessary to effectively communicate their research. The ability to present research clearly and persuasively is a vital skill for PhD candidates. This workshop provided a platform to learn and practice these skills, using innovative software tools designed for message composition and nonverbal communication training. The workshop was organized into several segments, each focusing on different aspects of research presentation: An introduction to the topic and project. A guide to downloading and accessing the necessary software. A session…
Read More