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…
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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…
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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,…
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Successful PhD Defense: Understanding Self-Regulated Learning in Blended Learning Environments

Successful PhD Defense: Understanding Self-Regulated Learning in Blended Learning Environments

Learning Analytics, PhD defense, School, Self-Regulation
On the 28th of June Hendrik Drachsler had the honor of being a jury member for the PhD defense of Esteban Villalobos at the University of Toulouse. Esteban successfully defended his thesis titled “Developing a Learning Analytics framework to understand the temporal behavior of students in Blended Learning Environments“. Especially in Blended Learning (BL) settings, Self-Regulated Learning (SRL) is crucial for student success. These environments require students to manage their learning not only in online, but also in traditional in-person activities. Esteban’s thesis advances our understanding of SRL in BL contexts through a comprehensive approach, using Learning Analytics (LA) techniques as well as the latest Sequence Analysis (SA) advancements to examine students’ behaviors via trace data and self-reported measures. One of the main goals of his thesis is the manifestation…
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New pub: Potentials and Challenges of Generative AI in Instruction and Research on Instruction

New pub: Potentials and Challenges of Generative AI in Instruction and Research on Instruction

Artificial Intelligence, Feedback, General education, Journal, New Pub, School
Artificial Intelligence (AI) is becoming such a part of our daily lives that soon it will be almost impossible to imagine life without it. Especially since the emergence of ChatGPT and other Large Language Models, endless new possibilities have arisen for the usage of AI in many areas, especially in educational settings. Currently, the effective use of AI in education, both in teaching and learning, remains largely undefined, as do its limitations. We are also missing clarity regarding the potential benefits of AI for instructional research and the ethical boundaries of its use in this field. The opportunities and challenges associated with integrating AI into educational practices and research are explored in a newly published article from Hendrik Drachsler, Knut Neumann and Jochen Kuhn. In their paper they identify specific…
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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…
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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…
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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…
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FoLA supports Simulation-based Training for High-risk Clinical Situations

FoLA supports Simulation-based Training for High-risk Clinical Situations

Assessment, Empirical Study, Feedback, Further Education, Higher Education, Learning Analytics, Learning Design, medical education, Multimodal Learning Analytics, Workshop
From May 16th to 17th, 2024, Hendrik Drachsler and Marcel Schmitz (TETRA AI, ZUYD University of Applied Science) had the pleasure of providing a FoLA workshop at the College of Anaesthesiologists of Ireland (CAI) in Dublin, Ireland, under the support of the Insight research centre. Together with members from CAI and from the ASSERT Centre, College of Medicine and Health, University College Cork (UCC), they used the FoLA tool to plan a simulation-based training for high-risk clinical situations using highly informative feedback. Data from these trainings will be collected and analyzed to determine how effective this training is in improving the performance of the attendees. The study is being planned to take place with around 100 doctors in training at two simulation training centers: at ASSERT Centre UCC and at…
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How to Implement and Scale Learning Analytics Infrastructures in the Cloud @ #JTELSS24

How to Implement and Scale Learning Analytics Infrastructures in the Cloud @ #JTELSS24

Critical Online Reasoning, Higher Education, Learning Analytics, Summer School, Workshop
At the 18th EATEL Summer School on Technology-Enhanced Learning (JTELSS 2024) in Gabicce Mare, Pesaro, Italy, Gianluca Romano and Sebastian Gombert conducted the workshop "From Learner Behavior to Big Data: How to Implement and Scale Learning Analytics Infrastructures in the Cloud”. In the ever-evolving world of cloud computing, Azure stands out as a robust platform offering a myriad of services and tools to help businesses innovate and scale. Recently, we had the chance to delve deep into Azure's ecosystem, exploring its billing structures, infrastructure capabilities, and budgeting models. Here's a glimpse into what we learned and how you can leverage Azure for tracking user behavior and managing costs effectively. One of the foundational aspects of working with Azure is understanding its billing structure, which is organized into tenants, subscriptions, and…
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