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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…
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HILA goes to school – Keynote at ISDT24, Linnaeus University, Sweden

HILA goes to school – Keynote at ISDT24, Linnaeus University, Sweden

Artificial Intelligence, Conference, Feedback, Keynote, Learning Analytics, School
What happens when Highly-Informative Learning Analytics (HILA) goes to school? That’s exactly what Hendrik Drachsler explored during his keynote at the 3rd International Symposium on Digital Transformation (ISDT24) in Linnaeus University Växjö, Sweden. His talk highlighted the impact of the AFLEK project, a transformative initiative under the HILA research program, which focuses on improving learning outcomes in secondary schools through actionable data and AI-driven tools. The keynote wasn't just about theoretical advances; it presented real-world applications that are actively shaping how secondary education functions today. Through three key publications, Drachsler demonstrated how the integration of Data-Enriched Learning Activities (DeLA), teacher dashboards, and empirical research has paved the way for improved teaching practices and measurable student success. Let’s dive into what happens when HILA meets the classroom. Key Highlights from Hendrik…
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A Warm Welcome: Our Guest Researcher Víctor Alonso-Prieto Begins His Visit

A Warm Welcome: Our Guest Researcher Víctor Alonso-Prieto Begins His Visit

Team
We are very excited to welcome Víctor Alonso-Prieto, who has just joined the EduTec team as a visiting researcher from the University of Valladolid, Spain. His three-month research visit from 10.09 till 15.12.2024 promises to inspire new collaborations and bring fresh insights into the field of educational technologies. His research stay at DIPF will be supervised by Dr. Daniele Di Mitri and he will work together with members of the HyTea project as well as other researchers from the EduTec and EduCS team. We look forward to this time of research and exchange! Here is a short introduction of our visitor Víctor: Current PhD project Víctor is currently pursuing a PhD in Transdisciplinary Research in Education. Víctor’s PhD project, which is co-supervised by Dr. Sara Lorena Villagrá-Sobrino and Dr. Yannis…
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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: A Human-centric Approach to Explain Evolving Data

New pub: A Human-centric Approach to Explain Evolving Data

Conference
A recent study led by Gabriella Casalino at the University "Aldo Moro" of Bari, Italy in collaboration with Daniele Di Mitri highlights the importance of transparency and explainability in Machine Learning models used in educational environments. As we embrace this technological shift driven by AI in education, it is imperative to address the ethical considerations surrounding AI applications in educational settings. A recent study has underscored the critical importance of transparency and explainability in machine learning models utilized in educational environments. At the forefront of this study is the introduction of DISSFCM, a dynamic incremental classification algorithm that harnesses the power of fuzzy logic to analyze and interpret students' interactions within learning platforms; by offering human-centric explanations, the research endeavours to deepen stakeholders' understanding of how AI models arrive at…
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