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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