New Pub: How Can Learning Analytics Dashboards Help Improve Students’ Self-Regulated Learning?

New Pub: How Can Learning Analytics Dashboards Help Improve Students’ Self-Regulated Learning?

Conference, Empirical Study, Learning Analytics, Publication, School, Self-Regulation
Learning Analytics Dashboards (LADs) are important and widely-used tools used to give feedback to students and to aid them in their self-regulating learning process. Much has been done to investigate the design of LADs, but there is still a lack of knowledge regarding how students interpret the information shown on LADs and how they actually use these tools while learning. In a newly published study, we try to fill this gap. In an experimental study, we compared two groups of students. One group was given personalized self-regulared learning (SRL) feedback on their interactions and learning advances. The control group was only given minimal feedback calculated from the average class scores. After reviewing their feedback, students submitted written reflections on how they would adjust their study behavior. The researchers then analyzed…
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New Pub: Conceptual Map Assessment Through Structure Classification

New Pub: Conceptual Map Assessment Through Structure Classification

Assessment, Conference, Feedback, Publication, School
In educational settings concept maps are often chosen as a tool to help knowledge constructions be visualized. While mapping out concepts and their relationships, students are able to show how well (or not well) they understand certain subjects. A newly published study, which was presented at the AIED 2024 in Recife, Brazil, takes their usage a step further, examining the structural patterns in concept maps and developing an automated system to classify them. The researchers categorized 511 different concept maps into three key structures: spoke, network and chain. Each structure type can provide its own insight about the deepness of students’ understanding. For example, a "spoke" structure may indicate a surface-level understanding, while a "network" might reflect a more complex comprehension. The researchers trained multiclass classification models using statistical data…
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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…
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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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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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The final Consortial Meeting of the MILKI-PSY Project was held in Cologne

The final Consortial Meeting of the MILKI-PSY Project was held in Cologne

Event, New Pub, Project meeting
At the end of May, all project partners of the Multimodal Immersive Learning with Artificial Intelligence for Psychomotor Skills (MILKI-PSY) project convened for the concluding session at the Cologne Game Lab and the German Sport University in Cologne. The project's aim was to develop artificial intelligence-supported, data-driven, multimodal, immersive learning environments for the autonomous acquisition of psychomotor skills. The research outcomes and their corresponding learning tools underwent evaluation. These included a virtual learning environment developed to facilitate the training process, innovative feedback methods to learn and refine movements, and the creation of Augmented Reality and Virtual Reality applications for sports such as golf, dancing, and running. Furthermore, virtual learning scenarios were devised for collaborative tasks with a robot in assembly work. It was demonstrated that innovative, immersive learning environments could…
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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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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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