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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New Pub: I don’t have time! But keep me in the loop: Co-designing requirements for a learning analytics cockpit with teachers

New Pub: I don’t have time! But keep me in the loop: Co-designing requirements for a learning analytics cockpit with teachers

Empirical Study, Learning Analytics, New Pub, Research Methods, School
Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved from digital learning environments is useful for teaching. Information elicited from formative assessment (FA), though, is a strong predictor for student performance and can be a useful data source for effective teacher dashboards. Especially in the secondary education context, FA and feedback on FA, have been extensively studied and shown to positively affect student learning outcomes. Moreover, secondary teachers struggle to make sense of the information displayed in dashboards and decide on pedagogical actions, such as providing feedback to students. Objectives: To facilitate the…
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New Pub: Students Want to Experiment While Teachers Care More About Assessment! Exploring How Novices and Experts Engage in Course Design

New Pub: Students Want to Experiment While Teachers Care More About Assessment! Exploring How Novices and Experts Engage in Course Design

Computer-supported collaborative learning, Conference, Conference, Higher Education, Learning Analytics, Learning Design, New Pub, Open access, Open science, Publication, Technical paper
Abstract: Learning Design (LD) is the strategic orchestration of educational components to create a rewarding experience for students and educators. Adapting it to real-world scenarios with evolving technologies, like learning analytics (LA), adds complexity but offers the potential for enhanced learning outcomes and engagement. Prior research highlights the growing importance of LA in informing LD decisions. The FoLA2 method offers a collaborative approach to course design considering LA implications. This study pursues two primary objectives. Firstly, to enhance the FoLA2 method by granting course designers access to the Open Learning Analytics Indicator Repository (OpenLAIR) that facilitates visual connections between LD pedagogies, LDLA activities, LA indicators and their metrics. Secondly, to explore how novice and expert groups utilize the FoLA2 methodology to design a course in Technology Enhanced Learning. The findings…
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New Pub: Feedback sources in essay writing: peer-generated or AI-generated feedback?

New Pub: Feedback sources in essay writing: peer-generated or AI-generated feedback?

Artificial Intelligence, Empirical Study, Feedback, Further Education, Journal, Publication
A newly published article discusses the use of peer feedback as a learning strategy, particularly in large classes where teachers face heavy workloads. For complex tasks like writing argumentative essays, peers may struggle to provide high-quality feedback due to the cognitive demands involved. The emergence of Artificial Intelligence (AI) tools, like ChatGPT, raises the question of whether AI can serve as a new feedback source for such tasks. To investigate this, a study compared ChatGPT-generated feedback with peer feedback on argumentative essays written by 74 graduate students from a Dutch university. The study collected essay data, peer feedback and ChatGPT-generated feedback, and then analyzed them using coding schemes. Results showed significant differences between ChatGPT and peer feedback, with ChatGPT offering more descriptive feedback while peers focused on identifying essay problems.…
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New Publication: Addressing gender in STEM classrooms: The impact of gender bias on women scientists’ experiences in higher education careers in Germany

New Publication: Addressing gender in STEM classrooms: The impact of gender bias on women scientists’ experiences in higher education careers in Germany

New Pub
 In an expert study conducted in Germany, Dana Kube and her research team delve into the complex dynamics of gender bias within STEM (Science, Technology, Engineering, and Mathematics) classrooms. The study, aimed at understanding the role gender plays in shaping the experiences of women scientists in higher education, sheds light on the challenges they face and proposes strategies for fostering gender inclusivity in STEM classrooms. The primary objective of the study was two-fold: first, to comprehensively examine the influence of gender and gender bias in STEM environments within higher education institutions, and second, to identify potential areas where Computer-Supported Collaborative Learning (CSCL) pedagogical interventions could mitigate these biases among students and teachers in German STEM departments. Employing the innovative group concept mapping method, the research team collaborated with women participants…
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Team led by Sebastian Gombert wins one of two tracks at BEA 2024 shared task on predicting Item Difficulty and Item Response Time

Team led by Sebastian Gombert wins one of two tracks at BEA 2024 shared task on predicting Item Difficulty and Item Response Time

Artificial Intelligence, Assessment, Award, Computational Psychometrics, Conference, Higher Education, New Pub, Workshop
For standardized exams to be fair and reliable, they must include a diverse range of question difficulties to accurately assess test taker abilities. Additionally, it's crucial to balance the time allotted per question to avoid making the test unnecessarily rushed or sluggish. The goal of this year's BEA shared task (competition) was to build systems which could predict Item Difficulty and Item Response Time for items taken from the United States Medical Licensing Examination (USMLE). EduTec member Sebastian Gombert designed systems which are able to predict both variables simultaneously. These placed first out of 43 for predicting Item Difficulty and fitfth out of 34 for predicting Item Response Time. They use modified versions of established transformer language models in a multitask setup. A corresponding system description paper titled Predicting Item…
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New Pub: AI program doesn’t make kids better at math, but it makes them more independent

New Pub: AI program doesn’t make kids better at math, but it makes them more independent

Assessment, Journal, Publication, School
Students who receive math tutoring from an artificial intelligence (AI) program perform no better than students who are taught by a "real" teacher. These students do, however, need less help learning. This is the conclusion of Rashmi Khazanchi from the Open University of the Netherlands together with Hendrik Drachsler and Daniele Di Mitri. Math Lessons with AI The researchers examined the effectiveness of the Assessment and Learning in Knowledge Spaces (ALEKS) tutoring program, called Intelligent Tutoring Systems (ITS). Previous studies have shown that students learn math better using software than traditional teaching methods. Previous studies on ALEKS have also shown that, thanks to this program, students memorize more knowledge, perform better, experience more engagement in mathematics and drop out less. The advantage of an ITS like ALEKS is that it…
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Personalizing running training with immersive technologies using a multimodal framework

Personalizing running training with immersive technologies using a multimodal framework

Journal, New Pub
To improve performance and prevent injuries, running training needs proper personalized supervision and planning. This study examines the factors that influence running training programs, and the benefits and challenges of personalized plans. It also investigates how multimodal, immersive and artificial intelligence (AI) technologies can improve personalized training. We did an exploratory sequential mixed research with running coaches. We analyzed the data and found relevant factors of the training process. We recognized four key aspects for running training: physical, technical, mental and body awareness. We used these aspects to create a framework that proposes multimodal, immersive and AI technologies to help personalized running training. It also lets coaches guide their athletes on each aspect personally. The framework aims to personalize the training by showing how coaches and multimodal learning experience agents…
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New Pub: From the Automated Assessment of Student Essay Content to Highly Informative Feedback: a Case Study

New Pub: From the Automated Assessment of Student Essay Content to Highly Informative Feedback: a Case Study

Artificial Intelligence, Assessment, Computational Psychometrics, Empirical Study, Feedback, Higher Education, Journal, Publication, Special Issue, Technical paper
How can we give students highly informative feedback on their essays using natural language processing? In our new paper, led by Sebastian Gombert, we present a case study on using GBERT and T5 models to generate feedback for educational psychology students. In this paper: ➡ We implemented a two-step pipeline that segments the essays and predicts codes from the segments. The codes are used to generate feedback texts informing the students about the correctness of their solutions and the content areas they need to improve. ➡ We used 689 manually labelled essays as training data for our models. We compared GBERT, T5, and bag-of-words baselines for both steps. The results showed that the transformer-based models outperformed the baselines in both steps. ➡ We evaluated the feedback with a learner cohort…
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