A Warm Welcome to Our Guest Researcher Paola Pavone Salafia

A Warm Welcome to Our Guest Researcher Paola Pavone Salafia

Artificial Intelligence, Team
We are pleased to announce that Paola Pavone Salafia, a doctoral researcher from the University of Macerata (UniMC) and the European University of Rome (UER), will be joining us as a guest researcher from 10.03 – 10.06.205. Paola's work focuses on the use of advanced technologies, particularly Artificial Intelligence (AI), in education to foster inclusive and innovative teaching practices. Her research aligns closely with our ongoing studies on learning disabilities, educational accessibility and teacher agency, particularly in the context of AI-supported teaching methodologies. Paola's research aims to explore how AI can enhance personalized learning for students with special educational needs, as well as investigate the role of AI as a “dual teacher”, which works alongside educators to enrich teaching experiences. Paola will join the HyTea project led by Daniele Di Mitri…
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New Pub: Memorizing Plans With an App

New Pub: Memorizing Plans With an App

Journal, Learning Analytics, Publication, School, Self-Regulation
Mobile phones and devices are an integral part of the daily lives of students, and educators are increasingly trying to take advantage of this day-to-day usage for educational purposes. But how can mobile technologies, like app-based learning activities, be designed to effectively help students in the learning process? [caption id="attachment_7331" align="alignright" width="500"] Screenshots of the reading (A), puzzle (B), and emoji (C) activity[/caption] A newly published study from Daniel Biedermann, Jasmin Breitwieser, Lea Nobbe, Hendrik Drachsler and Garvin Brod tries to answer this question. Using the PROMT app, the team compared three types of learning activities used by children aged 9 to 14 years to memorize one learning plan per day over the course of 27 days. The activities varied in their planned level of cognitive engagement based on the…
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New Pub: The Student Feedback Literacy Instrument (SFLI)

New Pub: The Student Feedback Literacy Instrument (SFLI)

Feedback, Further Education, Journal, New Pub
In the context of higher education, feedback plays an especially important role in the learning process. For students it is not only important to receive feedback, but also to be able to understand and process this feedback in a manner which helps them make learning progress. The knowledge, skills and attitudes students need to navigate the feedback process successfully are referred to as feedback literacy. A recently published study presents a refined version of the Student Feedback Literacy Instrument (SFLI), which offers a powerful tool to measure feedback literacy construct across multiple languages and cultures. The SFLI aims to measure feedback literacy across two key dimensions: feedback attitudes and feedback practices. The full-length version of the instrument was recently refined and tested, alongside a short-form version (SFLI-S), in a multilingual…
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Legal Assessment of AI and Learning Analytics in Teaching and Learning

Legal Assessment of AI and Learning Analytics in Teaching and Learning

Artificial Intelligence, Learning Analytics, Press, Report
As with any new technology, the laws and regulations relating to them seem to always be one step behind and one can feel somewhat lost in a foggy, legal grey zone. The same is true for the use of AI. Using AI in a legally compliant way depends on its specific application, its range and the technical details. This has to be checked and regulated in accordance with the law in order to be able to use each AI technology safely, for the intended purpose and in compliance with data protection regulations. But how can universities know if they are using Learning Analytics and AI technologies in a legally compliant manner? In a first step in answering this question, the Goethe University has recently published an extensive legal assessment about…
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PhD Defense: Achieving Gender Equity in STEM Education With CSCL

PhD Defense: Achieving Gender Equity in STEM Education With CSCL

Computer-supported collaborative learning, Gender, PhD defense
Our treasured colleague, Dana Kube, successfully defended her PhD thesis on November 29th at the Open University in Heerlen, Netherlands. We warmly congratulate Dr. Kube for her great academic achievements and advancements in the field of CSCL and gender research! In her dissertation titled “Gender & CSCL – Exploring the Relation of Computer-Supported Collaborative Learning (CSCL) and Gender Bias in Research and Practice”, Dana emphasizes that gender equity is not just a goal, but a necessity for sustainable development and illustrates the role of gender in research and practice. It remains a challenge to understand which aspects of gender are most important in research, and how to interpret findings in the context of pervasive gender stereotypes and biases. This issue is especially pressing in the field of STEM, where gender…
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PhD Defense: A Bridge between Learning Analytics and Learning Design

PhD Defense: A Bridge between Learning Analytics and Learning Design

Book, Event, Higher Education, Learning Analytics, Learning Design, Multimodal Learning Analytics, PhD defense, Publication, School
We warmly congratulate our esteemed associate partner, DR. Marcel Schmitz, on successfully defending his PhD thesis on November 29, 2024. Marcel is a senior lecturer and researcher in Data Intelligence and the Applied Data Science & Artificial Intelligence program at Zuyd University of Applied Sciences. In his dissertation, titled “Towards Learning Analytics-Supported Learning Design”, he focused on how education can be better personalized by incorporating learning analytics already in the design and course planning. His dissertation was supervised by Prof. Dr. Hendrik Drachsler (DIPF | Leibniz Institute & Goethe University Frankfurt), with co-supervisors Prof. Dr. Maren Scheffel (Ruhr University Bochum) and Dr. Roger Bemelmans (Zuyd University of Applied Sciences). Marcel's dissertation provides actionable strategies not only for higher education but also for other educational sectors. His work envisions a future…
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New Pub: Impact of Artificial Intelligence Based Systems to Improve Mathematics Achievement in Rural Schools

New Pub: Impact of Artificial Intelligence Based Systems to Improve Mathematics Achievement in Rural Schools

Artificial Intelligence, Journal, New Pub, School
Poor mathematics achievement, especially in rural areas, remains a persistent challenge. Schools in rural areas often struggle to attract and retain highly qualified mathematics teachers, and the teacher shortage across the United States further amplifies this issue. Numerous studies indicate that AI-based systems can enhance mathematics achievement and improve test scores on both standardized and non-standardized tests in K-12 and higher education. These systems offer adaptive and personalized education tailored to the unique needs of each student. By creating learning pathways based on students' current knowledge and offering real-time feedback and support, AI-based systems have the potential to improve learning outcomes across the P-20 educational spectrum. Despite the increasing adoption of AI-based tools, there is limited research on its impact on K-12 classrooms within rural contexts, especially among socioeconomically disadvantaged…
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New Pub: Understanding Learning Engagement in Asynchronous Online Settings

New Pub: Understanding Learning Engagement in Asynchronous Online Settings

Higher Education, Journal, Learning Analytics, Publication
A newly published study illustrates the complexities of learning engagement (LE) in asynchronous online settings (AOSs) for university students. For university students it can be difficult to learn in such environments since these lack real-time interactions. This also makes it difficult for teachers to measure how engaged students actually are with their study materials. Through trace data, learning analytics can be used as a foundation to analyze students’ learning methods and LE. The study investigates whether LE can be characterized by the sub-dimensions: effort, attention and content interest. The study also explores the question of which trace data from student behavior within AOSs can best represent these factors of LE in self-reports. The research involved 764 university students and utilized best-subset regression analysis to determine which indicators most reliably represent…
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PhD Defense on Software Infrastructure for Contextualized Learning Analytics in Online Education

PhD Defense on Software Infrastructure for Contextualized Learning Analytics in Online Education

Learning Analytics, PhD defense
We warmly congratulate our esteemed alumni George-Petru Ciordas-Hertel on the successful defense of his PhD thesis this past Tuesday, 05.11.2024!  Way to go, Dr. George! We are proud of you for achieving this milestone! At universities we have seen a big shift to online education in the past ten years, as universities have continuously integrated technology into educational environments. This development has brought students and educators new possibilities, but also challenges. A promising method is Learning Analytics (LA), which uses data to gain insights into learning behaviors and enhance educational outcomes. In his dissertation, George highlights a critical limitation in traditional learning analytics: they often overlook significant aspects of learners’ digital and physical environments. His research proposes that integrating contextual information from these environments could make LA even more effective.…
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Guest Talk at Monash University

Guest Talk at Monash University

Feedback, Invited talk
During his recent research visit to Australia, Daniele Di Mitri had the privilege of presenting at Monash University, specifically at the Centre for Learning Analytics Monash (COLAM). His talk, titled “The Quest for Automated Feedback,” explored the evolving role of AI in education, particularly in providing meaningful feedback to students. As generative AI tools like ChatGPT become increasingly popular among students seeking feedback on their essays, a critical question arises: How effective is this feedback? Daniele's research delves into the complexities of generating automated feedback, emphasising that it is not a one-size-fits-all solution. Feedback is inherently context-dependent, influenced by various factors, including the learner’s needs, the task at hand, and the feedback modality. The literature on feedback is vast and nuanced. Daniele referenced several foundational models, including Hattie & Timperley (2007) and…
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