New Pub: From Nervous to Noteworthy: Evaluating SPEAKS

New Pub: From Nervous to Noteworthy: Evaluating SPEAKS

Competence development, Conference, Conference, Higher Education
Public speaking can be nerve-wracking, but it’s also a skill every professional needs. Many students leave higher education feeling unprepared to speak confidently in front of an audience. Traditional courses exist, but providing enough guidance to every student is time- and resource-intensive. This is where SPEAKS comes in. SPEAKS (Speech content Preparation for Effective and Authentic Knowledge Sharing) is an educational software designed to guide students through preparing the content of their speeches. The tool and its evaluation were presented at ECEL 2025 in a paper authored by Nina Mouhammad, Jan Schneider, Roland Klemke and Daniele Di Mitri as part of the HyTea-project, highlighting its potential to support students in developing better speech content and becoming more confident regarding public speaking. The tool uses a fully scripted, chat-based interface with…
Read More
New Pub: Harnessing the Power of Gaming to Influence Policies Addressing Climate Change

New Pub: Harnessing the Power of Gaming to Influence Policies Addressing Climate Change

Conference, Game, Publication
As part of the GREAT (Games Realising Effective and Affective Transformation) project, co-funded by the European Union and UKRI, the project team has published the following paper at ECGBL which was held at Aarhus University, in October 2024. Harnessing the Power of Gaming to Influence Policies Addressing Climate Change – co-authored by Paul Hollins, Paul Watson, Anchal Garg, Jude Ower, Joost Schuur, David Griffiths, Barbara Kieslinger, Katharina Koller, Jane Yau, pages 403-413 Abstract: In this paper, the authors present the findings of an empirical case study examining the efficacy of the Games Realising Effective & Affective Transformation (GREAT) Case Study design process. The process is underpinned by an established Mixed Methodological Research (MMR) framework for eliciting the preferences of gamers and determining their priorities in climate change policies. Funded by…
Read More
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…
Read More
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…
Read More
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…
Read More
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…
Read More
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…
Read More
Atezaz’s Conference Paper Presentation at CSEDU in Angers, France

Atezaz’s Conference Paper Presentation at CSEDU in Angers, France

Conference, Conference, Event, Learning Analytics, Learning Design, Publication
Atezaz shared insights from their paper titled "Students Want to Experiment While Teachers Care More About Assessment! Exploring How Novices and Experts Engage in Course Design" at the CSEDU 2024 conference in Angers, France, delving into its implications and findings. Additionally, this paper received a nomination in the Best Student Paper category.
Read More
New Pub: LAxplore: An NLP-Based Tool for Distilling Learning Analytics and Learning Design Instruments out of Scientific Publications

New Pub: LAxplore: An NLP-Based Tool for Distilling Learning Analytics and Learning Design Instruments out of Scientific Publications

Artificial Intelligence, Conference, Conference, Learning Analytics, Learning Design, New Pub, Open access, Publication, Technical paper
Abstract: Each year, the amount of research publications is increasing. Staying on top of the state of the art is a pressing issue. The field of Learning Analytics (LA) is no exception, with the rise of digital education systems that are used broadly these days from K12 up to Higher Education. Keeping track of the advances in LA is challenging. This is especially the case for newcomers to the field, as well as for the increasing number of LA units that consult their teachers and scholars on applying evidence-based research outcomes in their lectures. To keep an overview of the rapidly growing research findings on LA, we developed LAxplore, a tool that uses NLP to extract relevant information from the LA literature. In this article, we present the evaluation of…
Read More
Conference: Paper presentation at IC3K 2023

Conference: Paper presentation at IC3K 2023

Artificial Intelligence, Conference, Conference, General education, Higher Education, Learning Analytics, Learning Design, New Pub, Publication, Technical paper
The purpose of the IC3K is to bring together researchers, engineers and practitioners on the areas of Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K is composed of three co-located conferences (KDIR, KEOD and KMIS), each specialized in at least one of the aforementioned main knowledge areas. Our paper titled "LAxplore: An NLP-Based Tool for Distilling Learning Analytics and Learning Design Instruments out of Scientific Publications" was accepted at the 15th International Conference on Knowledge Discovery and Information Retrieval (KDIR). Atezaz Ahmad presented the paper at the conference online. ABSTRACT: Each year, the amount of research publications is increasing. Staying on top of the state of the art is a pressing issue. The field of Learning Analytics (LA) is no exception, with the rise of digital education systems that are…
Read More