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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New Article – Gender diversity dynamics in a Computer Supported Collaborative Learning

New Article – Gender diversity dynamics in a Computer Supported Collaborative Learning

Artificial Intelligence, Computer-supported collaborative learning, Digitalisation, Empirical Study, Gender, Higher Education, Journal, Learning Design, New Pub, Open access, Publication, Special Issue, Team
🎉 Exciting News! Our article has just been published in the magazine of Computer Assisted Learning! 📰 We delved into the fascinating world of online group learning among adults, unravelling the mysteries of emergent team roles and their intricate connection to gender dynamics in communication. 🌐👥 Have you ever wondered how team roles subtly surface and evolve in online group learning discussions? We did, too! Our research explores the subtle nuances of team roles and their subversive emergence, especially when viewed through the lens of gender diversity, in order to understand how to support more productive learning for all participants. Gender and gender diversity are group features affecting social interaction and are critical for gender-inclusive and equitable education. As such, the role of gender and gender diversity is of particular…
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New Pub: Toward a comprehensive framework of social presence

New Pub: Toward a comprehensive framework of social presence

Computer-supported collaborative learning, Higher Education, Journal, Literature review, New Pub, Open access, Special Issue
Today, students in higher education likely come into contact with different modes of learning, e.g. online learning, blended learning, and, increasingly, hybrid learning. To the extent that communication is mediated by technology in these learning modes, students can experience varying degrees of social presence with regard to their peers. Social presence refers to the feeling that others are 'real' and 'close' despite the physical separation. Especially in learning scenarios that require communication and collaboration, social presence is a crucial consideration. Despite this, research on social presence is fragmented and many other relevant theoretical accounts, while potentially informative, have been neglected. This paper, coauthored by Karel Kreijns, Jane Yau, Joshua Weidlich, and Armin Weinberger, published in Frontiers in Education, Section Digital Education, attempts to provide a comprehensive account of social presence…
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How to improve Knowledge Tracing with hybrid machine learning techniques

How to improve Knowledge Tracing with hybrid machine learning techniques

Journal, New Pub
Knowledge Tracing is a well-known problem in AI for Education. It consists of monitoring how the student's knowledge changes during the learning process and accurately predicting their performance in future exercises. But how can we improve the current methods and overcome their limitations? In recent years, many advances have been made thanks to various machine learning and deep learning techniques. However, they have some pitfalls, such as modelling one skill at a time, ignoring the relationships between different skills, or inconsistent predictions, i.e. sudden spikes and falls across time steps. In our recently published systematic literature review, we aim to illustrate the state of the art in this field. Specifically, we want to identify the potential and the frontiers in integrating prior knowledge sources in the traditional machine learning pipeline…
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New pub: Measuring Efficacy of ALEKS as a Supportive Instructional Tool in K-12 Math Classroom with Underachieving Students

New pub: Measuring Efficacy of ALEKS as a Supportive Instructional Tool in K-12 Math Classroom with Underachieving Students

Assessment, Journal, New Pub, Publication, School
In a recent quasi-experimental research study, the effectiveness of Assessment and Learning in Knowledge Spaces (ALEKS), an Intelligent Tutoring System (ITS), took center stage in the realm of 8th-grade mathematics education. The study aimed to determine whether ALEKS could bring a statistically significant improvement in students' mathematics achievement compared to traditional teacher-led instructions. The research involved 158 8th-grade students categorized as 'underachieving students, with 60 in the teacher-led group and 98 in the ALEKS-led group. The study used a non-randomized approach to compare the outcomes of teacher-led instructions to ALEKS-led instructions over two consecutive years. In the first year McGraw's curriculum "Reveal" was used exclusively without ALEKS. In the second year ALEKS was incorporated as a supplemental tool in a math support class. The study incorporated a rigorous methodology, utilizing…
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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…
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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…
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Unveiling Gender Bias in Computer-Supported Collaborative Learning: Insights from a CS Hackathon Study

Unveiling Gender Bias in Computer-Supported Collaborative Learning: Insights from a CS Hackathon Study

Computer-supported collaborative learning, Digitalisation, Event, Gender, Higher Education, Journal, Learning Design, New Pub, Open access, Publication, Research topic
Gender stereotypes about women and men are prevalent in computer science (CS). The study's goal was to investigate the role of gender bias in computer-supported collaborative learning (CSCL), group work in a CS context, by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon. We applied an exploratory mixed-method approach using quantitative survey data, including collective self-esteem scales, at several time points during the hackathon, which was analysed with clustering and descriptive statistics and complemented with qualitative coding of interviews with participants. The Figure shows that, for both clusters, the self-esteem scores are predominantly located in the upper half of the scale, indicating a generally high (collective) self-esteem among all our participants. Nonetheless, all respective scores were lower for the women-dominated…
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