The exponential growth of scholarly publications in recent years has presented a daunting challenge for researchers to keep track of relevant articles within their research field. To address this issue, we examined the capabilities of InfraNodus, an AI-Powered text network analysis platform. InfraNodus promises to provide insights into any…

This article intends to investigate the consistency between a few popular generative AI robots in the evaluation of massive open online course (MOOC) platforms. The four robots experimented with in the study were Claude+, GPT-4, Sage, and Dragonfly, which were tasked with awarding rating scores to the eight major dimensions, namely (1)…

The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…

An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…

Recommender systems in educational contexts have proven effective to identify learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In current recommendation techniques, and in particular, in…

How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

Research on automated affect detection in educational software using play log data has shown promising results. Yet most studies use classroom-based software designed for adolescents or adults. In this paper, we aim to detect affection in an online educational platform primarily aimed at home use by young children. This presents two challenges: we…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

Promoting creativity is considered an important goal of education, but creativity is notoriously hard to define and measure. In this paper, we make the journey from defining a formal creativity and applying the measure in a practical domain. The measure relies on core theoretical concepts in creativity theory, namely fluency, flexibility, and…

This paper deals with a problem of digital competence acquisition and certification. In order to overcome the problem of still inadequate number of digitally competent students and the tools that merely focus on skills acquisition, this paper proposes the CRISS platform which is a unique cloud-based digital learning solution, based on the most…

In laboratory courses, the assessment of exercises and assignments typically is treated as a simple, quantifiable approach. This approach however rarely includes qualitative factors, especially if the grading is being automatically performed by the system, and provides little to no feedback for the students to reflect on their work. The role of…

Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…