The resolution of complex open-ended problems is a core aspect of engineering practice. This study aims to explore students' approaches to using large-language models (LLM) to tackle such problems in engineering. LLMs are highly versatile tools with immense potential in education; however, their effective use to solve open-ended problems requires students to evaluate and analyse information, consider diverse perspectives, and make informed decisions. This raises important questions about students' readiness to critically and responsibly use LLMs for these tasks, as well as the role of educators in fostering critical thinking skills while integrating LLMs into engineering courses. Using a mixed inductive and deductive coding approach to analyse dialogue records with LLMs from nine students and their responses in semi-structured interviews, this study uncovers several misconceptions about LLMs that hinder their effective use. Furthermore, we propose practical strategies for designing problem-solving tasks that enhance students' understanding of LLM capabilities and guide them toward responsible, critical engagement with these tools.

This study examines the effect of instructor presence: no lecturer, physical lecturer presence, and virtual lecturer presence as an avatar, on cognitive load and learning gain in video-based learning (VBL). We conducted a study with 33 participants using eye-tracking to measure cognitive load and knowledge pre-and post-tests to measure learning gain. The video stimuli included varied content designs: text-heavy, image-centric, and mixed-content slides. TThe results indicate that avatars effectively reduce cognitive load and improve learning outcomes across various types of slide content and answer cue delivery modes, particularly in image-centric or mixed-content designs and with visual-only or verbal cues. Additionally, using an avatar is recommended for delivering certain answer cues. These findings suggest that avatars have beneficial applications in VBL settings.

Students can be described as self-regulated learners when they are meta-cognitively, motivationally, and behaviourally active participants in their own learning. Flipping the classroom requires from students good self-regulated learning skills, primarily time management and study regularity, as they must have engaged in learning activities prior to attending live classes. In this short paper, we describe our approach of using learning analytics to demonstrate the impact of study regularity on academic success in a flipped learning environment. Our key contribution is the definition of a measure of study regularity that can uncover various students’ learning profiles during flipped learning. We are showing that the regularity measure correlate strongly with academic success and that it can be used to predict students’ performance. We then discuss how such a measure can also be used to raise student’s awareness about their learning behaviour and lack of appropriate strategy, to nudge the students into modifying their learning behaviour, and to monitor class behaviour, such as detecting a worrying students’ disengagement trend.

In this work-in-progress paper, we describe the participatory design approach we adopted for the inclusive design of a student-facing learning analytics dashboard. The objective is to involve learners throughout the design process to help prevent instructors’ biases ending up in the design. The design participants developed learner personas, use scenarios and storyboards to capture the broad spectrum of students' abilities, skills, objectives, and situations. These guided the decisions made for the essential features, functions, and interactive behaviours of the dashboard and for its initial functional implementation.

This work-in-progress paper presents two Augmented Reality applications for teaching fractography. The first application has little connection with reality, whereas the second application has a strong anchoring and dependency with reality: students need to have prepared physical lab samples to trigger the display of virtual elements on their phone. Student feedback reveals a tension with the teacher’s view on how much reality is needed. Where the teacher sees the use of physical samples to assess laboratory skills, many students view Augmented Reality as a learning complement on the theoretical rather than the experimental aspects of fractography.

Our research aims at understanding if robots could be good at public speaking, what they need to achieve the level of a good public speaker and how they may surpass a human public speaker. Previous research results indicate that designing a robot speaker by mimicking some of the behaviours of a human speaker is not enough to create an effective robot speech performance. It can in fact be counter productive to strive for human-likeliness. In this paper, we describe how we programmed a toy-like, non-anthropomorphic small robot (the Anki Vector robot) to deliver a speech by extracting pose and facial expression information from the video of a human speaker and loosely retargeting this information to the robot. We also describe our experimental plans to compare Vector’s speech delivery performance with the performance of a more anthropomorphic robot (the SoftBank Pepper robot), which has been programmed to closely mimic the human speaker’s behaviour. They are compared in terms of their ability to evoke the positive affective responses necessary to spark interest, motivate the audience to listen, and engage the audience in meaningful ways.

In this Innovative Practice work in progress paper, we discuss the convergence of two engineering disciplines (computer and materials sciences) for the co-creation of technology-based learning resources, achieved through trans disciplinary student-staff partnerships. The partnerships are made of producers (computer science students and staff) and clients (materials science students and staff) working together towards the creation of Augmented Reality (AR) and Virtual Reality (VR) interactive simulations that are made by students for students. The student-staff partnership was achieved through a careful balance of roles, knowledge, and experience. We achieved an equal partnership through mixing two very disparate disciplines that share little knowledge through the curriculum. We have observed multi-level benefits through the partnership: the student-producers develop technical and professional skills that allow them to competently address scientific and societal challenges. The student-clients acquire domain expertise needed to advise and guide the producers and manage projects. This is also a unique opportunity for staff since they experience learning from students, and the process during the development and testing of ideas can enhance their teaching practice and open new avenues for curriculum development.

This work-in-progress discusses Immersive Virtual Reality and Augmented Reality for teaching invisible phenomena and virtual science experiments in Materials Science. Immersion, coupled with 3D spatial interaction, is useful when the knowledge to be acquired is procedural, to create a sense of scale and to allow easy navigation within a large experimental space. Immersion is also beneficial to transport the learners into the world of the infinitesimally small, when the phenomena occur at atomic scale. Conversely, augmentation is better for experiencing phenomena that can be triggered by interacting with real objects. Deployment, affordability and use in actual teaching are also discussed.

Social robots acting as stand-ins for speakers or teachers would enable them to reach large audiences from anywhere in the world, increasing the options for distant learning. They would need to be endowed with effective public speaking skills though, in order to deliver their message, entertain, and maintain audience attention.

This paper describes our ongoing work to develop a visual sensing platform that can inform a robot teacher about the behaviour and affective state of its student audience. We have developed a multi-student behaviour recognition system, which can detect behaviours such as "listening" to the lecturer, "raising hand", or "sleeping". We have also developed a multi-student affect recognition system which, starting from eight basic emotions detected from facial expressions, can infer higher emotional states relevant to a learning context, such as "interested", "distracted" and "confused". Both systems are being tested with the Softbank robot Pepper that can respond to various students' behaviours and emotional states with adapted movements, postures and speech.

Bilingual education programs whose aim is to support the development of balanced bilingualism belong to "strong" forms of bilingual education. Other desired outcomes of strong forms of bilingual education are cognitive advantages and better school achievement. The goal of our research is to explore how technology can help introducing strong forms of bilingual education for minority language children in mainstream classrooms. We present a first prototype (the OCOL model) that successfully recreates a bilingual learning environment. A study into the prototype shows that appropriate technology can help children achieve balanced bilingualism and biliteracy. We then discuss the aims, requirements and enabling technologies for the deployment of bilingual educational systems for children in mainstream education. Key areas for further research are identified and discussed: supporting bilingual language development, supporting curriculum acquisition in two languages, providing fair assessment tools, and improving communication and collaboration in multilingual environments

Children, who are acquiring several languages from birth or at an early age, are typically raised in extremely complex and varied multilingual and multicultural environments. In their everyday life, these children are constantly exposed to several languages, different script systems and mixed cultural customs. Currently, few educational systems have been designed to specifically address their needs. In this paper, we discuss typical approaches to bilingual parenting and suggest several advantages to recreating multilingual learning contexts in educational software. As an example, we propose the "OCOL" (one character one language) model: a simulation of the popular OPOL (one parent one language) strategy adopted by many multilingual families. A prototype is currently being developed in English and Japanese.

The aim of our research is to explore new interaction paradigms for the design of multilingual educational software. In this poster, we present some early work on the use of multimodal interaction techniques to facilitate the simultaneous acquisition of more than one language during the period of primary language development. We suggest that multimodality can be used to deal with common multilingual phenomena such as language mixing and language dominance or specialization.