Learner Modelled Environments

Learner modelled environments (LMEs) are digital environments that are capable of automatically detecting learner’s behaviours in relation to a specific knowledge domain, to reason about those behaviours in order to asses learner’s performance, skills, socio-emotional and cognitive needs, and to act accordingly in a pedagogically appropriate manner. Digital environments that possess such capabilities are typically referred to as Intelligent Learning Environments, or more traditionally – as Intelligent Tutoring Systems (ITSs)

'I live in extremes': A qualitative investigation of Autistic adults' experiences of inertial rest and motion

'Autistic inertia' is a term used by Autistic people to refer to difficulties with starting and stopping tasks. However, there has not been much research on Autistic inertia. The research that is available on Autistic inertia has mostly focused on the negative aspects of inertia, rather than on the possible benefits of needing to continue tasks. In this research, we wanted to understand more about Autistic people's experiences of inertia and to work out what things might influence these experiences. Autistic and non-Autistic researchers spoke in-depth to 24 Autistic adults. We identified four key ideas from people's responses. Autistic people spoke about their inertial 'difficulties moving from one state to another' and described how these challenges affected them 'every single day'. While they experienced inertia as 'the single most disabling part of being Autistic', people also described the positive aspects of inertia, including the joy they felt when completely immersed in a task. Our Autistic participants emphasised that inertial difficulties are experienced by everyone, the intensity of these task-switching difficulties might be especially challenging for Autistic people. Our findings also reveal how Autistic inertia can be seen both as a disabling and as an enabling condition

Redesigning learning games for different learning contexts: Applying a serious game design framework to redesign Stop & Think

The Activity Theory-based Model of Serious Games (ATMSG) provides a visual framework through which designers and researchers can explicitly map the gaming, learning, and instructional design of their learning game mechanics and game flow. Here, we use the ATMSG to redesign an existing learning game, Stop & Think (S&T), which was created to train children to apply their inhibitory control skills when solving counterintuitive mathematics and science problems. S&T was previously found to be effective at increasing science and mathematics achievement when the activity was led by a teacher in the classroom. However, we sought to modify its design for use by children in an independent learning scenario (e.g., homeschooling). This work contributes to the literature by demonstrating how the ATMSG was used iteratively during the redesign of S&T for use in a child-led context. We found the ATMSG useful for (i) identifying design gaps created by removing the teacher from the gaming activity, thereby outlining areas of the game requiring modification, (ii) ideation to facilitate discussion about how different design ideas would impact the structure of the game and the feasibility of the approach, (iii) negotiating design decisions between team members, communicating proposed changes in the design amongst stakeholders, seeking approval from project leaders, and serving as a design document for developers, and (iv) cataloguing changes made to the game throughout the redesign process, thereby archiving versions of the game which can be used to reflect upon how each version might impact counterintuitive reasoning. Yet, we also found some challenges in using the ATMSG, including its lack of ability to represent non-structural design decisions (e.g., visual strategies, adaptivity), its impractical format for representing more complex games, and its time-consuming nature

How Do Executive Functions Influence Children’s Reasoning About Counterintuitive Concepts in Mathematics and Science?

Many scientific and mathematical concepts are counterintuitive because they conflict with misleading perceptual cues or incorrect naive theories that we build from our everyday experiences of the world. Executive functions (EFs) influence mathematics and science achievement, and inhibitory control (IC), in particular, might facilitate counterintuitive reasoning. Stop & Think (S&T) is a computerised learning activity that trains IC skills. It has been found effective in improving primary children’s mathematics and science academic performance in a large scale RCT trial (Palak et al., 2019; Wilkinson et al., Journal of Cognitive Enhancement, 4, 296–314, 2020). The current study aimed to investigate the role of EFs and the moderating effects of S&T training on counterintuitive mathematics and science reasoning. A sample of 372 children in school Years 3 (7- to 8-year-olds) and 5 (9- to 10-year-olds) were allocated to S&T, active control or teaching as usual conditions, and completed tasks assessing verbal and visuospatial working memory (WM), IC, IQ, and counterintuitive reasoning, before and after training. Cross-sectional associations between counterintuitive reasoning and EF were found in Year 5 children, with evidence of a specific role of verbal WM. The intervention benefited counterintuitive reasoning in Year 3 children only and EF measures were not found to predict which children would most benefit from the intervention. Combined with previous research, these results suggest that individual differences in EF play a lesser role in counterintuitive reasoning in younger children, while older children show a greater association between EFs and counterintuitive reasoning and are able to apply the strategies developed during the S&T training to mathematics and science subjects. This work contributes to understanding why specifically the S&T intervention is effective. This work was preregistered with the ISRCTN registry (TRN: 54726482) on 10/10/2017

Blending human and artificial intelligence to support autistic children’s social communication skills

This paper examines the educational efficacy of a learning environment in which children diagnosed with Autism Spectrum Conditions (ASC) engage in social interactions with an artificially intelligent (AI) virtual agent and where a human practitioner acts in support of the interactions. A multi-site intervention study in schools across the UK was conducted with 29 children with ASC and learning difficulties, aged 4-14 years old. For reasons related to data completeness and amount of exposure to the AI environment, data for 15 children was included in the analysis. The analysis revealed a significant increase in the proportion of social responses made by ASC children to human practitioners. The number of initiations made to human practitioners and to the virtual agent by the ASC children also increased numerically over the course of the sessions. However, due to large individual differences within the ASC group, this did not reach significance. Although no evidence of transfer to the real-world post-test was shown, anecdotal evidence of classroom transfer was reported. The work presented in this paper offers an important contribution to the growing body of research in the context of AI technology design and use for autism intervention in real school contexts. Specifically, the work highlights key methodological challenges and opportunities in this area by leveraging interdisciplinary insights in a way that (i) bridges between educational interventions and intelligent technology design practices, (ii) considers the design of technology as well as the design of its use (context and procedures) on par with one another, and (iii) includes design contributions from different stakeholders, including children with and without ASC diagnosis, educational practitioners and researchers

Digital Stories as a method for evidence-based practice and knowledge co-creation in technology-enhanced learning for children with autism

Storytelling is a powerful means of expression especially for voices that may be difficult to hear or represent in typical ways. This paper reports and reflects on our experiences of co-creating digital stories with school practitioners in a project focusing on embedding innovative technologies for children on the autism spectrum in classroom practice. The digital stories were short films or narrated sequences of slides and images that conveyed key views about experiences and practices with or around the technologies. The creation of the digital stories aimed to empower schools and individual teachers to construct and share their own authentic narratives and to build case examples of creative technology-enhanced teaching and learning. Through focusing on our experiences with one of the schools, we examine the use of digital stories as a method for enabling knowledge co-creation with practitioners and we discuss the evidential potential of digital stories. We argue that the co-creation of digital stories enabled teachers to find their voice in critiquing the usability, usefulness, efficacy and flexibility of the technologies. Furthermore, the stories, both the process of their creation and the final artefacts, provided a concrete grounding for knowledge co-creation about teaching practices and authentic Technology Enhanced Learning

Domain-Specific Inhibitory Control Training to Improve Children’s Learning of Counterintuitive Concepts in Mathematics and Science.

Evidence from cognitive neuroscience suggests that learning counterintuitive concepts in mathematics and science requires inhibitory control (IC). This prevents interference from misleading perceptual cues and naïve theories children have built from their experiences of the world. Here, we (1) investigate associations between IC, counterintuitive reasoning, and academic achievement and (2) evaluate a classroom-based computerised intervention, called Stop & Think, designed to embed IC training within the learning domain (i.e. mathematics and science content from the school curricula). Cross-sectional analyses of data from 627 children in Years 3 and 5 (7- to 10-year-olds) demonstrated that IC, measured on a Stroop-like task, was associated with counterintuitive reasoning and mathematics and science achievement. A subsample (n = 456) participated either in Stop & Think as a whole-class activity (teacher-led, STT) or using individual computers (pupil-led, STP), or had teaching as usual (TAU). For Year 3 children (but not Year 5), Stop & Think led to better counterintuitive reasoning (i.e. near transfer) in STT (p < .001, ηp2 = .067) and STP ((p < .01, ηp < .01, ηp 2 = .041) compared to TAU. Achievement data was not available for Year 3 STP or Year 5 STT. For Year 3, STT led to better science achievement (i.e. far transfer) compared to TAU (< .05, ηp2 = .077).There was no transfer to the Stroop-like measure of IC. Overall, these findings support the idea that IC may contribute to counterintuitive reasoning and mathematics and science achievement. Further, we provide preliminary evidence of a domain-specific IC intervention with transferable benefits to academic achievement for Year 3 children