Analysing collaborative problem-solving from students' physical interactions

Collaborative problem-solving (CPS) is a fundamental skill for success in modern societies, and part of the most common constructivist teaching approaches. However, its effective implementation and evaluation are challenging for educators. Current inquiries on the identification of the observable features and processes of CPS are progressing at a pace in digital learning environments. However, still, most learning and teaching occurs in physical environments. In my current research, I investigate differences in student behaviours when groups of students are solving problems collaboratively in face-to-face, practice-based learning (PBL) environments in high school and universities. My data is often based on students’ hand position and head direction, which can be automated deploying existing learning analytics systems. Using nonverbal indexes of students’ physical interactivity in PBL, I try to interpret the key parameters of CPS including synchrony, equality, individual accountability, and intra-individual variability. The ultimate aim of my research is to be able to continuously evaluate and support students’ collaborative learning during their engagement with constructivist pedagogies

Learning Sciences Beyond Cognition: Exploring Student Interactions in Collaborative Problem Solving

Composed of insightful essays from top figures in their respective fields, the book also shows how a thorough understanding of this critical discipline all but ensures better decision making when it comes to education

Integrating Physiological Indicators with a Competency Model for Enhanced Collaborative Problem Solving in Small Groups

Improving the collaboration process has long been a subject of inquiry. Yet, evaluating collaboration quality is a significant challenge for researchers and practitioners. Recently, the generalized competency model of collaborative problem solving (CPS) has been suggested, encompassing facets, sub-facets, and indicators (verbal and nonverbal) that directly align with CPS skills. Here we discuss the integration of physiological data to potentially further improve the detection of cognitive and affective aspects of CPS. This paper aims to bridge the gap between physiological data features or characteristics and collaboration quality. More specifically, we present our attempts to integrate physiological data with verbal and nonverbal indicators of a generalized competence model of CPS in small groups comprising four individuals. Moreover, this integration can be further developed into interventions such as reflective exercises or real-time feedback provided by AI agents, with the goal of enhancing collaborative skills

What the research says about the use of different technologies to enhance learning

Educational technology is growing fast, with schools, colleges and universities more than ever looking for the best ways to use technology to support learning. At the same time, there is an increasing appetite for learning and teaching practices to be backed up by evidence. Few resources are able to offer guidance that has been vigorously tested by research. Now, 'Enhancing Learning and Teaching with Technology' brings together researchers, technologists and educators to explore and show how technology can be designed and used for learning and teaching to best effect. It addresses what the research says about: - how and why learning happens and how different technologies can enhance it - engaging a variety of learners through technology and helping them benefit from it - how technology can support teaching. This book is an accessible introduction to learning and teaching with technology for teachers and other educational professionals, regardless of their experience with using technology for education

The significance of context for the emergence and implementation of research evidence: the case of collaborative problem-solving

One of the fundamental purposes of educational research is to provide evidence to facilitate effective practice. However, the evidence itself does not have much value for practitioners unless key information about the context from which the evidence was generated is also provided. In this paper, we use the word ‘context’ to refer to factors that are relevant for learning, including the interactions that learners experience with multiple people, artefacts, and environments. Unfortunately, in many educational research studies, either these factors do not get the required attention or information about them is presented in an incoherent structure. The resultant lack of information leads to two significant drawbacks. First, it creates confusion among practitioners who want to apply research evidence in their practice. Second, it leads to research studies that on the face of it are similar, but that in reality have resulted from evidence that has been collected in significantly different contexts being included under the same categories in reviews, meta-reviews, and best-evidence syntheses. In this paper, we draw on the concept of ‘relatability’ of evidence and present taxonomy for collaborative problem-solving (CPS) that can be used to provide the valuable information against which research evidence can be indexed. By addressing the need for more detailed information about the contextual factors from which the evidence is generated to bridge the gap between research and practice in CPS research, we aim to exemplify the approach that is needed in educational research more generally

Different modality, different design, different results: Exploring self-regulated learner clusters' engagement behaviours at individual, group and cohort activities

Self-Regulated Learning (SRL) competence is an important aspect of online learning. SRL is an internal process, but analytics can offer an externalisation trigger to allow for observable effects on learner behaviours. The purpose of this paper is to explore the relationship between students' SRL competence and their learning engagement behaviours observed in multimodal data. In a postgraduate course with 42 students, eighteen features from three types of data in seven learning activities were extracted to investigate multi-level SRL competence students' engagement behaviours. The results revealed that students with different SRL competence clusters might exhibit different behaviours in individual, group, and cohort level learning activities. Also, students with similar SRL competence might exhibit significantly different engagement behaviours in different learning activities, depending on the learning design. Therefore, while using engagement data in AIED systems; the modality of the data, specific analysis techniques used to process it, and the contextual particularities of the learning design should all be explicitly presented. So that, they can be considered in the interpretations of automated decisions about student achievement

Good Practical Science: Appendix 1 - Rapid Evidence Review

There is a clear need for more high-quality studies of practical work that have a tightly-defined focus and a rigorous methodological approach. We are confident that this finding would persist in a more extended review than a Rapid Evidence Assessment (REA), which is necessarily limited in scope. We would not recommend conducting a more in-depth, more traditional systematic review at this stage. There is a wealth of commentary on the purpose and usefulness of practical science, but very few robust studies. A more extensive search encompassing the grey literature would undoubtedly identify more studies, but they are unlikely to add significantly to the current knowledge base. This REA has highlighted the need for more evaluations of practical science in its various guises. There is a requirement for research that is clear in its aims, focus and definitions; has a sound methodology with adequate sample sizes and appropriate outcome measures; and is designed to shed light on the usefulness of practical science work across different contexts and for different purposes. Drawing from the literature, the report identifies five main purposes of practical science.These are to enhance student performance in conceptual understanding; practical skills; non-subject specific intellectual and personal attributes; attitudes towards science; and understanding of how science and scientists work. There is currently a much greater evidence base around practical work improving physical skills and dexterity compared with the other four purposes of practical work defined in this report

Confirmation bias and trust: Human factors that influence teachers' attitudes towards AI-based educational technology

Evidence from various domains underlines the key role that human factors, and especially, trust, play in the adoption of AI-based technology by professionals. As AI-based educational technology is increasingly entering K-12 education, it is expected that issues of trust would influence the acceptance of such technology by educators as well, but little is known about this matter. In this work, we bring the opinions and attitudes of science teachers that interacted with several types of AI-based technology for K-12. Among other things, our findings indicate that teachers are reluctant to accept AI-based recommendations when it contradicts their previous knowledge about their students, and that they expect AI to be absolutely correct even in situations that absolute truth may not exist (e.g., grading open-ended questions). The purpose of this paper is to provide initial findings and start mapping the terrain of this aspect of teacher-AI interaction, which is critical for the wide and effective deployment of AIED technologies in K-12 education

Dyadic joint visual attention interaction in face-to-face collaborative problem-solving at K-12 Maths Education: A Multimodal Approach

Collaborative problem-solving (CPS) is an essential skill in the workplace in the 21st century, but the assessment and support of the CPS process with scientifically objective evidence are challenging. This research aims to understand in-class CPS interaction by investigating the change of a dyad's cognitive engagement during a mathematics lesson. Here, we propose a multimodal evaluation of joint visual attention (JVA) based on eye gazes and eye blinks data as non-verbal indicators of dyadic cognitive engagement. Our results indicate that this multimodal approach can bring more insights into students' CPS process than unimodal evaluations of JVA in temporal analysis. This study contributes to the field by demonstrating the value of nonverbal multimodal JVA temporal analysis in CPS assessment and the utility of eye physiological data in improving the interpretation of dyadic cognitive engagement. Moreover, a method is proposed for capturing gaze convergence by considering eye fixations and the overlapping time between two eye gazes. We conclude the paper with our preliminary findings from a pilot study investigating the proposed approach in a real-world teaching context