The state of the art of diagnostic multiparty eye tracking in synchronous computer-mediated collaboration

In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an interactive tool to enable and evaluate shared gaze visualizations in remote interaction. We conducted a systematic literature review to provide a comprehensive overview of what to consider when using multiparty eye tracking as a diagnostic method in experiments and how to process the collected data to compute and analyze group-level metrics. By synthesizing our findings in an integrative conceptual framework, we identified fundamental requirements for a meaningful implementation. In addition, we derived several implications for future research, as multiparty eye tracking was mainly used to study the correlation between joint attention and task performance in dyadic interaction. We found multidimensional recurrence quantification analysis, a novel method to quantify group-level dynamics in physiological data, to be a promising procedure for addressing some of the highlighted research gaps. In particular, the computation method enables scholars to investigate more complex cognitive processes within larger groups, as it scales up to multiple data streams

The state of the art of diagnostic multiparty eye tracking in synchronous computer-mediated collaboration

In recent years, innovative multiparty eye tracking setups have been introduced to synchronously capture eye movements of multiple individuals engaged in computer-mediated collaboration. Despite its great potential for studying cognitive processes within groups, the method was primarily used as an interactive tool to enable and evaluate shared gaze visualizations in remote interaction. We conducted a systematic literature review to provide a comprehensive overview of what to consider when using multiparty eye tracking as a diagnostic method in experiments and how to process the collected data to compute and analyze group-level metrics. By synthesizing our findings in an integrative conceptual framework, we identified fundamental requirements for a meaningful implementation. In addition, we derived several implications for future research, as multiparty eye tracking was mainly used to study the correlation between joint attention and task performance in dyadic interaction. We found multidimensional recurrence quantification analysis, a novel method to quantify group-level dynamics in physiological data, to be a promising procedure for addressing some of the highlighted research gaps. In particular, the computation method enables scholars to investigate more complex cognitive processes within larger groups, as it scales up to multiple data streams

Virtual Reality in Mathematics Education (VRiME):An exploration of the integration and design of virtual reality for mathematics education

This thesis explores the use of Virtual Reality (VR) in mathematics education. Four VR prototypes were designed and developed during the PhD project to teach equations, geometry, and vectors and facilitate collaboration.Paper A investigates asymmetric VR for classroom integration and collaborative learning and presents a new taxonomy of asymmetric interfaces. Paper B proposes how VR could assist students with Autism Spectrum Disorder (ASD) in learning daily living skills involving basic mathematical concepts. Paper C investigates how VR could enhance social inclusion and mathematics learning for neurodiverse students. Paper D presents a VR prototype for teaching algebra and equation-solving strategies, noting positive student responses and the potential for knowledge transfer. Paper E investigates gesture-based interaction with dynamic geometry in VR for geometry education and presents a new taxonomy of learning environments. Finally, paper F explores the use of VR to visualise and contextualise mathematical concepts to teach software engineering students.The thesis concludes that VR offers promising avenues for transforming mathematics education. It aims to broaden our understanding of VR's educational potential, paving the way for more immersive learning experiences in mathematics education

Technology-Based Personalization: Instructional Reform in Five Public Schools

This dissertation addresses the question: How does an attempt to redesign instructional delivery using technology-based personalization affect the technical core of teaching, learning, and student outcomes? In recent years, many prominent educators, business leaders, and philanthropists have suggested that schools be redesigned to personalize students’ learning experiences using technology. However, the justification for these reforms remains largely theoretical. Empirical research on technology-based personalization is sparse, and what little research does exist focuses predominantly on macro effects rather than the specific school-level, class-level, student-level, and lesson-level mechanisms that contribute to overall student achievement. The absence of research that pushes inside the “black box” of implementation is particularly problematic given a century of failed attempts to reform the technical core of instructional delivery, with symbolic reforms typically withering in the face of institutional resistance. This study attempts to address that gap by examining the implementation of an innovative model for using technology-based personalization to deliver middle school math instruction. I draw upon theoretical tools from institutional theory, instructional improvement, and the history of educational reform to deepen our understanding of how technology-based personalization affects the role of students and teachers, the logistics of content delivery, and students’ learning outcomes. Unlike previous studies in K-12 settings, which typically use summative assessments and virtual control groups to estimate aggregate effects on student learning, this study examines the relationships among a diverse set of lesson-level variables, including instructional modality, instructional content, group size and composition, teacher characteristics, student characteristics, and learning outcomes. In doing so, this study contributes to our understanding of the on-the-ground processes and mechanisms by which technology- based personalization affects (or does not affect) student learning. Although the instructional model documented in this case study will remain anonymous, it is well known and respected among educators and philanthropists, and regarded as one of the most prominent and archetypical examples of technology-based personalization currently active in American schools. Using multiple methods, including novel applications of hierarchical linear modeling, cluster analysis, and heatmap data visualization, I explore: (a) the degree to which ground-level implementation of technology-based personalization represents an authentic departure from the traditional technology of schooling, and (b) the relationships among various elements of the model and student learning outcomes. I draw on longitudinal data from a full year of implementation in five schools, including the daily lesson assignments and assessment scores of 1,238 unique students supervised by 48 teachers. This study supports four main findings: (a) the program succeeds in altering the technical core of instruction in several fundamental ways; (b) policy and logistical constraints limit the program’s ability to reform the technical core of instruction to the degree that it aspires; (c) students who enter the program as already higher-performing are more successful on daily exit slips than students who enter the program with lower performance; and (d) the quantitative methods used in this paper represent useful and replicable tools for exploring the data produced by technology-based and personalized models

Developing Learning System in Pesantren The Role of ICT

According to Krashen's affective filter hypothesis, students who are highly motivated have a strong sense of self, enter a learning context with a low level of anxiety, and are much more likely to become successful language acquirers than those who do not. Affective factors, such as motivation, attitude, and anxiety, have a direct impact on foreign language acquisition. Horwitz et al. (1986) mentioned that many language learners feel anxious when learning foreign languages. Thus, this study recruits 100 college students to fill out the Foreign Language Classroom Anxiety Scale (FLCAS) to investigate language learning anxiety. Then, this study designs and develops an affective tutoring system (ATS) to conduct an empirical study. The study aims to improve students’ learning interest by recognizing their emotional states during their learning processes and provide adequate feedback. It is expected to enhance learners' motivation and interest via affective instructional design and then improve their learning performance

The student-produced electronic portfolio in craft education

The authors studied primary school students’ experiences of using an electronic portfolio in their craft education over four years. A stimulated recall interview was applied to collect user experiences and qualitative content analysis to analyse the collected data. The results indicate that the electronic portfolio was experienced as a multipurpose tool to support learning. It makes the learning process visible and in that way helps focus on and improves the quality of learning. © ISLS.Peer reviewe

Supporting Collaborative Learning in Computer-Enhanced Environments

As computers have expanded into almost every aspect of our lives, the ever-present graphical user interface (GUI) has begun facing its limitations. Demanding its own share of attention, GUIs move some of the users\u27 focus away from the task, particularly when the task is 3D in nature or requires collaboration. Researchers are therefore exploring other means of human-computer interaction. Individually, some of these new techniques show promise, but it is the combination of multiple approaches into larger systems that will allow us to more fully replicate our natural behavior within a computing environment. As computers become more capable of understanding our varied natural behavior (speech, gesture, etc.), the less we need to adjust our behavior to conform to computers\u27 requirements. Such capabilities are particularly useful where children are involved, and make using computers in education all the more appealing. Herein are described two approaches and implementations of educational computer systems that work not by user manipulation of virtual objects, but rather, by user manipulation of physical objects within their environment. These systems demonstrate how new technologies can promote collaborative learning among students, thereby enhancing both the students\u27 knowledge and their ability to work together to achieve even greater learning. With these systems, the horizon of computer-facilitated collaborative learning has been expanded. Included among this expansion is identification of issues for general and special education students, and applications in a variety of domains, which have been suggested