| dc.description.abstract | In the last ten years, higher education has witnessed a substantial increase in the number of learning technologies as a support to the more traditional classroom environments. Today’s technological advancements, from simple sensors to smartphones and wearables, enhance human capacities and empower humans to transcend physical barriers and time, to consume education in various new ways. Therefore, multimodal data have the potential to explore emerging learning practices that support and extend human cognitive capacities. Taking a multimodal approach, provides a unique opportunity to enrich the contemporary capacities of the current learning environments by augmenting learning analytics with multimodal data, to observe, capture, and analyze emergent and unpredictable behaviors, learning phenomena, learner-context and human-computer interactions, in real time and over time. Consequently, the overarching focus of this doctoral work is to build a more nuanced understanding of learning activities (i.e., what learners do) and learner behaviors, by investigating factors (e.g., contextual, intraindividual) that influence learning, particularly in technology-rich settings, where learning is associated with many aspects of human-computer interaction.
The research undertaken in this doctoral work provides implications related to how learning technology and user experience researchers and practitioners, can develop cross-platform and multimodal methodologies and innovations. Such methodologies can support sensemaking of the requirements that stem from different learning designs, stakeholders, group of learners, and learning contexts, thereby leading to design decisions that extend beyond individuals and toward dynamic, interconnected, and ever-evolving community of learners, instructors, tools, and content.
Based on the findings from our research work, we argue that methods and tools (e.g. multimodal learning analytics) that are not immediately influential to overcome the current traditional practices, but offer the prospect of sustained innovation in education, should be embraced and practiced in future, because they carry novelty, failures, and potentials for progress and advancement. We also argue that incorporating human values and needs in the design of learning technologies requires multi-disciplinary approaches, new methods, skills practical way. To that end, the aim of this doctoral work is to provoke deep and productive conversations about the process of augmenting learning analytics with multimodal data, and the advancement of the synergy and the research at the intersection between learning analytics and learning design, among the community of educators, researchers, and practitioners, from a post-evaluation design-aware process to permanent monitoring process of adaptation. and knowledge, to ensure that technology will serve human needs in the most ethical and practical way. To that end, the aim of this doctoral work is to provoke deep and productive conversations about the process of augmenting learning analytics with multimodal data, and the advancement of the synergy and the research at the intersection between learning analytics and learning design, among the community of educators, researchers, and practitioners, from a post-evaluation design-aware process to permanent monitoring process of adaptation | en_US |
