105 research outputs found
The role of learning theory in multimodal learning analytics
This study presents the outcomes of a semi-systematic
literature review on the role of learning theory in multimodal learning analytics (MMLA) research. Based on
previous systematic literature reviews in MMLA and
an additional new search, 35MMLA works were identified that use theory. The results show that MMLA
studies do not always discuss their findings within
an established theoretical framework. Most of the
theory-driven MMLA studies are positioned in the
cognitive and affective domains, and the three most
frequently used theories are embodied cognition,
cognitive load theory and control–value theory of
achievement emotions. Often, the theories are only
used to inform the study design, but there is a relationship between the most frequently used theories
and the data modalities used to operationalize those
theories. Although studies such as these are rare, the
findings indicate that MMLA affordances can, indeed,
lead to theoretical contributions to learning sciences.
In this work, we discuss methods of accelerating
theory-driven MMLA research and how this acceleration can extend or even create new theoretical
knowledge
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
Going Multimodal: Programmatic, Curricular, and Classroom Change
AS THE STUDENTS NOTE IN this epigraph, we do not live in a monomodal world. Rather, we experience the world and communicate through multiple modalities. To confine students to learning in only one mode, typically the textual mode in first-year writing courses, indeed limits, students\u27 understanding and creative potential-a point that has reemerged in considerations of education and the teaching of writing..
Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills
Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how?
The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds.
In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process.
In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates
Inventing Network Composition: Mobilizing Rhetorical Invention and Social Media for Digital Pedagogy
Inventing Network Composition: Mobilizing Rhetorical Invention and Social Media for Digital Pedagogy investigates how students learn through writing and invention in digital social networks. Pursuing a primary research question of How do student composers invent within networked social media environments?, the dissertation examines how social media and digital writing tools can help students to learn, connect, and share generatively. The core theoretical contribution that this dissertation offers is a theory of network composition, which is a mode of invention that composers engage in social media environments that is intensely social, that is structured by a digital interface, that is interactive and participatory, and that incorporates linguistic, visual, sonic, and other multimodal communication forms. Network composition manifests most notably in network composition pedagogy, which organically locates the work of composing, as well as the disciplinary work of rhetoric and composition, within networked social media environments.
This dissertation revisits and updates disciplinary exigencies related to rhetorical invention in digital networks, social media use in the writing classroom, and digital participation as a mode for learning. The dissertation offers an updated approach to invention called network-emergent rhetorical invention that approaches invention as a distributed emergence arising from a network of actants that includes humans, hardware, technologies, interfaces, communities, cultures, software, and infrastructures. It also features an IRB-approved qualitative case study that finds social media to support learning ecology formation, distributed expertise, rhetorical invention, digital and social media literacy development, rhetoric and writing skills formation, and digital citizenship activities. The dissertation additionally examines challenges for social media use in the writing classroom, considering how accessibility, digital aggression, digital discrimination, and data/privacy challenges can and should be navigated. The dissertation closes by speculating about futures for network composition and considering what is at stake for the future of learning, interaction, and participation in digital networks
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Investigating Collaboration as a Process with Theory-driven Learning Analytics
Although collaboration is considered a key 21st-century skill, oftentimes it is only assessed through the outcome measures of individual learners. In this paper, we draw upon collaborative cognitive load theory (CCLT) to explain the process of collaboration in learning from the point of view of the collective, rather than an individual learner. Using CCLT we suggest a new method of measuring the process of collaboration regardless of its outcome measures. Our approach — Collaborative Learning as a Process (CLaP) — uses social network analysis to evaluate the balance between interactivity gains and coordination costs of learner communities. Here, we demonstrate the approach using real-world data derived from the digital tracks of two online discussion communities. We argue that our conceptual approach can enable instructors and learners to unlock the black box of collaboration in learning. It has the potential to support the development of learner skills that go beyond cognition. We conclude the paper with the results of our investigation of the value of the approach to the online module instructor
Proceedings of the 1st Doctoral Consortium at the European Conference on Artificial Intelligence (DC-ECAI 2020)
1st Doctoral Consortium at the European Conference on
Artificial Intelligence (DC-ECAI 2020), 29-30 August, 2020
Santiago de Compostela, SpainThe DC-ECAI 2020 provides a unique opportunity for PhD students, who are close to finishing their doctorate research, to interact with experienced researchers in the field. Senior members of the community are assigned as mentors for each group of students based on the student’s research or similarity of research interests. The DC-ECAI 2020, which is held virtually this year, allows students from all over the world to present their research and discuss their ongoing research and career plans with their mentor, to do networking with other participants, and to receive training and mentoring about career planning and career option
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