The Orchestration Matrix: A Tool to Design Heterogeneous Classroom Ecosystems

Abstract: Modern classrooms are complex socio-technical spaces where multiple heterogeneous legacy tools and novel technologies coexist. The design and the study of such technological ecosystems (or of single technologies that have to integrate into one such ecosystem) is still under-researched, and we lack established conceptual tools to understand how a learning scenario is orchestrated across such heterogeneous sets of resources, and the role and affordances of each technology in it. In this contribution, we present the orchestration matrix, a simple table-like form that can help technology designers and researchers to analyze an existing technological classroom ecosystem from the point of view of teacher orchestration of a learning scenario, or propose new ecosystems that are (hopefully) more effective

Photometry of the Type Ia Supernovae 1999cc, 1999cl, and 2000cf

We present previously unpublished BVRI photometry of the Type Ia supernovae 1999cc and 2000cf along with revised photometry of SN 1999cl. We confirm that SN 1999cl is reddened by highly non-standard dust, with R_V = 1.55 +/- 0.08. Excepting two quasar-lensing galaxies whose low values of R_V are controversial, this is the only known object with a published value of R_V less than 2.0. SNe 1999cl and 2000cf have near-infrared absolute magnitudes at maximum in good agreement with other Type Ia SNe of mid-range decline rates.Comment: 28 pages, 5 figures, accepted for publication in the Astronomical Journal, 5 November 200

On the Ramsey numbers for stars versus complete graphs

For graphs G1, . . . , Gs, the multicolor Ramsey number R(G1, . . . , Gs) is the smallest integer r such that if we give any edge col-oring of the complete graph on r vertices with s colors then there exists a monochromatic copy of Gi colored with color i, for some 1 ≤ i ≤ s. In this work the multicolor Ramsey number R(Kp1 , . . . , Kpm , K1,q1 , . . . , K1,qn ) is determined for any set of com-plete graphs and stars in terms of R(Kp1 , . . . , Kpm )Ministerio de Educación y Ciencia MTM2008-06620-C03-02Junta de Andalucía P06-FQM-0164

A Modal-Based Partition of Unity Finite Element Method for Elastic Wave Propagation Problems in Layered Media

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] The time-harmonic propagation of elastic waves in layered media is simulated numerically by means of a modal-based Partition of Unity Finite Element Method (PUFEM). Instead of using the standard plane waves or the Bessel solutions of the Helmholtz equation to design the discretization basis, the proposed modal-based PUFEM explicitly uses the tensor-product expressions of the eigenmodes (the so-called Love and interior modes) of a spectral elastic transverse problem, which fulfil the coupling conditions among layers. This modal-based PUFEM approach does not introduce quadrature errors since the coefficients of the discrete matrices are computed in closed-form. A preliminary analysis of the high condition number suffered by the proposed method is also analyzed in terms of the mesh size and the number of eigenmodes involved in the discretization. The numerical methodology is validated through a number of test scenarios, where the reliability of the proposed PUFEM method is discussed by considering different modal basis and source terms. Finally, some indicators are introduced to select a convenient discrete PUFEM basis taking into account the observability of cracks located on a coupling boundary between two adjacent layers.This work has been supported by Xunta de Galicia project “Numerical simulation of high-frequency hydro-acoustic problems in coastal environments - SIMNUMAR” (EM2013/052), co-funded with European Regional Development Funds (ERDF). Moreover, the second and fifth authors have been supported by MICINN projects MTM2014-52876-R, MTM2017-82724-R, PID2019-108584RB-I00, and also by ED431C 2018/33 - M2NICA (Xunta de Galicia & ERDF) and ED431G 2019/01 - CITIC (Xunta de Galicia & ERDF). Additionally, the third author has been supported by Junta de Castilla y León under projects VA024P17 and VA105G18, co-financed by ERDF funds. This work has been funded for open access charge by Universidade da Coruña/CISUGXunta de Galicia; EM2013/052Xunta de Galicia; ED431C 2018/33Xunta de Galicia; ED431G 2019/01Junta de Castilla y León; VA024P17Junta de Castilla y León; VA105G1

Progress-Oriented Workshops for Doctoral Well-being: Evidence From a Two-Country Design-Based Research

This paper explores an intervention approach (in the form of workshops) focusing on doctoral progress, to address the problems of low emotional well-being experienced by many doctoral candidates. Doctoral education suffers from two severe overlapping problems: high dropout rates and widespread low emotional well-being (e.g., depression or anxiety symptoms). Yet, there are few interventional approaches specifically designed to address them in the doctoral student population. Among structural, psychosocial, and demographic factors influencing these problems, the self-perception of progress has emerged recently as a crucial motivational factor in doctoral persistence. This paper reports on an iterative design-based research study of workshop interventions to foster such perception of progress in doctoral students? everyday practice. We gathered mixed data over four iterations, with a total of 82 doctoral students from multiple disciplines in Spain and Estonia. An approach to preventive interventions that combines research-backed education about mental health and productivity, peer sharing and discussion of experiences, and indicators of progress, as well as self-tracking, analysis, and reflection upon everyday evidence of their own progress. The paper provides initial evidence of the effectiveness of the proposed interventions, across two institutions in two different countries. Further, our data confirms emergent research on the relationships among progress, emotional well-being, and dropout ideation in two new contexts. Finally, the paper also distills design knowledge about doctoral interventions that focus on progress, relevant for doctoral trainers, institutions, and researchers.This research has received funding from the European Union’s Horizon 2020 research and innova-tion programme under grant agreement No. 669074 (CEITER). It has also received funding from the European Union’s Erasmus Plus programme, grant agreement 2019-1-NO01-KA203-060280 (DE-TEL). The Universidad de Valladolid co-authors acknowledge funding of the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science, Innova-tion, and Universities, under project grant TIN2017-85179-C3-2-R (SmartLET), and PID2020-112584RB-C32, the European Regional Development Fund, and the Regional Government of Cas-tile and Leon, under project grant VA257P18

Towards Novel Researcher Tooling Based on Multimodal Analytics

Much of educational research today employs a complex mixture of qualitative and quantitative analyses, both during the exploratory and confirmatory phases. However, researchers are still stuck with tools that were developed mainly for single-perspective research. The problem is even more acute in emergent areas with complex, high-frequency data, such as multimodal learning analytics (MMLA). In this position paper, we posit that a new generation of researcher tools are needed to account for this new complexity of research processes. We also anticipate that such new wave of tools should leverage recent advances in computing technology, while keeping humans in the loop. The paper presents a proof-of-concept ongoing study focusing on one of the main points of friction in social sciences research: the manual coding of audio/video. The results of this study, to be presented in the workshop, will illustrate some of the advantages and unsolved challenges in the development of computationally-enhanced researcher tools that can lead to MMLA solutions usable in the real world

Orchestrating learning analytics (OrLA): Supporting inter-stakeholder communication about adoption of learning analytics at the classroom level

Producción CientíficaDespite the recent surge of interest in learning analytics (LA), their adoption in everyday classroom practice is still slow. Knowledge gaps and lack of inter-stakeholder communication (particularly with educational practitioners) have been posited as critical factors for previous LA adoption failures. Yet, what issues should researchers, practitioners and other actors communicate about, when considering the adoption of an LA innovation in a particular context? We reviewed and synthesised existing literature on four focus areas related to LA, their adoption, implications for practice, and more general factors that have emerged as crucial when studying everyday classroom adoption of technologies (i.e., classroom orchestration). This synthesis resulted in two conversational frameworks and an inter-stakeholder communication tool. These can be used to guide and support conversations and decisionmaking about the adoption of LA innovations. We illustrate their usefulness with examples of use in ongoing LA adoption processes in Australia, Spain and Estonia.Junta de Castilla y León (programa de apoyo a proyectos de investigación – Ref. VA082U16)Ministerio de Economía, Industria y Competitividad (Projects TIN2014-53199-C3-2-R and TIN2017-85179-C3-2-R),Ministerio de Educación, Cultura y Deporte (PRX17/00410

EFAR-MMLA: An evaluation framework to assess and report generalizability of machine learning models in MMLA

Producción CientíficaMultimodal Learning Analytics (MMLA) researchers are progressively employing machine learning (ML) techniques to develop predictive models to improve learning and teaching practices. These predictive models are often evaluated for their generalizability using methods from the ML domain, which do not take into account MMLA’s educational nature. Furthermore, there is a lack of systematization in model evaluation in MMLA, which is also reflected in the heterogeneous reporting of the evaluation results. To overcome these issues, this paper proposes an evaluation framework to assess and report the generalizability of ML models in MMLA (EFAR-MMLA). To illustrate the usefulness of EFAR-MMLA, we present a case study with two datasets, each with audio and log data collected from a classroom during a collaborative learning session. In this case study, regression models are developed for collaboration quality and its sub-dimensions, and their generalizability is evaluated and reported. The framework helped us to systematically detect and report that the models achieved better performance when evaluated using hold-out or cross-validation but quickly degraded when evaluated across different student groups and learning contexts. The framework helps to open up a “wicked problem” in MMLA research that remains fuzzy (i.e., the generalizability of ML models), which is critical to both accumulating knowledge in the research community and demonstrating the practical relevance of these techniques.Fondo Europeo de Desarrollo Regional - Agencia Nacional de Investigación (grants TIN2017-85179-C3-2-R and TIN2014-53199-C3-2-R)Fondo Europeo de Desarrollo Regional - Junta de Castilla y León (grant VA257P18)Comisión Europea (grant 588438-EPP-1- 2017-1-EL-EPPKA2-KA