Evolution in the Design and Functionality of Rubrics: from “Square” Rubrics to “Federated” Rubrics

The assessment of learning remains one of the most controversial and challenging aspects for teachers. Among some recent technical solutions, methods and techniques like eRubrics emerge in an attempt to solve the situation. Understanding that all teaching contexts are different and there can be no single solution for all cases, specific measures are adapted to contexts where teachers receive support from institutions and communities of practice. This paper presents the evolution of the eRubric service [1] which started from a first experience with paper rubrics, and, with time and after several I+D+R [2] educational projects, has evolved thanks to the support of a community of practice [3] and the exchange of experiences between teachers and researchers. This paper shows the results and functionality of the eRubrics service up to the date of publicationa.) Project I+D+i EDU2010-15432: eRubric federated service for assessing university learning http://erubrica.uma.es/?page_id=434. b.) Centre for the Design of eRubrics. National Distance Education System -Sined- Mexico. [http://erubrica.uma.es/?page_id=389

Study of Video Annotations In External Practices Of University Learning

The digital video as code and learning technology has extensive scientific literature (Bartolome, 1997; Aguaded and Sánchez, 2008). However, the increase of digital video services on the Internet has facilitated and increased the use of video for education. With a recent important increase of videos as contained in the MOOC (Massive Open Online Course). This context has also created the expansion of educational practices based on models for collaborative learning and mediated by technology (Computer Supported Learning collaborative -CSCL-). The study of these practices is proving to be effective for teachers in service and initial training practices if it is analyzed collectively (Hosack, Br tools, 2010;. Picci, Calvani, & Bonaiuti, 2012; Etscheidt & Curran, 2012; Ingram , 2014). There is interest in literature reviews on the reflective capabilities with the use of video for initial teacher training (Orland-Barak & Rachamim, 2009; Rich and Hannafin 2009; Rich & Trip, 2011) to which we expand in (Wallet, Cebrian & Desenne, 2015). This work is part of a research project in progress [1] which aims to implement a federated portfolio model of multimedia evidences. This model uses a digital portfolio (from now on we will call ePortfolios) with three different federated tools (1. Digital rubric or eRubric, 2. Webquest and 3. Open Video Annotations -Ova-) created by our research and development group Gtea [2 ]. The OVA tool was created within the MOOC of edX in collaboration with Harvard University in 2013 [3]. So it, we need to create another standalone tool to design their own interface to use this tool in this project. This design was evaluated through user usability and satisfaction (Monedero, Cebrian & Desenne, 2015). This study focuses on the ease and functionality of the OVA tool so that students to collect evidence on their digital multimedia portfolios. Especially, analyzes the competences that students show when annotate video in order to explain their learning experiences and respond to the skills that are required in the eRubrics in different teaching contexts (external and laboratory practices).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. R+D+i project: Study of the Impact of federated eRubrics on the evaluation of external practices competences Plan Nacional de I + D + i de Excelencia (2014-2017) Ministerio de Economía y competitividad, nº EDU2013-41974-P web: http://goo.gl/CN6ID

Analysis of the pedagogical perspective of the MOOCs available in Portuguese

After an initial stage of exponential growth in MOOCs, a need has arisen of to address several different aspects of these innovations in order to understand and develop them from different perspectives, such as this one, with the analysis of pedagogical dimensions aimed at improving course design. This paper presents an updated review of the literature and proposes five research lines for an in-depth approach. This study is part of a broader research project1 and here analyses 356 MOOCs delivered in Portuguese by 16 different platforms. The research design is quantitative, non-experimental and transversal. An adaptation of the MOOC Educational and Interactive Indicators Instrument —INdiMOOC-EdI— was used in the data collection process. The reliability and internal consistency analysis of that adaptation for the whole sample resulted in a Cronbach alpha score of 0.731. The data obtained enable us to classify the existing MOOCs in Portuguese according to descriptive, formative, and interactive components. These different types correlate with the quality indices, being negative in the first dimension (descriptive) and positive in the second and third ones (formative and interactive).Funded by the call for R&D&i projects named: «Estudio del impacto de las erubricas federada en evaluación de las competencias en el practicum» (Study on the impact of federated eRubrics in the evaluation of the competences in the practicum). Plan Nacional de I+D+i de Excelencia (National R&D&i Excellence Plan) (2014-16) no. EDU2013-41974-

High-throughput fuzzy clustering on heterogeneous architectures

[EN] The Internet of Things (IoT) is pushing the next economic revolution in which the main players are data and immediacy. IoT is increasingly producing large amounts of data that are now classified as "dark data'' because most are created but never analyzed. The efficient analysis of this data deluge is becoming mandatory in order to transform it into meaningful information. Among the techniques available for this purpose, clustering techniques, which classify different patterns into groups, have proven to be very useful for obtaining knowledge from the data. However, clustering algorithms are computationally hard, especially when it comes to large data sets and, therefore, they require the most powerful computing platforms on the market. In this paper, we investigate coarse and fine grain parallelization strategies in Intel and Nvidia architectures of fuzzy minimals (FM) algorithm; a fuzzy clustering technique that has shown very good results in the literature. We provide an in-depth performance analysis of the FM's main bottlenecks, reporting a speed-up factor of up to 40x compared to the sequential counterpart version.This work was partially supported by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18, and by Spanish Ministry of Science, Innovation and Universities under grants TIN2016-78799-P (AEI/FEDER, UE), RTI2018-096384-B-I00, RTI2018-098156-B-C53 and RTC-2017-6389-5.Cebrian, JM.; Imbernón, B.; Soto, J.; García, JM.; Cecilia-Canales, JM. (2020). High-throughput fuzzy clustering on heterogeneous architectures. Future Generation Computer Systems. 106:401-411. https://doi.org/10.1016/j.future.2020.01.022S401411106Waldrop, M. M. (2016). The chips are down for Moore’s law. Nature, 530(7589), 144-147. doi:10.1038/530144aCecilia, J. M., Timon, I., Soto, J., Santa, J., Pereniguez, F., & Munoz, A. (2018). High-Throughput Infrastructure for Advanced ITS Services: A Case Study on Air Pollution Monitoring. IEEE Transactions on Intelligent Transportation Systems, 19(7), 2246-2257. doi:10.1109/tits.2018.2816741Singh, D., & Reddy, C. K. (2014). A survey on platforms for big data analytics. Journal of Big Data, 2(1). doi:10.1186/s40537-014-0008-6Stephens, N., Biles, S., Boettcher, M., Eapen, J., Eyole, M., Gabrielli, G., … Walker, P. (2017). The ARM Scalable Vector Extension. IEEE Micro, 37(2), 26-39. doi:10.1109/mm.2017.35Wright, S. A. (2019). Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems. Future Generation Computer Systems, 92, 900-902. doi:10.1016/j.future.2018.11.020Jain, A. K., Murty, M. N., & Flynn, P. J. (1999). Data clustering. ACM Computing Surveys, 31(3), 264-323. doi:10.1145/331499.331504Lee, J., Hong, B., Jung, S., & Chang, V. (2018). Clustering learning model of CCTV image pattern for producing road hazard meteorological information. Future Generation Computer Systems, 86, 1338-1350. doi:10.1016/j.future.2018.03.022Pérez-Garrido, A., Girón-Rodríguez, F., Bueno-Crespo, A., Soto, J., Pérez-Sánchez, H., & Helguera, A. M. (2017). Fuzzy clustering as rational partition method for QSAR. Chemometrics and Intelligent Laboratory Systems, 166, 1-6. doi:10.1016/j.chemolab.2017.04.006H.S. Nagesh, S. Goil, A. Choudhary, A scalable parallel subspace clustering algorithm for massive data sets, in: Proceedings 2000 International Conference on Parallel Processing, 2000, pp. 477–484.Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 10(2-3), 191-203. doi:10.1016/0098-3004(84)90020-7Havens, T. C., Bezdek, J. C., Leckie, C., Hall, L. O., & Palaniswami, M. (2012). Fuzzy c-Means Algorithms for Very Large Data. IEEE Transactions on Fuzzy Systems, 20(6), 1130-1146. doi:10.1109/tfuzz.2012.2201485Flores-Sintas, A., Cadenas, J., & Martin, F. (1998). A local geometrical properties application to fuzzy clustering. Fuzzy Sets and Systems, 100(1-3), 245-256. doi:10.1016/s0165-0114(97)00038-9Soto, J., Flores-Sintas, A., & Palarea-Albaladejo, J. (2008). Improving probabilities in a fuzzy clustering partition. Fuzzy Sets and Systems, 159(4), 406-421. doi:10.1016/j.fss.2007.08.016Timón, I., Soto, J., Pérez-Sánchez, H., & Cecilia, J. M. (2016). Parallel implementation of fuzzy minimals clustering algorithm. Expert Systems with Applications, 48, 35-41. doi:10.1016/j.eswa.2015.11.011Flores-Sintas, A., M. Cadenas, J., & Martin, F. (2001). Detecting homogeneous groups in clustering using the Euclidean distance. Fuzzy Sets and Systems, 120(2), 213-225. doi:10.1016/s0165-0114(99)00110-4Wang, H., Potluri, S., Luo, M., Singh, A. K., Sur, S., & Panda, D. K. (2011). MVAPICH2-GPU: optimized GPU to GPU communication for InfiniBand clusters. Computer Science - Research and Development, 26(3-4), 257-266. doi:10.1007/s00450-011-0171-3Kaltofen, E., & Villard, G. (2005). On the complexity of computing determinants. computational complexity, 13(3-4), 91-130. doi:10.1007/s00037-004-0185-3Johnson, S. C. (1967). Hierarchical clustering schemes. Psychometrika, 32(3), 241-254. doi:10.1007/bf02289588Saxena, A., Prasad, M., Gupta, A., Bharill, N., Patel, O. P., Tiwari, A., … Lin, C.-T. (2017). A review of clustering techniques and developments. Neurocomputing, 267, 664-681. doi:10.1016/j.neucom.2017.06.053Woodley, A., Tang, L.-X., Geva, S., Nayak, R., & Chappell, T. (2019). Parallel K-Tree: A multicore, multinode solution to extreme clustering. Future Generation Computer Systems, 99, 333-345. doi:10.1016/j.future.2018.09.038Kwedlo, W., & Czochanski, P. J. (2019). A Hybrid MPI/OpenMP Parallelization of $K$ -Means Algorithms Accelerated Using the Triangle Inequality. IEEE Access, 7, 42280-42297. doi:10.1109/access.2019.2907885Li, Y., Zhao, K., Chu, X., & Liu, J. (2013). Speeding up k-Means algorithm by GPUs. Journal of Computer and System Sciences, 79(2), 216-229. doi:10.1016/j.jcss.2012.05.004Saveetha, V., & Sophia, S. (2018). Optimal Tabu K-Means Clustering Using Massively Parallel Architecture. Journal of Circuits, Systems and Computers, 27(13), 1850199. doi:10.1142/s0218126618501992Djenouri, Y., Djenouri, D., Belhadi, A., & Cano, A. (2019). Exploiting GPU and cluster parallelism in single scan frequent itemset mining. Information Sciences, 496, 363-377. doi:10.1016/j.ins.2018.07.020Krawczyk, B. (2016). GPU-Accelerated Extreme Learning Machines for Imbalanced Data Streams with Concept Drift. Procedia Computer Science, 80, 1692-1701. doi:10.1016/j.procs.2016.05.509Fang, Y., Chen, Q., & Xiong, N. (2019). A multi-factor monitoring fault tolerance model based on a GPU cluster for big data processing. Information Sciences, 496, 300-316. doi:10.1016/j.ins.2018.04.053Tanweer, S., & Rao, N. (2019). Novel Algorithm of CPU-GPU hybrid system for health care data classification. Journal of Drug Delivery and Therapeutics, 9(1-s), 355-357. doi:10.22270/jddt.v9i1-s.244

Metodología para evaluar el impacto de las erúbricas y las anotaciones de vídeo en las prácticas externas

Esta comunicación presenta el estudio del ePortafolios de evidencias multimedias para la evaluación formativa de los aprendizajes en las prácticas externas, analizando la naturaleza de las evidencias presentadas como las anotaciones producidas entre el tutor, los estudiantes de prácticas y estudiantes de las asignaturas teóricas en la universidad. Con esta metodología establecemos una relación poco habitual en el aprendizaje teórico-práctico, y la asignación de significados y análisis de estas experiencias entre los estudiantes de asignaturas teóricas y estudiantes en las prácticas externas. Esta metodología nos permite analizar el sentido de dichas experiencias y evidencias audiovisuales con eRúbricas y Anotaciones de video. Para dicho estudio se utilizará análisis de categorías y las estadísticas que proporcionan las herramientas, buscando sus posibilidades y funcionalidades para dicho estudio, como testeo piloto de un estudio de mayor amplitud. El grupo está constituido por 8 estudiantes de prácticas externas en centros de secundaria del grado de pedagogía y estudiantes del mismo grado en la troncal de Recursos didácticos y tecnológicos para la educación.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech 2015. Proyecto I+D+i Estudio del impacto de las erubricas federada en evaluación de las competencias en el practicum. Plan Nacional de I + D + i de Excelencia (2014-2017) Ministerio de Economía y competitividad, nº EDU2013-41974-P

Evaluation of Clustering Algorithms on HPC Platforms

[EN] Clustering algorithms are one of the most widely used kernels to generate knowledge from large datasets. These algorithms group a set of data elements (i.e., images, points, patterns, etc.) into clusters to identify patterns or common features of a sample. However, these algorithms are very computationally expensive as they often involve the computation of expensive fitness functions that must be evaluated for all points in the dataset. This computational cost is even higher for fuzzy methods, where each data point may belong to more than one cluster. In this paper, we evaluate different parallelisation strategies on different heterogeneous platforms for fuzzy clustering algorithms typically used in the state-of-the-art such as the Fuzzy C-means (FCM), the Gustafson-Kessel FCM (GK-FCM) and the Fuzzy Minimals (FM). The experimental evaluation includes performance and energy trade-offs. Our results show that depending on the computational pattern of each algorithm, their mathematical foundation and the amount of data to be processed, each algorithm performs better on a different platform.This work has been partially supported by the Spanish Ministry of Science and Innovation, under the Ramon y Cajal Program (Grant No. RYC2018-025580-I) and by the Spanish "Agencia Estatal de Investigacion" under grant PID2020-112827GB-I00 /AEI/ 10.13039/501100011033, and under grants RTI2018-096384-B-I00, RTC-2017-6389-5 and RTC2019-007159-5, by the Fundacion Seneca del Centro de Coordinacion de la Investigacion de la Region de Murcia under Project 20813/PI/18, and by the "Conselleria de Educacion, Investigacion, Cultura y Deporte, Direccio General de Ciencia i Investigacio, Proyectos AICO/2020", Spain, under Grant AICO/2020/302.Cebrian, JM.; Imbernón, B.; Soto, J.; Cecilia-Canales, JM. (2021). Evaluation of Clustering Algorithms on HPC Platforms. Mathematics. 9(17):1-20. https://doi.org/10.3390/math917215612091

Programación y robótica educativa: enfoque didáctico-técnico y experiencias de aula

En esta comunicación vamos analizar los antecedentes de la robótica, aproximándonos al concepto de robótica educativa. Posteriormente, haremos una semblanza de las teorías didácticas relacionadas con este tópico, junto con aspectos de carácter técnico relacionados con la programación y el pensamiento computacional. También analizaremos la situación de la robótica educativa y el pensamiento computacional en algunos países de nuestro entorno y en las distintas comunidades autónomas españolas, junto con instituciones universitarias, civiles y empresariales de nuestro país. Todo ello desde un enfoque académico en el que se recogen las aportaciones de diversos autores.Universidad de Málaga. Campus Internacional Andalucía Tec

The Efficacy of Therapeutic Respiratory Muscle Training Interventions in People with Bronchiectasis: A Systematic Review and Meta-Analysis

Background: Respiratory muscle dysfunction is an important health problem with high morbidity and mortality and associated costs in patients with bronchiectasis (BC). The aim of this study was to analyse the effects of therapeutic respiratory muscle training (RMT) interventions on improving sputum clearance, ventilator function, muscle strength and functional capacity in BC. Methods: Systematic review and meta-analysis were conducted following PRISMA guidelines. Two independent investigators searched using several electronic databases. The methodological quality of nine studies was assessed using the PEDro scale. Study selection/eligibility criteria: The following were included: randomised controlled trials, randomised crossover trials and pilot studies of patients with BC that used the intervention as RMT (inspiratory/expiratory) and evaluations of respiratory muscle strength (maximal expiratory pressure/maximal inspiratory pressure). This systematic review was registered in PROSPERO (CRD42017075101). Nine studies were included, five of which obtained an A recommendation grade, three with B, and one with C. Study quality was poor to good (mean PEDro Score of 6.375 out of 10). Studies had small sample sizes (8-98). Results show improvements on PImax in favour of therapeutic respiratory muscle training intervention (MD = 6.08; 95% CI = 1.38, 10.77; p < 0.01; I-2 = 92%). However, high heterogeneity was identified on meta-analysis

The video guides and social tagging with the methodology of video annotation

Producto del PIE Video guías docentesTeaching guides are mandatory for quality agencies to evaluate teaching programmes, just as institutions require teachers to comply with them. This teaching resource has been seen as a very effective tool for the information and orientation of students in university programmes. However, the reality may turn out to be different, as the current practices with these guides are often not the desirable ones, as they are not used, read and studied by students with the level of depth that teachers wish, and in some cases they may be a mere formality for students, thus losing all their potential and meaning. The communication we present aims to present the results of a teaching innovation project to break this problem by producing video guides as digital resources that are more motivating for students. In addition, to design and experiment with a new methodology for its application and analysis of these resources in teaching programmes of any kind (face-to-face, blended and online programmes) by means of multimedia annotations. In this work we present the objectives, methodologies and resources proposed in this project, as the main conclusions we have reached as it has been to check a greater participation in the understanding of the programmes by the students, as a more active and motivating methodology to work with these resources in the classroom for an online modalityPIE. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Eicosapentaenoic acid stimulates AMP-activated protein kinase and increases visfatin secretion in cultured murine adipocytes

Visfatin is an adipokine highly expressed in visceral AT (adipose tissue) of humans and rodents, the production of which seems to be dysregulated in excessive fat accumulation and conditions of insulin resistance. EPA (eicosapentaenoic acid), an n−3 PUFA (polyunsaturated fatty acid), has been demonstrated to exert beneficial effects in obesity and insulin resistance conditions, which have been further linked to its reported ability to modulate adipokine production by adipocytes. TNF-α (tumour necrosis factor-α) is a pro-inflammatory cytokine whose production is increased in obesity and is involved in the development of insulin resistance. Control of adipokine production by some insulin-sensitizing compounds has been associated with the stimulation of AMPK (AMP-activated protein kinase). The aim of the present study was to examine in vitro the effects of EPA on visfatin production and the potential involvement of AMPK both in the absence or presence of TNF-α. Treatment with the pro-inflammatory cytokine TNF-α (1 ng/ml) did not modify visfatin gene expression and protein secretion in primary cultured rat adipocytes. However, treatment of these primary adipocytes with EPA (200 μmol/l) for 24 h significantly increased visfatin secretion (P<0.001) and mRNA gene expression (P<0.05). Moreover, the stimulatory effect of EPA on visfatin secretion was prevented by treatment with the AMPK inhibitor Compound C, but not with the PI3K (phosphoinositide 3-kinase) inhibitor LY294002. Similar results were observed in 3T3-L1 adipocytes. Moreover, EPA strongly stimulated AMPK phosphorylation alone or in combination with TNF-α in 3T3-L1 adipocytes and pre-adipocytes. The results of the present study suggest that the stimulatory action of EPA on visfatin production involves AMPK activation in adipocytes