206 research outputs found
DOME: recommendations for supervised machine learning validation in biology
Get PDFSupervised machine learning is widely used in biology and deserves more scrutiny. We present a set of
community-wide recommendations (DOME) aiming to help establish standards of supervised machine
learning validation in biology. Formulated as questions, the DOME recommendations improve the
assessment and reproducibility of papers when included as supplementary material.The work of the Machine Learning Focus Group was funded by ELIXIR, the research infrastructure for life-science data. IW was funded by the A*STAR Career Development Award (project no. C210112057) from the Agency for Science, Technology and Research (A*STAR), Singapore. D.F. was supported by Estonian Research Council grants (PRG1095, PSG59 and ERA-NET TRANSCAN-2 (BioEndoCar)); Project No 2014-2020.4.01.16-0271, ELIXIR and the European Regional Development Fund through EXCITE Center of Excellence. S.C.E.T. has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie Grant agreements No. 778247 and No. 823886, and Italian Ministry of University and Research PRIN 2017 grant 2017483NH8.Peer Reviewed"Article signat per 8 autors més 28 autors/es de l' ELIXIR Machine Learning Focus Group: Emidio Capriotti, Rita Casadio, Salvador Capella-Gutierrez, Davide Cirillo, Alessio Del Conte, Alexandros C. Dimopoulos, Victoria Dominguez Del Angel, Joaquin Dopazo, Piero Fariselli, José Maria Fernández, Florian Huber, Anna Kreshuk, Tom Lenaerts, Pier Luigi Martelli, Arcadi Navarro, Pilib Ó Broin, Janet Piñero, Damiano Piovesan, Martin Reczko, Francesco Ronzano, Venkata Satagopam, Castrense Savojardo, Vojtech Spiwok, Marco Antonio Tangaro, Giacomo Tartari, David Salgado, Alfonso Valencia & Federico Zambelli"Postprint (author's final draft
Machine learning in Biology: Establishing Standards
No full textThe presentation of the DOME Recommendations, that was delivered in the context of the "Machine Learning good practices" workshop (NTB-W01 – ECCB2022 at ECCB 2022, on behalf of the ELIXIR Machine Learning Focus Group
The ELIXIR Machine Learning Focus Group: achievements and road ahead
No full textDOME is a set of community-wide recommendations for reporting supervised machine learning–based analyses applied to biological studies. Broad adoption of these recommendations will help improve machine learning assessment and reproducibility.
This talk was given in the context of the ML4Microbiome Symposium "Grand Challenges of Data-Intensive Science in microbiome & metagenome data analysis and training" - 14 Oct 2021 - ML4 Microbiom
Exploring teacher professional learning for future-oriented schooling
Get PDFSets out some of the early findings from a pilot project to explore the qualities that future-oriented teachers might need and how those qualities might be developed.
Summary
In educational discussions today, there is concern that our schools are not adequately preparing today’s learners for the increasingly fast-changing world they will live and work in. The terms “future-oriented” and/or “21st century” teaching and learning occur frequently in policy documents, and “future focus” is a key principle of our national curriculum.3 However, while there is a great deal of talk about “21st century” learners’ needs, and how best to meet these needs, there is very little discussion of what “21st century” or “future-oriented” teachers look like, or how today’s teachers might become “future-oriented”. This, it seems to us, is a major gap. Developing a future-oriented education system cannot be done without teachers who understand—and are committed to doing—what is needed. However, many of today’s teachers are not well-prepared for this work, and most professional learning programmes are not designed to scaffold the kind of “future practice” needed.
What qualities do future-oriented teachers need? To what extent are these qualities different from those required of 20th century teachers? How are these qualities best developed? Can we expect all teachers to develop them? Can these new qualities be simply added to a 20th century teacher’s existing repertoire of knowledge and skills? While there is a focus on teachers’ ICT knowledge and skills, the educational research literature has had little to say on other qualities needed by future-oriented teachers, and these questions are not a focus in the wider education sector
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Machine Learning-based Author Identification for Social Media Forensics
No full textSocial media have gained extreme popularity due to the explosive growth of cyberinfrastructures, mobile devices, Internet technologies, and services. However, they also provide potential anonymity, which in turn harbors hacker forums, carding shops, underground marketplace, dark websites, and so on. As a result, social media have become the playground of cyber threat actors who conduct various malicious operations such as selling stolen cards, disseminating misinformation, propagating hacking tools, spreading malware samples, planning cyberattacks, and organizing trolling campaigns. Therefore, it is urgent to study effective methods that can identify the authors behind the digital text in order to enable forensic analysis, enhance security, and reduce social media misuse. In recent years, machine learning-based author identification has become a promising solution to identify the author of text. However, it is still an underexplored research field in social media forensics. This thesis investigates machine learning-based author identification subfields, including author attribution, author verification, author clustering, and their applications to social media forensics.
Internet Relay Chat (IRC) has traditionally been used for legitimate purposes. Yet, cyber threat actors extensively abuse it to generate a wide range of illegal content and perform malicious behaviors due to its potential anonymity and popularity among hackers. Unfortunately, author identification research in IRC remains a largely underexplored area. In this thesis, we first present our automatic social media monitoring and threat detection method that can effectively collect data for author identification tasks and then present a novel author attribution framework and its application to IRC. It consists of a holistic feature extraction model and an ensemble of ensembles for multi-class classification. We then bring a novel author verification framework under the principle of one-class learning to effectively verify the authorship of IRC texts.
This research also examines author clustering for social media forensics. Most author identification studies focus on author attribution and author verification, while the author clustering research is largely ignored. Meanwhile, cyber threat actors widely make use of Twitter to create alias accounts for numerous malicious purposes, especially in trolling campaigns and misinformation propagations. Thus, developing an effective author clustering method for Twitter is urgent. In this research, we developed a novel unsupervised learning-based author clustering framework and its application to Twitter. We delivered the capability to identify the group among many Twitter aliases even without prior knowledge of the number of authors.
We address the effectiveness and demonstrate the feasibility of our author identification frameworks through diverse experiments. Our author attribution approach can achieve more than 90% attribution accuracy given hundreds of candidates in the author attribution experiments. In the author verification experiments, over 70% of author cases, our author verification approach can achieve more than 99% AUC. In the author clustering experiments given more than one hundred unlabeled text samples, our author clustering approach attains an average accuracy of 81.93% when knowing the number of authors and an average accuracy of 74.78% without prior knowledge of the number of authors
A practice based learning environment for engineering students: Acquiring competencies for working on advanced manufacturing engineering
No full textThis thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis the author describes the design and operation of a learning environment aimed at imparting technical, technological and managerial knowledge, developing understanding of the underlying issues and enhancing team work skills for an advanced technology future. He offers an analysis of learning, education and training and compares group work with individual tasks, presents a major case study and illustrates the features which distinguish the approach from role play, simulation and experiential learning. When staff at Brunel University were faced with the problem of teaching Computer Integrated Manufacturing (CIM) to engineering students on thin sandwich type undergraduate degree programmes the writer suggested the use of an approach he would later describe as 'practice based learning' or 'real life simulation'. The fourth year course in CIM is designed as a double option for the complementary undergraduate courses, Brunel Manufacturing Engineering (BME) and Special Engineering Programmes (SEP). It is an extension of the Manufacturing Design and Practice course in years one to three of the BME course and of the Design strand on SEP, both of which restrict students' work to the use of individual machine tools and stand alone computing facilities. A wide range of teaching methods is used on the CIM course, including lectures by course staff, presentations by experts and, as the major element, a large group project involving all the students on the course, organised in a management matrix, coordinated by the students and supported by the staff acting as experts. The students also undertake assignment work alongside the technical tasks, to focus their thinking and to improve written communication skills. While the course described cannot replace more than a small proportion of the more conventional lecture, laboratory and tutorial teaching on an engineering programme, it provides a setting where students can experiment and learn about their own strengths and weaknesses in a realistic situation and in the context of teamwork. It also offers a space where they can make quite serious mistakes without direct consequences to their careers. The experience of seven years leads the author to believe that advanced manufacturing technologies and the associated management techniques should be taught in a project based environment with clear and real targets and realistic constraints, offering students challenges to which they can only rise through close and creative team work. The management of task execution must be left largely in the students' own hands. A high level of "consultant" type support is essential though, allied to an assessment scheme which promises and ensures fair treatment of the individual. The different parts of the thesis will be relevant to readers depending on their interest and background. Chapter 1 sets the scene and outlines the approach taken. Following this broad outline of the scope of the dissertation the author places Computer Integrated Manufacturing in a wider context in chapter 2, by providing an introduction to the underlying issues of computer integration and human factors. He puts forward a case for new approaches to the education and training of engineers and managers who will be working in Computer Integrated Manufacturing and Advanced Manufacturing Environments in general. Chapter 3 is devoted to the management of projects while chapter 4 is used to question the role of the engineer. Chapters 5 and 6 provide an introduction to theories of knowledge, teaching, learning and motivation. Chapters 7 and 8 are devoted to particular aspects of engineering education, while chapter 9 reviews the approach used at Brunel University. The topical issues of competence and its relevance to engineering education is discussed in chapter 10, leading into chapters 11 and 12 which deal with aspects of the CIM course. Chapters 13 and 14 are devoted to case-studies and particular tools. The key question of assessment of a practice oriented and team based course is addressed in chapter 15, followed by an evaluation of the CIM process and its application to engineering education of a full time nature which is included in chapters 17 and 18.Funding was obtained from The General Electric Company Prize 1993: Manufacturing Systems Engineering
Supporting professional identity in undergraduate Early Years students through reflective practice
Get PDFThis study investigates how full-time undergraduates in Early Years conceptualise and judge good practice and how they evaluate and reflect on their own performance. It examines how students use reflective processes, and how the teaching of reflection supports the development of their individual professional vision, values and ethics.
Data were gathered from first and second year students using semi-structured questions in interviews, questionnaires and focus group discussions. They conceptualise good practice as a combination of academic knowledge, interpersonal skills and intuitive responses to individual situations and report that they understand the processes of reflection. However, students continue to rely on other people to confirm that their practice is competent or good, and are reluctant to use or trust their own judgements about their performance.
This indicates that a new pedagogic approach is required to instil in students greater acceptance of their placement experiences as vehicles for learning, and more confidence in their own abilities and authority to judge professional practice
Discussion forums in a blended learning approach for social studies: the influence of cognitive learning styles on attitudes towards asynchronous collaboration in a South East Asian university
Get PDFTo keep pace with ubiquitous computing in all aspects of society, universities have invested heavily in off-the-shelf or in-house learning management systems, and teachers are being encouraged to seek ways in which to optimize the role of information and communication technology to support their teaching and learning activities; both on the campus and beyond campus borders. However, many students in residential universities are resistant to embracing CMC-mediated activities as an integral part of their coursework, and this attitude underscores the importance of understanding how these students are affected by the implementation of the new teaching and learning strategies associated with a 'blended learning' approach. This study explores a particular context in which discussion forums were deployed as a replacement to traditional face-to-face tutorial discussions. Research subjects (n=147), health psychology students at a South East Asian university, completed a Felder Soloman Index of Learning Styles (ILS) questionnaire before being assigned to online discussion forum groups of 8 or 9 students per group. During the 9 weeks of the tutorial assignment activity, student interactions in the discussion forums were monitored and transcripts of their postings and replies were analysed and coded. Quantitative data from attitude survey MCQs, grades, peer ratings and usage statistics, as well as qualitative data from attitude survey open-answer questions and one-to-one interviews, were also gathered and analysed. The findings identified a number of weaknesses and drawbacks of using discussion forums: notably that students who felt uncomfortable about expressing their opinions in discussion forums also had difficulty understanding what was being communicated in the postings and didn't trust their group members; students who were identified as having a moderate to strong 'Sequential' cognitive learning style preference were more likely to indicate that they had a difficult time working in the discussion forums; and students who were identified as having a moderate to strong 'Active' cognitive learning style preference tended to make fewer forum postings. Nevertheless, since the scope of the information quoted, and opinions generated, in the discussion forum postings was noticeably greater than what was generally brought up in face-to-face discussions, and because the majority of students worked independently and responsibly, this particular blended learning approach was deemed a success by the course instructor. However, the author puts forward a number of recommendations to instructional designers, practitioners and students for designing, setting up and running a similar but more flexible approach as an alternative to traditional large-class face-to-face tutorial discussions
Extensión de la especificación IMS Learning Design desde la adaptación e integración de unidades de aprendizaje
Get PDFIMS Learning Design (IMS-LD) representa una corriente actual en aprendizaje online y blended que se caracteriza porque: a) Es una especificación que pretende estandarizar procesos de aprendizaje, así como reutilizarlos en diversos contextos b) Posee una expresividad pedagógica más elaborada que desarrollos anteriores o en proceso c) Mantiene una relación cordial y prometedora con Learning Management Systems (LMSs), herramientas de autoría y de ejecución d) Existe una amplia variedad de grupos de investigación y proyectos europeos trabajando sobre ella, lo que augura una sostenibilidad, al menos académica Aun así, IMS Learning Design es un producto inicial (se encuentra en su primera versión, de 2003) y mejorable en diversos aspectos, como son la expresividad pedagógica y la interoperabilidad. En concreto, en esta tesis nos centramos en el aprendizaje adaptativo o personalizado y en la integración de Unidades de Aprendizaje, como dos de los pilares que definen la especificación, y que al mismo tiempo la potencian considerablemente. El primero (aprendizaje adaptativo) hace que se puedan abordar itinerarios individuales personalizados de estudio, tanto en flujo de aprendizaje como en contenido o interfaz; el segundo (integración) permite romper el aislamiento de los paquetes de información o cursos (Unidades de Aprendizaje, UoL) y establecer un diálogo con otros sistemas (LMSs), modelos y estándares, así como una reutilización de dichas UoLs en diversos contextos. En esta tesis realizamos un estudio de la especificación desde la base, analizando su modelo de información y cómo se construyen Unidades de Aprendizaje. Desde el Nivel A al Nivel C analizamos y criticamos la estructura de la especificación basándonos en un estudio teórico y una investigación práctica fruto del modelado de Unidades de Aprendizaje reales y ejecutables que nos proporcionan una información muy útil de base, y que mayormente adjuntamos en los anexos, para no interferir en el flujo de lectura del cuerpo principal. A partir de este estudio, analizamos la integración de Unidades de Aprendizaje con otros sistemas y especificaciones, abarcando desde la integración mínima mediante un enlace directo hasta la compartición de variables y estados que permiten una comunicación en tiempo real de ambas partes. Exponemos aquí también las conclusiones de diversos casos de estudio basados en adaptación que se anexan al final de la tesis y que se vuelven un instrumento imprescindible para lograr una solución real y aplicable. Como segundo pilar de la tesis complementario a la integración de Unidades de Aprendizaje, estudiamos el aprendizaje adaptativo: Los tipos, los avances y los enfoques y restricciones de modelado dentro de IMS-LD. Por último, y como complemento de la investigación teórica, a través de diversos casos prácticos estudiamos la manera en que IMS-LD modela la perzonalización del aprendizaje y hasta qué punto. Este primer bloque de análisis (general, integración y aprendizaje adaptativo) nos permite realizar una crítica estructural de IMS-LD en dos grandes apartados: Modelado y Arquitectura. Modelado apunta cuestiones que necesitan mejora, modificación, extensión o incorporación de elementos de modelado dentro de IMS-LD, como son procesos, componentes y recursos de programación. Arquitectura engloba otras cuestiones centradas en la comunicación que realiza IMS-LD con el exterior y que apuntan directamente a capas estructurales de la especificación, más allá del modelado. Aunque se encuentra fuera del núcleo de esta tesis, también se ha realizado una revisión de aspectos relacionados con Herramientas de autoría, por ser este un aspecto que condiciona el alcance del modelado y la penetración de la especificación en los distintos públicos objetivo. Sobre Herramientas, no obstante, no realizamos ninguna propuesta de mejora. La solución desarrollada, se centra en las diversas cuestiones sobre Modelado y Arquitectura encontradas en el análisis. Esta solución se compone de un conjunto de propuestas de estructuras, nuevas o ya existentes y modificadas, a través de las que se refuerza la capacidad expresiva de la especificación y la capacidad de interacción con un entorno de trabajo ajeno. Esta investigación de tres años ha sido llevada a cabo entre 2004 y 2007, principalmente con colegas de The Open University of The Netherlands, The University of Bolton, Universitat Pompeu Fabra y del departamento Research & Innovation de ATOS Origin, y ha sido desarrollada parcialmente dentro de proyectos europeos como UNFOLD, EU4ALL y ProLearn. La conclusión principal que se extrae de esta investigación es que IMS-LD necesita una reestructuración y modificación de ciertos elementos, así como la incorporación de otros nuevos, para mejorar una expresividad pedagógica y una capacidad de integración con otros sistemas de aprendizaje y estándares eLearning, si se pretenden alcanzar dos de los objetivos principales establecidos de base en la definición de esta especificación: La personalización del proceso de aprendizaje y la interoperabilidad real. Aun así, es cierto que la implantación de la especificación se vería claramente mejorada si existieran unas herramientas de más alto nivel (preferiblemente con planteamiento visual) que permitieran un modelado sencillo por parte de los usuarios finales reales de este tipo de especificaciones, como son los profesores, los creadores de contenido y los pedagogos-didactas que diseñan la experienicia de aprendizaje. Este punto, no obstante, es ajeno a la especificación y afecta a la interpretación que de la misma realizan los grupos de investigación y compañías que desarrollan soluciones de autoría. _____________________________________________IMS Learning Design (IMS-LD) is a current asset in eLearning and blended learning, due
to several reasons:
a) It is a specification that points to standardization and modeling of learning processes,
and not just content; at the same time, it is focused on the re-use of the information
packages in several contexts;
b) It shows a deeper pedagogical expressiveness than other specifications, already
delivered or in due process
c) It is integrated at different levels into well-known Learning Management Systems
(LMSs)
d) There are a huge amount of European research projects and groups working with it,
which aims at sustainability (in academia, at least)
Nevertheless, IMS-LD is roughly an initial outcome (be aware that we are still working
with the same release, dated on 2003). Therefore, it can and must be improved in
several aspects, i.e., pedagogical expressiveness and interoperability. In this thesis, we
concentrate on Adaptive Learning (or Personalised Learning) and on the Integration of
Units of Learning (UoLs). They both are core aspects which the specification is built upon.
They also can improve it significantly. Adaptation makes personalised learning itineraries,
adapted to every role, to every user involved in the process, and focus on several
aspects, i.e., flow, content and interface. Integration fosters the re-use of IMS-LD
information packages in different contexts and connects both-ways UoLs with other
specifications, models and LMSs. In order to achive these goals we carry out a threephase
analysis. First, analysis of IMS-LD in several steps: foundations, information
model, construction of UoLs. From Level A to Level C, we analyse and review the
specification structure. We lean on a theoretical frameword, along with a practical
approach, coming from the actual modeling of real UoLs which give an important report
back. Out of this analysis we get a report on the general structure of IMS-LD.
Second, analysis and review of the integration of UoLs with several LMSs, models and
specifications: we analyse three different types of integration: a) minimal integration,
with a simple link between parts; b) embedded integration, with a marriage of both parts
in a single information package; and d) full integration, sharing variables and states
between parts. In this step, we also show different case studies and report our partial
conclusions.
And third, analysis and review of how IMS-LD models adaptive learning: we define,
classify and explain several types of adaptation and we approach them with the specificacion. A key part of this step is the actual modeling of UoLs showing adaptive
learning processes. We highlight pros and cons and stress drawbacks and weak points
that could be improved in IMS-LD to support adaptation, but also general learning
processes
Out of this three-step analysis carried out so far (namely general, integration,
adaptation) we focus our review of the IMS-LD structure and information model on two
blocks: Modeling and Architecture. Modeling is focused on process, components and
programming resources of IMS-LD. Architecture is focused on the communication that
IMS-LD establishes outside, both ways, and it deals with upper layers of the specification,
beyong modeling issues. Modeling and Architecture issues need to be addressed in order
to improve the pedagogical expressiveness and the integration of IMS-LD. Furthermore,
we provide an orchestrated solution which meets these goals. We develop a structured
and organized group of modifications and extensions of IMS-LD, which match the
different reported problems issues. We suggest modifications, extensions and addition of
different elements, aiming at the strength of the specification on adaptation and
integration, along with general interest issues.
The main conclusion out of this research is that IMS-LD needs a re-structure and a
modification of some elements. It also needs to incorporate new ones. Both actions
(modification and extension) are the key to improve the pedagogical expressiveness and
the integration with other specifications and eLearning systems. Both actions aim at two
clear objectives in the definition of IMS-LD: the personalisation of learning processes,
and a real interoperability. It is fair to highlight the welcome help of high-level visual
authoring tools. They can support a smoother modeling process that could focus on
pedagogical issues and not on technical ones, so that a broad target group made of
teachers, learning designers, content creators and pedagogues could make use of the
specification in a simpler way. However, this criticism is outside the specification, so
outside the core of this thesis too.
This three-year research (2004-2007) has been carried out along with colleagues from
The Open University of The Netherlands, The University of Bolton, Universitat Pompeu
Fabra and from the Department of Research & Innovation of ATOS Origin. In addition, a
few European projects, like UNFOLD, EU4ALL and ProLearn, have partially supported it
Integration of e-learning systems into academic programmes in South African universities
No full textIncludes bibliographical references.This study set out to investigate the identified contradictions in conceptions, and to explain limited usage of a C/LMS among lecturers in South African universities. The goal was to empower curriculum planners, educators, policy makers, learners, system administrators and developers, with insight to improve e-Learning activities, and to make conceptual and theoretical contributions to the scientific body of knowledge. For this purpose, the interpretive research paradigm was adopted, together with qualitative data collection and analytical methods to investigate the factors affecting the integration of C/LMSs into academic programmes. Interviews were held with individual lecturers, and with groups of students at the Universities of Cape Town (UCT), Stellenbosch (US), the Western Cape (UWC), and the Cape Peninsula University of Technology (CPUT)
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