How should we measure online learning activity?

The proliferation of Web-based learning objects makes finding and evaluating resources a considerable hurdle for learners to overcome. While established learning analytics methods provide feedback that can aid learner evaluation of learning resources, the adequacy and reliability of these methods is questioned. Because engagement with online learning is different from other Web activity, it is important to establish pedagogically relevant measures that can aid the development of distinct, automated analysis systems. Content analysis is often used to examine online discussion in educational settings, but these instruments are rarely compared with each other which leads to uncertainty regarding their validity and reliability. In this study, participation in Massive Open Online Course (MOOC) comment forums was evaluated using four different analytical approaches: the Digital Artefacts for Learning Engagement (DiAL-e) framework, Bloom's Taxonomy, Structure of Observed Learning Outcomes (SOLO) and Community of Inquiry (CoI). Results from this study indicate that different approaches to measuring cognitive activity are closely correlated and are distinct from typical interaction measures. This suggests that computational approaches to pedagogical analysis may provide useful insights into learning processes.

Big Code Applications and Approaches

The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.

Vision-Based Solutions for Human-Robot Collaboration in Industrial Workcells

Industrial robots are both versatile and high performant, enabling the flexible automation typical of the modern Smart Factories. For safety reasons, however, they must be relegated inside closed fences and/or virtual safety barriers, to keep them strictly separated from human operators. This can be a limitation in some scenarios in which it is useful to combine the human cognitive skill with the accuracy and repeatability of a robot, or simply to allow a safe coexistence in a shared workspace. Collaborative robots (cobots), on the other hand, are intrinsically limited in speed and power in order to share workspace and tasks with human operators, and feature the very intuitive hand guiding programming method. Cobots, however, cannot compete with industrial robots in terms of performance, and are thus useful only in a limited niche, where they can actually bring an improvement in productivity and/or in the quality of the work thanks to their synergy with human operators. The limitations of both the pure industrial and the collaborative paradigms can be overcome by combining industrial robots with artificial vision. In particular, vision can be exploited for a real-time adjustment of the pre-programmed task-based robot trajectory, by means of the visual tracking of dynamic obstacles (e.g. human operators). This strategy allows the robot to modify its motion only when necessary, thus maintain a high level of productivity but at the same time increasing its versatility. Other than that, vision offers the possibility of more intuitive programming paradigms for the industrial robots as well, such as the programming by demonstration paradigm. These possibilities offered by artificial vision enable, as a matter of fact, an efficacious and promising way of achieving human-robot collaboration, which has the advantage of overcoming the limitations of both the previous paradigms yet keeping their strengths.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

A Brazilian Original Pedagogical Approach To The Teaching Of Neurology.

The two-arm Clinical Decisions/Diagnostic Workshop (CD/DW) approach to undergraduate medical education has been successfully used in Brazil. Present the CD/DW approach to the teaching of stroke, with the results of its pre-experimental application and of a comparative study with the traditional lecture-case discussion approach. Application of two questionnaires (opinion and Knowledge-Attitudes-Perceptions-KAP) to investigate the non-inferiority of the CD/DW approach. The method was well accepted by teachers and students alike, the main drawback being the necessarily long time for its completion by the students, a feature that may better cater for different educational needs. The comparative test showed the CD/DW approach to lead to slightly higher cognitive acquisition as opposed to the traditional method, clearly showing its non-inferiority status. The CD/DW approach seems to be another option for teaching neurology in undergraduate medical education, with the bonus of respecting each learner`s time.

Delivery Of A Urology Online Course Using Moodle Versus Didactic Lectures Methods.

To subjectively and objectively compare an accessible interactive electronic library using Moodle with lectures for urology teaching of medical students. Forty consecutive fourth-year medical students and one urology teacher were exposed to two teaching methods (4 weeks each) in the form of problem-based learning: - lectures and - student-centered group discussion based on Moodle (modular object-oriented dynamic learning environment) full time online delivered (24/7) with video surgeries, electronic urology cases and additional basic principles of the disease process. All 40 students completed the study. While 30% were moderately dissatisfied with their current knowledge base, online learning course delivery using Moodle was considered superior to the lectures by 86% of the students. The study found the following observations: (1) the increment in learning grades ranged from 7.0 to 9.7 for students in the online Moodle course compared to 4.0-9.6 to didactic lectures; (2) the self-reported student involvement in the online course was characterized as large by over 60%; (3) the teacher-student interaction was described as very frequent (50%) and moderately frequent (50%); and (4) more inquiries and requisitions by students as well as peer assisting were observed from the students using the Moodle platform. The Moodle platform is feasible and effective, enthusing medical students to learn, improving immersion in the urology clinical rotation and encouraging the spontaneous peer assisted learning. Future studies should expand objective evaluations of knowledge acquisition and retention.

The case of thyroid hormones: how to learn physiology by solving a detective case

Lellis-Santos C, Giannocco G, Nunes MT. The case of thyroid hormones: how to learn physiology by solving a detective case. Adv Physiol Educ 35: 219-226, 2011; doi:10.1152/advan.00135.2010.Thyroid diseases are prevalent among endocrine disorders, and careful evaluation of patients' symptoms is a very important part in their diagnosis. Developing new pedagogical strategies, such as problem-based learning (PBL), is extremely important to stimulate and encourage medical and biomedical students to learn thyroid physiology and identify the signs and symptoms of thyroid dysfunction. The present study aimed to create a new pedagogical approach to build deep knowledge about hypo-/hyperthyroidism by proposing a hands-on activity based on a detective case, using alternative materials in place of laboratory animals. After receiving a description of a criminal story involving changes in thyroid hormone economy, students collected data from clues, such as body weight, mesenteric vascularization, visceral fat, heart and thyroid size, heart rate, and thyroid-stimulating hormone serum concentration to solve the case. Nevertheless, there was one missing clue for each panel of data. Four different materials were proposed to perform the same practical lesson. Animals, pictures, small stuffed toy rats, and illustrations were all effective to promote learning, and the detective case context was considered by students as inviting and stimulating. The activity can be easily performed independently of the institution's purchasing power. The practical lesson stimulated the scientific method of data collection and organization, discussion, and review of thyroid hormone actions to solve the case. Hence, this activity provides a new strategy and alternative materials to teach without animal euthanization.

Undergraduate teaching of ideal and real fluid flows: The value of real-world experimental projects

This study describes the pedagogical impact of real-world experimental projects undertaken as part of an advanced undergraduate Fluid Mechanics subject at an Australian university. The projects have been organised to complement traditional lectures and introduce students to the challenges of professional design, physical modelling, data collection and analysis. The physical model studies combine experimental, analytical and numerical work in order to develop students’ abilities to tackle real-world problems. A first study illustrates the differences between ideal and real fluid flow force predictions based upon model tests of buildings in a large size wind tunnel used for research and professional testing. A second study introduces the complexity arising from unsteady non-uniform wave loading on a sheltered pile. The teaching initiative is supported by feedback from undergraduate students. The pedagogy of the course and projects is discussed with reference to experiential, project-based and collaborative learning. The practical work complements traditional lectures and tutorials, and provides opportunities which cannot be learnt in the classroom, real or virtual. Student feedback demonstrates a strong interest for the project phases of the course. This was associated with greater motivation for the course, leading in turn to lower failure rates. In terms of learning outcomes, the primary aim is to enable students to deliver a professional report as the final product, where physical model data are compared to ideal-fluid flow calculations and real-fluid flow analyses. Thus the students are exposed to a professional design approach involving a high level of expertise in fluid mechanics, with sufficient academic guidance to achieve carefully defined learning goals, while retaining sufficient flexibility for students to construct there own learning goals. The overall pedagogy is a blend of problem-based and project-based learning, which reflects academic research and professional practice. The assessment is a mix of peer-assessed oral presentations and written reports that aims to maximise student reflection and development. Student feedback indicated a strong motivation for courses that include a well-designed project component.

Lectures and other types of teaching

A questionnaire on lectures was completed by 351 students (84% response) and 35 staff (76% response) from all five years of the veterinary course at the University of Queensland. Staff and students in all five years offered limited support for a reduction in the number of lectures in the course and the majority supported a reduction in the number of lectures in the clinical years. Students in the clinical years only and appropriate staff agreed that the number of lectures in fifth year should be reduced but were divided as to whether lectures in fifth year should be abolished. There was limited support for replacement of some lectures by computer assisted learning (CAL) programs, but strong support for replacement of some lectures by subject-based problem based learning (PBL) and strong support for more self-directed learning by students. Staff and students strongly supported the inclusion of more clinical problem solving in lectures in the clinical years and wanted these lectures to be more interactive. There was little support for lectures in the clinical years to be of the same type as in the preclinical years.

Graduate entry to medical studies: thoughts from 'down under' (editorial)

This invited editorial, reflecting on expectations of changing to graduate entry, eg enhanced maturity in the student cohort with greater self-sufficiency and taking of responsibility for learning in the context of adoption of a problem-based learning model, examines experiences of early post-change years and raises questions for contemplation by medical schools considering graduate entry.

Lidar com o sofrimento em Fisioterapia: a experiência formativa na ESTSP-IPP

A comunicação e a relação terapêutica são reconhecidamente domínios de competência dos profissionais de saúde cujas funções impliquem o contacto com doentes (Corney, 2000; Grilo & Pedro, 2005; Pio Abreu, 1998). Além do seu papel determinante na adesão terapêutica, a qualidade da comunicação e da relação terapêutica estabelecida tem particular impacto no sofrimento da pessoa, tomado como constructo multidimensional (McIntyre, 2004). Tradicionalmente descurados na formação académica, estes temas tendem actualmente a ganhar expressão nos currículos, para o que contribuíram, no espaço europeu, as recomendações para a adequação a Bolonha (Lopes, 2004). Neste trabalho, descrevemos a metodologia de formação adoptada para estes domínios na licenciatura em Fisioterapia da ESTSP-IPP, a funcionar segundo o modelo pedagógico designado Problem-Based Learning (Walsh, 2005; Macedo, 2009). Além dos conhecimentos disseminados ao longo de toda a estrutura curricular, temas como a comunicação (Watzlawick, Bavelas & Jackson, 1967/1993), a escuta activa (Gordon & Edwards, 1997), a relação terapêutica (Rogers, 1957/1992, 1980, 1985), as competências e microcompetências/técnicas de atendimento e de observação (Ivey, 1983; Ivey & Downing, 1990; Ivey, Gluckstern & Ivey, 2006) ou as comunicações difíceis (Faulkner, Maguire & Regnard, 1994; Maguire, 2000) são alvo de formação mais intensiva ao longo de cerca de 16 semanas consecutivas do 1º ciclo de estudos, com recurso a diferentes tipologias de aula visando desenvolver, além dos conhecimentos, atitudes e habilidades nestes domínios.

A influência do modelo pedagógico em variáveis psicológicas de estudantes do 1º ano da ESTSP-IPP

Introdução – A adaptação ao ensino superior reveste-se de experiências académicas que podem constituir fonte de stress para os estudantes. A implementação de novos modelos pedagógicos, no âmbito do processo de Bolonha, introduz novas variáveis cujo impacto, designadamente em termos de saúde, importa conhecer. Este estudo tem como objetivo analisar as associações entre modelo pedagógico (Problem Based Learning – PBL vs. modelos próximos do tradicional) e variáveis psicológicas (coping, desregulação emocional, sintomas psicossomáticos, perceção de stress e afeto). Metodologia – O estudo tem um design transversal. Foram usados os seguintes questionários online: Brief-COPE, Escala de Dificuldades de Regulação Emocional, Questionário de Manifestações Físicas de Mal-Estar, Escala de Stress Percebido e Escala de Afeto Positivo e Negativo. A amostra é constituída por 183 estudantes do primeiro ano (84% do género feminino) de cursos da Escola Superior de Tecnologia da Saúde do Porto – Instituto Politécnico do Porto (ESTSP-IPP). Resultados – Foram encontradas correlações significativas entre as variáveis demográficas e psicológicas. Considerando diferentes modelos pedagógicos, foram encontradas diferenças significativas nas variáveis psicológicas. Os principais preditores de stress na amostra foram: ser mulher, frequentar uma licenciatura no modelo PBL, ter maiores índices de desregulação emocional, apresentar mais sintomas psicossomáticos, menos afeto positivo e mais afeto negativo. Conclusão – As diferenças encontradas entre modelos pedagógicos são discutidas, possibilitando a reflexão sobre as implicações práticas e sugestões para futuras investigações.

Students' engagement in schools : differentiation and promotion

The objective of this work is to present elements of the project Student engagement in Schools (SES). The team consists of 10 researchers from six Universities. Student engagement in schools is a multidimensional construct that unites affective, behavioural, and cognitive dimensions of student adaptation in the school and has influence on students’outcomes. The team of researchers conceptualized two major studies, a differential study to analyze the relations between SES and contextual factors, personal factors, student’s outcomes, and a quasi-experimental study to analyze the effects on SES of a specific intervention programmes. In study 1, the sample size is around 600 students (150 6th graders, 150 7th graders, 150 9th graders, and 150 10th graders). We shall focus on years of school transition, with rural and urban populations, on different regions of the country, and on students with different family background. We shall conduct questionnaires with national and international scales. The study 2 will involve students in 7th and 9th grade, from four classes, two of the experimental group and two of the control group. Patterns of verbal communication between a teacher and students can influence the classroom environment and SES. This model of communication would result in more effective student management and more time on-task for learning.

Methodology for in-game certification in serious games

Serious games are starting to attain a higher role as tools for learning in various contexts, but in particular in areas such as education and training. Due to its characteristics, such as rules, behavior simulation and feedback to the player's actions, serious games provide a favorable learning environment where errors can occur without real life penalty and students get instant feedback from challenges. These challenges are in accordance with the intended objectives and will self-adapt and repeat according to the student’s difficulty level. Through motivating and engaging environments, which serve as base for problem solving and simulation of different situations and contexts, serious games have a great potential to aid players developing professional skills. But, how do we certify the acquired knowledge and skills? With this work we intend to propose a methodology to establish a relationship between the game mechanics of serious games and an array of competences for certification, evaluating the applicability of various aspects in the design and development of games such as the user interfaces and the gameplay, obtaining learning outcomes within the game itself. Through the definition of game mechanics combined with the necessary pedagogical elements, the game will ensure the certification. This paper will present a matrix of generic skills, based on the European Framework of Qualifications, and the definition of the game mechanics necessary for certification on tour guide training context. The certification matrix has as reference axes: skills, knowledge and competencies, which describe what the students should learn, understand and be able to do after they complete the learning process. The guides-interpreters welcome and accompany tourists on trips and visits to places of tourist interest and cultural heritage such as museums, palaces and national monuments, where they provide various information. Tour guide certification requirements include skills and specific knowledge about foreign languages and in the areas of History, Ethnology, Politics, Religion, Geography and Art of the territory where it is inserted. These skills are communication, interpersonal relationships, motivation, organization and management. This certification process aims to validate the skills to plan and conduct guided tours on the territory, demonstrate knowledge appropriate to the context and finally match a good group leader. After defining which competences are to be certified, the next step is to delineate the expected learning outcomes, as well as identify the game mechanics associated with it. The game mechanics, as methods invoked by agents for interaction with the game world, in combination with game elements/objects allows multiple paths through which to explore the game environment and its educational process. Mechanics as achievements, appointments, progression, reward schedules or status, describe how game can be designed to affect players in unprecedented ways. In order for the game to be able to certify tour guides, the design of the training game will incorporate a set of theoretical and practical tasks to acquire skills and knowledge of various transversal themes. For this end, patterns of skills and abilities in acquiring different knowledge will be identified.