The experience of teaching statistics to non-specialist students in Saudi universities

Undoubtedly, statistics has become one of the most important subjects in the modern world, where its applications are ubiquitous. The importance of statistics is not limited to statisticians, but also impacts upon non-statisticians who have to use statistics within their own disciplines. Several studies have indicated that most of the academic departments around the world have realized the importance of statistics to non-specialist students. Therefore, the number of students enrolled in statistics courses has vastly increased, coming from a variety of disciplines. Consequently, research within the scope of statistics education has been able to develop throughout the last few years. One important issue is how statistics is best taught to, and learned by, non-specialist students. This issue is controlled by several factors that affect the learning and teaching of statistics to non-specialist students, such as the use of technology, the role of the English language (especially for those whose first language is not English), the effectiveness of statistics teachers and their approach towards teaching statistics courses, students’ motivation to learn statistics and the relevance of statistics courses to the main subjects of non-specialist students. Several studies, focused on aspects of learning and teaching statistics, have been conducted in different countries around the world, particularly in Western countries. Conversely, the situation in Arab countries, especially in Saudi Arabia, is different; here, there is very little research in this scope, and what there is does not meet the needs of those countries towards the development of learning and teaching statistics to non-specialist students. This research was instituted in order to develop the field of statistics education. The purpose of this mixed methods study was to generate new insights into this subject by investigating how statistics courses are currently taught to non-specialist students in Saudi universities. Hence, this study will contribute towards filling the knowledge gap that exists in Saudi Arabia. This study used multiple data collection approaches, including questionnaire surveys from 1053 non-specialist students who had completed at least one statistics course in different colleges of the universities in Saudi Arabia. These surveys were followed up with qualitative data collected via semi-structured interviews with 16 teachers of statistics from colleges within all six universities where statistics is taught to non-specialist students in Saudi Arabia’s Eastern Region. The data from questionnaires included several types, so different techniques were used in analysis. Descriptive statistics were used to identify the demographic characteristics of the participants. The chi-square test was used to determine associations between variables. Based on the main issues that are raised from literature review, the questions (items scales) were grouped and five key groups of questions were obtained which are: 1) Effectiveness of Teachers; 2) English Language; 3) Relevance of Course; 4) Student Engagement; 5) Using Technology. Exploratory data analysis was used to explore these issues in more detail. Furthermore, with the existence of clustering in the data (students within departments within colleges, within universities), multilevel generalized linear models for dichotomous analysis have been used to clarify the effects of clustering at those levels. Factor analysis was conducted confirming the dimension reduction of variables (items scales). The data from teachers’ interviews were analysed on an individual basis. The responses were assigned to one of the eight themes that emerged from within the data: 1) the lack of students’ motivation to learn statistics; 2) students' participation; 3) students’ assessment; 4) the effective use of technology; 5) the level of previous mathematical and statistical skills of non-specialist students; 6) the English language ability of non-specialist students; 7) the need for extra time for teaching and learning statistics; and 8) the role of administrators. All the data from students and teachers indicated that the situation of learning and teaching statistics to non-specialist students in Saudi universities needs to be improved in order to meet the needs of those students. The findings of this study suggested a weakness in the use of statistical software applications in these courses. This study showed that there is lack of application of technology such as statistical software programs in these courses, which would allow non-specialist students to consolidate their knowledge. The results also indicated that English language is considered one of the main challenges in learning and teaching statistics, particularly in institutions where English is not used as the main language. Moreover, the weakness of mathematical skills of students is considered another major challenge. Additionally, the results indicated that there was a need to tailor statistics courses to the needs of non-specialist students based on their main subjects. The findings indicate that statistics teachers need to choose appropriate methods when teaching statistics courses.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

“English Language Learning Strategies used by the Foreign Language Department Seminar Students Year 2006 with Either Above Eight Grade or Below it Obtained in Their Studies in the Basic Skills Area.

Nowadays language communication plays an important role in the world. For the technological explosion in the 20th century, the electronic mass media collapsed space and time barriers in human communication, enabling people to interact and live on a global scale. In this sense, the earth has been turned into a village by the electronic mass media. It not only changes the distance between countries, societies, but also shortens it between people. It means that the technological advancement makes the earth become a village. Since the distance between people is shortened, language communication becomes more important than before. To enhance language abilities, people can apply many different types of language learning strategies according to the learning styles that they have in order to learn the target language. In the Foreign Language Department of University of El Salvador Seminar students year 2006 apply different language learning strategies which make some of them get a grade either above eight or below it. To understand learning strategies, people can go back to basic term, strategy. This word comes from the ancient Greek term strategia meaning generalship or the art of war. A different, but related, word is tactics, which are tools to achieve the success of strategies. The two expressions share some basic implied characteristics: planning, competition, conscious manipulation, and movement toward a goal.

Movement Sonification: Effects on Motor Learning beyond Rhythmic Adjustments

Motor learning is based on motor perception and emergent perceptual-motor representations. A lot of behavioral research is related to single perceptual modalities but during last two decades the contribution of multimodal perception on motor behavior was discovered more and more. A growing number of studies indicates an enhanced impact of multimodal stimuli on motor perception, motor control and motor learning in terms of better precision and higher reliability of the related actions. Behavioral research is supported by neurophysiological data, revealing that multisensory integration supports motor control and learning. But the overwhelming part of both research lines is dedicated to basic research. Besides research in the domains of music, dance and motor rehabilitation, there is almost no evidence for enhanced effectiveness of multisensory information on learning of gross motor skills. To reduce this gap, movement sonification is used here in applied research on motor learning in sports. Based on the current knowledge on the multimodal organization of the perceptual system, we generate additional real-time movement information being suitable for integration with perceptual feedback streams of visual and proprioceptive modality. With ongoing training, synchronously processed auditory information should be initially integrated into the emerging internal models, enhancing the efficacy of motor learning. This is achieved by a direct mapping of kinematic and dynamic motion parameters to electronic sounds, resulting in continuous auditory and convergent audiovisual or audio-proprioceptive stimulus arrays. In sharp contrast to other approaches using acoustic information as error-feedback in motor learning settings, we try to generate additional movement information suitable for acceleration and enhancement of adequate sensorimotor representations and processible below the level of consciousness. In the experimental setting, participants were asked to learn a closed motor skill (technique acquisition of indoor rowing). One group was treated with visual information and two groups with audiovisual information (sonification vs. natural sounds). For all three groups learning became evident and remained stable. Participants treated with additional movement sonification showed better performance compared to both other groups. Results indicate that movement sonification enhances motor learning of a complex gross motor skill-even exceeding usually expected acoustic rhythmic effects on motor learning.

e-Astro: O e-learning aplicado ao ensino da astronomia: Planetas telúricos

A investigação em didáctica das ciências tem mostrado que a generalidade dos alunos manifesta cada vez menos interesse para aprender ciências. No entanto, o incremento da importância de temas científicos no nosso dia-a-dia, exige dos indivíduos um conhecimento científico cada vez mais aprofundado. O estudo da Astronomia permite abordar e interligar os conteúdos de tisica mais facilmente, tomando possível a aproximação do conhecimento científico ao conhecimento do quotidiano, mostrando a estreita ligação entre a Física, a Sociedade e a Tecnologia. O processo de ensino-aprendizagem encontra-se em mudança devido à integração das T.I.C. Através da internet e tirando partido da multimédia é possível desenvolver uma formação científica adequada que contribua para o despertar da curiosidade e do interesse dos alunos pela Ciência. Tendo em conta os pressupostos anteriores pretende-se, com este estudo, desenvolver uma plataforma de e-learning e recursos multimédia que satisfaçam estes requisitos. ABSTRACT; The investigation in didactics of sciences has been showing that the generality of students show less and less interest to learn sciences. However, the increment of the importance of scientific themes in our day-to-day life, demands from the individuals an increasingly deeper scientific knowledge. The study of Astronomy allows to approach and to interconnect physics subjects more easily, making possible the approach of scientific knowledge to the knowledge of everyday life, showing the narrow connection among Physics, Society and Technology. The teaching-learning process is in change duet the integration of the I.C.T. Through the internet and taking advantage of multimedia it is possible to develop an appropriate scientific formation that contributes to the awakening of curiosity and of the student's interest for Science. Having in mind the previous presuppositions is intended, with this study, to develop an e-learning platform and multimedia resources that satisfy these requirements.

Intergenerational learning with ICT: a case study

In a context of rapid demographic and technological changes, digital skills are essential in order for citizens to actively participate in society. However, digital literacy for all citizens, especially for the older population, is not yet a reality. It is increasingly crucial for active ageing, lifelong learning, and life-wide learning that the elderly learn digital skills. Intergenerational learning can play a key role in achieving a wide range of goals. This paper focuses on the contribution of intergenerational learning to digital and social inclusion. We promoted ICT intergenerational workshops and chose the case study methodolog y to study three distinct cases of intergenerational learning with ICT. The results show that intergenerational learning with ICT contributes to the digital literacy of adults and seniors and fosters lifelong learning, active ageing, and understanding and solidarity among generations. We reveal the benefits of the intergenerational learning process for all participants and suggest some ways to achieve intergenerational learning through ICT in order to build more socially and digitally cohesive societies.

Investigating problem-based learning in Saudi Arabian mathematics education: a TIMSS-related study

The aim of this study is to investigate the effectiveness of problem-based learning (PBL) on students’ mathematical performance. This includes mathematics achievement and students’ attitudes towards mathematics for third and eighth grade students in Saudi Arabia. Mathematics achievement includes, knowing, applying, and reasoning domains, while students’ attitudes towards mathematics covers, ‘Like learning mathematics’, ‘value mathematics’, and ‘a confidence to learn mathematics’. This study goes deeper to examine the interaction of a PBL teaching strategy, with trained face-to-face and self-directed learning teachers, on students’ performance (mathematics achievement and attitudes towards mathematics). It also examines the interaction between different ability levels of students (high and low levels) with a PBL teaching strategy (with trained face-to-face or self-directed learning teachers) on students’ performance. It draws upon findings and techniques of the TIMSS international benchmarking studies. Mixed methods are used to analyse the quasi-experimental study data. One -way ANOVA, Mixed ANOVA, and paired t-tests models are used to analyse quantitative data, while a semi-structured interview with teachers, and author’s observations are used to enrich understanding of PBL and mathematical performance. The findings show that the PBL teaching strategy significantly improves students’ knowledge application, and is better than the traditional teaching methods among third grade students. This improvement, however, occurred only with the trained face-to-face teacher’s group. Furthermore, there is robust evidence that using a PBL teaching strategy could raise significantly students’ liking of learning mathematics, and confidence to learn mathematics, more than traditional teaching methods among third grade students. Howe ver, there was no evidence that PBL could improve students’ performance (mathematics achievement and attitudes towards mathematics), more than traditional teaching methods, among eighth grade students. In 8th grade, the findings for low achieving students show significant improvement compared to high achieving students, whether PBL is applied or not. However, for 3th grade students, no significant difference in mathematical achievement between high and low achieving students was found. The results were not expected for high achieving students and this is also discussed. The implications of these findings for mathematics education in Saudi Arabia are considered.

Towards an understanding of Pakistani undergraduates’ current attitudes towards learning and speaking English

The English language has an important place in Pakistan and in its education system, not least because of the global status of English and its role in employment. Realising the need to enhance language learning outcomes, especially at the tertiary level, the Higher Education Commission (HEC) of Pakistan has put in place some important measures to improve the quality of English language teaching practice through its English Language Teaching Reforms (ELTR) project. However, there is a complex linguistic, educational and ethnic diversity in Pakistan and that diversity, alongside the historical and current role of English in the country, makes any language teaching reform particularly challenging. I argue, in this thesis, that reform to date has largely ignored the issues of learner readiness to learn and learner perceptions of the use of English. I argue that studying learner attitudes is important if we are to understand how learners perceive the practice of learning and the use of English in their lives. This study focuses on the attitudes of undergraduate learners of English as a foreign language at two universities in the provinces of Sindh and Balochistan in Pakistan. These provinces have experienced long struggles and movements related to linguistic and ethnic rights and both educate students from all of the districts of their respective provinces. Drawing on debates around linguistic imperialism, economic necessity, and linguistic and educational diversity, I focus on learners’ perceptions about learning and speaking English, asking what their attitudes are towards learning and speaking English with particular reference to socio-psychological factors at a given time and context, including perceived threats to their culture, religion, and mother tongue. I ask how they make choices about learning and speaking English in different domains of language use and question their motivation to learn and speak English. Additionally, I explore issues of anxiety with reference to their use of English. Following a predominantly qualitative mixed methods research approach, the study employs two research tools: an adapted Likert Scale questionnaire completed by 300 students and semi-structured interviews with 20 participants from the two universities. The data were analysed through descriptive statistics and qualitative content analysis, with each set of data synthesised for interpretation. The findings suggest that, compared with the past, the majority of participants hold positive attitudes towards learning and speaking English regardless of their ethnic or linguistic backgrounds. Most of these undergraduate students do not perceive the use of English as a threat to their culture, mother tongue or religious values but, instead, they have a pragmatic and, at the same time, aspirational attitude to the learning and use of English. I present these results and conclude this thesis with reference to ways in which this small-scale study contributes to a better understanding of learner attitudes and perceptions. Acknowledging the limitations of this study, I suggest ways in which the study, enhanced and extended by further research, might have implications for practice, theory and policy in English language teaching and learning in Pakistan.

A Visual Analytics Approach to Comparing Cohorts of Event Sequences

Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

Action and perception: Neural indices of learning in infants

Early human development offers a unique perspective in investigating the potential cognitive and social implications of action and perception. Specifically, during infancy, action production and action perception undergo foundational developments. One essential component to examine developments in action processing is the analysis of others’ actions as meaningful and goal-directed. Little research, however, has examined the underlying neural systems that may be associated with emerging action and perception abilities, and infants’ learning of goal-directed actions. The current study examines the mu rhythm—a brain oscillation found in the electroencephalogram (EEG)—that has been associated with action and perception. Specifically, the present work investigates whether the mu signal is related to 9-month-olds’ learning of a novel goal-directed means-end task. The findings of this study demonstrate a relation between variations in mu rhythm activity and infants’ ability to learn a novel goal-directed means-end action task (compared to a visual pattern learning task used as a comparison task). Additionally, we examined the relations between standardized assessments of early motor competence, infants’ ability to learn a novel goal-directed task, and mu rhythm activity. We found that: 1a) mu rhythm activity during observation of a grasp uniquely predicted infants’ learning on the cane training task, 1b) mu rhythm activity during observation and execution of a grasp did not uniquely predict infants’ learning on the visual pattern learning task (comparison learning task), 2) infants’ motor competence did not predict infants’ learning on the cane training task, 3) mu rhythm activity during observation and execution was not related to infants’ measure of motor competence, and 4) mu rhythm activity did not predict infants’ learning on the cane task above and beyond infants’ motor competence. The results from this study demonstrate that mu rhythm activity is a sensitive measure to detect individual differences in infants’ action and perception abilities, specifically their learning of a novel goal-directed action.

Community School of São Miguel de Machede: A decade of Learning

the Community School of São Miguel de Machede exists since 1998. A model of Community Education has been developed in this decade of existence, which not being confined to the frequent profiles of the most common approaches in Adult Education, has been the result of a process of symbiosis between a practice that normally precedes the conceptualization and a thought which has always expressed the concern of interpreting and enrich that practice. Setting on a model of learning based on the PADéCA – Program of Helping the Development of the Capacity to Learn, proposed by Berbaum (1988), the Community School of São Miguel de Machede has been developing several activities centred on a fundamental concern: to create easy and qualified accesses, in this community (council of Evora), so that the respective members can learn to exercise their principal rights of citizenship, in the territory where they live and in a circumstance of equality of opportunities in relation to the remaining fellow countrymen. Being a project with a decade of life, it is now possible to speak of a history full of stories and learning experiences, which occurred as a result of a rich interaction between the initial thoughts and impulses of the theoretical approaches and a reality full of unexpectedness, mutability and humanity resulting from the complexity that a living community presents, with a history and a present, but not always with clear and positive idea about the respective future.

Perceived benefits, motivations and preferences for foreign language learning by older adults. Insights from an initiative in Cuenca, Ecuador

El presente estudio analiza las percepciones y actitudes que tienen los adultos mayores de la ciudad de Cuenca, Ecuador hacia el aprendizaje del inglés. Un total de 151 adultos mayores (con edad promedio de 70.3 años) respondió a un cuestionario con 50 ítems. Se llevó a cabo análisis factoriales, de regresión múltiple y cluster con el propósito de definir las dimensiones subyacentes en las percepciones, motivaciones y ambiciones de los adultos mayores para aprender un idioma extranjero, y su relación con las características sociodemográficas de los participantes. Los resultados señalan que el interés por estudiar un idioma extranjero está basado en la percepción de que aquello mejora la interacción social de las personas, su desarrollo personal, el funcionamiento y mantenimiento de la mente y memoria, y que activa y vuelve su vida más dinámica. Los resultados además revelaron que la principal motivación de los participantes para tomar un curso de inglés está relacionada con el potencial de usar este idioma en la vida diaria y el de leer profusamente en esa lengua extranjera. La duración del curso y la obtención de un certificado fueron factores determinantes que permitieron agrupar a los participantes en función de sus preferencias en lo que respecta al diseño práctico de un curso de inglés. Adicionalmente, la edad y el nivel de instrucción fueron variables determinantes de motivación que influyeron en la mayor parte de las respuestas dadas por los participantes.

Interactive storytelling to improve the listening skill of 8th grade at INAN High School

Este trabajo de investigación se trata de Cuentacuentos de respuesta física total y su influencia en el proceso de enseñanza-aprendizaje de Inglés como segunda lengua de los estudiantes del octavo grado de Educación General Básica del Colegio "INTEGRACIÓN ANDINA" en la ciudad de Cuenca en el Año Lectivo 2014 y 2015. Es necesario un nuevo sistema educativo para responder a las necesidades de la sociedad actual para permitir el desarrollo general de la educación, implementando un nuevo programa de enseñanza en el aprendizaje del Inglés a través de la narración. La búsqueda de una mejor manera de aprender y enseñar es responsabilidad ineludible de todos los maestros que deben enfrentar los desafíos con entusiasmo mientras se mira hacia innovaciones futuras permitiendo a los estudiantes mejorar sus habilidades de escucha y demás destrezas. Dado que el 90% de conocimiento de un nuevo idioma se adquiere a través de la lectura; el uso de Cuentacuentos ayuda a los estudiantes a adquirir el conocimiento necesario que será la base para un alto nivel cultural, tanto en el aprendizaje y en el desarrollo de habilidades de lenguaje, la lectura es un medio esencial para el desarrollo cultural en Educación. La falta de preparación en la lectura obstaculiza los esfuerzos del maestro secundario para lograr una formación integral en el alumno. Es necesario implementar estrategias para tratar de superar la falta de lectura, mediante el uso de la narración de cuentos en clase para animar a los estudiantes a leer en casa.

Traditional games are recovered from generation to generation

Communities, neighborhoods, and other environments are currently immersed in a series of situations and problems that have favored the deterioration of social, cultural and spiritual values, which are essential for harmony with oneself, others, and the environment. Stereotypes have captured minds and settings have been reduced to indoor spaces, hemmed in by security bars and protective devices.  Peace, fraternity and happiness are diminishing.  It is at this point that the social, spiritual and professional work of specialists in the recreational field contributes to rescue and restructure society. Traditional games and singing games are then the tools used to facilitate relationships, contribute to the learning process, and exhibit skills.  They are fundamental in a person’s life since they are a social and cultural expression of how humans have adapted to their environment (Maestro, 2005).  They do not take ethnicity, age, sex or social conditions into consideration.  Traditional games are also a way of promoting health, improving motor, cognitive and emotional skills and a means of encouraging creativity and imagination and developing a sense of rhythm.  Their goal is to attain a state of personal well-being.  They are a way to release tension and accumulated energy and to get away from the daily routine.  They represent a bridge to learn about oneself, the environment, values, habits, and traditions. In this document, readers will learn how traditional games are transmitted, what their characteristics are, why they are an important tool in today’s society, how they are prepared, and how they can be revived and preserved.

Studies of CMS data access patterns with machine learning techniques

This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy over time and different access patterns, and ultimately to extract suggested actions based on this information (e.g. targetted disk clean-up and/or data replication). In this sense, the application of Machine Learning techniques allows to learn from past data and to gain predictability potential for the future CMS data access patterns. Chapter 1 provides an introduction to High Energy Physics at the LHC. Chapter 2 describes the CMS Computing Model, with special focus on the data management sector, also discussing the concept of dataset popularity. Chapter 3 describes the study of CMS data access patterns with different depth levels. Chapter 4 offers a brief introduction to basic machine learning concepts and gives an introduction to its application in CMS and discuss the results obtained by using this approach in the context of this thesis.