ne-Course for Learning Programming

Difficulties in learning programming are a constant concern in engineering courses. In many research studies involving the learning programming must of the solutions presented, from the beginning of the first programming languages, was to apply different type of problems analysis. Literature relating to the understanding of nature of learning programming skills has been focused explicitly on the teaching methodology and few of them focus on abilities, characteristics and knowledge acquired over the life cycle of learning programming in each student. Most of the students enrolled in engineering courses, where programming is a crucial competence, never had the opportunity to develop skills of computational thinking. In this paper, we focus our work on the learning programming developing and applying a set of exercises where students with more difficulties can express and develop their skills in computational thinking. In order to understand some programming students difficulties we have create a set of exercises, and apply it to a pre-programming course, that allows teachers to understand how students analyse and comprehend aspects such as visualization, spatial interpretation and physical manipulation. This paper also reports on results obtained from a class experiment where Memory Transfer Language was used by students to learn programming. All the exercises must be resolved without any type of technology, designed as a ne-course (no electronic course) for learning programming

ne-Course for Learning Programming

Difficulties in learning programming are a constant concern in engineering courses. In many research studies involving the learning programming must of the solutions presented, from the beginning of the first programming languages, was to apply different type of problems analysis. Literature relating to the understanding of nature of learning programming skills has been focused explicitly on the teaching methodology and few of them focus on abilities, characteristics and knowledge acquired over the life cycle of learning programming in each student. Most of the students enrolled in engineering courses, where programming is a crucial competence, never had the opportunity to develop skills of computational thinking. In this paper, we focus our work on the learning programming developing and applying a set of exercises where students with more difficulties can express and develop their skills in computational thinking. In order to understand some programming students difficulties we have create a set of exercises, and apply it to a pre-programming course, that allows teachers to understand how students analyse and comprehend aspects such as visualization, spatial interpretation and physical manipulation. This paper also reports on results obtained from a class experiment where Memory Transfer Language was used by students to learn programming. All the exercises must be resolved without any type of technology, designed as a ne-course (no electronic course) for learning programming

Students\u27 explanations in complex learning of disciplinary programming

Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with low ability to do programming engage in a more thorough explanation process than students with high ability. This dissertation concludes proposing an adaptation to the instructional principles of worked-examples for the context of CSE education

TRACING LEARNING ENVIRONMENT IN JAVA PROGRAMMING LANGUAGE

The visualisation approach is one of the programming learning styles that has been taken into account in programming education. A collection of visualisation tools has emerged with the aim of assisting novice programmers in learning how to program. Each tool has its own set of features that may or may not be helpful in gaining a better understanding. The methods that we used in this study are focused on using memory referencing and visualisation to clarify what happens during individual program statement executions. Understanding the efficacy of current instructional resources is a critical component of gathering students' requirements and needs for future improvement. The “Tracing Learning Environment” (TLE) is developed for novice programmers to help them trace the sequence of execution of a software program and the reserved place of data in the memory. The framework relies on using visualisation as the programs are run and to show the effect of each statement in the code. It provides an environment for learners to see what happens to the data while running the program. The specification of the TLE draws largely on research regarding the role of visualisation in teaching computer programming and associated literature on tools to support learning programming. The TLE framework has been evaluated by conducting an empirical study using a mixed-method approach with novice and expert participants. The study has included surveys, focus groups, and semi-structured interviews. Student performance was measured before and after using the visualisation tool and compared with a control group who participated in a standard teaching session only. Early findings highlighted the need to visualise the control of the execution of code, evaluation of expressions, represent the class hierarchy along with the importance of a good interface/usability of the tool and to consider the programming languages supported. The evaluation findings are in line with the literature surrounding the benefits of using visualisation in learning to program. The findings found visualisation increased the students’ performance and confidence. When compared to the regular lab activities, the visualisation contributed to better understanding and support for learning to program.Ministry of Education, Saudi Arabi

Prior knowledge contribution to declarative learning. A study in amnesia, aging and Alzheimer's disease

L'étude expérimentale de la mémoire humaine a connu deux moments historiques dans les soixante dernières années. 1957 marque la découverte du rôle du lobe temporal interne bilatéral dans l'apprentissage conscient, déclaratif. 1997 marque la découverte de deux systèmes de mémoire déclarative, épisodique et sémantique. Ces découvertes résultent d'études de cas en neuropsychologie. Cette thèse s'inscrit dans la tradition neuropsychologique: sa genèse doit tout à un patient souffrant d'une forme atypique d'amnésie développementale, le patient KA. Son point de départ est une étude de cas approfondie, avec deux résultats surprenants. Malgré une amnésie sévère, KA dispose de connaissances sémantiques exceptionnelles. Par ailleurs, il montre des capacités préservées d'apprentissage explicite, mais uniquement pour des stimuli concrets, pas abstraits. En conséquence, cette thèse a exploré deux pistes de recherche. Premièrement, nous avons caractérisé les processus préservés d'apprentissage déclaratif et l'anatomie cérébrale chez ce patient. Deuxièmement, nous avons étudié le rôle des connaissances préalables dans l'apprentissage: comment ce que l'on sait influence ce dont nous nous souvenons ? Une première série d'expériences montre chez ce patient une atteinte sévère et sélective de l'ensemble du système hippocampique, alors que les structures sous- hippocampiques (cortex entorhinal, périrhinal et parahippocampique) sont préservées. Malgré une amnésie épisodique sévère, nous montrons des connaissances sémantiques supranormales et des aptitudes d'apprentissage explicite rapide. Ces aptitudes sont toutefois restreintes aux stimuli associés à des connaissances préalables. Une seconde série d'expériences explore l'hypothèse selon laquelle les connaissances préalables facilitent l'apprentissage en mémoire déclarative, même dans les situations où le lobe temporal interne est fragilisé, comme dans le vieillissement, ou lésé, comme chez le patient KA ou dans la maladie d'Alzheimer. Nos résultats suggèrent l'existence de processus d'apprentissage rapide en mémoire déclarative, indépendants du système hippocampique et sensibles à la présence de représentations préexistantes. Ces processus semblent affectés par la maladie d'Alzheimer, et ce en lien avec un défaut d'activité des régions sous-hippocampiques antérieures. A l'inverse, les sujets âgés sains peuvent utiliser les connaissances préalables et pourraient ainsi compenser le déclin de la mémoire associative. Ce travail s'accorde avec les modèles postulant une dissociation fonctionnelle au sein du lobe temporal interne pour l'apprentissage déclaratif. Il soutient les propositions neurocognitives et computationnelles récentes, suggérant une voie d'apprentissage néocortical rapide mobilisable dans certaines circonstances. Il met en exergue la dynamique des apprentissages en mémoire déclarative et notamment l'intrication fondamentale entre "savoir" et "se souvenir". Ce que je sais a un impact profond sur ce dont je vais me souvenir. Cette thèse permet d'envisager de nouveaux outils cognitifs pour le diagnostic de la maladie d'Alzheimer. De plus, il semble que des lésions temporales internes auront un impact distinct sur l'apprentissage selon le statut des informations à mémoriser en mémoire à long terme, offrant un regard nouveau sur les effets stimulus-dépendants dans l'amnésie. Une considération approfondie des connaissances préalables associées au contenu de nos expériences, et leur caractérisation détaillée, est requise pour affiner les modèles de la mémoire déclarative. Ces résultats apportent de nouvelles pistes de recherche quant aux circonstances épargnant l'apprentissage, notamment associatif, lors du vieillissement. Plus généralement, ils contribuent à la compréhension des déterminants d'un apprentissage réussi, en mettant l'accent sur les recouvrements entre processus de récupération et d'acquisition. Des applications potentielles en découlent dans le domaine éducatif.The experimental study of human memory has had two historic moments in the last sixty years. 1957 marks the discovery of the role of the medial temporal lobes in conscious learning. 1997 marks the discovery of two systems of declarative memory, namely episodic and semantic memories. These major breakthroughs are owed to clinical case studies in neuropsychology. This thesis follows on from the neuropsychological tradition: its genesis owes everything to a patient suffering from an atypical form of developmental amnesia, the patient KA. The starting point of this work was a thorough neuropsychological study of this patient. Two striking findings shortly arose. First, despite lifelong amnesia, KA had acquired exceptional levels of knowledge about the world. Second, remaining explicit learning abilities were restricted to meaningful, not meaningless, memoranda. As a consequence, we have investigated two research pathways in that thesis. First, we aimed at better characterizing preserved learning abilities and brain structure of the patient KA. Second, our goal was to explore how prior knowledge affects new declarative learning or, put simply, how do we learn what we know? In a first series of behavioural and neuroimaging experiments, we have shown in this patient a severe and selective damage of the whole extended hippocampal system, but preserved subhippocampal structures (entorhinal, perirhinal and parahippocampal cortex). The patient suffers from severe episodic amnesia, but we bring striking evidence for supranormal semantic knowledge as well as normal explicit learning skills. These skills were, however, restricted to familiar stimuli, that is, stimuli carrying pre-experimental knowledge. In a second series of behavioural and neuroimaging experiments, we explored the hypothesis that prior knowledge can facilitate new learning in declarative memory, even in aging or in situations where structures of the medial temporal lobe are or injured, as in amnesia or Alzheimer's disease. Our results suggest the existence of processes allowing fast learning in declarative memory, independently of the hippocampal system, and that are sensitive to the presence of pre-existing representations in long-term memory. Such learning processes appear to be selectively affected by Alzheimer's disease at the pre-dementia stage, in relation to a lack of activation of subhippocampal regions. In contrast, healthy elderly were able to rely on these learning processes to compensate for the decline in associative memory associated with aging. This work lends support to the models postulating a functional dissociation with respect to learning in declarative memory. It indeed strengthens recent neurocognitive and computational accounts that suggest a rapid neocortical learning path under certain circumstances. It highlights the dynamics of learning in declarative memory and in particular the fundamental entanglement between "knowing" and "remembering". What I know profoundly impacts what I will remember. The present thesis points towards new cognitive tools for the diagnosis of Alzheimer's disease. It further brings evidence that medial temporal lesions differentially impact learning depending on the status of the memoranda in long-term memory, which sheds a new light on material-specific effects in amnesia. Our work speaks for a thorough consideration of whether the contents of events have prior representations within long-term memory, and to further better characterize their nature if we are to better understand learning mechanisms. It also brings additional clues for a deeper understanding of how learning and memory can be preserved in aging. More generally, it contributes to a better understanding of the factors determining successful learning, with a focus on how retrieval and acquisition processes overlap during learning. Such findings have potential applications in the educational field

Compendium for Early Career Researchers in Mathematics Education

The purpose of this Open Access compendium, written by experienced researchers in mathematics education, is to serve as a resource for early career researchers in furthering their knowledge of the state of the field and disseminating their research through publishing. To accomplish this, the book is split into four sections: Empirical Methods, Important Mathematics Education Themes, Academic Writing and Academic Publishing, and a section Looking Ahead. The chapters are based on workshops that were presented in the Early Career Researcher Day at the 13th International Congress on Mathematical Education (ICME-13). The combination of presentations on methodological approaches and theoretical perspectives shaping the field in mathematics education research, as well as the strong emphasis on academic writing and publishing, offered strong insight into the theoretical and empirical bases of research in mathematics education for early career researchers in this field. Based on these presentations, the book provides a state-of-the-art overview of important theories from mathematics education and the broad variety of empirical approaches currently widely used in mathematics education research. This compendium supports early career researchers in selecting adequate theoretical approaches and adopting the most appropriate methodological approaches for their own research. Furthermore, it helps early career researchers in mathematics education to avoid common pitfalls and problems while writing up their research and it provides them with an overview of the most important journals for research in mathematics education, helping them to select the right venue for publishing and disseminating their work

Compendium for Early Career Researchers in Mathematics Education

The purpose of this Open Access compendium, written by experienced researchers in mathematics education, is to serve as a resource for early career researchers in furthering their knowledge of the state of the field and disseminating their research through publishing. To accomplish this, the book is split into four sections: Empirical Methods, Important Mathematics Education Themes, Academic Writing and Academic Publishing, and a section Looking Ahead. The chapters are based on workshops that were presented in the Early Career Researcher Day at the 13th International Congress on Mathematical Education (ICME-13). The combination of presentations on methodological approaches and theoretical perspectives shaping the field in mathematics education research, as well as the strong emphasis on academic writing and publishing, offered strong insight into the theoretical and empirical bases of research in mathematics education for early career researchers in this field. Based on these presentations, the book provides a state-of-the-art overview of important theories from mathematics education and the broad variety of empirical approaches currently widely used in mathematics education research. This compendium supports early career researchers in selecting adequate theoretical approaches and adopting the most appropriate methodological approaches for their own research. Furthermore, it helps early career researchers in mathematics education to avoid common pitfalls and problems while writing up their research and it provides them with an overview of the most important journals for research in mathematics education, helping them to select the right venue for publishing and disseminating their work

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications