Extending the learning object definition to represent programming problems

The present generation of eLearning platforms values the interchange of learning objects standards. Nevertheless, for specialized domains these standards are insufficient to fully describe all the assets, especially when they are used as input for other eLearning services. To address this issue we extended an existing learning objects standard to the particular requirements of a specialized domain, namely the automatic evaluation of programming problems. The focus of this paper is the definition of programming problems as learning objects. We introduce a new schema to represent metadata related to automatic evaluation that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. This new schema is being used in an interoperable repository of learning objects, called crimsonHex.

Defining programming problems as learning objects

Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue we extended existing learning object standards to the particular requirements of a specialized domain. We present a definition of programming problems as learning objects that is compatible both with Learning Management Systems and with systems performing automatic evaluation of programs. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the valuation engine; and the roles of different assets - tests cases, program solutions, etc. We present also the EduJudge project and its main services as a case study on the use of the proposed definition of programming problems as learning objects.

Robust learning in safety-related domains : machine learning methods for solving safety-related application problems

Magdeburg, Univ., Fak. für Informatik, Diss., 2009

Problems and potentialities of e-Learning for regular undergraduate courses in emergency medicine

BACKGROUND: E-learning techniques are spreading at great speed in medicine, raising concerns about the impact of adopting them. Websites especially designed to host courses are becoming more common. There is a lack of evidence that these systems could enhance student knowledge acquisition. GOAL: To evaluate the impact of using dedicated-website tools over cognition of medical students exposed to a first-aid course. METHODS: Prospective study of 184 medical students exposed to a twenty-hour first-aid course. We generated a dedicated-website with several sections (lectures, additional reading material, video and multiple choice exercises). We constructed variables expressing the student's access to each section. The evaluation was composed of fifty multiple-choice tests, based on clinical problems. We used multiple linear regression to adjust for potential confounders. RESULTS: There was no association of website intensity of exposure and the outcome - beta-coeficient 0.27 (95%CI - 0.454 - 1.004). These findings were not altered after adjustment for potential confounders - 0.165 (95%CI -0.628 - 0.960). CONCLUSION: A dedicated website with passive and active capabilities for aiding in person learning had not shown association with a better outcome.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Phonological and Syntactic Problems faced by Speakers of Bafoussam-Bamileke as L1 in Learning English as L2

Carrying out this research on the difficulties encountered by Bafoussam-Bamileke's native speakers learning English as their L2 helps to unveil many syntactic and phonological problems that require a great interest no only to teachers but also to learners in order to reach an acceptable level of accuracy and fluency. We have also provided some ways to solve those problems efficiently.

Teaching and learning German language and culture in higher education in Britain:problems, challenges and didactical implications. A case study

The aim of this thesis is to explore key aspects and problems of the institutionalised teaching and learning of German language and culture in the context of German Studies in British Higher Education (HE). This investigation focuses on teaching and learning experiences in one department of German Studies in the UK, which is the micro-context of the present study, in order to provide an in-depth insight into real-life problems, strengths and weaknesses as they occur in the practice of teaching and learning German. Following Lamb (2004) and Holliday (1994), the present study acts on the assumption that each micro-context does not exist in vacuo but is always embedded in a wider socio-political and education environment, namely the macro-context, which largely determines how and what is taught. The macro-analysis of the present study surveys the socio-political developments that have recently affected the sector of modern languages and specifically the discipline of German Studies in the UK. It demonstrates the impact they have had on teaching and learning German at the undergraduate level in Britain. This context is interesting inasmuch as the situation in Britain is to a large extent a paradigmatic example of the developments in German Studies in English-speaking countries. Subsequently, the present study explores learning experiences of a group of thirty-five first year students. It focuses on their previous experiences in learning German, exposure to the target language, motivation, learning strategies and difficulties encountered, when learning German at the tertiary level. Then, on the basis of interviews with five lecturers of German, teaching experience in the context under study is explored, problems and successful teaching strategies discussed.

Forming of Learning Set for Neural Networks in Problems of Losless Data Compression

questions of forming of learning sets for artificial neural networks in problems of lossless data compression are considered. Methods of construction and use of learning sets are studied. The way of forming of learning set during training an artificial neural network on the data stream is offered.

On Neuron Mechanisms Used to Resolve Mental Problems of Identification and Learning in Sensorium

The paper considers some possible neuron mechanisms that do not contradict biological data. They are represented in terms of the notion of an elementary sensorium discussed in the previous authors’ works. Such mechanisms resolve problems of two large classes: when identification mechanisms are used and when sensory learning mechanisms are applied along with identification.

Learning with MOOCs: promises and problems

Massive Open Online Courses (MOOCs) may be considered to be a new form of virtual technology enhanced learning environments. Since their first appearance in 2008, the increase in the number of MOOCs has been dramatic. The hype about MOOCs was accompanied by great expectations: 2012 was named the Year of the MOOCs and it was expected that MOOCs would revolutionise higher education. Two types of MOOCs may be distinguished: cMOOCs as proposed by Siemens, based on his ideas of connectivism, and xMOOCs developed in institutions such as Stanford and MIT. Although MOOCs have received a great deal of attention, they have also met with criticism. The time has therefore come to critically reflect upon this phenomenon.