Image Segmentation Based on Learning Cellular Automata Using Soft Computing Approach
NASA Astrophysics Data System (ADS)
Das, Debasis; Ray, Abhishek
2010-10-01
Image Segmentation refers to the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. A Cellular Automata (CA) is a computing model of complex system using simple rule. It divides the problem space into number of cells and each cell can be in one or several final states. Cells are affected by its neighbor's to the simple rule. Learning Cellular Automata (LCA) is a variant of automata that interact with random environment having as goal to improve its behavior. This paper proposes an image segmentation technique based on LCA using soft computing approach. This proposed method works in two steps, the first step is called as soft segmentation where the input image(s) is/are analyzed through LCA and the second step is called as soft computing approach where the analyzed image is segmented through fuzzy C-means algorithm.
Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein
2016-06-01
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy.
Irregular Cellular Learning Automata.
Esnaashari, Mehdi; Meybodi, Mohammad Reza
2015-08-01
Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found.
Genetic learning automata for function optimization.
Howell, M N; Gordon, T J; Brandao, F V
2002-01-01
Stochastic learning automata and genetic algorithms (GAs) have previously been shown to have valuable global optimization properties. Learning automata have, however, been criticized for having a relatively slow rate of convergence. In this paper, these two techniques are combined to provide an increase in the rate of convergence for the learning automata and also to improve the chances of escaping local optima. The technique separates the genotype and phenotype properties of the GA and has the advantage that the degree of convergence can be quickly ascertained. It also provides the GA with a stopping rule. If the technique is applied to real-valued function optimization problems, then bounds on the range of the values within which the global optima is expected can be determined throughout the search process. The technique is demonstrated through a number of bit-based and real-valued function optimization examples.
Decentralized indirect methods for learning automata games.
Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis
2011-10-01
We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.
Automata Learning with Automated Alphabet Abstraction Refinement
NASA Astrophysics Data System (ADS)
Howar, Falk; Steffen, Bernhard; Merten, Maik
on is the key when learning behavioral models of realistic systems, but also the cause of a major problem: the introduction of non-determinism. In this paper, we introduce a method for refining a given abstraction to automatically regain a deterministic behavior on-the-fly during the learning process. Thus the control over abstraction becomes part of the learning process, with the effect that detected non-determinism does not lead to failure, but to a dynamic alphabet abstraction refinement. Like automata learning itself, this method in general is neither sound nor complete, but it also enjoys similar convergence properties even for infinite systems as long as the concrete system itself behaves deterministically, as illustrated along a concrete example.
A quantum model for autonomous learning automata
NASA Astrophysics Data System (ADS)
Siomau, Michael
2014-05-01
The idea of information encoding on quantum bearers and its quantum-mechanical processing has revolutionized our world and brought mankind on the verge of enigmatic era of quantum technologies. Inspired by this idea, in present paper, we search for advantages of quantum information processing in the field of machine learning. Exploiting only basic properties of the Hilbert space, superposition principle of quantum mechanics and quantum measurements, we construct a quantum analog for Rosenblatt's perceptron, which is the simplest learning machine. We demonstrate that the quantum perceptron is superior to its classical counterpart in learning capabilities. In particular, we show that the quantum perceptron is able to learn an arbitrary (Boolean) logical function, perform the classification on previously unseen classes and even recognize the superpositions of learned classes—the task of high importance in applied medical engineering.
LAHS: A novel harmony search algorithm based on learning automata
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Yousefi, Moslem; Abdullah, Abdul Hanan; Darus, Amer Nordin
2013-12-01
This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.
A novel cellular automata based approach to storm sewer design
NASA Astrophysics Data System (ADS)
Guo, Y.; Walters, G. A.; Khu, S. T.; Keedwell, E.
2007-04-01
Optimal storm sewer design aims at minimizing capital investment on infrastructure whilst ensuring good system performance under specified design criteria. An innovative sewer design approach based on cellular automata (CA) principles is introduced in this paper. Cellular automata have been applied as computational simulation devices in various scientific fields. However, some recent research has indicated that CA can also be a viable and efficient optimization engine. This engine is heuristic and largely relies on the key properties of CA: locality, homogeneity, and parallelism. In the proposed approach, the CA-based optimizer is combined with a sewer hydraulic simulator, the EPA Storm Water Management Model (SWMM). At each optimization step, according to a set of transition rules, the optimizer updates all decision variables simultaneously based on the hydraulic situation within each neighbourhood. Two sewer networks (one small artificial network and one large real network) have been tested in this study. The CA optimizer demonstrated its ability to obtain near-optimal solutions in a remarkably small number of computational steps in a comparison of its performance with that of a genetic algorithm.
A cellular automata approach for modeling surface water runoff
NASA Astrophysics Data System (ADS)
Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko
2015-04-01
This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced
Perceptions of teaching and learning automata theory in a college-level computer science course
NASA Astrophysics Data System (ADS)
Weidmann, Phoebe Kay
This dissertation identifies and describes student and instructor perceptions that contribute to effective teaching and learning of Automata Theory in a competitive college-level Computer Science program. Effective teaching is the ability to create an appropriate learning environment in order to provide effective learning. We define effective learning as the ability of a student to meet instructor set learning objectives, demonstrating this by passing the course, while reporting a good learning experience. We conducted our investigation through a detailed qualitative case study of two sections (118 students) of Automata Theory (CS 341) at The University of Texas at Austin taught by Dr. Lily Quilt. Because Automata Theory has a fixed curriculum in the sense that many curricula and textbooks agree on what Automata Theory contains, differences being depth and amount of material to cover in a single course, a case study would allow for generalizable findings. Automata Theory is especially problematic in a Computer Science curriculum since students are not experienced in abstract thinking before taking this course, fail to understand the relevance of the theory, and prefer classes with more concrete activities such as programming. This creates a special challenge for any instructor of Automata Theory as motivation becomes critical for student learning. Through the use of student surveys, instructor interviews, classroom observation, material and course grade analysis we sought to understand what students perceived, what instructors expected of students, and how those perceptions played out in the classroom in terms of structure and instruction. Our goal was to create suggestions that would lead to a better designed course and thus a higher student success rate in Automata Theory. We created a unique theoretical basis, pedagogical positivism, on which to study college-level courses. Pedagogical positivism states that through examining instructor and student perceptions
Link prediction based on temporal similarity metrics using continuous action set learning automata
NASA Astrophysics Data System (ADS)
Moradabadi, Behnaz; Meybodi, Mohammad Reza
2016-10-01
Link prediction is a social network research area that tries to predict future links using network structure. The main approaches in this area are based on predicting future links using network structure at a specific period, without considering the links behavior through different periods. For example, a common traditional approach in link prediction calculates a chosen similarity metric for each non-connected link and outputs the links with higher similarity scores as the prediction result. In this paper, we propose a new link prediction method based on temporal similarity metrics and Continuous Action set Learning Automata (CALA). The proposed method takes advantage of using different similarity metrics as well as different time periods. In the proposed algorithm, we try to model the link prediction problem as a noisy optimization problem and use a team of CALAs to solve the noisy optimization problem. CALA is a reinforcement based optimization tool which tries to learn the optimal behavior from the environment feedbacks. To determine the importance of different periods and similarity metrics on the prediction result, we define a coefficient for each of different periods and similarity metrics and use a CALA for each coefficient. Each CALA tries to learn the true value of the corresponding coefficient. Final link prediction is obtained from a combination of different similarity metrics in different times based on the obtained coefficients. The link prediction results reported here show satisfactory of the proposed method for some social network data sets.
Distributed learning automata-based algorithm for community detection in complex networks
NASA Astrophysics Data System (ADS)
Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza
2016-03-01
Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.
Apostolico, A; Bejerano, G
2000-01-01
Statistical modeling of sequences is a central paradigm of machine learning that finds multiple uses in computational molecular biology and many other domains. The probabilistic automata typically built in these contexts are subtended by uniform, fixed-memory Markov models. In practice, such automata tend to be unnecessarily bulky and computationally imposing both during their synthesis and use. Recently, D. Ron, Y. Singer, and N. Tishby built much more compact, tree-shaped variants of probabilistic automata under the assumption of an underlying Markov process of variable memory length. These variants, called Probabilistic Suffix Trees (PSTs) were subsequently adapted by G. Bejerano and G. Yona and applied successfully to learning and prediction of protein families. The process of learning the automaton from a given training set S of sequences requires theta(Ln2) worst-case time, where n is the total length of the sequences in S and L is the length of a longest substring of S to be considered for a candidate state in the automaton. Once the automaton is built, predicting the likelihood of a query sequence of m characters may cost time theta(m2) in the worst case. The main contribution of this paper is to introduce automata equivalent to PSTs but having the following properties: Learning the automaton, for any L, takes O (n) time. Prediction of a string of m symbols by the automaton takes O (m) time. Along the way, the paper presents an evolving learning scheme and addresses notions of empirical probability and related efficient computation, which is a by-product possibly of more general interest.
Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model
NASA Astrophysics Data System (ADS)
Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran
2014-09-01
Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.
Learning to construct pushdown automata for accepting deterministic context-free languages
NASA Astrophysics Data System (ADS)
Sen, Sandip; Janakiraman, Janani
1992-03-01
Genetic algorithms (GAs) are a class of probabilistic optimization algorithms which utilize ideas from natural genetics. In this paper, we apply the genetic algorithm to a difficult machine learning problem, viz., to learn the description of pushdown automata (PDA) to accept a context-free language (CFL), given legal and illegal sentences of the language. Previous work has involved the use of GAs in learning descriptions for finite state machines for accepting regular languages. CFLs are known to properly include regular languages, and hence, the learning problem addressed here is of a greater complexity. The ability to accept context free languages can be applied to a number of practical problems like text processing, speech recognition, etc.
Li, Ming; Miao, Chunyan; Leung, Cyril
2015-01-01
Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches. PMID:26690162
Li, Ming; Miao, Chunyan; Leung, Cyril
2015-12-04
Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2014-01-01
We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.
Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
Consequences of landscape fragmentation on Lyme disease risk: a cellular automata approach.
Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O
2012-01-01
The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial
High Detailed Debris Flows Hazard Maps by a Cellular Automata Approach
NASA Astrophysics Data System (ADS)
Lupiano, V.; Lucà, F.; Robustelli, G.; Rongo, R.; D'Ambrosio, D.; Spataro, W.; Avolio, M. V.
2012-04-01
The individuation of areas that are more likely to be interested by new debris flows in regions that are particularly exposed to such kind of phenomena is of fundamental relevance for mitigating possible consequences, both in terms of loss of human lives and material properties. Here we show the adaption of a recent methodology, already successfully applied to lava flows, for defining flexible high-detailed and reliable hazard maps. The methodology relies on both an adequate knowledge of the study area, assessed by an accurate analysis of its past behavior, together with a reliable numerical model for simulating debris flows on present topographic data (the Cellular Automata model SCIDDICA, in the present case). Furthermore, High Performance Parallel Computing is employed for increasing computational efficiency, due to the great number of simulations of hypothetical events that are required for characterizing the susceptibility to flow invasion of the study area. The application of the presented methodology to the case of Gragnano (Italy) pointed out the goodness of the proposed approach, suggesting its appropriateness for land use planning and Civil Defense applications.
NASA Astrophysics Data System (ADS)
Pandey, Ras B.
1998-03-01
A stochastic cellular automata (SCA) approach is introduced to study the growth and decay of cellular population in an immune response model relevant to HIV. Four cell types are considered: macrophages (M), helper cells (H), cytotoxic cells (C), and viral infected cells (V). Mobility of the cells is introduced and viral mutation is considered probabilistically. In absence of mutation, the population of the host cells, helper (N_H) and cytotxic (N_C) cells in particular, dominates over the viral population (N_V), i.e., N_H, NC > N_V, the immune system wins over the viral infection. Variation of cellular population with time exhibits oscillations. The amplitude of oscillations in variation of N_H, NC and NV with time decreases at high mobility even at low viral mutation; the rate of viral growth is nonmonotonic with NV > N_H, NC in the long time regime. The viral population is much higher than that of the host cells at higher mutation rate, a possible cause of AIDS.
Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment
Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina
2014-01-01
Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670
Efficient Algorithms for Handling Nondeterministic Automata
NASA Astrophysics Data System (ADS)
Vojnar, Tomáš
Finite (word, tree, or omega) automata play an important role in different areas of computer science, including, for instance, formal verification. Often, deterministic automata are used for which traditional algorithms for important operations such as minimisation and inclusion checking are available. However, the use of deterministic automata implies a need to determinise nondeterministic automata that often arise during various computations even when the computations start with deterministic automata. Unfortunately, determinisation is a very expensive step since deterministic automata may be exponentially bigger than the original nondeterministic automata. That is why, it appears advantageous to avoid determinisation and work directly with nondeterministic automata. This, however, brings a need to be able to implement operations traditionally done on deterministic automata on nondeterministic automata instead. In particular, this is the case of inclusion checking and minimisation (or rather reduction of the size of automata). In the talk, we review several recently proposed techniques for inclusion checking on nondeterministic finite word and tree automata as well as Büchi automata. These techniques are based on using the so called antichains, possibly combined with a use of suitable simulation relations (and, in the case of Büchi automata, the so called Ramsey-based or rank-based approaches). Further, we discuss techniques for reducing the size of nondeterministic word and tree automata using quotienting based on the recently proposed notion of mediated equivalences. The talk is based on several common works with Parosh Aziz Abdulla, Ahmed Bouajjani, Yu-Fang Chen, Peter Habermehl, Lisa Kaati, Richard Mayr, Tayssir Touili, Lorenzo Clemente, Lukáš Holík, and Chih-Duo Hong.
Ship interaction in narrow water channels: A two-lane cellular automata approach
NASA Astrophysics Data System (ADS)
Sun, Zhuo; Chen, Zhonglong; Hu, Hongtao; Zheng, Jianfeng
2015-08-01
In narrow waterways, closed ships might interact due to hydrodynamic forces. To avoid clashes, different lane-changing rules are required. In this paper, a two-lane cellular automata model is proposed to investigate the traffic flow patterns in narrow water channels. Numerical experiments show that ship interaction can form "lumps" in traffic flow which will significantly depress the flux. We suggest that the lane-changing frequency of fast ships should be limited.
2014-01-01
Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area
Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach.
Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng
2015-11-01
Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges.
Learning deterministic finite automata with a smart state labeling evolutionary algorithm.
Lucas, Simon M; Reynolds, T Jeff
2005-07-01
Learning a Deterministic Finite Automaton (DFA) from a training set of labeled strings is a hard task that has been much studied within the machine learning community. It is equivalent to learning a regular language by example and has applications in language modeling. In this paper, we describe a novel evolutionary method for learning DFA that evolves only the transition matrix and uses a simple deterministic procedure to optimally assign state labels. We compare its performance with the Evidence Driven State Merging (EDSM) algorithm, one of the most powerful known DFA learning algorithms. We present results on random DFA induction problems of varying target size and training set density. We also studythe effects of noisy training data on the evolutionary approach and on EDSM. On noise-free data, we find that our evolutionary method outperforms EDSM on small sparse data sets. In the case of noisy training data, we find that our evolutionary method consistently outperforms EDSM, as well as other significant methods submitted to two recent competitions.
Simulation of abrasive water jet cutting process: Part 2. Cellular automata approach
NASA Astrophysics Data System (ADS)
Orbanic, Henri; Junkar, Mihael
2004-11-01
A new two-dimensional cellular automata (CA) model for the simulation of the abrasive water jet (AWJ) cutting process is presented. The CA calculates the shape of the cutting front, which can be used as an estimation of the surface quality. The cutting front is formed based on material removal rules and AWJ propagation rules. The material removal rule calculates when a particular part of the material will be removed with regard to the energy of AWJ. The AWJ propagation rule calculates the distribution of AWJ energy through CA by using a weighted average. The modelling with CA also provides a visual narrative of the moving of the cutting front, which is hard to observe in real process. The algorithm is fast and has been successfully tested in comparison to cutting fronts obtained with cutting experiments of aluminium alloy.
NASA Astrophysics Data System (ADS)
Heng, Fong Wan; Siang, Gan Yee; Sarmin, Nor Haniza; Turaev, Sherzod
2014-06-01
Recently, the relation of automata and groups has been studied. It was shown that properties of groups can be studied using state diagrams of modified automata and modified Watson-Crick automata. In this work, we investigate the relation of subgroups with the modified finite and Watson-Crick automata. We also establish the conditions for the recognition of subgroups by using the modified automata.
Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo
2013-10-01
The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.
Modeling the “learning process” of the teacher in a tutorial-like system using learning automata.
Oommen, B John; Hashem, M Khaled
2013-12-01
Unlike the field of tutorial systems, where a real-life student interacts and learns from a software system, our research focuses on a new philosophy in which no entity needs to be a real-life individual. Such systems are termed as tutorial-like systems, and research in this field endeavors to model every component of the system using an appropriate learning model [in our case, a learning automaton (LA)].1 While models for the student, the domain, the teacher, etc., have been presented elsewhere, the aim of this paper is to present a new approach to model how the teacher, in this paradigm, of our tutorial-like system "learns and improves his "teaching skills" while being himself an integral component of the system. We propose to model the "learning process" of the teacher by using a higher level LA, referred to as the metateacher, whose task is to assist the teacher himself. Ultimately, the intention is that the latter can communicate the teaching material to the student(s) in a manner customized to the particular student's ability and progress. In short, the teacher will infer the progress of the student and initiate a strategy by which he can "custom-communicate" the material to each individual student. The results that we present in a simulated environment validate the model for the teacher and for the metateacher. The use of the latter can be seen to significantly improve the teaching abilities of the teacher.
NASA Technical Reports Server (NTRS)
Hinchey, Michael G. (Inventor); Margaria, Tiziana (Inventor); Rash, James L. (Inventor); Rouff, Christopher A. (Inventor); Steffen, Bernard (Inventor)
2010-01-01
Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.
Granmo, Ole-Christoffer; Oommen, B John; Myrer, Svein Arild; Olsen, Morten Goodwin
2007-02-01
This paper considers the nonlinear fractional knapsack problem and demonstrates how its solution can be effectively applied to two resource allocation problems dealing with the World Wide Web. The novel solution involves a "team" of deterministic learning automata (LA). The first real-life problem relates to resource allocation in web monitoring so as to "optimize" information discovery when the polling capacity is constrained. The disadvantages of the currently reported solutions are explained in this paper. The second problem concerns allocating limited sampling resources in a "real-time" manner with the purpose of estimating multiple binomial proportions. This is the scenario encountered when the user has to evaluate multiple web sites by accessing a limited number of web pages, and the proportions of interest are the fraction of each web site that is successfully validated by an HTML validator. Using the general LA paradigm to tackle both of the real-life problems, the proposed scheme improves a current solution in an online manner through a series of informed guesses that move toward the optimal solution. At the heart of the scheme, a team of deterministic LA performs a controlled random walk on a discretized solution space. Comprehensive experimental results demonstrate that the discretization resolution determines the precision of the scheme, and that for a given precision, the current solution (to both problems) is consistently improved until a nearly optimal solution is found--even for switching environments. Thus, the scheme, while being novel to the entire field of LA, also efficiently handles a class of resource allocation problems previously not addressed in the literature.
NASA Astrophysics Data System (ADS)
Dottori, F.; Todini, E.
2011-01-01
Over the last decade, several flood inundation models based on a reduced complexity approach have been developed and successfully applied in a wide range of practical cases. In the present paper, a model based on the cellular automata approach is analyzed in detail and tested in several numerical cases, comparing the results both with analytical solutions and different hydraulic models. In order to improve the model’s performance, the original code based on the diffusive wave equations and a constant time step scheme is modified through the implementation of two techniques available in literature: an inertial formulation for the computation of discharges, originally developed for the LISFLOOD-FP model by Bates et al. (2010); and the incorporation of a local adaptive time step algorithm, based on a technique originally presented by Zhang et al. (1994). The analysis of the numerical cases showed that the proposed model can be a valuable tool for the simulation of flood inundation events. When applied to one-dimensional numerical cases, the model well reproduced the wave propagation, whereas it showed some limitations in reproducing two-dimensional flow dynamics in respect to a model based on the full shallow water equations. However, differences were found to be comparable with the uncertainty level related to available data for actual flood events. The use of the inertial formulation was very effective in all the cases, and reduced run time up to 97% as compared with the diffusive formulation, although it did not improve the overall accuracy of results. Finally, the incorporation of the local time step algorithm produced a speedup from 1.2 x to 4 x, depending on the simulation and the model version in use, with no loss of accuracy in the results.
Cellular automata and its applications in protein bioinformatics.
Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen
2011-09-01
With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.
A cellular automata model for social-learning processes in a classroom context
NASA Astrophysics Data System (ADS)
Bordogna, C. M.; Albano, E. V.
2002-02-01
A model for teaching-learning processes that take place in the classroom is proposed and simulated numerically. Recent ideas taken from the fields of sociology, educational psychology, statistical physics and computational science are key ingredients of the model. Results of simulations are consistent with well-established empirical results obtained in classrooms by means of different evaluation tools. It is shown that students engaged in collaborative groupwork reach higher achievements than those attending traditional lectures only. However, in many cases, this difference is subtle and consequently very difficult to be detected using tests. The influence of the number of students forming the collaborative groups on the average knowledge achieved is also studied and discussed.
ERIC Educational Resources Information Center
WIENS, JACOB H.
TO PERMIT COMPARATIVE ANALYSIS FOR PURPOSES OF EDUCATIONAL PLANNING AT SAN MATEO, FIVE INSTITUTIONS WITH SYSTEMS PROGRAMS ARE EVALUATED ON THE BASIS OF TRIP NOTES. OAKLAND COMMUNITY COLLEGE HAS BEEN COMPLETELY ORGANIZED AROUND THE VOLUNTARY WORK-STUDY LABORATORY APPROACH TO LEARNING. ORAL ROBERTS UNIVERSITY, OKLAHOMA CHRISTIAN COLLEGE, HENRY FORD…
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio
2013-10-01
We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.
Two-lane traffic rules for cellular automata: A systematic approach
Nagel, K. |; Wolf, D.E. |; Wagner, P. |; Simon, P.
1997-11-05
Microscopic modeling of multi-lane traffic is usually done by applying heuristic lane changing rules, and often with unsatisfying results. Recently, a cellular automation model for two-lane traffic was able to overcome some of these problems and to produce a correct density inversion at densities somewhat below the maximum flow density. In this paper, the authors summarize different approaches to lane changing and their results, and propose a general scheme, according to which realistic lane changing rules can be developed. They test this scheme by applying it to several different lane changing rules, which, in spite of their differences, generate similar and realistic results. The authors thus conclude that, for producing realistic results, the logical structure of the lane changing rules, as proposed here, is at least as important as the microscopic details of the rules.
A multi-layer cellular automata approach for algorithmic generation of virtual case studies: VIBe.
Sitzenfrei, R; Fach, S; Kinzel, H; Rauch, W
2010-01-01
Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data.
Automata representation for Abelian groups
NASA Astrophysics Data System (ADS)
Fong, Wan Heng; Gan, Yee Siang; Sarmin, Nor Haniza; Turaev, Sherzod
2013-04-01
A finite automaton is one of the classic models of recognition devices, which is used to determine the type of language a string belongs to. A string is said to be recognized by a finite automaton if the automaton "reads" the string from the left to the right starting from the initial state and finishing at a final state. Another type of automata which is a counterpart of sticker systems, namely Watson-Crick automata, is finite automata which can scan the double-stranded tapes of DNA strings using the complimentary relation. The properties of groups have been extended for the recognition of finite automata over groups. In this paper, two variants of automata, modified deterministic finite automata and modified deterministic Watson-Crick automata are used in the study of Abelian groups. Moreover, the relation between finite automata diagram over Abelian groups and the Cayley table is introduced. In addition, some properties of Abelian groups are presented in terms of automata.
Plasmonic Nanostructured Cellular Automata
NASA Astrophysics Data System (ADS)
Alkhazraji, Emad; Ghalib, A.; Manzoor, K.; Alsunaidi, M. A.
2017-03-01
In this work, we have investigated the scattering plasmonic resonance characteristics of silver nanospheres with a geometrical distribution that is modelled by Cellular Automata using time-domain numerical analysis. Cellular Automata are discrete mathematical structures that model different natural phenomena. Two binary one-dimensional Cellular Automata rules are considered to model the nanostructure, namely rule 30 and rule 33. The analysis produces three-dimensional scattering profiles of the entire plasmonic nanostructure. For the Cellular Automaton rule 33, the introduction of more Cellular Automata generations resulted only in slight red and blue shifts in the plasmonic modes with respect to the first generation. On the other hand, while rule 30 introduced significant red shifts in the resonance peaks at early generations, at later generations however, a peculiar effect is witnessed in the scattering profile as new peaks emerge as a feature of the overall Cellular Automata structure rather than the sum of the smaller parts that compose it. We strongly believe that these features that emerge as a result adopting the different 256 Cellular Automata rules as configuration models of nanostructures in different applications and systems might possess a great potential in enhancing their capability, sensitivity, efficiency, and power utilization.
Automata-Based Verification of Temporal Properties on Running Programs
NASA Technical Reports Server (NTRS)
Giannakopoulou, Dimitra; Havelund, Klaus; Lan, Sonie (Technical Monitor)
2001-01-01
This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.
Synchronization of Regular Automata
NASA Astrophysics Data System (ADS)
Caucal, Didier
Functional graph grammars are finite devices which generate the class of regular automata. We recall the notion of synchronization by grammars, and for any given grammar we consider the class of languages recognized by automata generated by all its synchronized grammars. The synchronization is an automaton-related notion: all grammars generating the same automaton synchronize the same languages. When the synchronizing automaton is unambiguous, the class of its synchronized languages forms an effective boolean algebra lying between the classes of regular languages and unambiguous context-free languages. We additionally provide sufficient conditions for such classes to be closed under concatenation and its iteration.
NASA Astrophysics Data System (ADS)
Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.
2012-08-01
Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.
Immune Responses: Getting Close to Experimental Results with Cellular Automata Models
NASA Astrophysics Data System (ADS)
Dos Santos, Rita Maria Zorzenon
Cellular automata approaches are powerful tools to model local and nonlocal interactions generating cooperative behavior. In the last decade, the question of whether cellular automata could embed realistic assumptions about the interactions among cells and molecules of the immune system was quite controversial. Recent results have shown that it is possible to use cellular automata approaches to describe realistically the interactions between the elements of the immune system. The first models using cellular automata approaches, boolean and threshold or window automata, were based on experimental evidence and were mainly used to understand the logic of global immune responses like immunization, tolerance, paralysis, etc. Recently, new classes of cellular automata models which include time delay, stochasticity or adaptation have lead to results that can be compared with in vivo experimental data.
NASA Technical Reports Server (NTRS)
Havelund, Klaus
2014-01-01
The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.
Probabilistic cellular automata.
Agapie, Alexandru; Andreica, Anca; Giuclea, Marius
2014-09-01
Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.
Weighted Automata and Weighted Logics
NASA Astrophysics Data System (ADS)
Droste, Manfred; Gastin, Paul
In automata theory, a fundamental result of Büchi and Elgot states that the recognizable languages are precisely the ones definable by sentences of monadic second order logic. We will present a generalization of this result to the context of weighted automata. We develop syntax and semantics of a quantitative logic; like the behaviors of weighted automata, the semantics of sentences of our logic are formal power series describing ‘how often’ the sentence is true for a given word. Our main result shows that if the weights are taken in an arbitrary semiring, then the behaviors of weighted automata are precisely the series definable by sentences of our quantitative logic. We achieve a similar characterization for weighted Büchi automata acting on infinite words, if the underlying semiring satisfies suitable completeness assumptions. Moreover, if the semiring is additively locally finite or locally finite, then natural extensions of our weighted logic still have the same expressive power as weighted automata.
Game level layout generation using evolved cellular automata
NASA Astrophysics Data System (ADS)
Pech, Andrew; Masek, Martin; Lam, Chiou-Peng; Hingston, Philip
2016-01-01
Design of level layouts typically involves the production of a set of levels which are different, yet display a consistent style based on the purpose of a particular level. In this paper, a new approach to the generation of unique level layouts, based on a target set of attributes, is presented. These attributes, which are learned automatically from an example layout, are used for the off-line evolution of a set of cellular automata rules. These rules can then be used for the real-time generation of level layouts that meet the target parameters. The approach is demonstrated on a set of maze-like level layouts. Results are presented to show the effect of various CA parameters and rule representation.
Using cellular automata to generate image representation for biological sequences.
Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C
2005-02-01
A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.
Predictability in cellular automata.
Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius
2014-01-01
Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.
The Wonder Approach to learning
L’Ecuyer, Catherine
2014-01-01
Wonder, innate in the child, is an inner desire to learn that awaits reality in order to be awakened. Wonder is at the origin of reality-based consciousness, thus of learning. The scope of wonder, which occurs at a metaphysical level, is greater than that of curiosity. Unfortunate misinterpretations of neuroscience have led to false brain-based ideas in the field of education, all of these based on the scientifically wrong assumption that children’s learning depends on an enriched environment. These beliefs have re-enforced the Behaviorist Approach to education and to parenting and have contributed to deadening our children’s sense of wonder. We suggest wonder as the center of all motivation and action in the child. Wonder is what makes life genuinely personal. Beauty is what triggers wonder. Wonder attunes to beauty through sensitivity and is unfolded by secure attachment. When wonder, beauty, sensitivity and secure attachment are present, learning is meaningful. On the contrary, when there is no volitional dimension involved (no wonder), no end or meaning (no beauty) and no trusting predisposition (secure attachment), the rigid and limiting mechanical process of so-called learning through mere repetition become a deadening and alienating routine. This could be described as training, not as learning, because it does not contemplate the human being as a whole. PMID:25339882
Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris
2016-08-09
In this article, we focus on the electron-vibrational problem of the tetrameric mixed-valence (MV) complexes proposed for implementation as four-dot molecular quantum cellular automata (mQCA).1 Although the adiabatic approximation explored in ref 2 is an appropriate tool for the qualitative analysis of the basic characteristics of mQCA, like vibronic trapping of the electrons encoding binary information and cell-cell response, it loses its accuracy providing moderate vibronic coupling and fails in the description of the discrete pattern of the vibronic levels. Therefore, a precise solution of the quantum-mechanical vibronic problem is of primary importance for the evaluation of the shapes of the electron transfer optical absorption bands and quantitative analysis of the main parameters of tetrameric quantum cells. Here, we go beyond the Born-Oppenheimer paradigm and present a solution of the quantum-mechanical pseudo Jahn-Teller (JT) vibronic problem in bielectronic MV species (exemplified by the tetra-ruthenium complexes) based on the recently developed symmetry-assisted approach.3,4 The mathematical approach to the vibronic eigenproblem takes into consideration the point symmetry basis, and therefore, the total matrix of the JT Hamiltonian is blocked to the maximum extent. The submatrices correspond to the irreducible representations (irreps) of the point group. With this tool, we also extend the theory of the mQCA cell beyond the limit of prevailing Coulomb repulsion in the electronic pair (adopted in ref 2), and therefore, the general pseudo-JT problems for spin-singlet ((1)B1g, 2(1)A1g, (1)B2g, (1)Eu) ⊗ (b1g + eu) and spin-triplet states ((3)A2g, (3)B1g, 2(3)Eu) ⊗ (b1g + eu) in a square-planar bielectronic system are solved. The obtained symmetry-adapted electron-vibrational functions are employed for the calculation of the profiles (shape functions) of the charge transfer absorption bands in the tetrameric MV complexes and for the discussion of the
Weighted Watson-Crick automata
NASA Astrophysics Data System (ADS)
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-01
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.
Weighted Watson-Crick automata
Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku
2014-07-10
There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.
Blended Learning: An Innovative Approach
ERIC Educational Resources Information Center
Lalima; Dangwal, Kiran Lata
2017-01-01
Blended learning is an innovative concept that embraces the advantages of both traditional teaching in the classroom and ICT supported learning including both offline learning and online learning. It has scope for collaborative learning; constructive learning and computer assisted learning (CAI). Blended learning needs rigorous efforts, right…
Multipebble Simulations for Alternating Automata
NASA Astrophysics Data System (ADS)
Clemente, Lorenzo; Mayr, Richard
We study generalized simulation relations for alternating Büchi automata (ABA), as well as alternating finite automata. Having multiple pebbles allows the Duplicator to "hedge her bets" and delay decisions in the simulation game, thus yielding a coarser simulation relation. We define (k 1,k 2)-simulations, with k 1/k 2 pebbles on the left/right, respectively. This generalizes previous work on ordinary simulation (i.e., (1,1)-simulation) for nondeterministic Büchi automata (NBA)[4] in and ABA in [5], and (1,k)-simulation for NBA in [3].
Modeling biological pathway dynamics with timed automata.
Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N
2014-05-01
Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.
Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study †
Tîrnăucă, Cristina; Montaña, José L.; Ontañón, Santiago; González, Avelino J.; Pardo, Luis M.
2016-01-01
Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent’s actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches. PMID:27347956
Efficient Translation of LTL Formulae into Buchi Automata
NASA Technical Reports Server (NTRS)
Giannakopoulou, Dimitra; Lerda, Flavio
2001-01-01
Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.
Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.
ERIC Educational Resources Information Center
Biggs, John B.
This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…
Design and Evaluation of Two Blended Learning Approaches: Lessons Learned
ERIC Educational Resources Information Center
Cheung, Wing Sum; Hew, Khe Foon
2011-01-01
In this paper, we share two blended learning approaches used at the National Institute of Education in Singapore. We have been using these two approaches in the last twelve years in many courses ranging from the diploma to graduate programs. For the first blended learning approach, we integrated one asynchronous communication tool with face to…
A Colloquial Approach: An Active Learning Technique.
ERIC Educational Resources Information Center
Arce, Pedro
1994-01-01
Addresses the problem of the effectiveness of teaching methodologies on fundamental engineering courses such as transport phenomena. Recommends the colloquial approach, an active learning strategy, to increase student involvement in the learning process. (ZWH)
E-Learning Approach in Teacher Training
ERIC Educational Resources Information Center
Yucel, Seda A.
2006-01-01
There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational…
Project Management Approaches for Online Learning Design
ERIC Educational Resources Information Center
Eby, Gulsun; Yuzer, T. Volkan
2013-01-01
Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…
Scalable asynchronous execution of cellular automata
NASA Astrophysics Data System (ADS)
Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo
2016-10-01
The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.
Selective networks and recognition automata.
Reeke, G N; Edelman, G M
1984-01-01
The results we have presented demonstrate that a network based on a selective principle can function in the absence of forced learning or an a priori program to give recognition, classification, generalization, and association. While Darwin II is not a model of any actual nervous system, it does set out to solve one of the same problems that evolution had to solve--the need to form categories in a bottom-up manner from information in the environment, without incorporating the assumptions of any particular observer. The key features of the model that make this possible are (1) Darwin II incorporates selective networks whose initial specificities enable them to respond without instruction to unfamiliar stimuli; (2) degeneracy provides multiple possibilities of response to any one stimulus, at the same time providing functional redundancy against component failure; (3) the output of Darwin II is a pattern of response, making use of the simultaneous responses of multiple degenerate groups to avoid the need for very high specificity and the combinatorial disaster that would imply; (4) reentry within individual networks vitiates the limitations described by Minsky and Papert for a class of perceptual automata lacking such connections; and (5) reentry between intercommunicating networks with different functions gives rise to new functions, such as association, that either one alone could not display. The two kinds of network are roughly analogous to the two kinds of category formation that people use: Darwin, corresponding to the exemplar description of categories, and Wallace, corresponding to the probabilistic matching description of categories. These principles lead to a new class of pattern-recognizing machine of which Darwin II is just an example. There are a number of obvious extensions to this work that we are pursuing. These include giving Darwin II the capability to deal with stimuli that are in motion, an ability that probably precedes the ability of biological
Cellular Automata and the Humanities.
ERIC Educational Resources Information Center
Gallo, Ernest
1994-01-01
The use of cellular automata to analyze several pre-Socratic hypotheses about the evolution of the physical world is discussed. These hypotheses combine characteristics of both rigorous and metaphoric language. Since the computer demands explicit instructions for each step in the evolution of the automaton, such models can reveal conceptual…
Optimal online learning: a Bayesian approach
NASA Astrophysics Data System (ADS)
Solla, Sara A.; Winther, Ole
1999-09-01
A recently proposed Bayesian approach to online learning is applied to learning a rule defined as a noisy single layer perceptron. In the Bayesian online approach, the exact posterior distribution is approximated by a simple parametric posterior that is updated online as new examples are incorporated to the dataset. In the case of binary weights, the approximate posterior is chosen to be a biased binary distribution. The resulting online algorithm is shown to outperform several other online approaches to this problem.
Accelerated learning approaches for maintenance training
Erickson, E.J.
1991-01-01
As a training tool, Accelerated Learning techniques have been in use since 1956. Trainers from a variety of applications and disciplines have found success in using Accelerated Learning approaches, such as training aids, positive affirmations, memory aids, room arrangement, color patterns, and music. Some have thought that maintenance training and Accelerated Learning have nothing in common. Recent training applications by industry and education of Accelerated Learning are proving very successful by several standards. This paper cites available resource examples and challenges maintenance trainers to adopt new ideas and concepts to accelerate learning in all training setting. 7 refs.
Astrobiological Complexity with Probabilistic Cellular Automata
NASA Astrophysics Data System (ADS)
Vukotić, Branislav; Ćirković, Milan M.
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.
Astrobiological complexity with probabilistic cellular automata.
Vukotić, Branislav; Ćirković, Milan M
2012-08-01
The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.
Learning Families: Intergenerational Approach to Literacy Teaching and Learning
ERIC Educational Resources Information Center
Hanemann, Ulrike, Ed.
2015-01-01
Within a learning family, every member is a lifelong learner. A family literacy and learning approach is more likely to break the intergenerational cycle of low education and inadequate literacy skills, particularly among disadvantaged families and communities. The selection of case studies presented in this compilation show that for an…
Learning Geometry through Discovery Learning Using a Scientific Approach
ERIC Educational Resources Information Center
In'am, Akhsanul; Hajar, Siti
2017-01-01
The objective of this present research is to analyze the implementation of learning geometry through a scientific learning consisting of three aspects: 1) teacher's activities, 2) students' activities and, 3) the achievement results. The adopted approach is a descriptive-quantitative one and the subject is the Class VII students of Islamic Junior…
A Reinforcement Learning Approach to Control.
1997-05-31
acquisition is inherently a partially observable Markov decision problem. This report describes an efficient, scalable reinforcement learning approach to the...deployment of refined intelligent gaze control techniques. This report first lays a theoretical foundation for reinforcement learning . It then introduces...perform well in both high and low SNR ATR environments. Reinforcement learning coupled with history features appears to be both a sound foundation and a practical scalable base for gaze control.
A Hybrid Approach to Active Learning.
ERIC Educational Resources Information Center
Ramsier, R. D.
2001-01-01
Describes an approach to incorporate active learning strategies into the first semester of a university-level introductory physics course. Combines cooperative and peer-based methods inside the classroom with project-based learning outside the classroom in an attempt to develop students' transferable skills as well as improving their understanding…
A Guided Discovery Approach for Learning Glycolysis.
ERIC Educational Resources Information Center
Schultz, Emeric
1997-01-01
Argues that more attention should be given to teaching students how to learn the rudiments of specific metabolic pathways. This approach describes a unique way of learning the glycolytic pathway in stepwise fashion. The pedagogy involves clear rote components that are connected to a set of generalizations that develop and enhance important…
Constructivist Learning Approach in Science Teaching
ERIC Educational Resources Information Center
Demirci, Cavide
2009-01-01
Constructivism is not a new concept. It has its roots in philosophy and has been applied to sociology and anthropology, as well as cognitive psychology and education. The aim of this research is to reveal if there is a significant difference between the means of achievement and retention learning scores of constructivist learning approach applied…
A Learning Cycle Approach To Introducing Osmosis.
ERIC Educational Resources Information Center
Lawson, Anton E.
2000-01-01
Presents an inquiry activity with a learning cycle approach to engage students in testing their own hypotheses about how molecules move through cell membranes. Offers student materials and teacher materials, including teaching tips for each phase of the learning cycle. (Contains 11 references.) (ASK)
An approach to elemental task learning
Belmans, P
1990-01-01
In this article we deal with the automated learning of tasks by a robotic system through observation of a human operator. Particularly, we explain what is meant by a learning ability in autonomous robots and in teleoperation systems, where several operators and several machines may work in cooperation to perform tasks. We discuss different approaches to learning in these systems and outline the features of the models they are based upon. This leads us to choose an analytical model suited for tasks analysis. We then present the software architecture for our proposed approach and show the first results obtained on sample tests. 5 refs., 9 figs.
A Transfer Learning Approach for Network Modeling
Huang, Shuai; Li, Jing; Chen, Kewei; Wu, Teresa; Ye, Jieping; Wu, Xia; Yao, Li
2012-01-01
Networks models have been widely used in many domains to characterize the interacting relationship between physical entities. A typical problem faced is to identify the networks of multiple related tasks that share some similarities. In this case, a transfer learning approach that can leverage the knowledge gained during the modeling of one task to help better model another task is highly desirable. In this paper, we propose a transfer learning approach, which adopts a Bayesian hierarchical model framework to characterize task relatedness and additionally uses the L1-regularization to ensure robust learning of the networks with limited sample sizes. A method based on the Expectation-Maximization (EM) algorithm is further developed to learn the networks from data. Simulation studies are performed, which demonstrate the superiority of the proposed transfer learning approach over single task learning that learns the network of each task in isolation. The proposed approach is also applied to identification of brain connectivity networks of Alzheimer’s disease (AD) from functional magnetic resonance image (fMRI) data. The findings are consistent with the AD literature. PMID:24526804
Diversity Learning: A Different Approach.
ERIC Educational Resources Information Center
Wilcox, Herbert S.; Waagbo, Jean M.
2001-01-01
Reports on the Community College of Baltimore County's (Maryland) service learning program for diversity education, which is unique to American community colleges. States that students and faculty members spent two weeks in Belize, establishing a summer camp program for children to develop English skills. Asserts that volunteers benefited from the…
Xtoys: Cellular automata on xwindows
Creutz, M.
1995-08-15
Xtoys is a collection of xwindow programs for demonstrating simulations of various statistical models. Included are xising, for the two dimensional Ising model, xpotts, for the q-state Potts model, xautomalab, for a fairly general class of totalistic cellular automata, xsand, for the Bak-Tang-Wiesenfield model of self organized criticality, and xfires, a simple forest fire simulation. The programs should compile on any machine supporting xwindows.
A Cognitive Approach to e-Learning
Greitzer, Frank L.; Rice, Douglas M.; Eaton, Sharon L.; Perkins, Michael C.; Scott, Ryan T.; Burnette, John R.; Robertson, Sarah R.
2003-12-01
Like traditional classroom instruction, distributed learning derives from passive training paradigms. Just as student-centered classroom teaching methods have been applied over several decades of classroom instruction, interactive approaches have been encouraged for distributed learning. While implementation of multimedia-based training features may appear to produce active learning, sophisticated use of multimedia features alone does not necessarily enhance learning. This paper describes the results of applying cognitive science principles to enhance learning in a student-centered, distributed learning environment, and lessons learned in developing and delivering this training. Our interactive, scenario-based approach exploits multimedia technology within a systematic, cognitive framework for learning. The basis of the application of cognitive principles is the innovative use of multimedia technology to implement interaction elements. These simple multimedia interactions, which are used to support new concepts, are later combined with other interaction elements to create more complex, integrated practical exercises. This technology-based approach may be applied in a variety of training and education contexts, but is especially well suited for training of equipment operators and maintainers. For example, it has been used in a sustainment training application for the United States Army's Combat Support System Automated Information System Interface (CAISI). The CAISI provides a wireless communications capability that allows various logistics systems to communicate across the battlefield. Based on classroom training material developed by the CAISI Project Office, the Pacific Northwest National Laboratory designed and developed an interactive, student-centered distributed-learning application for CAISI operators and maintainers. This web-based CAISI training system is also distributed on CD media for use on individual computers, and material developed for the computer
Classifying cellular automata using grossone
NASA Astrophysics Data System (ADS)
D'Alotto, Louis
2016-10-01
This paper proposes an application of the Infinite Unit Axiom and grossone, introduced by Yaroslav Sergeyev (see [7] - [12]), to the development and classification of one and two-dimensional cellular automata. By the application of grossone, new and more precise nonarchimedean metrics on the space of definition for one and two-dimensional cellular automata are established. These new metrics allow us to do computations with infinitesimals. Hence configurations in the domain space of cellular automata can be infinitesimally close (but not equal). That is, they can agree at infinitely many places. Using the new metrics, open disks are defined and the number of points in each disk computed. The forward dynamics of a cellular automaton map are also studied by defined sets. It is also shown that using the Infinite Unit Axiom, the number of configurations that follow a given configuration, under the forward iterations of cellular automaton maps, can now be computed and hence a classification scheme developed based on this computation.
Learning Centers: A Personalized Approach to Mainstreaming.
ERIC Educational Resources Information Center
Babich, Betsy; Thompson, Cecelia
The manual provides information about using learning centers in mainstreamed home economics classrooms. The initial chapter introduces the rationale for the approach and presents a three-stage model depicting an integrational approach to mainstreaming. Chapter 2 outlines typical characteristics and recommendations for accommodating students with…
Generalized information-lossless automata. I
Speranskii, D.V.
1995-01-01
Huffman and Even introduced classes of abstract automata, which they called respectively information-lossless automata (ILL) and information-lossless automata of finite order (ILLFO). The underlying property of these automata is the ability to reconstruct unknown input sequences from observations of the output response, assuming that the true initial state of the automaton is known. Similar classes of automata introduced in are called essentially information-lossless automata, and they are capable of reconstructing the unknown input word without knowledge of the initial state of the automaton. It is only assumed that the set of possible initial states of the automaton is the set of all automaton states. In this paper we analyze a structural analog of an abstract ILL-automaton whose set of initial states may be of arbitrary cardinality. This class of automata is thus a generalization of the classical ILL-automata, which allows not only for the structure of the input and output alphabets, but also for the configuration of the set of possible initial states.
Understanding Observational Learning: An Interbehavioral Approach
Fryling, Mitch J; Johnston, Cristin; Hayes, Linda J
2011-01-01
Observational learning is an important area in the field of psychology and behavior science more generally. Given this, it is essential that behavior analysts articulate a sound theory of how behavior change occurs through observation. This paper begins with an overview of seminal research in the area of observational learning, followed by a consideration of common behavior analytic conceptualizations of these findings. The interbehavioral perspective is then outlined, shedding light on some difficulties with the existing behavior analytic approaches. The implications of embracing the interbehavioral perspective for understanding the most complex sorts of behavior, including those involved in observational learning are considered. PMID:22532764
On the secure obfuscation of deterministic finite automata.
Anderson, William Erik
2008-06-01
In this paper, we show how to construct secure obfuscation for Deterministic Finite Automata, assuming non-uniformly strong one-way functions exist. We revisit the software protection approaches originally proposed by [5, 10, 12, 17] and revise them to the current obfuscation setting of Barak et al. [2]. Under this model, we introduce an efficient oracle that retains some 'small' secret about the original program. Using this secret, we can construct an obfuscator and two-party protocol that securely obfuscates Deterministic Finite Automata against malicious adversaries. The security of this model retains the strong 'virtual black box' property originally proposed in [2] while incorporating the stronger condition of dependent auxiliary inputs in [15]. Additionally, we show that our techniques remain secure under concurrent self-composition with adaptive inputs and that Turing machines are obfuscatable under this model.
Stochastic computing with biomolecular automata.
Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud
2004-07-06
Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure.
Cellular automata for traffic simulations
NASA Astrophysics Data System (ADS)
Wolf, Dietrich E.
1999-02-01
Traffic phenomena such as the transition from free to congested flow, lane inversion and platoon formation can be accurately reproduced using cellular automata. Being computationally extremely efficient, they simulate large traffic systems many times faster than real time so that predictions become feasible. A riview of recent results is given. The presence of metastable states at the jamming transition is discussed in detail. A simple new cellular automation is introduced, in which the interaction between cars is Galilei-invariant. It is shown that this type of interaction accounts for metastable states in a very natural way.
Symmetry analysis of cellular automata
NASA Astrophysics Data System (ADS)
García-Morales, V.
2013-01-01
By means of B-calculus [V. García-Morales, Phys. Lett. A 376 (2012) 2645] a universal map for deterministic cellular automata (CAs) has been derived. The latter is shown here to be invariant upon certain transformations (global complementation, reflection and shift). When constructing CA rules in terms of rules of lower range a new symmetry, “invariance under construction” is uncovered. Modular arithmetic is also reformulated within B-calculus and a new symmetry of certain totalistic CA rules, which calculate the Pascal simplices modulo an integer number p, is then also uncovered.
Approach to Learning and Assessment in Physics.
ERIC Educational Resources Information Center
Dickie, Leslie
The objectives of this exploratory study were to determine: (1) the approach to learning of physics students (N=142) at John Abbott College (Quebec, Canada) as determined by the Study Process Questionnaire; (2) the intellectual demands of quizzes, tests, and final exams in physics using a scheme derived from Bloom's taxonomy; and (3) the…
An Approach to Learning by Construction
ERIC Educational Resources Information Center
Bagarukayo, Emily; Weide, Theo; Meijden, Henny
2012-01-01
This paper proposes an innovative idea for providing affordable, sustainable, and meaningful education for students in Least Developed Countries (LDCs). The authors show how a Digital Learning Environment (DLE) can play a central role in community development. The authors develop and validate an approach for introduction of an ICT education…
Team Building: A Structured Learning Approach.
ERIC Educational Resources Information Center
Mears, Peter; Voehl, Frank
This book is a learner's manual for a course on how to develop empowered teams for higher education management, how to function effectively as a team member, and how to objectively evaluate one's impact on the team. Taking a hands-on approach to learning about quality, the course introduces quality principles, asks students to apply these in a…
Transformative Learning Approaches for Public Relations Pedagogy
ERIC Educational Resources Information Center
Motion, Judy; Burgess, Lois
2014-01-01
Public relations educators are frequently challenged by students' flawed perceptions of public relations. Two contrasting case studies are presented in this paper to illustrate how socially-oriented paradigms may be applied to a real-client project to deliver a transformative learning experience. A discourse-analytic approach is applied within the…
A Mixed Learning Approach in Mechatronics Education
ERIC Educational Resources Information Center
Yilmaz, O.; Tuncalp, K.
2011-01-01
This study aims to investigate the effect of a Web-based mixed learning approach model on mechatronics education. The model combines different perception methods such as reading, listening, and speaking and practice methods developed in accordance with the vocational background of students enrolled in the course Electromechanical Systems in…
Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach
ERIC Educational Resources Information Center
Schumacher, Thomas
2015-01-01
The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…
ERIC Educational Resources Information Center
Chiu, Thomas K. F.; Churchill, Daniel
2016-01-01
Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…
Towards a voxel-based geographic automata for the simulation of geospatial processes
NASA Astrophysics Data System (ADS)
Jjumba, Anthony; Dragićević, Suzana
2016-07-01
Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.
Stimulus-Response Theory of Finite Automata, Technical Report No. 133.
ERIC Educational Resources Information Center
Suppes, Patrick
The central aim of this paper and its projected successors is to prove in detail that stimulus-response theory, or at least a mathematically precise version, can give an account of the learning of many phrase-structure grammars. Section 2 is concerned with standard notions of finite and probabilistic automata. An automaton is defined as a device…
Prehospital curriculum development: a learning objective approach.
Schafermeyer, R W
1993-02-01
Prehospital curriculum development is a time-consuming, yet essential, component of emergency medical technician and paramedic education. Over the past several years, much has changed within the EMS system and with the approach to educating the prehospital care provider. Learning is defined as a permanent change in behavior that comes about as a result of a planned experience. This planned experience must include learning objectives that incorporate assessment of presenting signs and symptoms and demonstrate the prehospital care providers' psychomotor skills in providing prehospital care based on that assessment.
Quantum features of natural cellular automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2016-03-01
Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement.
A Decomposition Theorem for Finite Automata.
ERIC Educational Resources Information Center
Santa Coloma, Teresa L.; Tucci, Ralph P.
1990-01-01
Described is automata theory which is a branch of theoretical computer science. A decomposition theorem is presented that is easier than the Krohn-Rhodes theorem. Included are the definitions, the theorem, and a proof. (KR)
Reversibility of a Symmetric Linear Cellular Automata
NASA Astrophysics Data System (ADS)
Del Rey, A. Martín; Sánchez, G. Rodríguez
The characterization of the size of the cellular space of a particular type of reversible symmetric linear cellular automata is introduced in this paper. Specifically, it is shown that those symmetric linear cellular with 2k + 1 cells, and whose transition matrix is a k-diagonal square band matrix with nonzero entries equal to 1 are reversible. Furthermore, in this case the inverse cellular automata are explicitly computed. Moreover, the reversibility condition is also studied for a general number of cells.
Towards an Integrated Approach for Research on Lifelong Learning
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.; Kirschner, Paul A.; Paas, Fred; Sloep, Peter B.; J. Caniels, Marjolein C.
2009-01-01
There is little dispute that lifelong learning is essential to the further development of the knowledge society. Nonetheless, lifelong learning is not reaching its full potential because the currently used approaches to lifelong learning are too fragmented and, often, formal approaches to education and learning are simply "translated" from initial…
Understanding Fatty Acid Metabolism through an Active Learning Approach
ERIC Educational Resources Information Center
Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.
2010-01-01
A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…
Comparing Team Learning Approaches through the Lens of Activity Theory
ERIC Educational Resources Information Center
Park, Sunyoung; Cho, Yonjoo; Yoon, Seung Won; Han, Heeyoung
2013-01-01
Purpose: The purpose of this study is to examine the distinctive features of three team learning approaches (action learning, problem-based learning, and project-based learning), compare and contrast them, and discuss implications for practice and research. Design/methodology/approach: The authors used Torraco's integrative literature review…
Economic Gardening through Entrepreneurship Education: A Service-Learning Approach
ERIC Educational Resources Information Center
Desplaces, David E.; Wergeles, Fred; McGuigan, Patrick
2009-01-01
This article outlines the implementation of a service-learning approach in an entrepreneurship programme using an "economic gardening" strategy. Economic Gardening through Service-Learning (EGS-L) is an approach to economic development that helps local businesses and students grow through a facilitated learning process. Learning is made possible…
ChemApproach: Validation of a Questionnaire to Assess the Learning Approaches of Chemistry Students
ERIC Educational Resources Information Center
Lastusaari, Mika; Laakkonen, Eero; Murtonen, Mari
2016-01-01
The theory of learning approaches has proven to be one of the most powerful theories explaining university students' learning. However, learning approaches are sensitive to the situation and the content of learning. Chemistry has its own specific features that should be considered when exploring chemistry students' learning habits, specifically…
Fuzzy automata and pattern matching
NASA Technical Reports Server (NTRS)
Setzer, C. B.; Warsi, N. A.
1986-01-01
A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.
Generic framework for mining cellular automata models on protein-folding simulations.
Diaz, N; Tischer, I
2016-05-13
Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.
Modelling of the cellular automata space deformation within the RCAFE framework
NASA Astrophysics Data System (ADS)
Sitko, Mateusz; Madej, Łukasz
2016-10-01
Development of the innovative approach to micro scale cellular automata (CA) space deformation during dynamic recrystallization process (DRX) is the main goal of the present paper. Major assumptions of the developed CA DRX model as well as novel space deformation algorithm, which is based on the random cellular automata concept and FE method, are described. Algorithms and methods to transfer input/output data between FE and CA are presented in detail. Visualization tool to analyze progress of deformation in the irregular CA space is also highlighted. Finally, initial results in the form of deformed and recrystallized microstructures are presented and discussed.
Maximizing exposure therapy: an inhibitory learning approach.
Craske, Michelle G; Treanor, Michael; Conway, Christopher C; Zbozinek, Tomislav; Vervliet, Bram
2014-07-01
Exposure therapy is an effective approach for treating anxiety disorders, although a substantial number of individuals fail to benefit or experience a return of fear after treatment. Research suggests that anxious individuals show deficits in the mechanisms believed to underlie exposure therapy, such as inhibitory learning. Targeting these processes may help improve the efficacy of exposure-based procedures. Although evidence supports an inhibitory learning model of extinction, there has been little discussion of how to implement this model in clinical practice. The primary aim of this paper is to provide examples to clinicians for how to apply this model to optimize exposure therapy with anxious clients, in ways that distinguish it from a 'fear habituation' approach and 'belief disconfirmation' approach within standard cognitive-behavior therapy. Exposure optimization strategies include (1) expectancy violation, (2) deepened extinction, (3) occasional reinforced extinction, (4) removal of safety signals, (5) variability, (6) retrieval cues, (7) multiple contexts, and (8) affect labeling. Case studies illustrate methods of applying these techniques with a variety of anxiety disorders, including obsessive-compulsive disorder, posttraumatic stress disorder, social phobia, specific phobia, and panic disorder.
Maximizing Exposure Therapy: An Inhibitory Learning Approach
Craske, Michelle G.; Treanor, Michael; Conway, Chris; Zbozinek, Tomislav; Vervliet, Bram
2014-01-01
Exposure therapy is an effective approach for treating anxiety disorders, although a substantial number of individuals fail to benefit or experience a return of fear after treatment. Research suggests that anxious individuals show deficits in the mechanisms believed to underlie exposure therapy, such as inhibitory learning. Targeting these processes may help improve the efficacy of exposure-based procedures. Although evidence supports an inhibitory learning model of extinction, there has been little discussion of how to implement this model in clinical practice. The primary aim of this paper is to provide examples to clinicians for how to apply this model to optimize exposure therapy with anxious clients, in ways that distinguish it from a ‘fear habituation’ approach and ‘belief disconfirmation’ approach within standard cognitive-behavior therapy. Exposure optimization strategies include 1) expectancy violation, 2) deepened extinction, 3) occasional reinforced extinction, 4) removal of safety signals, 5) variability, 6) retrieval cues, 7) multiple contexts, and 8) affect labeling. Case studies illustrate methods of applying these techniques with a variety of anxiety disorders, including obsessive-compulsive disorder, posttraumatic stress disorder, social phobia, specific phobia, and panic disorder. PMID:24864005
Lattice gas automata for flow and transport in geochemical systems
Janecky, D.R.; Chen, S.; Dawson, S.; Eggert, K.C.; Travis, B.J.
1992-01-01
Lattice gas automata models are described, which couple solute transport with chemical reactions at mineral surfaces within pore networks. Diffusion in a box calculations are illustrated, which compare directly with Fickian diffusion. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because hydrodynamic transport, solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible.
Lattice gas automata for flow and transport in geochemical systems
Janecky, D.R.; Chen, S.; Dawson, S.; Eggert, K.C.; Travis, B.J.
1992-05-01
Lattice gas automata models are described, which couple solute transport with chemical reactions at mineral surfaces within pore networks. Diffusion in a box calculations are illustrated, which compare directly with Fickian diffusion. Chemical reactions at solid surfaces, including precipitation/dissolution, sorption, and catalytic reaction, can be examined with the model because hydrodynamic transport, solute diffusion and mineral surface processes are all treated explicitly. The simplicity and flexibility of the approach provides the ability to study the interrelationship between fluid flow and chemical reactions in porous materials, at a level of complexity that has not previously been computationally possible.
Noisy quantum cellular automata for quantum versus classical excitation transfer.
Avalle, Michele; Serafini, Alessio
2014-05-02
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
Noisy Quantum Cellular Automata for Quantum versus Classical Excitation Transfer
NASA Astrophysics Data System (ADS)
Avalle, Michele; Serafini, Alessio
2014-05-01
We introduce a class of noisy quantum cellular automata on a qubit lattice that includes all classical Markov chains, as well as maps where quantum coherence between sites is allowed to build up over time. We apply such a construction to the problem of excitation transfer through 1D lattices, and compare the performance of classical and quantum dynamics with equal local transition probabilities. Our discrete approach has the merits of stripping down the complications of the open system dynamics, of clearly isolating coherent effects, and of allowing for an exact treatment of conditional dynamics, all while capturing a rich variety of dynamical behaviors.
Social learning in Models and Cases - an Interdisciplinary Approach
NASA Astrophysics Data System (ADS)
Buhl, Johannes; De Cian, Enrica; Carrara, Samuel; Monetti, Silvia; Berg, Holger
2016-04-01
Our paper follows an interdisciplinary understanding of social learning. We contribute to the literature on social learning in transition research by bridging case-oriented research and modelling-oriented transition research. We start by describing selected theories on social learning in innovation, diffusion and transition research. We present theoretical understandings of social learning in techno-economic and agent-based modelling. Then we elaborate on empirical research on social learning in transition case studies. We identify and synthetize key dimensions of social learning in transition case studies. In the following we bridge between more formal and generalising modelling approaches towards social learning processes and more descriptive, individualising case study approaches by interpreting the case study analysis into a visual guide on functional forms of social learning typically identified in the cases. We then try to exemplarily vary functional forms of social learning in integrated assessment models. We conclude by drawing the lessons learned from the interdisciplinary approach - methodologically and empirically.
ERIC Educational Resources Information Center
Malie, Senian; Akir, Oriah
2012-01-01
Learning approaches, learning methods and learning environments have different effects on students? academic performance. However, they are not the sole factors that impact students? academic achievement. The aims of this research are three-fold: to determine the learning approaches preferred by most students and the impact of the learning…
ERIC Educational Resources Information Center
Vanthournout, Gert; Coertjens, Liesje; Gijbels, David; Donche, Vincent; Van Petegem, Peter
2013-01-01
Research regarding the development of students' learning approaches have at times reported unexpected or lack of expected changes. The current study explores the idea of differential developments in learning approaches according to students' initial learning profiles as a possible explanation for these outcomes. A learning profile is conceived as…
Concept Based Approach for Adaptive Personalized Course Learning System
ERIC Educational Resources Information Center
Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali
2013-01-01
One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…
Component-Based Approach in Learning Management System Development
ERIC Educational Resources Information Center
Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey
2013-01-01
The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…
Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches
ERIC Educational Resources Information Center
Yilmaz, M. Betul; Orhan, Feza
2010-01-01
Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…
Information-theoretic approach to interactive learning
NASA Astrophysics Data System (ADS)
Still, S.
2009-01-01
The principles of statistical mechanics and information theory play an important role in learning and have inspired both theory and the design of numerous machine learning algorithms. The new aspect in this paper is a focus on integrating feedback from the learner. A quantitative approach to interactive learning and adaptive behavior is proposed, integrating model- and decision-making into one theoretical framework. This paper follows simple principles by requiring that the observer's world model and action policy should result in maximal predictive power at minimal complexity. Classes of optimal action policies and of optimal models are derived from an objective function that reflects this trade-off between prediction and complexity. The resulting optimal models then summarize, at different levels of abstraction, the process's causal organization in the presence of the learner's actions. A fundamental consequence of the proposed principle is that the learner's optimal action policies balance exploration and control as an emerging property. Interestingly, the explorative component is present in the absence of policy randomness, i.e. in the optimal deterministic behavior. This is a direct result of requiring maximal predictive power in the presence of feedback.
A Bayesian Approach to Learning Scoring Systems.
Ertekin, Şeyda; Rudin, Cynthia
2015-12-01
We present a Bayesian method for building scoring systems, which are linear models with coefficients that have very few significant digits. Usually the construction of scoring systems involve manual effort-humans invent the full scoring system without using data, or they choose how logistic regression coefficients should be scaled and rounded to produce a scoring system. These kinds of heuristics lead to suboptimal solutions. Our approach is different in that humans need only specify the prior over what the coefficients should look like, and the scoring system is learned from data. For this approach, we provide a Metropolis-Hastings sampler that tends to pull the coefficient values toward their "natural scale." Empirically, the proposed method achieves a high degree of interpretability of the models while maintaining competitive generalization performances.
Course Management Systems and Blended Learning: An Innovative Learning Approach
ERIC Educational Resources Information Center
Chou, Amy Y.; Chou, David C.
2011-01-01
This article utilizes Rogers' innovation-decision process model (2003) and Beckman and Berry's innovation process model (2007) to create an innovative learning map that illustrates three learning methods (i.e., face-to-face learning, online learning, and blended learning) in two types of innovation (i.e., incremental innovation and radical…
Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches
ERIC Educational Resources Information Center
Wang, Victor C. X.
2010-01-01
As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…
Approaches to Learning and Study Orchestrations in High School Students
ERIC Educational Resources Information Center
Cano, Francisco
2007-01-01
In the framework of the SAL (Students' approaches to learning) position, the learning experience (approaches to learning and study orchestrations) of 572 high school students was explored, examining its interrelationships with some personal and familial variables. Three major results emerged. First, links were found between family's intellectual…
Investigative Primary Science: A Problem-Based Learning Approach
ERIC Educational Resources Information Center
Etherington, Matthew B.
2011-01-01
This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…
Computational approaches to motor learning by imitation.
Schaal, Stefan; Ijspeert, Auke; Billard, Aude
2003-01-01
Movement imitation requires a complex set of mechanisms that map an observed movement of a teacher onto one's own movement apparatus. Relevant problems include movement recognition, pose estimation, pose tracking, body correspondence, coordinate transformation from external to egocentric space, matching of observed against previously learned movement, resolution of redundant degrees-of-freedom that are unconstrained by the observation, suitable movement representations for imitation, modularization of motor control, etc. All of these topics by themselves are active research problems in computational and neurobiological sciences, such that their combination into a complete imitation system remains a daunting undertaking-indeed, one could argue that we need to understand the complete perception-action loop. As a strategy to untangle the complexity of imitation, this paper will examine imitation purely from a computational point of view, i.e. we will review statistical and mathematical approaches that have been suggested for tackling parts of the imitation problem, and discuss their merits, disadvantages and underlying principles. Given the focus on action recognition of other contributions in this special issue, this paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Based on the formalization of motor control in terms of control policies and their associated performance criteria, useful taxonomies of imitation learning can be generated that clarify different approaches and future research directions. PMID:12689379
Multipartite cellular automata and the superposition principle
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
2016-05-01
Cellular automata (CA) can show well known features of quantum mechanics (QM), such as a linear updating rule that resembles a discretized form of the Schrödinger equation together with its conservation laws. Surprisingly, a whole class of “natural” Hamiltonian CA, which are based entirely on integer-valued variables and couplings and derived from an action principle, can be mapped reversibly to continuum models with the help of sampling theory. This results in “deformed” quantum mechanical models with a finite discreteness scale l, which for l→0 reproduce the familiar continuum limit. Presently, we show, in particular, how such automata can form “multipartite” systems consistently with the tensor product structures of non-relativistic many-body QM, while maintaining the linearity of dynamics. Consequently, the superposition principle is fully operative already on the level of these primordial discrete deterministic automata, including the essential quantum effects of interference and entanglement.
Cellular Automata Simulation for Wealth Distribution
NASA Astrophysics Data System (ADS)
Lo, Shih-Ching
2009-08-01
Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.
Learning Approaches, Demographic Factors to Predict Academic Outcomes
ERIC Educational Resources Information Center
Nguyen, Tuan Minh
2016-01-01
Purpose: The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors. Design/Methodology/Approach: ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An…
Cyber Asynchronous versus Blended Cyber Approach in Distance English Learning
ERIC Educational Resources Information Center
Ge, Zi-Gang
2012-01-01
This study aims to compare the single cyber asynchronous learning approach with the blended cyber learning approach in distance English education. Two classes of 70 students participated in this study, which lasted one semester of about four months, with one class using the blended approach for their English study and the other only using the…
A Narrative Approach for Organizational Learning in a Diverse Organisation
ERIC Educational Resources Information Center
Lamsa, Anna-Maija; Sintonen, Teppo
2006-01-01
Purpose: This paper aims to construct an approach referred to as "the participatory narrative" for organizational learning in diverse organizations. The approach is grounded in an understanding of organizational learning as the process of social construction which is narratively mediated. Design/methodology/approach: The participatory narrative is…
Alternative Assessment Approaches for Online Learning Environments in Higher Education.
ERIC Educational Resources Information Center
Reeves, Thomas C.
2000-01-01
Describes the need and prospects for alternative assessment approaches in online learning environments in higher education. Explains the difference between assessment and evaluation and discusses three approaches to integrating alternative assessment approaches into online learning environments: cognitive assessment, performance assessment, and…
Edu-mining: A Machine Learning Approach
NASA Astrophysics Data System (ADS)
Srimani, P. K.; Patil, Malini M.
2011-12-01
Mining Educational data is an emerging interdisciplinary research area that mainly deals with the development of methods to explore the data stored in educational institutions. The educational data is referred as Edu-DATA. Queries related to Edu-DATA are of practical interest as SQL approach is insufficient and needs to be focused in a different way. The paper aims at developing a technique called Edu-MINING which converts raw data coming from educational institutions using data mining techniques into useful information. The discovered knowledge will have a great impact on the educational research and practices. Edu-MINING explores Edu-DATA, discovers new knowledge and suggests useful methods to improve the quality of education with regard to teaching-learning process. This is illustrated through a case study.
Particle learning for probabilistic deterministic finite automata
2011-09-01
The plpdfa software is a product of an LDRD project at LLNL entitked "Adaptive Sampling for Very High Throughput Data Streams" (tracking number 11-ERD-035). This software was developed by a graduate student summer intern, Chris Challis, who worked under project PI Dan Merl furing the summer of 2011. The software the source code is implementing is a statistical analysis technique for clustering and classification of text-valued data. The method had been previously published by the PI in the open literature.
Machine learning: An artificial intelligence approach
Michalski, R.S.; Carbonell, J.G.; Mitchell, T.M.
1983-01-01
This book contains tutorial overviews and research papers on contemporary trends in the area of machine learning viewed from an AI perspective. Research directions covered include: learning from examples, modeling human learning strategies, knowledge acquisition for expert systems, learning heuristics, discovery systems, and conceptual data analysis.
Fuzzy cellular automata models in immunology
Ahmed, E.
1996-10-01
The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level.
Do Learning Approaches of Medical Students Affect Their Satisfaction with Problem-Based Learning?
ERIC Educational Resources Information Center
Gurpinar, Erol; Kulac, Esin; Tetik, Cihat; Akdogan, Ilgaz; Mamakli, Sumer
2013-01-01
The aim of this research was to determine the satisfaction of medical students with problem-based learning (PBL) and their approaches to learning to investigate the effect of learning approaches on their levels of satisfaction. The study group was composed of medical students from three different universities, which apply PBL at different levels…
ERIC Educational Resources Information Center
Baeten, Marlies; Dochy, Filip; Struyven, Katrien
2013-01-01
Previous research has shown the difficulty of enhancing students' approaches to learning, in particular the deep approach, through student-centred teaching methods such as problem- and case-based learning. This study investigates whether mixed instructional methods combining case-based learning and lectures have the power to enhance students'…
Students' Questions: Building a Bridge between Kolb's Learning Styles and Approaches to Learning
ERIC Educational Resources Information Center
de Jesus, Helena T. Pedrosa; Almeida, Patricia Albergaria; Teixeira-Dias, Jose Joaquim; Watts, Mike
2006-01-01
Purpose: The purpose of this study is to identify the types of questions that students ask during the learning of chemistry; discuss the role of students' questions in the process of constructing knowledge, and investigate the relationship between students' questions, approaches to learning, and learning styles. Design/methodology/approach: The…
Opening Lines: Approaches to the Scholarship of Teaching and Learning.
ERIC Educational Resources Information Center
Hutchings, Pat, Ed.
This publication features reports by eight Carnegie Scholars who are working to develop a scholarship of teaching and learning that will advance the profession of teaching and improve student learning. Following the Introduction, "Approaching the Scholarship of Teaching and Learning" (Pat Hutchings), the papers are: "Investigating Student Learning…
A Learning Progressions Approach to Early Algebra Research and Practice
ERIC Educational Resources Information Center
Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Knuth, Eric
2015-01-01
We detail a learning progressions approach to early algebra research and how existing work around learning progressions and trajectories in mathematics and science education has informed our development of a four-component theoretical framework consisting of: a curricular progression of learning goals across big algebraic ideas; an instructional…
(Re)Conceptualizing Design Approaches for Mobile Language Learning
ERIC Educational Resources Information Center
Hoven, Debra; Palalas, Agnieszka
2011-01-01
An exploratory study conducted at George Brown College in Toronto, Canada between 2007 and 2009 investigated language learning with mobile devices as an approach to augmenting ESP learning by taking learning outside the classroom into the real-world context. In common with findings at other community colleges, this study identified inadequate…
Clickers in the Classroom: An Active Learning Approach
ERIC Educational Resources Information Center
Martyn, Margie
2007-01-01
Current research describes the benefits of active learning approaches. Clickers, or student response systems, are a technology used to promoted active learning. Most research on the benefits of using clickers in the classroom has shown that students become engaged and enjoy using them. However, research on learning outcomes has only compared the…
Demarcating Advanced Learning Approaches from Methodological and Technological Perspectives
ERIC Educational Resources Information Center
Horvath, Imre; Peck, David; Verlinden, Jouke
2009-01-01
In the field of design and engineering education, the fast and expansive evolution of information and communication technologies is steadily converting traditional learning approaches into more advanced ones. Facilitated by Broadband (high bandwidth) personal computers, distance learning has developed into web-hosted electronic learning. The…
Adult Learning in Health and Safety: Some Issues and Approaches.
ERIC Educational Resources Information Center
O Fathaigh, Mairtin
This document, which was developed for presentation at a seminar on adult learning and safety, examines approaches to occupational safety and health (OSH) learning/training in the workplace. Section 1 examines selected factors affecting adults' learning in workplace OSH programs. The principal dimensions along which individual adult learners will…
Approaches of Inquiry Learning With Multimedia Resources in Primary Classrooms
ERIC Educational Resources Information Center
So, Wing-Mui Winnie; Kong, Siu-Cheung
2007-01-01
This study aims to examine the design of approaches for inquiry learning with multimedia resources in primary classrooms. The study describes the development of a multimedia learning unit that helps learners understand the natural phenomenon of the movement of the Earth. An analysis of the use of the multimedia learning unit by a teacher in two…
Investigating Teachers' Views of Student-Centred Learning Approach
ERIC Educational Resources Information Center
Seng, Ernest Lim Kok
2014-01-01
Conventional learning is based on low levels of students' participation where students are rarely expected to ask questions or to challenge the theories of the academic. A paradigm shift in curriculum has resulted in implementing student-centred learning (SCL) approach, putting students as the centre of the learning process. This mode of…
Curriculum Design Requirements and Challenges of the Learning Society Approach
ERIC Educational Resources Information Center
Karimi, Sedighe; Nasr, Ahmad-Reza; Sharif, Mostafa
2012-01-01
Entering the twenty-first century with the development of communities, they are faced with the necessity of moving towards a learning society. University must extend the learning opportunities and improve the quality of them with curriculum design by learning society approach to respond to the necessity. Researchers believe that some conditions…
Many-body approach to the dynamics of batch learning
NASA Astrophysics Data System (ADS)
Wong, K. Y. Michael; Li, S.; Tong, Y. W.
2000-09-01
Using the cavity method and diagrammatic methods, we model the dynamics of batch learning of restricted sets of examples, widely applicable to general learning cost functions, and fully taking into account the temporal correlations introduced by the recycling of the examples. The approach is illustrated using the Adaline rule learning teacher-generated or random examples.
University students' approaches to learning first-year mathematics.
Alkhateeb, Haitham M
2003-12-01
This study assessed reliability and validity of the Approaches to earning Mathematics Questionnaire, for 218 university students. The study also identified the relationship between subscales. Internal consistency as Cronbach alpha was .77 for the Surface Approach to Learning scale and .88 for the Deep Approach to Learning scale. Principal components analysis yielded a two-factor solution accounting for only 34.6% of variance. The factors were interpreted as Surface Approach and Deep Approach to learning mathematics, as in Australia. The former subscale scores were negatively correlated -.2 with the latter subscale scores.
Characterization of one-dimensional cellular automata rules through topological network features
NASA Astrophysics Data System (ADS)
D'Alotto, Lou; Pizzuti, Clara
2016-10-01
The paper investigates the relationship between the classification schemes, defined by Wolfram and Gilman, of one-dimensional cellular automata through concepts coming from network theory. An automaton is represented with a network, generated from the elementary rule defining its behavior. Characteristic features of this graph are computed and machine learning classification models are built. Such models allow to classify automaton rules and to compare Wolfram's and Gilman's classes by comparing the classes predicted by these models.
Material representations: from the genetic code to the evolution of cellular automata.
Rocha, Luis Mateus; Hordijk, Wim
2005-01-01
We present a new definition of the concept of representation for cognitive science that is based on a study of the origin of structures that are used to store memory in evolving systems. This study consists of novel computer experiments in the evolution of cellular automata to perform nontrivial tasks as well as evidence from biology concerning genetic memory. Our key observation is that representations require inert structures to encode information used to construct appropriate dynamic configurations for the evolving system. We propose criteria to decide if a given structure is a representation by unpacking the idea of inert structures that can be used as memory for arbitrary dynamic configurations. Using a genetic algorithm, we evolved cellular automata rules that can perform nontrivial tasks related to the density task (or majority classification problem) commonly used in the literature. We present the particle catalogs of the new rules following the computational mechanics framework. We discuss if the evolved cellular automata particles may be seen as representations according to our criteria. We show that while they capture some of the essential characteristics of representations, they lack an essential one. Our goal is to show that artificial life can be used to shed new light on the computation-versus-dynamics debate in cognitive science, and indeed function as a constructive bridge between the two camps. Our definitions of representation and cellular automata experiments are proposed as a complementary approach, with both dynamics and informational modes of explanation.
Simulating invasion with cellular automata: connecting cell-scale and population-scale properties.
Simpson, Matthew J; Merrifield, Alistair; Landman, Kerry A; Hughes, Barry D
2007-08-01
Interpretive and predictive tools are needed to assist in the understanding of cell invasion processes. Cell invasion involves cell motility and proliferation, and is central to many biological processes including developmental morphogenesis and tumor invasion. Experimental data can be collected across a wide range of scales, from the population scale to the individual cell scale. Standard continuum or discrete models used in isolation are insufficient to capture this wide range of data. We develop a discrete cellular automata model of invasion with experimentally motivated rules. The cellular automata algorithm is applied to a narrow two-dimensional lattice and simulations reveal the formation of invasion waves moving with constant speed. The simulation results are averaged in one dimension-these data are used to identify the time history of the leading edge to characterize the population-scale wave speed. This allows the relationship between the population-scale wave speed and the cell-scale parameters to be determined. This relationship is analogous to well-known continuum results for Fisher's equation. The cellular automata algorithm also produces individual cell trajectories within the invasion wave that are analogous to cell trajectories obtained with new experimental techniques. Our approach allows both the cell-scale and population-scale properties of invasion to be predicted in a way that is consistent with multiscale experimental data. Furthermore we suggest that the cellular automata algorithm can be used in conjunction with individual data to overcome limitations associated with identifying cell motility mechanisms using continuum models alone.
Aberg, Kristoffer Carl; Doell, Kimberly C; Schwartz, Sophie
2016-01-01
Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.
Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie
2016-01-01
Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807
Generational diversity: teaching and learning approaches.
Johnson, Susan A; Romanello, Mary L
2005-01-01
Nursing students represent multiple generations--Baby Boomers, Generation X, and now the Millennials. Each generation has its own set of values, ideas, ethics, beliefs, and learning styles. The authors describe the context, characteristics, and learning styles of each generation and provide suggestions for enhanced teaching and learning across multiple generations. Using generational diversity as a teaching tool in the classroom is also discussed.
A Guided Discovery Approach for Learning Metabolic Pathways
ERIC Educational Resources Information Center
Schultz, Emeric
2005-01-01
Learning the wealth of information in metabolic pathways is both challenging and overwhelming for students. A step-by-step guided discovery approach to the learning of the chemical steps in gluconeogenesis and the citric acid cycle is described. This approach starts from concepts the student already knows, develops these further in a logical…
Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach
ERIC Educational Resources Information Center
Hassan, Moshood Ayinde
2011-01-01
The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…
The Learning of Consumer Skills in Adolescents: An Eclectic Approach.
ERIC Educational Resources Information Center
Kuo, Cheng
A study investigated the learning of consumer skills by adolescents, using two theoretical approaches--the social learning and the family communication pattern approaches. It was hypothesized that (1) assuming that parents are more experienced consumers than are adolescents, frequent discussion with parents on consumption matters are likely to…
Students' Approaches to Learning a New Mathematical Model
ERIC Educational Resources Information Center
Flegg, Jennifer A.; Mallet, Daniel G.; Lupton, Mandy
2013-01-01
In this article, we report on the findings of an exploratory study into the experience of undergraduate students as they learn new mathematical models. Qualitative and quantitative data based around the students' approaches to learning new mathematical models were collected. The data revealed that students actively adopt three approaches to…
Forward-Oriented Design for Learning: Illustrating the Approach
ERIC Educational Resources Information Center
Dimitriadis, Yannis; Goodyear, Peter
2013-01-01
This paper concerns sustainable approaches to design for learning, emphasising the need for designs to be able to thrive outside of the protective niches of project-based innovation. It builds on the "in medias res" framework and more specifically on a forward-oriented approach to design for learning: one that takes a pro-active design…
Enhancing the Teaching-Learning Process: A Knowledge Management Approach
ERIC Educational Resources Information Center
Bhusry, Mamta; Ranjan, Jayanthi
2012-01-01
Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…
Hong Kong Students' Approaches to Learning: Cross-Cultural Comparisons
ERIC Educational Resources Information Center
Dasari, Bhoomiah
2009-01-01
Anecdotal evidence abounds in Hong Kong to the effect that students entering tertiary education are predisposed to a "rote" learning approach. With the internalisation of higher education in many countries, there is still insufficient understanding of how Chinese students approach their learning. Except few studies were conducted…
Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios
NASA Astrophysics Data System (ADS)
Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William
Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.
Approach to Learning of Sub-Degree Students in Hong Kong
ERIC Educational Resources Information Center
Chan, Yiu Man; Chan, Christine Mei Sheung
2010-01-01
The learning approaches and learning experiences of 404 sub-degree students were assessed by using a Study Process Questionnaire and a Learning Experience Questionnaire. While the learning approaches in this study meant whether students used a deep learning or surface learning approach, the learning experiences referred to students' perceptions…
Argumentation based joint learning: a novel ensemble learning approach.
Xu, Junyi; Yao, Li; Li, Le
2015-01-01
Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification.
A systems biology approach to learning autophagy.
Klionsky, Daniel J; Kumar, Anuj
2006-01-01
With its relevance to our understanding of eukaryotic cell function in the normal and disease state, autophagy is an important topic in modern cell biology; yet, few textbooks discuss autophagy beyond a two- or three-sentence summary. Here, we report an undergraduate/graduate class lesson for the in-depth presentation of autophagy using an active learning approach. By our method, students will work in small groups to solve problems and interpret an actual data set describing genes involved in autophagy. The problem-solving exercises and data set analysis will instill within the students a much greater understanding of the autophagy pathway than can be achieved by simple rote memorization of lecture materials; furthermore, the students will gain a general appreciation of the process by which data are interpreted and eventually formed into an understanding of a given pathway. As the data sets used in these class lessons are largely genomic and complementary in content, students will also understand first-hand the advantage of an integrative or systems biology study: No single data set can be used to define the pathway in full-the information from multiple complementary studies must be integrated in order to recapitulate our present understanding of the pathways mediating autophagy. In total, our teaching methodology offers an effective presentation of autophagy as well as a general template for the discussion of nearly any signaling pathway within the eukaryotic kingdom.
Lifelong Learning in Architectural Design Studio: The Learning Contract Approach
ERIC Educational Resources Information Center
Hassanpour, B.; Che-Ani, A. I.; Usman, I. M. S.; Johar, S.; Tawil, N. M.
2015-01-01
Avant-garde educational systems are striving to find lifelong learning methods. Different fields and majors have tested a variety of proposed models and found varying difficulties and strengths. Architecture is one of the most critical areas of education because of its special characteristics, such as learning by doing and complicated evaluation…
Problem Finding in Professional Learning Communities: A Learning Study Approach
ERIC Educational Resources Information Center
Tan, Yuen Sze Michelle; Caleon, Imelda Santos
2016-01-01
This study marries collaborative problem solving and learning study in understanding the onset of a cycle of teacher professional development process within school-based professional learning communities (PLCs). It aimed to explore how a PLC carried out collaborative problem finding--a key process involved in collaborative problem solving--that…
Nonsynchronous updating in the multiverse of cellular automata.
Reia, Sandro M; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.
Nonsynchronous updating in the multiverse of cellular automata
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Kinouchi, Osame
2015-04-01
In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.
NASA Astrophysics Data System (ADS)
Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen
2016-06-01
In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.
Kavianpour, Hamidreza; Vasighi, Mahdi
2017-02-01
Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.
A New Approach to Group Learning
ERIC Educational Resources Information Center
Parsons, Jerry
1976-01-01
To help teachers plan strategy for working with a learning group, 12 factors affecting a learning group are discussed and a series of check points are identified as criteria for evaluation. Concepts and principles of group dynamics are drawn from sociology and the work of Carl Rogers. (Author/AJ)
Child Development: An Active Learning Approach
ERIC Educational Resources Information Center
Levine, Laura E.; Munsch, Joyce
2010-01-01
Within each chapter of this innovative topical text, the authors engage students by demonstrating the wide range of real-world applications of psychological research connected to child development. In particular, the distinctive Active Learning features incorporated throughout the book foster a dynamic and personal learning process for students.…
Chaos automata: iterated function systems with memory
NASA Astrophysics Data System (ADS)
Ashlock, Dan; Golden, Jim
2003-07-01
Transforming biological sequences into fractals in order to visualize them is a long standing technique, in the form of the traditional four-cornered chaos game. In this paper we give a generalization of the standard chaos game visualization for DNA sequences. It incorporates iterated function systems that are called under the control of a finite state automaton, yielding a DNA to fractal transformation system with memory. We term these fractal visualizers chaos automata. The use of memory enables association of widely separated sequence events in the drawing of the fractal, finessing the “forgetfulness” of other fractal visualization methods. We use a genetic algorithm to train chaos automata to distinguish introns and exons in Zea mays (corn). A substantial issue treated here is the creation of a fitness function that leads to good visual separation of distinct data types.
Unambiguous Finite Automata over a Unary Alphabet
NASA Astrophysics Data System (ADS)
Okhotin, Alexander
Nondeterministic finite automata (NFA) with at most one accepting computation on every input string are known as unambiguous finite automata (UFA). This paper considers UFAs over a unary alphabet, and determines the exact number of states in DFAs needed to represent unary languages recognized by n-state UFAs: the growth rate of this function is e^{Θ(sqrt[3]{n ln^2 n})}. The conversion of an n-state unary NFA to a UFA requires UFAs with g(n)+O(n^2)=e^{sqrt{n ln n}(1+o(1))} states, where g(n) is Landau's function. In addition, it is shown that the complement of n-state unary UFAs requires up to at least n 2 - o(1) states in an NFA, while the Kleene star requires up to exactly (n - 1)2 + 1 states.
GARDENS OF EDEN OF ELEMENTARY CELLULAR AUTOMATA.
Barrett, C. L.; Chen, W. Y. C.; Reidys, C. M.
2001-01-01
Using de Bruijn graphs, we give a characterization of elementary cellular automata on the linear lattice that do not have any Gardens of Eden. It turns out that one can easily recoginze a CA that does not have any Gardens of Eden by looking at its de Bruijn graph. We also present a sufficient condition for the set of words accepted by a CA not to constitute a finite-complement language.
Cellular automata in photonic cavity arrays.
Li, Jing; Liew, T C H
2016-10-31
We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.
A Team Approach to Successful Learning: Peer Learning Coaches in Chemistry
ERIC Educational Resources Information Center
Popejoy, Kate; Asala, Kathryn S.
2013-01-01
High failure rates in introductory large lecture chemistry courses for STEM majors have been of concern for years. Through our weekly Team Approach to Successful Learning (TASL) workshops, students learn and apply problem-solving strategies, coached by specially trained peer learning coaches (LCs). These coaches concurrently enroll in Chemistry…
ERIC Educational Resources Information Center
Baeten, Marlies; Dochy, Filip; Struyven, Katrien; Parmentier, Emmeline; Vanderbruggen, Anne
2016-01-01
The use of student-centred learning environments in education has increased. This study investigated student teachers' instructional preferences for these learning environments and how these preferences are related to their approaches to learning. Participants were professional Bachelor students in teacher education. Instructional preferences and…
ERIC Educational Resources Information Center
Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen
2016-01-01
In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to…
Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.
ERIC Educational Resources Information Center
Conlan, Owen; Dagger, Declan; Wade, Vincent
E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…
ERIC Educational Resources Information Center
Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung
2013-01-01
Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…
ERIC Educational Resources Information Center
Zandi, Hamed; Kaivanpanah, Shiva; Alavi, Sayyed Mohammad
2015-01-01
Contract learning as an approach to individualizing education in the context of assessment for learning is relatively underexplored in English as a Foreign Language instruction. The present study used a mixed-methods design to investigate its efficacy to provide feedback to students and improve self-directed learning. Furthermore, it studied…
ERIC Educational Resources Information Center
Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia
2016-01-01
This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…
Approaches to Learning and Kolb's Learning Styles of Undergraduates with Better Grades
NASA Astrophysics Data System (ADS)
Almeida, Patrícia; Teixeira-Dias, José Joaquim; Martinho, Mariana; Balasooriya, Chinthaka
The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades. The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.
Learning from project experiences using a legacy-based approach
NASA Technical Reports Server (NTRS)
Cooper, Lynne P.; Majchrzak, Ann; Faraj, Samer
2005-01-01
As project teams become used more widely, the question of how to capitalize on the knowledge learned in project teams remains an open issue. Using previous research on shared cognition in groups, an approach to promoting post-project learning was developed. This Legacy Review concept was tested on four in tact project teams. The results from those test sessions were used to develop a model of team learning via group cognitive processes. The model and supporting propositions are presented.
Learning Approach and Learning Strengths: A Case Study in an Ultraorthodox Community
ERIC Educational Resources Information Center
Aflalo, Ester
2012-01-01
This study furthers the understanding of the connections between learning approaches and learning strengths. The research population embraced 65 males from the Jewish ultraorthodox community, who abide by distinct methods of study. One group follows the very didactic, linear and structured approach with performance orientation, while the second…
ERIC Educational Resources Information Center
Herrmann, Kim Jesper
2014-01-01
This study examines differences in university students' approaches to learning when attending tutorials as well as variation in students' perceptions of tutorials as an educational arena. In-depth qualitative analysis of semi-structured interviews with undergraduates showed how surface and deep approaches to learning were revealed in the…
ERIC Educational Resources Information Center
Nordin, Abu Bakar; Alias, Norlidah
2013-01-01
Today teachers in schools and lecturers in institutions of higher learning are endowed with a wide range of new teaching experiences through web-based teaching and learning approaches (WBTLA), which was not possible before through the traditional classroom approach. With the use of WBTLA emerged problems related to usability in technical,…
Learning Styles and Approaches to Learning in Excellent and Average First-Year University Students
ERIC Educational Resources Information Center
Gargallo López, Bernardo; Almerich Cerveró, Gonzalo; Suárez Rodríguez, Jesús M.; García Félix, Eloïna; Garfella Esteban, Pedro R.
2013-01-01
We assessed the learning approaches and learning styles of a sample of 148 excellent students selected from 11 degrees from nine centers of the Polytechnic University of Valencia (Spain), and we compared the results with those of a sample of 133 average students from the same centers. We found that excellent students took deeper approach than…
Towards Time Automata and Multi-Agent Systems
NASA Technical Reports Server (NTRS)
Hutzler, G.; Klaudel, H.; Wang, D. Y.
2004-01-01
The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.
Cellular automata simulation of traffic including cars and bicycles
NASA Astrophysics Data System (ADS)
Vasic, Jelena; Ruskin, Heather J.
2012-04-01
As 'greening' of all aspects of human activity becomes mainstream, transportation science is also increasingly focused around sustainability. Modal co-existence between motorised and non-motorised traffic on urban networks is, in this context, of particular interest for traffic flow modelling. The main modelling problems here are posed by the heterogeneity of vehicles, including size and dynamics, and by the complex interactions at intersections. Herein we address these with a novel technique, based on one-dimensional cellular automata components, for modelling network infrastructure and its occupancy by vehicles. We use this modelling approach, together with a corresponding vehicle behaviour model, to simulate combined car and bicycle traffic for two elemental scenarios-examples of components that would be used in the building of an arbitrary network. Results of simulations performed on these scenarios, (i) a stretch of road and (ii) an intersection causing conflict between cars and bicycles sharing a lane, are presented and analysed.
Quantum state transfer through noisy quantum cellular automata
NASA Astrophysics Data System (ADS)
Avalle, Michele; Genoni, Marco G.; Serafini, Alessio
2015-05-01
We model the transport of an unknown quantum state on one dimensional qubit lattices by means of a quantum cellular automata (QCA) evolution. We do this by first introducing a class of discrete noisy dynamics, in the first excitation sector, in which a wide group of classical stochastic dynamics is embedded within the more general formalism of quantum operations. We then extend the Hilbert space of the system to accommodate a global vacuum state, thus allowing for the transport of initial on-site coherences besides excitations, and determine the dynamical constraints that define the class of noisy QCA in this subspace. We then study the transport performance through numerical simulations, showing that for some instances of the dynamics perfect quantum state transfer is attainable. Our approach provides one with a natural description of both unitary and open quantum evolutions, where the homogeneity and locality of interactions allow one to take into account several forms of quantum noise in a plausible scenario.
Developing a Competency-Based Assessment Approach for Student Learning
ERIC Educational Resources Information Center
Dunning, Pamela T.
2014-01-01
Higher education accrediting bodies are increasing the emphasis on assessing student learning outcomes as opposed to teaching methodology. The purpose of this article is to describe the process used by Troy University's Master of Public Administration program to change their assessment approach from a course learning objective perspective to a…
A Motivational Approach to Student Learning: The Landlord Technique.
ERIC Educational Resources Information Center
Lanford, Horace
A motivational approach to student learning that has been implemented in several courses at Wright University in Ohio consists of six efforts: (1) to instill in students the knowledge of motivation, both from within and without; (2) to make students members of cohesive work groups; (3) to apply theory learned; (4) to demonstrate achievement of…
Approaches to Learning: Supporting Brain Development for School Success
ERIC Educational Resources Information Center
Petersen, Sandra
2012-01-01
Prenatally and in infants and toddlers, the brain is being constructed as a foundation for all later learning. Positive early experiences contribute to the formation of a brain that is capable, early in infancy, of utilizing and strengthening the basic processes of learning. Throughout a lifetime, a person will repeatedly use these approaches to…
Blending Online Learning with Traditional Approaches: Changing Practices
ERIC Educational Resources Information Center
Condie, Rae; Livingston, Kay
2007-01-01
Considerable claims have been made for the development of e-learning, either as stand-alone programmes or alongside more traditional approaches to teaching and learning, for students across school and tertiary education. National initiatives have improved the position of schools in terms of access to hardware and electronic networking, software…
Practical Approaches to Using Learning Styles in Higher Education.
ERIC Educational Resources Information Center
Dunn, Rita, Ed.; Griggs, Shirley A., Ed.
The focus of this collection of essays is on new approaches to teaching in higher education. Selections are organized in five sections; the first section focuses on learning styles, while the remaining sections focus on applications in various academic disciplines. The chapters include: (1) "Capitalizing on College Students' Learning Styles:…
Digital Games and Learning in Cyberspace: A Dialogical Approach
ERIC Educational Resources Information Center
Ravenscroft, Andrew; McAlister, Simon
2006-01-01
Currently there is considerable enthusiasm for exploring how we can apply digital gaming paradigms to learning. But these approaches are often weak in linking the game-playing activity to transferable social or conceptual processes and skills that constitute, or are related to, learning. In contrast, this article describes a "dialogue…
A Hybrid Approach to University Subject Learning Activities
ERIC Educational Resources Information Center
Osorio Gomez, Luz Adriana; Duart, Josep M.
2012-01-01
In order to get a better understanding of subject design and delivery using a hybrid approach, we have studied a hybrid learning postgraduate programme offered by the University of the Andes, Bogota, Colombia. The study analyses students' perceptions of subject design and delivery, with particular reference to learning activities and the roles of…
Designing Interactive Learning Environments: An Approach from First Principles
ERIC Educational Resources Information Center
Scott, Bernard; Cong, Chunyu
2007-01-01
Purpose: Today's technology supports the design of more and more sophisticated interactive learning environments. This paper aims to argue that such design should develop from first principles. Design/methodology/approach: In the paper by first principles is meant: learning theory and principles of course design. These principles are briefly…
Situated Poetry Learning Using Multimedia Resource Sharing Approach
ERIC Educational Resources Information Center
Yang, Che-Ching; Tseng, Shian-Shyong; Liao, Anthony Y. H.; Liang, Tyne
2013-01-01
Educators have emphasized the importance of situating students in an authentic learning environment. By using such approach, teachers can encourage students to learn Chinese poems by browsing content resources and relevant online multimedia resources by using handheld devices. Nevertheless, students in heterogeneous network environments may have…
Inquiry Role Approach: A Model for Counselor Involvement in Learning.
ERIC Educational Resources Information Center
Bingman, Richard M.; And Others
The Inquiry Role Approach (IRA) is a strategy for classroom learning in which students work as 4-member teams and assume roles as Team Coordinator, Process Advisor, Data Recorder, and Technical Advisor. Cognitive as well as affective objectives are identified which relate to optimum learning and personal growth in the classroom. The counselor's…
Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach
ERIC Educational Resources Information Center
Man, Thomas Wing Yan
2006-01-01
Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which…
Contextualized Teaching & Learning: A Promising Approach for Basic Skills Instruction
ERIC Educational Resources Information Center
Baker, Elaine DeLott; Hope, Laura; Karandjeff, Kelley
2009-01-01
Contextualized teaching and learning (CTL), or the concept of relating subject matter content to meaningful situations that are relevant to students' lives, offers one promising approach to helping students learn more effectively. This brief offers instructors, college leaders, policy makers and funders a high-level summary of the CTL…
Sound Foundations: Organic Approaches to Learning Notation in Beginning Band
ERIC Educational Resources Information Center
West, Chad
2016-01-01
By starting with a foundation of sound before sight, we can help our students learn notation organically in a way that honors the natural process. This article describes five organic approaches to learning notation in beginning band: (1) iconic notation, (2) point and play, (3) student lead-sheet, (4) modeling, and (5) kid dictation. While…
Students' Studying and Approaches to Learning in Introductory Biology
ERIC Educational Resources Information Center
Tomanek, Debra; Montplaisir, Lisa
2004-01-01
This exploratory study was conducted in an introductory biology course to determine 1) how students used the large lecture environment to create their own learning tasks during studying and 2) whether meaningful learning resulted from the students' efforts. Academic task research from the K-12 education literature and student approaches to…
A Challenge-Feedback Learning Approach to Teaching International Business
ERIC Educational Resources Information Center
Sternad, Dietmar
2015-01-01
This article introduces a challenge-feedback learning (CFL) approach based on the goal-setting theory of human motivation, the deliberate practice theory of expert performance, and findings from the research on active and collaborative learning. The core of the teaching concept is the CFL cycle in which students repeatedly progress through four…
Learning Objects Update: Review and Critical Approach to Content Aggregation
ERIC Educational Resources Information Center
Balatsoukas, Panos; Morris, Anne; O'Brien, Ann
2008-01-01
The structure and composite nature of a learning object is still open to interpretation. Although several theoretical studies advocate integrated approaches to the structure and aggregation level of learning objects, in practice, many content specifications, such as SCORM, IMS Content Packaging, and course authoring tools, do not explicitly state…
Blended Learning in Higher Education: Three Different Design Approaches
ERIC Educational Resources Information Center
Alammary, Ali; Sheard, Judy; Carbone, Angela
2014-01-01
Blended learning has been growing in popularity as it has proved to be an effective approach for accommodating an increasingly diverse student population whilst adding value to the learning environment through incorporation of online teaching resources. Despite this growing interest, there is ongoing debate about the definition of the concept of…
Group Experiential Learning with Undergraduate Nursing Students: An Interdisciplinary Approach
ERIC Educational Resources Information Center
Pistole, M. Carole; Kinyon, Jane; Keith, Cynthia Bozich
2008-01-01
This research examined an interdisciplinary, collaborative experiential group learning approach, in which undergraduate nursing students met in small groups led by counseling doctoral student co-leaders. Statistical analysis suggests that the teaching method lead to learning of group concepts. Discussion addresses anecdotal observations,…
Exploiting the features of the finite state automata for biomolecular computing.
Martínez-Pérez, Israel Marck; Ignatova, Zoya; Zimmermann, Karl-Heinz
2009-01-01
Here, we review patents that have emerged in the field of DNA-based computing focusing thereby on the discoveries using the concept of molecular finite state automata. A finite state automaton, operating on a finite sequence of symbols and converting information from one to another, provides a basis for developing molecular-scale autonomous programmable models of biomolecular computation at cellular level. We also provide a brief overview on inventions which methodologically support the DNA-based computational approach.
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
2008-01-01
and † denotes the Moore - Penrose inverse . Eq. (3) asks Â to minimize the error in predicting the state at time t + 1 from the state at time t. Given...A Constraint Generation Approach to Learning Stable Linear Dynamical Systems Sajid M. Siddiqi Byron Boots Geoffrey J. Gordon January 2008...REPORT DATE JAN 2008 2. REPORT TYPE 3. DATES COVERED 00-00-2008 to 00-00-2008 4. TITLE AND SUBTITLE A Constraint Generation Approach to Learning
Promoting Hybrid Learning through a Sharable eLearning Approach
ERIC Educational Resources Information Center
Bai, Xin; Smith, Michael B.
2010-01-01
Educational technology is developing rapidly, making education more accessible, affordable, adaptable, and equitable. Students now have the option to choose a campus that can provide an excellent blended learning curriculum with minimal geographical restraints. We explored ways to maximize the power of educational technologies to improve teaching…
Larvae, Ladies and Learning: The Project Approach.
ERIC Educational Resources Information Center
Whitham, Laurel; Killoran, Isabel
2003-01-01
Describes the Project Approach and how it was used in a Grade 1 exploration of Painted Lady butterflies in Ontario, Canada. Outlines the students' experience with the project and examines the compatibility of the Project Approach with the Ontario Science and Technology Curriculum document. Maintains that the Project Approach supports and…
A Conceptual Data Model for Flood Based on Cellular Automata Using Moving Object Data Model
NASA Astrophysics Data System (ADS)
Rachmatullah, R. S.; Azizah, F. N.
2017-01-01
Flood is considered as the costliest natural disaster in Indonesia due to its frequent occurrences as well as the extensive damage that it causes. Several studies provide different flood prediction models based on various hydrological factors. A lot of these models use grid-to-grid approach, making them suitable to be modelled as cellular automata. This paper presents a conceptual data model for flood based on cellular automata model using spatio-temporal data model, especially the moving object data model, as the modelling approach. The conceptual data model serves as the model of data structures within an environment for flood prediction simulation. We describe two conceptual data models as the alternatives to model the data structures of flood model. We create the data model based on the study to the factors that constitute the flood models. The first conceptual data model alternative focuses on the cell/grid as the main entity type. The changes of the states of the cells are stored as moving integer. The second alternative emphasizes on flood as the main entity type. The changes of the flood area are stored as moving region. Both alternatives introduce some advantages and disadvantages and the choice rely on the purpose of the use of the data model. We present a proposal of the architecture of a flood prediction system using cellular automata as the modelling approach. As the continuation of this work, further design and implementation details must be provided.
An active learning approach to Bloom's Taxonomy.
Weigel, Fred K; Bonica, Mark
2014-01-01
As educators strive toward improving student learning outcomes, many find it difficult to instill their students with a deep understanding of the material the instructors share. One challenge lies in how to provide the material with a meaningful and engaging method that maximizes student understanding and synthesis. By following a simple strategy involving Active Learning across the 3 primary domains of Bloom's Taxonomy (cognitive, affective, and psychomotor), instructors can dramatically improve the quality of the lesson and help students retain and understand the information. By applying our strategy, instructors can engage their students at a deeper level and may even find themselves enjoying the process more.
Learning topological maps: An alternative approach
Buecken, A.; Thrun, S.
1996-12-31
Our goal is autonomous real-time control of a mobile robot. In this paper we want to show a possibility to learn topological maps of a large-scale indoor environment autonomously. In the literature there are two paradigms how to store information on the environment of a robot: as a grid-based (geometric) or as a topological map. While grid-based maps are considerably easy to learn and maintain, topological maps are quite compact and facilitate fast motion-planning.
ERIC Educational Resources Information Center
Heikkila, Annamari; Niemivirta, Markku; Nieminen, Juha; Lonka, Kirsti
2011-01-01
This study investigated the relationships among approaches to learning, regulation of learning, cognitive and attributional strategies, stress, exhaustion, and study success. University students (N = 437) from three faculties filled in a questionnaire concerning their self-reported study behaviour, cognitive strategies, and well-being. Their…
A Cognitive Approach to Student-Centered e-Learning
Greitzer, Frank L.
2002-09-30
Like traditional classroom instruction, distance/electronic learning (e-Learning) derives from largely behaviorist computer-based instruction paradigms that tend to reflect passive training philosophies. Over the past thirty years, more flexible, student-centered classroom teaching methods have been advocated based on the concepts of ''discovery'' learning and ''active'' learning; student-centered approaches are likewise encouraged in the development of e-Learning applications. Nevertheless, many e-Learning applications that employ state-of-the art multimedia technology in which students interact with simulations, animations, video, and sounds still fail to meet their expected training potential. Implementation of multimedia-based training features may give the impression of engaging the student in more active forms of learning, but sophisticated use of multimedia features does not necessarily produce the desired effect. This paper briefly reviews some general guidelines for applying cognitive science principles to development of student-centered e-Learning applications and describes a cognitive approach to e-Learning development that is being undertaken for the US Army.
Flipped Approach to Mobile Assisted Language Learning
ERIC Educational Resources Information Center
Yamamoto, Junko
2013-01-01
There are abundant possibilities for using smart phones and tablet computers for foreign language learning. However, if there is an emphasis on memorization or on technology, language learners may not develop proficiency in their target language. Therefore, language teachers should be familiar with strategies for facilitating creative…
The Learning Centers Approach to Instruction.
ERIC Educational Resources Information Center
George, Paul S.; And Others
The learning center is a place for using and storing materials that relate to a special interest or curriculum area. It is a place where the students, after consulting with the teacher, may go to work; where ideas, materials, and activities are presented on a variety of levels of difficulty. Teachers, however, must first decide what the role of…
Newton's First Law: A Learning Cycle Approach
ERIC Educational Resources Information Center
McCarthy, Deborah
2005-01-01
To demonstrate how Newton's first law of motion applies to students' everyday lives, the author developed a learning cycle series of activities on inertia. The discrepant event at the heart of these activities is sure to elicit wide-eyed stares and puzzled looks from students, but also promote critical thinking and help bring an abstract concept…
Bangladeshi EFL Learners' Approach towards Learning English
ERIC Educational Resources Information Center
Fathema, Fawzia
2015-01-01
Bangladesh is a poverty stricken country with a huge population "unemployed' in respect of the definition of Economics including both male and female. Government is striving hard to make the people well-equipped with necessary skills and learning in order that they can prove themselves fit for the upcoming challenges of the global economy and…
Enterprise Approaches to Information and Learning Technology
ERIC Educational Resources Information Center
Ferrell, Gill
2007-01-01
Like it or not, an institution's IT infrastructure is a matter with which institutional strategic planners must concern themselves. Information systems represent a significant investment, they perform mission-critical functions, and the appropriate use of information and learning technologies can have a critical part to play in delivering against…
A psychological approach to learning causal networks.
Zargoush, Manaf; Alemi, Farrokh; Esposito Vinzi, Vinzenzo; Vang, Jee; Kheirbek, Raya
2014-06-01
We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms.
Teaching and Learning Forgiveness: A Multidimensional Approach
ERIC Educational Resources Information Center
Malcolm, Lois; Ramsey, Janet
2006-01-01
This essay seeks to illumine the teaching and learning of the practice of forgiveness by relating a range of theoretical perspectives (theological, psychological, and socio-cultural) to the process of cultivating the practical wisdom needed for forgiveness. We discuss how a Trinitarian "epistemology of the cross" might lead one to a new way of…
Learning disabilities and learned helplessness: a heuristic approach.
Hersh, C A; Stone, B J; Ford, L
1996-02-01
This study investigated whether students with learning disabilities exhibited learned helpless behavior at a greater rate than their normal achieving peers when confronted with reading failure. Forty-five third grade students from a suburban elementary schools were participants in the study. Thirty of the subjects were classified as having a learning disability (LD) and the remaining 15 subjects were from regular education (RE) classrooms. Fifteen of the students with LD were placed in the treatment group and the remaining fifteen were placed in the control group. All the regular education students were placed in the treatment group. After randomly assigning the students with LD into either a treatment (stressed) group or a control (nonstressed) group, the stressed students were administered a reading instrument in order to measure how they dealt with failure. A one-way ANCOVA was conducted to determine whether significant differences existed between the groups based on their posttest scores. The results indicate that stressed students with LD have a significantly more difficult time recovering from stress than their regular education peers.
CarboCAT: A cellular automata model of heterogeneous carbonate strata
NASA Astrophysics Data System (ADS)
Burgess, Peter M.
2013-04-01
CarboCAT is a new numerical model of carbonate deposystems that uses a cellular automata to calculate lithofacies spatial distributions and hence to calculate the accumulation of heterogeneous carbonate strata in three dimensions. CarboCAT includes various geological processes, including tectonic subsidence, eustatic sea-level oscillations, water depth-dependent carbonate production rates in multiple carbonate factories, lateral migration of carbonate lithofacies bodies, and a simple representation of sediment transport. Results from the model show stratigraphically interesting phenomena such as heterogeneous strata with complex stacking patterns, laterally discontinuous subaerial exposure surfaces, nonexponential lithofacies thickness distributions, and sensitive dependence on initial conditions whereby small changes in the model initial conditions have a large effect on the final model outcome. More work is required to fully assess CarboCAT, but these initial results suggest that a cellular automata approach to modeling carbonate strata is likely to be a useful tool for investigating the nature and origins of heterogeneity in carbonate strata.
Theory Based Approaches to Learning. Implications for Adult Educators.
ERIC Educational Resources Information Center
Bolton, Elizabeth B.; Jones, Edward V.
This paper presents a codification of theory-based approaches that are applicable to adult learning situations. It also lists some general guidelines that can be used when selecting a particular approach or theory as a basis for planning instruction. Adult education's emphasis on practicality and the relationship between theory and practice is…
Vocation, Motivation and Approaches to Learning: A Comparative Study
ERIC Educational Resources Information Center
Arquero, Jose Luis; Fernández-Polvillo, Carmen; Hassall, Trevor; Joyce, John
2015-01-01
Purpose: The individual characteristics of students can have a strong influence on the success of the adopted innovations in terms of their transferability and sustainability. The purpose of this paper is to compare the motivations and approaches to learning on degrees with differing vocational components. Design/methodology/approach:…
Measuring University Students' Approaches to Learning Statistics: An Invariance Study
ERIC Educational Resources Information Center
Chiesi, Francesca; Primi, Caterina; Bilgin, Ayse Aysin; Lopez, Maria Virginia; del Carmen Fabrizio, Maria; Gozlu, Sitki; Tuan, Nguyen Minh
2016-01-01
The aim of the current study was to provide evidence that an abbreviated version of the Approaches and Study Skills Inventory for Students (ASSIST) was invariant across different languages and educational contexts in measuring university students' learning approaches to statistics. Data were collected on samples of university students attending…
3 Colleges' Different Approaches Shape Learning in Econ 101
ERIC Educational Resources Information Center
Berrett, Dan
2012-01-01
No matter the college, a class in the principles of microeconomics is likely to cover the discipline's greatest hits. The author attends three economics courses at three colleges, and finds three very different approaches. In this article, the author discusses three colleges' different approaches that shape learning in Econ 101.
Student Approaches to Learning in Relation to Online Course Completion
ERIC Educational Resources Information Center
Balter, Olle; Cleveland-Innes, Martha; Pettersson, Kerstin; Scheja, Max; Svedin, Maria
2013-01-01
This study investigates the relationship between approaches to studying and course completion in two online preparatory university courses in mathematics and computer programming. The students participating in the two courses are alike in age, gender, and approaches to learning. Four hundred and ninety-three students participating in these courses…
Work Transitions as Told: A Narrative Approach to Biographical Learning
ERIC Educational Resources Information Center
Hallqvist, Anders; Hyden, Lars-Christer
2013-01-01
In this article, we introduce a narrative approach to biographical learning; that is, an approach that considers autobiographical storytelling as a practice through which claims about life history are performed and negotiated. Using insights from narrative theory, we highlight evaluations in those narratives and suggest their crucial role in…
Effective Learning Approaches for Sustainability: A Student Perspective
ERIC Educational Resources Information Center
Erskine, Laura; Johnson, Scott D.
2012-01-01
The authors offer an exploratory glimpse into the perceived effectiveness of learning approaches presently being used to teach students about sustainability in a business school setting. Sustainability is a topic of growing importance in business and business education. Using teaching approaches generated through self-reports related to the…
The Teaching-Learning Environment, an Information-Dynamic Approach
ERIC Educational Resources Information Center
De Blasio, Cataldo; Järvinen, Mika
2014-01-01
In the present study a generalized approach is given for the description of acquisition procedures with a particular focus on the knowledge acquisition process. The learning progression is given as an example here letting the theory to be applied to different situations. An analytical approach is performed starting from the generalized fundamental…
Learning styles and approaches to learning among medical undergraduates and postgraduates
2013-01-01
Background The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. Methods We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. Results A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners. Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p < 0.05). Mean scores for the superficial approach did not differ significantly between groups. Conclusions The learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period. PMID:23521845
Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A
2016-01-07
Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.
The scientific learning approach using multimedia-based maze game to improve learning outcomes
NASA Astrophysics Data System (ADS)
Setiawan, Wawan; Hafitriani, Sarah; Prabawa, Harsa Wara
2016-02-01
The objective of curriculum 2013 is to improve the quality of education in Indonesia, which leads to improving the quality of learning. The scientific approach and supported empowerment media is one approach as massaged of curriculum 2013. This research aims to design a labyrinth game based multimedia and apply in the scientific learning approach. This study was conducted in one of the Vocational School in Subjects of Computer Network on 2 (two) classes of experimental and control. The method used Mix Method Research (MMR) which combines qualitative in multimedia design, and quantitative in the study of learning impact. The results of a survey showed that the general of vocational students like of network topology material (68%), like multimedia (74%), and in particular, like interactive multimedia games and flash (84%). Multimediabased maze game developed good eligibility based on media and material aspects of each value 840% and 82%. Student learning outcomes as a result of using a scientific approach to learning with a multimediabased labyrinth game increase with an average of gain index about (58%) and higher than conventional multimedia with index average gain of 0.41 (41%). Based on these results the scientific approach to learning by using multimediabased labyrinth game can improve the quality of learning and increase understanding of students. Multimedia of learning based labyrinth game, which developed, got a positive response from the students with a good qualification level (75%).
Scaling behavior in probabilistic neuronal cellular automata.
Manchanda, Kaustubh; Yadav, Avinash Chand; Ramaswamy, Ramakrishna
2013-01-01
We study a neural network model of interacting stochastic discrete two-state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective temperature). There are avalanches of neuronal activity, namely, spatially and temporally contiguous sites of activity; a detailed numerical study of these activity avalanches is presented, and single, joint, and marginal probability distributions are computed. At the critical point, we find that the scaling exponents for the variables are in good agreement with a mean-field theory.
On Binary-State Phyllosilicate Automata
NASA Astrophysics Data System (ADS)
Adamatzky, Andrew
Phyllosilicate is a sheet of silicate tetrahedra bound by basal oxygens. A phyllosilicate automaton is a regular network of finite state machines, which mimics the structure of phyllosilicate. A node of a binary state phyllosilicate automaton takes states 0 and 1. A node updates its state in discrete time depending on a sum of states of its three (silicon nodes) or six (oxygen nodes) closest neighbors. We phenomenologically select the main types of patterns generated by phyllosilicate automata based on their shape: convex and concave hulls, almost circularly growing patterns, octagonal patterns, and those with dendritic growth; and, the patterns' interior: disordered, solid, labyrinthine. We also present the rules exhibiting traveling localizations.
Spectral Approaches to Learning Predictive Representations
2012-09-01
Dean P. Foster, and Lyle H. Ungar . Spectral learning of latent-variable pcfgs. In ACL (1), pages 223–231, 2012. 1.1 [26] Paramveer S. Dhillon, Jordan...Rodu, Michael Collins, Dean P. Foster, and Lyle H. Ungar . Spectral dependency parsing with latent variables. In EMNLP-CoNLL, pages 205–213, 2012. 1.1...H. Ungar . Spectral dimensionality reduction for hmms. CoRR, abs/1203.6130, 2012. 1.1 [34] Kenji Fukumizu, Le Song, and Arthur Gretton. Kernel bayes
Evoked Prior Learning Experience and Approach to Learning as Predictors of Academic Achievement
ERIC Educational Resources Information Center
Trigwell, Keith; Ashwin, Paul; Millan, Elena S.
2013-01-01
Background: In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate,…
ERIC Educational Resources Information Center
Cavanagh, Rob
2012-01-01
This report is about one of two phases in an investigation into associations between student engagement in classroom learning and the classroom learning environment. Both phases applied the same instrumentation to the same sample. The difference between the phases was in the measurement approach applied. This report is about application of the…
ERIC Educational Resources Information Center
Chun, Eul Jung; Hertzog, Nancy B.; Gaffney, Janet S.; Dymond, Stacy K.
2012-01-01
The researchers described in this case study how Service Learning was incorporated within the context of an early childhood program where the teachers used the Project Approach. The Service Learning project was embedded in an investigation about water and was designed to help tsunami victims in Asia. Participants included two teachers and 12…
ERIC Educational Resources Information Center
Ismail, Habsah; Hassan, Aminuddin; Muhamad, Mohd. Mokhtar; Ali, Wan Zah Wan; Konting, Mohd. Majid
2013-01-01
This is an investigation of the students' beliefs about the nature of knowledge or epistemological beliefs, and the relation of these beliefs on their learning approaches. Students chosen as samples of the study were from both public and private higher institutions of learning in Malaysia. The instrument used in the study consists of 49 items…
To Learn More about Learning: The Value-Added Role of Qualitative Approaches to Assessment
ERIC Educational Resources Information Center
Newhart, Daniel W.
2015-01-01
As we face increasing accountability in higher education, how we measure student learning should exceed the calls for an account of learning that places students at the center. Qualitative approaches to assessment and theoretical underpinnings gleaned from the qualitative research tradition may provide a way that we can support a more holistic…
The Effects of Computer Supported Problem Based Learning on Students' Approaches to Learning
ERIC Educational Resources Information Center
Ak, Serife
2011-01-01
The purpose of this paper is to investigate the effects of computer supported problem based learning on students' approaches to learning. The research was conducted as a pre-test and posttest one-grouped design used to achieve the objectives of the study. The experimental process of study lasted 5 weeks and was carried out on 78 university…
ERIC Educational Resources Information Center
Sung, Han-Yu; Hwang, Gwo-Jen
2013-01-01
In this study, a collaborative game-based learning environment is developed by integrating a grid-based Mindtool to facilitate the students to share and organize what they have learned during the game-playing process. To evaluate the effectiveness of the proposed approach, an experiment has been conducted in an elementary school natural science…
ERIC Educational Resources Information Center
Kek, Megan A. Yih Chyn; Darmawan, I. Gusti Ngurah; Chen, Yu Sui
2007-01-01
This article presents the quantitative findings from a mixed methods study of students and faculty at a private medical university in Malaysia. In particular, the relationships among students' individual characteristics, general self-efficacy, family context, university and classroom learning environments, curriculum, approaches to learning, and…
Galaxy morphology - An unsupervised machine learning approach
NASA Astrophysics Data System (ADS)
Schutter, A.; Shamir, L.
2015-09-01
Structural properties poses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a network of similarities between galaxy morphological types, and automatically deduce a morphological sequence of galaxies. Application of the method to the EFIGI catalog show that the morphological scheme produced by the algorithm is largely in agreement with the De Vaucouleurs system, demonstrating the ability of computer vision and machine learning methods to automatically profile galaxy morphological sequences. The unsupervised analysis method is based on comprehensive computer vision techniques that compute the visual similarities between the different morphological types. Rather than relying on human cognition, the proposed system deduces the similarities between sets of galaxy images in an automatic manner, and is therefore not limited by the number of galaxies being analyzed. The source code of the method is publicly available, and the protocol of the experiment is included in the paper so that the experiment can be replicated, and the method can be used to analyze user-defined datasets of galaxy images.
A blended learning approach to teaching CVAD care and maintenance.
Hainey, Karen; Kelly, Linda J; Green, Audrey
2017-01-26
Nurses working within both acute and primary care settings are required to care for and maintain central venous access devices (CVADs). To support these nurses in practice, a higher education institution and local health board developed and delivered CVAD workshops, which were supported by a workbook and competency portfolio. Following positive evaluation of the workshops, an electronic learning (e-learning) package was also introduced to further support this clinical skill in practice. To ascertain whether this blended learning approach to teaching CVAD care and maintenance prepared nurses for practice, the learning package was evaluated through the use of electronic questionnaires. Results highlighted that the introduction of the e-learning package supported nurses' practice, and increased their confidence around correct clinical procedures.
ERIC Educational Resources Information Center
Phan, Huy P.
2006-01-01
Introduction: The work of reflective thinking (Mezirow, 1991, 1998) and epistemological beliefs (Schommer, 1990, 1993; Schommer-Aikins, Duell & Hutter, 2005) is increasingly recognized as playing an important role in students' academic learning. Furthermore, students' approaches to their learning are also considered as contributing factors…
Interrelations between Self-Efficacy and Learning Approaches: A Developmental Approach
ERIC Educational Resources Information Center
Phan, Huy Phuong
2011-01-01
Two major theoretical frameworks in educational psychology, namely student approaches to learning (SAL) and self-efficacy have been used extensively to explain and predict students' learning and academic achievement. There is a substantial body of research studies, for example, that documents the positive interrelations between individuals'…
Students awareness of learning styles and their perceptions to a mixed method approach for learning
Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder
2015-01-01
Background: Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Hypothesis: Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Aim: Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Materials and Methods: Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. Results: There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Conclusion: Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning. PMID:26380214
A cellular automata model of bone formation.
Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia
2017-04-01
Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model.
Weyl, Dirac and Maxwell Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
Recent advances on quantum foundations achieved the derivation of free quantum field theory from general principles, without referring to mechanical notions and relativistic invariance. From the aforementioned principles a quantum cellular automata (QCA) theory follows, whose relativistic limit of small wave-vector provides the free dynamics of quantum field theory. The QCA theory can be regarded as an extended quantum field theory that describes in a unified way all scales ranging from an hypothetical discrete Planck scale up to the usual Fermi scale. The present paper reviews the automaton theory for the Weyl field, and the composite automata for Dirac and Maxwell fields. We then give a simple analysis of the dynamics in the momentum space in terms of a dispersive differential equation for narrowband wave-packets. We then review the phenomenology of the free-field automaton and consider possible visible effects arising from the discreteness of the framework. We conclude introducing the consequences of the automaton dispersion relation, leading to a deformed Lorentz covariance and to possible effects on the thermodynamics of ideal gases.
A Digital Approach to Learning Petrology
NASA Astrophysics Data System (ADS)
Reid, M. R.
2011-12-01
In the undergraduate igneous and metamorphic petrology course at Northern Arizona University, we are employing petrographic microscopes equipped with relatively inexpensive ( $200) digital cameras that are linked to pen-tablet computers. The camera-tablet systems can assist student learning in a variety of ways. Images provided by the tablet computers can be used for helping students filter the visually complex specimens they examine. Instructors and students can simultaneously view the same petrographic features captured by the cameras and exchange information about them by pointing to salient features using the tablet pen. These images can become part of a virtual mineral/rock/texture portfolio tailored to individual student's needs. Captured digital illustrations can be annotated with digital ink or computer graphics tools; this activity emulates essential features of more traditional line drawings (visualizing an appropriate feature and selecting a representative image of it, internalizing the feature through studying and annotating it) while minimizing the frustration that many students feel about drawing. In these ways, we aim to help a student progress more efficiently from novice to expert. A number of our petrology laboratory exercises involve use of the camera-tablet systems for collaborative learning. Observational responsibilities are distributed among individual members of teams in order to increase interdependence and accountability, and to encourage efficiency. Annotated digital images are used to share students' findings and arrive at an understanding of an entire rock suite. This interdependence increases the individual's sense of responsibility for their work, and reporting out encourages students to practice use of technical vocabulary and to defend their observations. Pre- and post-course student interest in the camera-tablet systems has been assessed. In a post-course survey, the majority of students reported that, if available, they would use
Learning about Aboriginal contexts: the reading circle approach.
Begoray, Deborah L; Banister, Elizabeth
2008-07-01
As more opportunities arise for nursing students to obtain experience in community sites, they will be called on to practice in culturally appropriate ways more often. Although nurses remain challenged by the range of populations needing differentiated approaches, Aboriginal cultural contexts deserve special attention. Nurse educators must help students increase their understanding of Aboriginal life and ways of knowing. One way to facilitate this understanding is through a learning approach called reading circles. Reading circles offer a structure in the classroom for students to interact about ideas or readings. The reading circle process is congruent with Aboriginal ways of learning, which emphasize working in circle, with each member having a role and an equal chance to be heard. Aboriginal students in the class may be particularly comfortable with this learning method. This article describes specific steps for incorporating the reading circle approach into the nurse education classroom.
A Museum Approach to Computer Learning.
ERIC Educational Resources Information Center
Wall, Roger
1986-01-01
Compares and contrasts the approaches taken by museums and schools in computer education. Reviews representative museum computer programs as "Keyboards for Kids" for preschool children of the Franklin Institute in Philadelphia and the teacher training project of Boston's Museum of Science. Offers perspectives on expanded program options.…
Learning with PROLOG--A New Approach.
ERIC Educational Resources Information Center
Scherz, Zahava; And Others
1986-01-01
Discusses the features and advantages of the computer language PROLOG, and explains the approach taken in teaching it as a first computer language. Includes an example of the use of PROLOG in programming a science lesson on elements for junior high students. (ML)
Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster
Marques-Pita, Manuel; Rocha, Luis M.
2013-01-01
We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics – a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity – with the ultimate goal of explaining how do cells and tissues ‘compute’. PMID:23520449
Canalization and control in automata networks: body segmentation in Drosophila melanogaster.
Marques-Pita, Manuel; Rocha, Luis M
2013-01-01
We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.
Mayya, Shreemathi S; Rao, A Krishna; Ramnarayan, K
2002-11-01
This study explored the difference in learning approaches and difficulties of Nepali and Indian undergraduate students of dental science. A locally developed inventory was used to measure learning approach and learning difficulties. Data collected from 166 Indians and 69 Nepalis were compared. The scores on various scales of the inventory indicate that Nepalis are more fearful and less confident regarding examination and course completion and have significantly less positive perception about academic capability. Indian students scored significantly higher on motivation, interest, and deep processing. The language problem was significantly greater for Nepali students. Higher percentages of Nepalis experienced various academic and nonacademic problems. The study highlights the need to consider difference in learning approach among the students of health science courses that admit students from different academic, nonacademic, and cultural backgrounds.
Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy
ERIC Educational Resources Information Center
Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay
2016-01-01
The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…
Viewing hybrid systems as products of control systems and automata
NASA Technical Reports Server (NTRS)
Grossman, R. L.; Larson, R. G.
1992-01-01
The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.
System learning approach to assess sustainability and ...
This paper presents a methodology that combines the power of an Artificial Neural Network and Information Theory to forecast variables describing the condition of a regional system. The novelty and strength of this approach is in the application of Fisher information, a key method in Information Theory, to preserve trends in the historical data and prevent over fitting projections. The methodology was applied to demographic, environmental, food and energy consumption, and agricultural production in the San Luis Basin regional system in Colorado, U.S.A. These variables are important for tracking conditions in human and natural systems. However, available data are often so far out of date that they limit the ability to manage these systems. Results indicate that the approaches developed provide viable tools for forecasting outcomes with the aim of assisting management toward sustainable trends. This methodology is also applicable for modeling different scenarios in other dynamic systems. Indicators are indispensable for tracking conditions in human and natural systems, however, available data is sometimes far out of date and limit the ability to gauge system status. Techniques like regression and simulation are not sufficient because system characteristics have to be modeled ensuring over simplification of complex dynamics. This work presents a methodology combining the power of an Artificial Neural Network and Information Theory to capture patterns in a real dyna
A developmental approach to learning causal models for cyber security
NASA Astrophysics Data System (ADS)
Mugan, Jonathan
2013-05-01
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Cellular Automata Methods in Mathematical Physics.
NASA Astrophysics Data System (ADS)
Smith, Mark Andrew
Cellular automata (CA) are fully discrete, spatially -distributed dynamical systems which can serve as an alternative framework for mathematical descriptions of physical systems. Furthermore, they constitute intrinsically parallel models of computation which can be efficiently realized with special-purpose cellular automata machines. The basic objective of this thesis is to determine techniques for using CA to model physical phenomena and to develop the associated mathematics. Results may take the form of simulations and calculations as well as proofs, and applications are suggested throughout. We begin by describing the structure, origins, and modeling categories of CA. A general method for incorporating dissipation in a reversible CA rule is suggested by a model of a lattice gas in the presence of an external potential well. Statistical forces are generated by coupling the gas to a low temperature heat bath. The equilibrium state of the coupled system is analyzed using the principle of maximum entropy. Continuous symmetries are important in field theory, whereas CA describe discrete fields. However, a novel CA rule for relativistic diffusion based on a random walk shows how Lorentz invariance can arise in a lattice model. Simple CA models based on the dynamics of abstract atoms are often capable of capturing the universal behaviors of complex systems. Consequently, parallel lattice Monte Carlo simulations of abstract polymers were devised to respect the steric constraints on polymer dynamics. The resulting double space algorithm is very efficient and correctly captures the static and dynamic scaling behavior characteristic of all polymers. Random numbers are important in stochastic computer simulations; for example, those that use the Metropolis algorithm. A technique for tuning random bits is presented to enable efficient utilization of randomness, especially in CA machines. Interesting areas for future CA research include network simulation, long-range forces
Factors Contributing to Changes in a Deep Approach to Learning in Different Learning Environments
ERIC Educational Resources Information Center
Postareff, Liisa; Parpala, Anna; Lindblom-Ylänne, Sari
2015-01-01
The study explored factors explaining changes in a deep approach to learning. The data consisted of interviews with 12 students from four Bachelor-level courses representing different disciplines. We analysed and compared descriptions of students whose deep approach either increased, decreased or remained relatively unchanged during their courses.…
The Effects of Discipline on Deep Approaches to Student Learning and College Outcomes
ERIC Educational Resources Information Center
Nelson Laird, Thomas F.; Shoup, Rick; Kuh, George D.; Schwarz, Michael J.
2008-01-01
"Deep learning" represents student engagement in approaches to learning that emphasize integration, synthesis, and reflection. Because learning is a shared responsibility between students and faculty, it is important to determine whether faculty members emphasize deep approaches to learning and to assess how much students employ these approaches.…
Partially Ordered Two-Way Büchi Automata
NASA Astrophysics Data System (ADS)
Kufleitner, Manfred; Lauser, Alexander
We introduce partially ordered two-way Büchi automata over infinite words. As for finite words, the nondeterministic variant recognizes the fragment Σ2 of first-order logic FO[<] and the deterministic version yields the Δ2-definable ω-languages. As a byproduct of our results, we show that deterministic partially ordered two-way Büchi automata are effectively closed under Boolean operations.
Multilevel programmable logic array schemes for microprogrammed automata
Barkalov, A.A.
1995-03-01
Programmable logic arrays (PLAs) provide an efficient tool for implementation of logic schemes of microprogrammed automata (MPA). The number of PLAs in the MPA logic scheme can be minimized by increasing the number of levels. In this paper, we analyze the structures of multilevel schemes of Mealy automata, propose a number of new structures, consider the corresponding correctness conditions, and examine some problems that must be solved in order to satisfy these conditions.
SCMP: An E-Learning Content Migration and Standardization Approach (A Singaporean Perspective)
ERIC Educational Resources Information Center
Kong, Hinny P.; Lim, William K. H.; Wang, Lei; Gay, Robert
2006-01-01
E-learning standards ensure interoperability and reusability of learning contents. Learning objects that are standard conformant allow a learning management system (LMS) to import learning objects and track user learning progress more easily. This article provides a comprehensive approach complete with both a procedure and a software tool for…
Mathematical Critical Thinking Ability through Contextual Teaching and Learning Approach
ERIC Educational Resources Information Center
Kurniati; Kusumah, Yaya S.; Sabandar, Jozua; Herman, Tatang
2015-01-01
This research aimed to examine the effect of the application of contextual teaching and learning (CTL) approach to the enhance of mathematical critical thinking ability (MCTA) of Primary School Teacher Students (PSTS). This research is an experimental study with the population of all students PSTS who took algebra subject matter of one university…
A Child-Centred Approach to Learning about Healthy Eating
ERIC Educational Resources Information Center
Telford, Francesca
2013-01-01
Science involves children in exploring and gaining understanding about the world they live in. Use of a creative and imaginative approach to science can enhance this learning in many ways (Coates and Wilson, 2003). When presented with the challenge of teaching a series of science lessons on food and nutrition to a mixed class of years 4 and 5…
Using an Active-Learning Approach to Teach Epigenetics
ERIC Educational Resources Information Center
Colon-Berlingeri, Migdalisel
2010-01-01
Epigenetics involves heritable changes in gene expression that do not involve alterations in the DNA sequence. I developed an active-learning approach to convey this topic to students in a college genetics course. I posted a brief summary of the topic before class to stimulate exchange in cooperative groups. During class, we discussed the…
Cognitive Ability, Learning Approaches and Personality Correlates of General Knowledge
ERIC Educational Resources Information Center
Furnham, Adrian; Swami, Viren; Arteche, Adriane; Chamorro-Premuzic, Tomas
2008-01-01
The relationship between general knowledge (GK) and cognitive ability (IQ and abstract reasoning), learning approaches, and personality ("big five" traits and typical intellectual engagement) was investigated in a sample of 101 British undergraduates. As predicted, GK was positively correlated with cognitive ability (more so with IQ than…
Constructivist Approach Enhances the Learning: A Search of Reality
ERIC Educational Resources Information Center
Dev, Meenu
2016-01-01
The primary aim of the study was to study the effect of constructivist approach of teaching on the learning of English Language on Primary School Students. The study consisted of 60 students of class VI from Janta Brahmi Sr. Secondary School, Nathupur, Sonipat. A single quasi experimental pre-test and post-test design was applied in the present…
A Home Learning Center Approach to Early Stimulation. Final Report.
ERIC Educational Resources Information Center
Gordon, Ira J.; Guinagh, Barry J.
The Home Learning Center (HLC) Project, a combination of research and demonstration containing phases of basic research, material development and field testing of materials and delivery system, began in 1968 as a longitudinal investigation of a home-oriented approach to intervention in the lives of very young children which might enhance their…
Developing a Student-Centered Approach to Reflective Learning.
ERIC Educational Resources Information Center
Stefani, Lorraine A. J.; Clarke, Joe; Littlejohn, Allison H.
2000-01-01
Presents a student-centered approach to reflective learning through a partnership between disciplinary-based academic staff and educational development staff members in a postgraduate Environmental Engineering Postgraduate Diploma/MSc program at the University of Strathclyde. Students were encouraged to maintain project management logbooks to…
Study Process Questionnaire Manual. Student Approaches to Learning and Studying.
ERIC Educational Resources Information Center
Biggs, John B.
This manual describes the theory behind the Study Process Questionnaire (SPQ) and explains what the subscale and scale scores mean. The SPQ is a 42-item self-report questionnaire used in Australia to assess the extent to which a tertiary student at a college or university endorses different approaches to learning and the motives and strategies…
Defining Leadership: Collegiate Women's Learning Circles: A Qualitative Approach
ERIC Educational Resources Information Center
Preston-Cunningham, Tammie; Elbert, Chanda D.; Dooley, Kim E.
2017-01-01
The researchers employed qualitative methods to evaluate first-year female students' definition of "leadership" through involvement in the Women's Learning Circle. The findings revealed that students defined leadership in two dimensions: traits and behaviors. The qualitative findings explore a multidimensional approach to the voices of…
Re"modeling" College Algebra: An Active Learning Approach
ERIC Educational Resources Information Center
Pinzon, D.; Pinzon, K.; Stackpole, M.
2016-01-01
In this paper, we discuss active learning in College Algebra at Georgia Gwinnett College. This approach has been used in more than 20 sections of College Algebra taught by the authors in the past four semesters. Students work in small, structured groups on guided inquiry activities after watching 15-20 minutes of videos before class. We discuss a…
Understanding the Science-Learning Environment: A Genetically Sensitive Approach
ERIC Educational Resources Information Center
Haworth, Claire M. A.; Davis, Oliver S. P.; Hanscombe, Ken B.; Kovas, Yulia; Dale, Philip S.; Plomin, Robert
2013-01-01
Previous studies have shown that environmental influences on school science performance increase in importance from primary to secondary school. Here we assess for the first time the relationship between the science-learning environment and science performance using a genetically sensitive approach to investigate the aetiology of this link. 3000…
Taking Laptops Schoolwide: A Professional Learning Community Approach
ERIC Educational Resources Information Center
Green, Tim; Donovan, Loretta; Bass, Kim
2010-01-01
A defined collaboration, such as a Professional Learning Community (PLC), can help expand a one-to-one program. In this article, the authors discuss four factors to consider in starting a collaborative approach at one's school: (1) school climate; (2) communication; (3) collaboration; and (4) progression of use.
Approaches to Teaching Plant Nutrition. Children's Learning in Science Project.
ERIC Educational Resources Information Center
Leeds Univ. (England). Centre for Studies in Science and Mathematics Education.
During the period 1984-1986, over 30 teachers from the Yorkshire (England) region have worked in collaboration with the Children's Learning in Science Project (CLIS) developing and testing teaching schemes in the areas of energy, particle theory, and plant nutrition. The project is based upon the constructivist approach to teaching. This document…
Evaluating Experiential Learning Programs: The Case Study Approach.
ERIC Educational Resources Information Center
Stevenson, Robert
1985-01-01
Demonstrates how case study evaluation concentrates on a single situation to present a holistic view of an experiential learning program and reveals unique and unanticipated features. Outlines steps of planning, gathering, analyzing, synthesizing, and reporting data and considers the advantages and disadvantages of the case study approach. (LFL)
Three Approaches to Cooperative Learning in Higher Education.
ERIC Educational Resources Information Center
Kaufman, David; Sutow, Elliott; Dunn, Ken
1997-01-01
Offers a rationale for using cooperative learning in higher education, identifying six elements essential to its success: positive interdependence; face-to-face verbal interaction; individual accountability; social skills; group processing; appropriate grouping. Describes and compares three distinct approaches in medicine, dentistry, and…
Evaluation Theory in Problem-Based Learning Approach.
ERIC Educational Resources Information Center
Hsu, Yu-chen
The purpose of this paper is to review evaluation theories and techniques in both the medical and educational fields and to propose an evaluation theory to explain the condition variables, the method variables, and the outcome variables of student assessment in a problem-based learning (PBL) approach. The PBL definition and process are presented,…
Human Resource Building--An Approach to Service Learning
ERIC Educational Resources Information Center
Rajan, Sonika
2009-01-01
Background: Isabella Thoburn College at Lucknow, Uttar Pradesh, India has initiated Service Learning Program for its students through 4 issue based centers. One of the centers AIDS Awareness Center for Counseling, Education, and Training (AACCET) is in the field of HIV/AIDS. It follows 6 pronged approach to achieve its objectives and one of the…
Teaching and Learning Cycles in a Constructivist Approach to Instruction
ERIC Educational Resources Information Center
Singer, Florence Mihaela; Moscovici, Hedy
2008-01-01
This study attempts to analyze and synthesize the knowledge collected in the area of conceptual models used in teaching and learning during inquiry-based projects, and to propose a new frame for organizing the classroom interactions within a constructivist approach. The IMSTRA model consists in three general phases: Immersion, Structuring,…
Approaches and Strategies in Next Generation Science Learning
ERIC Educational Resources Information Center
Khine, Myint Swe, Ed.; Saleh, Issa M., Ed.
2013-01-01
"Approaches and Strategies in Next Generation Science Learning" examines the challenges involved in the development of modern curriculum models, teaching strategies, and assessments in science education in order to prepare future students in the 21st century economies. This comprehensive collection of research brings together science educators,…
Learning Outcomes of Two Approaches to Multicultural Music Education
ERIC Educational Resources Information Center
Abril, Carlos R.
2006-01-01
The purpose of this study was to examine the effect of multicultural music instruction on classroom learning outcomes. Fifth-grade children (10-11 years of age; N = 170) from four schools were randomly assigned to one of two instructional treatments: music concept and sociocultural context. The former approach used formal elements of music as a…
Can Virtual Museums Motivate Students? Toward a Constructivist Learning Approach
ERIC Educational Resources Information Center
Katz, James E.; Halpern, Daniel
2015-01-01
This study aims to assess the effectiveness of immersive environments that have been implemented by museums to attract new visitors. Based on the frameworks introduced by telepresence and media richness theories, and following a constructivist-based learning approach, we argue that the greater the similarity of an online museum experience is to…
Team Building: A Structured Learning Approach. Instructor's Manual.
ERIC Educational Resources Information Center
Mears, Peter; Voehl, Frank
This publication is an instructor's manual to a course on developing empowered management teams for higher education, teamworking skills, and team role evaluation skills. The course itself takes a hands-on approach to learning about quality, introduces continuous quality improvement principles, asks students to apply these in a structured…
The Law Review Approach: What the Humanities Can Learn
ERIC Educational Resources Information Center
Mendenhall, Allen
2013-01-01
Readers of this journal probably know how the peer review process works in the humanities disciplines and at various journals. Therefore the author explains how the law review process generally works and then what the humanities can learn and borrow from the law review process. He ends by advocating for a hybrid law review/peer review approach to…
Evaluating Action Learning: A Critical Realist Complex Network Theory Approach
ERIC Educational Resources Information Center
Burgoyne, John G.
2010-01-01
This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…
A Multiple Cross-Cultural Comparison of Approaches to Learning
ERIC Educational Resources Information Center
Bowden, Mark P.; Abhayawansa, Subhash; Manzin, Gregoria
2015-01-01
This study compares learning approaches of local English-speaking students and students from Asian countries studying at an Australian metropolitan university. The sample consists of students across 13 different countries. Unlike previous studies, students from Asian countries are subdivided into two categories: students from Confucian Heritage…
Students Approach to Learning and Their Use of Lecture Capture
ERIC Educational Resources Information Center
Vajoczki, Susan; Watt, Susan; Marquis, Nick; Liao, Rose; Vine, Michelle
2011-01-01
This study examined lecture capture as a way of enhancing university education, and explored how students with different learning approaches used lecture capturing (i.e., podcasts and vodcasts). Results indicate that both deep and surface learners report increased course satisfaction and better retention of knowledge in courses with traditional…
Transferring Knowledge across Cultures: A Learning Competencies Approach
ERIC Educational Resources Information Center
Kayes, Anna B.; Kayes, D. Christopher; Yamazaki, Yoshitaka
2005-01-01
At the heart of any successful cross-cultural knowledge transfer effort lies an individual or group of individuals with the skills to manage a complex, ambiguous and often stressful process. The ability to manage the knowledge transfer process depends as much on learning in real time as it does on rational planning. Yet, few approaches to…
A Narrative Approach to Supporting Students Diagnosed with Learning Disabilities
ERIC Educational Resources Information Center
Lambie, Glenn W.; Milsom, Amy
2010-01-01
Students diagnosed with learning disabilities experience many challenges that school counselors may address through narrative therapy. Narrative therapy is a postmodern, social constructionist approach based on the theoretical construct that individuals create their notions of truth and meaning of life through interpretive stories. This article…
NASA Astrophysics Data System (ADS)
Hong, Yuh-Fong
With the rapid growth of online courses in higher education institutions, research on quality of learning for online courses is needed. However, there is a notable lack of research in the cited literature providing evidence that online distance education promotes the quality of independent learning to which it aspires. Previous studies focused on academic outcomes and technology applications which do not monitor students' learning processes, such as their approaches to learning. Understanding students' learning processes and factors influencing quality of learning will provide valuable information for instructors and institutions in providing quality online courses and programs. The purpose of this study was to identify and investigate college biology teachers' approaches to teaching and students' learning styles, and to examine the impact of approaches to teaching and learning styles on students' approaches to learning via online instruction. Data collection included eighty-seven participants from five online biology courses at a community college in the southern area of Texas. Data analysis showed the following results. First, there were significant differences in approaches to learning among students with different learning styles. Second, there was a significant difference in students' approaches to learning between classes using different approaches to teaching. Three, the impact of learning styles on students' approaches to learning was not influenced by instructors' approaches to teaching. Two conclusions were obtained from the results. First, individuals with the ability to perceive information abstractly might be more likely to adopt deep approaches to learning than those preferring to perceive information through concrete experience in online learning environments. Second, Teaching Approach Inventory might not be suitable to measure approaches to teaching for online biology courses due to online instructional design and technology limitations. Based on
Particles and Patterns in Cellular Automata
Jen, E.; Das, R.; Beasley, C.E.
1999-06-03
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Our objective has been to develop tools for studying particle interactions in a class of dynamical systems characterized by discreteness, determinism, local interaction, and an inherently parallel form of evolution. These systems can be described by cellular automata (CA) and the behavior we studied has improved our understanding of the nature of patterns generated by CAs, their ability to perform global computations, and their relationship to continuous dynamical systems. We have also developed a rule-table mathematics that enables one to custom-design CA rule tables to generate patterns of specified types, or to perform specified computational tasks.
On Matrices, Automata, and Double Counting
NASA Astrophysics Data System (ADS)
Beldiceanu, Nicolas; Carlsson, Mats; Flener, Pierre; Pearson, Justin
Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint defined by a finite-state automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We evaluate the impact of our methods on a large set of nurse rostering problem instances.
SELF-ORGANIZED CRITICALITY AND CELLULAR AUTOMATA
CREUTZ,M.
2007-01-01
Cellular automata provide a fascinating class of dynamical systems based on very simple rules of evolution yet capable of displaying highly complex behavior. These include simplified models for many phenomena seen in nature. Among other things, they provide insight into self-organized criticality, wherein dissipative systems naturally drive themselves to a critical state with important phenomena occurring over a wide range of length and the scales. This article begins with an overview of self-organized criticality. This is followed by a discussion of a few examples of simple cellular automaton systems, some of which may exhibit critical behavior. Finally, some of the fascinating exact mathematical properties of the Bak-Tang-Wiesenfeld sand-pile model [1] are discussed.
Traffic jam dynamics in stochastic cellular automata
Nagel, K. |; Schreckenberg, M.
1995-09-01
Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA) and in NRW (Germany) for large scale microsimulations of network traffic.
Mammogram segmentation using maximal cell strength updation in cellular automata.
Anitha, J; Peter, J Dinesh
2015-08-01
Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.
Modeling Second-Order Chemical Reactions using Cellular Automata
NASA Astrophysics Data System (ADS)
Hunter, N. E.; Barton, C. C.; Seybold, P. G.; Rizki, M. M.
2012-12-01
Cellular automata (CA) are discrete, agent-based, dynamic, iterated, mathematical computational models used to describe complex physical, biological, and chemical systems. Unlike the more computationally demanding molecular dynamics and Monte Carlo approaches, which use "force fields" to model molecular interactions, CA models employ a set of local rules. The traditional approach for modeling chemical reactions is to solve a set of simultaneous differential rate equations to give deterministic outcomes. CA models yield statistical outcomes for a finite number of ingredients. The deterministic solutions appear as limiting cases for conditions such as a large number of ingredients or a finite number of ingredients and many trials. Here we present a 2-dimensional, probabilistic CA model of a second-order gas phase reaction A + B → C, using a MATLAB basis. Beginning with a random distribution of ingredients A and B, formation of C emerges as the system evolves. The reaction rate can be varied based on the probability of favorable collisions of the reagents A and B. The model permits visualization of the conversion of reagents to products, and allows one to plot concentration vs. time for A, B and C. We test hypothetical reaction conditions such as: limiting reagents, the effects of reaction probabilities, and reagent concentrations on the reaction kinetics. The deterministic solutions of the reactions emerge as statistical averages in the limit of the large number of cells in the array. Modeling results for dynamic processes in the atmosphere will be presented.
Learning nursing through simulation: A case study approach towards an expansive model of learning.
Berragan, Liz
2014-08-01
This study explores the impact of simulation upon learning for undergraduate nursing students. The study objectives were (a) to explore the experiences of participating in simulation education for a small group of student nurses; and (b) to explore learning through simulation from the perspectives of the nursing students, the nurse educators and the nurse mentors. Conducted as a small-scale narrative case study, it tells the unique stories of a small number of undergraduate nursing students, nurse mentors and nurse educators and explores their experiences of learning through simulation. Data analysis through progressive focusing revealed that the nurse educators viewed simulation as a means of helping students to learn to be nurses, whilst, the nurse mentors suggested that simulation helped them to determine nursing potential. The students' narratives showed that they approached simulation learning in different ways resulting in a range of outcomes: those who were successfully becoming nurses, those who were struggling or working hard to become nurses and those who were not becoming nurses. Theories of professional practice learning and activity theory present an opportunity to articulate and theorise the learning inherent in simulation activities. They recognise the links between learning and the environment of work and highlight the possibilities for learning to inspire change and innovation.
ERIC Educational Resources Information Center
Gijbels, David; Coertjens, Liesje; Vanthournout, Gert; Struyf, Elke; Van Petegem, Peter
2009-01-01
Inciting a deep approach to learning in students is difficult. The present research poses two questions: can a constructivist learning-assessment environment change students' approaches towards a more deep approach? What effect does additional feedback have on the changes in learning approaches? Two cohorts of students completed questionnaires…
Residents’ perceptions of simulation as a clinical learning approach
Walsh, Catharine M.; Garg, Ankit; Ng, Stella L.; Goyal, Fenny; Grover, Samir C.
2017-01-01
Background Simulation is increasingly being integrated into medical education; however, there is little research into trainees’ perceptions of this learning modality. We elicited trainees’ perceptions of simulation-based learning, to inform how simulation is developed and applied to support training. Methods We conducted an instrumental qualitative case study entailing 36 semi-structured one-hour interviews with 12 residents enrolled in an introductory simulation-based course. Trainees were interviewed at three time points: pre-course, post-course, and 4–6 weeks later. Interview transcripts were analyzed using a qualitative descriptive analytic approach. Results Residents’ perceptions of simulation included: 1) simulation serves pragmatic purposes; 2) simulation provides a safe space; 3) simulation presents perils and pitfalls; and 4) optimal design for simulation: integration and tension. Key findings included residents’ markedly narrow perception of simulation’s capacity to support non-technical skills development or its use beyond introductory learning. Conclusion Trainees’ learning expectations of simulation were restricted. Educators should critically attend to the way they present simulation to learners as, based on theories of problem-framing, trainees’ a priori perceptions may delimit the focus of their learning experiences. If they view simulation as merely a replica of real cases for the purpose of practicing basic skills, they may fail to benefit from the full scope of learning opportunities afforded by simulation. PMID:28344719
Theoretical Description of Teaching-Learning Processes: A Multidisciplinary Approach
NASA Astrophysics Data System (ADS)
Bordogna, Clelia M.; Albano, Ezequiel V.
2001-09-01
A multidisciplinary approach based on concepts from sociology, educational psychology, statistical physics, and computational science is developed for the theoretical description of teaching-learning processes that take place in the classroom. The emerging model is consistent with well-established empirical results, such as the higher achievements reached working in collaborative groups and the influence of the structure of the group on the achievements of the individuals. Furthermore, another social learning process that takes place in massive interactions among individuals via the Internet is also investigated.
Theoretical description of teaching-learning processes: a multidisciplinary approach.
Bordogna, C M; Albano, E V
2001-09-10
A multidisciplinary approach based on concepts from sociology, educational psychology, statistical physics, and computational science is developed for the theoretical description of teaching-learning processes that take place in the classroom. The emerging model is consistent with well-established empirical results, such as the higher achievements reached working in collaborative groups and the influence of the structure of the group on the achievements of the individuals. Furthermore, another social learning process that takes place in massive interactions among individuals via the Internet is also investigated.
NASA Astrophysics Data System (ADS)
Roth, Wolff-Michael
2012-06-01
Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.
ERIC Educational Resources Information Center
Chu, Hui-Chun; Hung, Chun-Ming
2015-01-01
In this study, the game-based development approach is proposed for improving the learning motivation, problem solving skills, and learning achievement of students. An experiment was conducted on a learning activity of an elementary school science course to evaluate the performance of the proposed approach. A total of 59 sixth graders from two…
Machine learning approach for objective inpainting quality assessment
NASA Astrophysics Data System (ADS)
Frantc, V. A.; Voronin, V. V.; Marchuk, V. I.; Sherstobitov, A. I.; Agaian, S.; Egiazarian, K.
2014-05-01
This paper focuses on a machine learning approach for objective inpainting quality assessment. Inpainting has received a lot of attention in recent years and quality assessment is an important task to evaluate different image reconstruction approaches. Quantitative metrics for successful image inpainting currently do not exist; researchers instead are relying upon qualitative human comparisons in order to evaluate their methodologies and techniques. We present an approach for objective inpainting quality assessment based on natural image statistics and machine learning techniques. Our method is based on observation that when images are properly normalized or transferred to a transform domain, local descriptors can be modeled by some parametric distributions. The shapes of these distributions are different for noninpainted and inpainted images. Approach permits to obtain a feature vector strongly correlated with a subjective image perception by a human visual system. Next, we use a support vector regression learned on assessed by human images to predict perceived quality of inpainted images. We demonstrate how our predicted quality value repeatably correlates with a qualitative opinion in a human observer study.
Tseng, Min-Chen; Chen, Chia-Cheng
2016-11-17
This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.
Revising a design course from a lecture approach to a project-based learning approach
NASA Astrophysics Data System (ADS)
Kunberger, Tanya
2013-06-01
In order to develop the evaluative skills necessary for successful performance of design, a senior, Geotechnical Engineering course was revised to immerse students in the complexity of the design process utilising a project-based learning (PBL) approach to instruction. The student-centred approach stresses self-directed group learning, which focuses on the process rather than the result and underscores not only the theoretical but also the practical constraints of a problem. The shift in course emphasis, to skills over concepts, results in reduced content coverage but increased student ability to independently acquire a breadth of knowledge.
Using Cellular Automata for Parking Recommendations in Smart Environments
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671
Using cellular automata for parking recommendations in smart environments.
Horng, Gwo-Jiun
2014-01-01
In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space.
ERIC Educational Resources Information Center
Hoe, Siu Loon
2008-01-01
Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…
Variability in University Students' Use of Technology: An "Approaches to Learning" Perspective
ERIC Educational Resources Information Center
Mimirinis, Mike
2016-01-01
This study reports the results of a cross-case study analysis of how students' approaches to learning are demonstrated in blended learning environments. It was initially propositioned that approaches to learning as key determinants of the quality of student learning outcomes are demonstrated specifically in how students utilise technology in…
ERIC Educational Resources Information Center
Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green
2015-01-01
In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…
A reinforcement learning approach to gait training improves retention
Hasson, Christopher J.; Manczurowsky, Julia; Yen, Sheng-Che
2015-01-01
Many gait training programs are based on supervised learning principles: an individual is guided towards a desired gait pattern with directional error feedback. While this results in rapid adaptation, improvements quickly disappear. This study tested the hypothesis that a reinforcement learning approach improves retention and transfer of a new gait pattern. The results of a pilot study and larger experiment are presented. Healthy subjects were randomly assigned to either a supervised group, who received explicit instructions and directional error feedback while they learned a new gait pattern on a treadmill, or a reinforcement group, who was only shown whether they were close to or far from the desired gait. Subjects practiced for 10 min, followed by immediate and overnight retention and over-ground transfer tests. The pilot study showed that subjects could learn a new gait pattern under a reinforcement learning paradigm. The larger experiment, which had twice as many subjects (16 in each group) showed that the reinforcement group had better overnight retention than the supervised group (a 32% vs. 120% error increase, respectively), but there were no differences for over-ground transfer. These results suggest that encouraging participants to find rewarding actions through self-guided exploration is beneficial for retention. PMID:26379524
Team-Based Learning: A New Approach Toward Improving Education.
Rezaee, Rita; Moadeb, Neda; Shokrpour, Nasrin
2016-10-01
Team-based learning is designed to provide students with both conceptual and procedural knowledge, aiming to enhance active learning and critical thinking. In the present study, team-based learning and lecture methods in teaching the "hospital organization and management" course among hospital management students were compared. This quasi-experimental study was conducted on 25 undergraduate students of management. Teaching sessions were divided into two parts. The first part was taught with interactive lectures and the second part with team-based learning method. The students' knowledge was measured before, immediately and two months (late post-test) after teaching. Finally, the mean scores of the final exam and students' satisfaction towards the methods of teaching were measured. There was an improvement in test scores of the students after the TBL sessions when compared to the test scores after lecture sessions (P<0.001). Also, TBL group had significantly a higher amount of knowledge retention compared to the lecture group (P<0.001), but no significant relationship was found between the mean scores of the final exam in the TBL and lecture groups (P=0.116). Finally, the majority of the respondents were more satisfied with TBL sessions compared to the ones held through lecture (P=0.037). The results indicated that TBL provides a better outcome for students. We found that the TBL approach allowed us to create an active learning environment that contributed to the improvement of the students' performances.
A reinforcement learning approach to gait training improves retention.
Hasson, Christopher J; Manczurowsky, Julia; Yen, Sheng-Che
2015-01-01
Many gait training programs are based on supervised learning principles: an individual is guided towards a desired gait pattern with directional error feedback. While this results in rapid adaptation, improvements quickly disappear. This study tested the hypothesis that a reinforcement learning approach improves retention and transfer of a new gait pattern. The results of a pilot study and larger experiment are presented. Healthy subjects were randomly assigned to either a supervised group, who received explicit instructions and directional error feedback while they learned a new gait pattern on a treadmill, or a reinforcement group, who was only shown whether they were close to or far from the desired gait. Subjects practiced for 10 min, followed by immediate and overnight retention and over-ground transfer tests. The pilot study showed that subjects could learn a new gait pattern under a reinforcement learning paradigm. The larger experiment, which had twice as many subjects (16 in each group) showed that the reinforcement group had better overnight retention than the supervised group (a 32% vs. 120% error increase, respectively), but there were no differences for over-ground transfer. These results suggest that encouraging participants to find rewarding actions through self-guided exploration is beneficial for retention.
Alkhateeb, Haitham M; Mji, Andile
2009-10-01
The goal of this 3-yr. study was to explore the learning styles and approaches to learning mathematics of elementary education majors. Two questionnaires, the Learning Style Inventory and the Approaches to Learning Mathematics Questionnaire, were administered to 149 women and 32 men (M = 20.1 yr., SD. = 2.1; range = 18-31). All were in their first or second years of college and enrolled in Mathematics for Elementary School Teachers at a Midwestern U.S. university. Results on the Learning Style Inventory indicated that a majority scored as either Accommodators, i.e., they primarily followed learning modes involving Active Experimentation and Concrete Experience, or as Divergers, i.e., approaching learning by focusing on Concrete Experience and Reflective Observation. A weak but statistically significant association was observed on the Approaches questionnaire between the Surface Approach and Reflective Observation.
An adaptive deep learning approach for PPG-based identification.
Jindal, V; Birjandtalab, J; Pouyan, M Baran; Nourani, M
2016-08-01
Wearable biosensors have become increasingly popular in healthcare due to their capabilities for low cost and long term biosignal monitoring. This paper presents a novel two-stage technique to offer biometric identification using these biosensors through Deep Belief Networks and Restricted Boltzman Machines. Our identification approach improves robustness in current monitoring procedures within clinical, e-health and fitness environments using Photoplethysmography (PPG) signals through deep learning classification models. The approach is tested on TROIKA dataset using 10-fold cross validation and achieved an accuracy of 96.1%.
NASA Astrophysics Data System (ADS)
Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi
2015-08-01
Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.
Cellular Automata as a Computational Model for Low-Level Vision
NASA Astrophysics Data System (ADS)
Broggi, Alberto; D'Andrea, Vincenzo; Destri, Giulio
In this paper we discuss the use of the Cellular Automata (CA) computational model in computer vision applications on massively parallel architectures. Motivations and guidelines of this approach to low-level vision in the frame of the PROMETHEUS project are discussed. The hard real-time requirement of actual application can be only satisfied using an ad hoc VLSI massively parallel architecture (PAPRICA). The hardware solutions and the specific algorithms can be efficiently verified and tested only using, as a simulator, a general purpose machine with a parent architecture (CM-2). An example of application related to feature extraction is discussed.
Modern approaches in deep learning for SAR ATR
NASA Astrophysics Data System (ADS)
Wilmanski, Michael; Kreucher, Chris; Lauer, Jim
2016-05-01
Recent breakthroughs in computational capabilities and optimization algorithms have enabled a new class of signal processing approaches based on deep neural networks (DNNs). These algorithms have been extremely successful in the classification of natural images, audio, and text data. In particular, a special type of DNNs, called convolutional neural networks (CNNs) have recently shown superior performance for object recognition in image processing applications. This paper discusses modern training approaches adopted from the image processing literature and shows how those approaches enable significantly improved performance for synthetic aperture radar (SAR) automatic target recognition (ATR). In particular, we show how a set of novel enhancements to the learning algorithm, based on new stochastic gradient descent approaches, generate significant classification improvement over previously published results on a standard dataset called MSTAR.
NASA Astrophysics Data System (ADS)
Cox, Brian N.; Snead, Malcolm L.
2016-02-01
We argue in favor of representing living cells as automata and review demonstrations that autonomous cells can form patterns by responding to local variations in the strain fields that arise from their individual or collective motions. An autonomous cell's response to strain stimuli is assumed to be effected by internally-generated, internally-powered forces, which generally move the cell in directions other than those implied by external energy gradients. Evidence of cells acting as strain-cued automata have been inferred from patterns observed in nature and from experiments conducted in vitro. Simulations that mimic particular cases of pattern forming share the idealization that cells are assumed to pass information among themselves solely via mechanical boundary conditions, i.e., the tractions and displacements present at their membranes. This assumption opens three mechanisms for pattern formation in large cell populations: wavelike behavior, kinematic feedback in cell motility that can lead to sliding and rotational patterns, and directed migration during invasions. Wavelike behavior among ameloblast cells during amelogenesis (the formation of dental enamel) has been inferred from enamel microstructure, while strain waves in populations of epithelial cells have been observed in vitro. One hypothesized kinematic feedback mechanism, "enhanced shear motility", accounts successfully for the spontaneous formation of layered patterns during amelogenesis in the mouse incisor. Directed migration is exemplified by a theory of invader cells that sense and respond to the strains they themselves create in the host population as they invade it: analysis shows that the strain fields contain positional information that could aid the formation of cell network structures, stabilizing the slender geometry of branches and helping govern the frequency of branch bifurcation and branch coalescence (the formation of closed networks). In simulations of pattern formation in
Computing cellular automata spectra under fixed boundary conditions via limit graphs
NASA Astrophysics Data System (ADS)
Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.
2016-01-01
Cellular automata are fully discrete complex systems with parallel and homogeneous behavior studied both from the theoretical and modeling viewpoints. The limit behaviors of such systems are of particular interest, as they give insight into their emerging properties. One possible approach to investigate such limit behaviors is the analysis of the growth of graphs describing the finite time behavior of a rule in order to infer its limit behavior. Another possibility is to study the Fourier spectrum describing the average limit configurations obtained by a rule. While the former approach gives the characterization of the limit configurations of a rule, the latter yields a qualitative and quantitative characterisation of how often particular blocks of states are present in these limit configurations. Since both approaches are closely related, it is tempting to use one to obtain information about the other. Here, limit graphs are automatically adjusted by configurations directly generated by their respective rules, and use the graphs to compute the spectra of their rules. We rely on a set of elementary cellular automata rules, on lattices with fixed boundary condition, and show that our approach is a more reliable alternative to a previously described method from the literature.
ERIC Educational Resources Information Center
Çolak, Esma
2015-01-01
Problem Statement: For this study, a cooperative learning process was designed in which students with different learning styles could help each other in heterogeneous groups to perform teamwork-based activities. One aspect deemed important in this context was whether the instructional environment designed to reach students with different learning…
ERIC Educational Resources Information Center
Park, Jiyeon; Jeon, Dongryul
2015-01-01
The systemizing and empathizing brain type represent two contrasted students' characteristics. The present study investigated differences in the conceptions and approaches to learning science between the systemizing and empathizing brain type students. The instruments are questionnaires on the systematizing and empathizing, questionnaires on the…
ERIC Educational Resources Information Center
McKay-Jackson, Cassandra
2014-01-01
The traditional teaching of reading, writing, and arithmetic alone will not fully prepare students to lead with integrity, govern fairly, analyze problems, and work collectively with people different from themselves. Social emotional learning (SEL) has been described as one of the missing links in academic education, but a restrictive approach to…
A Self-Regulated Learning Approach for Children with Learning/Behavior Disorders
ERIC Educational Resources Information Center
Benevento, Joan A.
2004-01-01
This book is designed to be an intervention model based on the concepts of Piaget's study of constructivism. The application of this approach will help children with learning/ behavioral disorders actively participate in a fuller integration of their own psychomotor, affective, and cognitive information processing skills and adaptation. The work…
Influence Based Learning Program Scientific Learning Approach to Science Students Generic Skills
ERIC Educational Resources Information Center
Wahyuni, Ida; Amdani, Khairul
2016-01-01
This study aims to determine the influence of scientific approach based learning program (P2BPS) against generic science skills of students. The method used in this research is "quasi experiment" with "two-group pretest posttest" design.The population in this study were all students who take courses in general physics II at the…
ERIC Educational Resources Information Center
Baeten, Marlies; Dochy, Filip; Struyven, Katrien
2008-01-01
This study focused on the relationships between experiences with portfolio assessment, students' approaches to learning and their assessment preferences by means of a pre- and post-test design in an authentic class setting. The participants were 138 first-year professional bachelor's degree students in office management. They were assessed by…
Relations between Students' Approaches to Learning, Experienced Emotions and Outcomes of Learning
ERIC Educational Resources Information Center
Trigwell, Keith; Ellis, Robert A.; Han, Feifei
2012-01-01
Quantitative analyses conducted on the self-reports of first year university students suggest that there is a relationship between the ways they emotionally experience their course and the approach they take to the learning of that course. Students who more strongly experience positive emotions, such as hope and pride, and more weakly experience…
Student Learning Approaches in the UAE: The Case for the Achieving Domain
ERIC Educational Resources Information Center
McLaughlin, James; Durrant, Philip
2017-01-01
The deep versus surface learning approach dichotomy has dominated recent research in student learning approach dimensions. However, the achievement dimension may differ in importance in non-Western and vocational tertiary settings. The aim was to assess how Emirati tertiary students could be characterized in terms of their learning approaches. The…
ERIC Educational Resources Information Center
Beausaert, Simon A. J.; Segers, M. S. R; Wiltink, Danique P. A.
2013-01-01
Background: Research on the relation between teaching and learning approaches has been mainly conducted in higher education and it is not yet clear to what extent the results can be generalised when it comes to secondary education. Purpose: The purpose of this study was to research how students in secondary education perceive their teachers'…
Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.
Chen, Yangzhou; Guo, Yuqi; Wang, Ying
2017-03-29
In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.
Evaluation of students' perception of their learning environment and approaches to learning
NASA Astrophysics Data System (ADS)
Valyrakis, Manousos; Cheng, Ming
2015-04-01
This work presents the results of two case studies designed to assess the various approaches undergraduate and postgraduate students undertake for their education. The first study describes the results and evaluation of an undergraduate course in Water Engineering which aims to develop the fundamental background knowledge of students on introductory practical applications relevant to the practice of water and hydraulic engineering. The study assesses the effectiveness of the course design and learning environment from the perception of students using a questionnaire addressing several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning, and methods of communication and assessment. The second study investigates the effectiveness of supervisory arrangements based on the perceptions of engineering undergraduate and postgraduate students. Effective supervision requires leadership skills that are not taught in the University, yet there is rarely a chance to get feedback, evaluate this process and reflect. Even though the results are very encouraging there are significant lessons to learn in improving ones practice and develop an effective learning environment to student support and guidance. The findings from these studies suggest that students with high level of intrinsic motivation are deep learners and are also top performers in a student-centered learning environment. A supportive teaching environment with a plethora of resources and feedback made available over different platforms that address students need for direct communication and feedback has the potential to improve student satisfaction and their learning experience. Finally, incorporating a multitude of assessment methods is also important in promoting deep learning. These results have deep implications about student learning and can be used to further improve course design and delivery in the future.
Icing detection from geostationary satellite data using machine learning approaches
NASA Astrophysics Data System (ADS)
Lee, J.; Ha, S.; Sim, S.; Im, J.
2015-12-01
Icing can cause a significant structural damage to aircraft during flight, resulting in various aviation accidents. Icing studies have been typically performed using two approaches: one is a numerical model-based approach and the other is a remote sensing-based approach. The model based approach diagnoses aircraft icing using numerical atmospheric parameters such as temperature, relative humidity, and vertical thermodynamic structure. This approach tends to over-estimate icing according to the literature. The remote sensing-based approach typically uses meteorological satellite/ground sensor data such as Geostationary Operational Environmental Satellite (GOES) and Dual-Polarization radar data. This approach detects icing areas by applying thresholds to parameters such as liquid water path and cloud optical thickness derived from remote sensing data. In this study, we propose an aircraft icing detection approach which optimizes thresholds for L1B bands and/or Cloud Optical Thickness (COT) from Communication, Ocean and Meteorological Satellite-Meteorological Imager (COMS MI) and newly launched Himawari-8 Advanced Himawari Imager (AHI) over East Asia. The proposed approach uses machine learning algorithms including decision trees (DT) and random forest (RF) for optimizing thresholds of L1B data and/or COT. Pilot Reports (PIREPs) from South Korea and Japan were used as icing reference data. Results show that RF produced a lower false alarm rate (1.5%) and a higher overall accuracy (98.8%) than DT (8.5% and 75.3%), respectively. The RF-based approach was also compared with the existing COMS MI and GOES-R icing mask algorithms. The agreements of the proposed approach with the existing two algorithms were 89.2% and 45.5%, respectively. The lower agreement with the GOES-R algorithm was possibly due to the high uncertainty of the cloud phase product from COMS MI.
On the topological sensitivity of cellular automata
NASA Astrophysics Data System (ADS)
Baetens, Jan M.; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
Quantum Features of Natural Cellular Automata
NASA Astrophysics Data System (ADS)
Elze, Hans-Thomas
We review the properties of discrete and integer-valued, hence "natural", cellular automata (CA), a particular class of which comprises "Hamiltonian CA" with equations of motion that bear strong similarities to Hamilton's equations, despite presenting discrete updating rules. The resulting dynamics is linear in the same sense as unitary evolution described by the Schrödinger equation. Employing Shannon's Sampling Theorem, we construct an invertible map between such CA and continuous quantum mechanical models which incorporate a fundamental discreteness scale. This leads to one-to-one correspondence of quantum mechanical and CA conservation laws. In order to illuminate the all-important issue of linearity, we presently introduce an extension of the class of CA incorporating nonlinearities. We argue that these imply non-local effects in the continuous quantum mechanical description of intrinsically local discrete CA, enforcing locality entails linearity. We recall the construction of admissible CA observables and the existence of solutions of the modified dispersion relation for stationary states, besides discussing next steps of the deconstruction of quantum mechanical models in terms of deterministic CA.
On the topological sensitivity of cellular automata.
Baetens, Jan M; De Baets, Bernard
2011-06-01
Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.
Dynamic behavior of multirobot systems using lattice gas automata
NASA Astrophysics Data System (ADS)
Stantz, Keith M.; Cameron, Stewart M.; Robinett, Rush D., III; Trahan, Michael W.; Wagner, John S.
1999-07-01
Recent attention has been given to the deployment of an adaptable sensor array realized by multi-robotic systems (or swarms). Our group has been studying the collective, autonomous behavior of these such systems and their applications in the area of remote-sensing and emerging threats. To accomplish such tasks, an interdisciplinary research effort at Sandia National Laboratories are conducting tests in the fields of sensor technology, robotics, and multi- agents architectures. Our goal is to coordinate a constellation of point sensors using unmanned robotic vehicles (e.g., RATLERs, Robotic All-Terrain Lunar Exploration Rover- class vehicles) that optimizes spatial coverage and multivariate signal analysis. An overall design methodology evolves complex collective behaviors realized through local interaction (kinetic) physics and artificial intelligence. Learning objectives incorporate real-time operational responses to environmental changes. This paper focuses on our recent work understanding the dynamics of many-body systems according to the physics-based hydrodynamic model of lattice gas automata. Three design features are investigated. One, for single-speed robots, a hexagonal nearest-neighbor interaction topology is necessary to preserve standard hydrodynamic flow. Two, adaptability, defined by the swarm's rate of deformation, can be controlled through the hydrodynamic viscosity term, which, in turn, is defined by the local robotic interaction rules. Three, due to the inherent nonlinearity of the dynamical equations describing large ensembles, stability criteria ensuring convergence to equilibrium states is developed by scaling information flow rates relative to a swarm's hydrodynamic flow rate. An initial test case simulates a swarm of twenty-five robots maneuvering past an obstacle while following a moving target. A genetic algorithm optimizes applied nearest-neighbor forces in each of five spatial regions distributed over the simulation domain. Armed with
Irreversibility and dissipation in finite-state automata
NASA Astrophysics Data System (ADS)
Ganesh, Natesh; Anderson, Neal G.
2013-12-01
Irreversibility and dissipation in finite-state automata (FSA) are considered from a physical-information-theoretic perspective. A quantitative measure for the computational irreversibility of finite automata is introduced, and a fundamental lower bound on the average energy dissipated per state transition is obtained and expressed in terms of FSA irreversibility. The irreversibility measure and energy bound are germane to any realization of a deterministic automaton that faithfully registers abstract FSA states in distinguishable states of a physical system coupled to a thermal environment, and that evolves via a sequence of interactions with an external system holding a physical instantiation of a random input string. The central result, which is shown to follow from quantum dynamics and entropic inequalities alone, can be regarded as a generalization of Landauer's Principle applicable to FSAs and tailorable to specified automata. Application to a simple FSA is illustrated.
Lempel-Ziv complexity analysis of one dimensional cellular automata.
Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B
2015-12-01
Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.
An active, collaborative approach to learning skills in flow cytometry.
Fuller, Kathryn; Linden, Matthew D; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N; Röhrig, Kimberley J
2016-06-01
Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula.
Learning the Task Management Space of an Aircraft Approach Model
NASA Technical Reports Server (NTRS)
Krall, Joseph; Menzies, Tim; Davies, Misty
2014-01-01
Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.
Novel educational approaches to enhance learning and interest in nephrology.
Jhaveri, Kenar D; Sparks, Matthew A; Shah, Hitesh H
2013-07-01
The number of U.S. medical graduates pursuing careers in nephrology has declined over the last several years. Some of the proposed reasons for this declining interest include difficult-to-understand or unstimulating kidney pathophysiology courses in medical school; disheartening inpatient elective experiences; and few opportunities to experience the other aspects of nephrology careers such as outpatient nephrology clinics, outpatient dialysis, and kidney transplantation. Novel and alternative educational approaches should be considered by the nephrology training community to enhance the understanding of nephrology from medical school to fellowship training. Newer teaching methods and styles should also be incorporated to adapt to today's learner. These innovative educational approaches may not only increase interest in nephrology careers, but they may also enhance and maintain interest during nephrology fellowship. In this article, we will review several educational approaches that may enhance teaching and learning in nephrology.
Sheynikhovich, Denis; Arleo, Angelo
2010-12-13
In contrast to predictions derived from the associative learning theory, a number of behavioral studies suggested the absence of competition between geometric cues and landmarks in some experimental paradigms. In parallel to these studies, neurobiological experiments suggested the existence of separate independent memory systems which may not always interact according to classic associative principles. In this paper we attempt to combine these two lines of research by proposing a model of spatial learning that is based on the theory of multiple memory systems. In our model, a place-based locale strategy uses activities of modeled hippocampal place cells to drive navigation to a hidden goal, while a stimulus-response taxon strategy, presumably mediated by the dorso-lateral striatum, learns landmark-approaching behavior. A strategy selection network, proposed to reside in the prefrontal cortex, implements a simple reinforcement learning rule to switch behavioral strategies. The model is used to reproduce the results of a behavioral experiment in which an interaction between a landmark and geometric cues was studied. We show that this model, built on the basis of neurobiological data, can explain the lack of competition between the landmark and geometry, potentiation of geometry learning by the landmark, and blocking. Namely, we propose that the geometry potentiation is a consequence of cooperation between memory systems during learning, while blocking is due to competition between the memory systems during action selection.
Ensemble Learning Approaches to Predicting Complications of Blood Transfusion
Murphree, Dennis; Ngufor, Che; Upadhyaya, Sudhindra; Madde, Nagesh; Clifford, Leanne; Kor, Daryl J.; Pathak, Jyotishman
2016-01-01
Of the 21 million blood components transfused in the United States during 2011, approximately 1 in 414 resulted in complication [1]. Two complications in particular, transfusion-related acute lung injury (TRALI) and transfusion-associated circulatory overload (TACO), are especially concerning. These two alone accounted for 62% of reported transfusion-related fatalities in 2013 [2]. We have previously developed a set of machine learning base models for predicting the likelihood of these adverse reactions, with a goal towards better informing the clinician prior to a transfusion decision. Here we describe recent work incorporating ensemble learning approaches to predicting TACO/TRALI. In particular we describe combining base models via majority voting, stacking of model sets with varying diversity, as well as a resampling/boosting combination algorithm called RUSBoost. We find that while the performance of many models is very good, the ensemble models do not yield significantly better performance in terms of AUC. PMID:26737958
A machine learning approach for the prediction of settling velocity
NASA Astrophysics Data System (ADS)
Goldstein, Evan B.; Coco, Giovanni
2014-04-01
We use a machine learning approach based on genetic programming to predict noncohesive particle settling velocity. The genetic programming routine is coupled to a novel selection algorithm that determines training data from a collected database of published experiments (985 measurements). While varying the training data set size and retaining an invariant validation set we perform multiple iterations of genetic programming to determine the least data needed to train the algorithm. This method retains a maximum quantity of data for testing against published predictors. The machine learning predictor for settling velocity performs better than two common predictors in the literature and indicates that particle settling velocity is a nonlinear function of all the provided independent variables: nominal diameter of the settling particle, kinematic viscosity of the fluid, and submerged specific gravity of the particle.
A machine learning approach to nonlinear modal analysis
NASA Astrophysics Data System (ADS)
Worden, K.; Green, P. L.
2017-02-01
Although linear modal analysis has proved itself to be the method of choice for the analysis of linear dynamic structures, its extension to nonlinear structures has proved to be a problem. A number of competing viewpoints on nonlinear modal analysis have emerged, each of which preserves a subset of the properties of the original linear theory. From the geometrical point of view, one can argue that the invariant manifold approach of Shaw and Pierre is the most natural generalisation. However, the Shaw-Pierre approach is rather demanding technically, depending as it does on the analytical construction of a mapping between spaces, which maps physical coordinates into invariant manifolds spanned by independent subsets of variables. The objective of the current paper is to demonstrate a data-based approach motivated by Shaw-Pierre method which exploits the idea of statistical independence to optimise a parametric form of the mapping. The approach can also be regarded as a generalisation of the Principal Orthogonal Decomposition (POD). A machine learning approach to inversion of the modal transformation is presented, based on the use of Gaussian processes, and this is equivalent to a nonlinear form of modal superposition. However, it is shown that issues can arise if the forward transformation is a polynomial and can thus have a multi-valued inverse. The overall approach is demonstrated using a number of case studies based on both simulated and experimental data.
Simulation of interdiffusion and voids growth based on cellular automata
NASA Astrophysics Data System (ADS)
Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong
2017-02-01
In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.
The 3-dimensional cellular automata for HIV infection
NASA Astrophysics Data System (ADS)
Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei
2014-04-01
The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.
A reinforcement learning approach to instrumental contingency degradation in rats.
Dutech, Alain; Coutureau, Etienne; Marchand, Alain R
2011-01-01
Goal-directed action involves a representation of action consequences. Adapting to changes in action-outcome contingency requires the prefrontal region. Indeed, rats with lesions of the medial prefrontal cortex do not adapt their free operant response when food delivery becomes unrelated to lever-pressing. The present study explores the bases of this deficit through a combined behavioural and computational approach. We show that lesioned rats retain some behavioural flexibility and stop pressing if this action prevents food delivery. We attempt to model this phenomenon in a reinforcement learning framework. The model assumes that distinct action values are learned in an incremental manner in distinct states. The model represents states as n-uplets of events, emphasizing sequences rather than the continuous passage of time. Probabilities of lever-pressing and visits to the food magazine observed in the behavioural experiments are first analyzed as a function of these states, to identify sequences of events that influence action choice. Observed action probabilities appear to be essentially function of the last event that occurred, with reward delivery and waiting significantly facilitating magazine visits and lever-pressing respectively. Behavioural sequences of normal and lesioned rats are then fed into the model, action values are updated at each event transition according to the SARSA algorithm, and predicted action probabilities are derived through a softmax policy. The model captures the time course of learning, as well as the differential adaptation of normal and prefrontal lesioned rats to contingency degradation with the same parameters for both groups. The results suggest that simple temporal difference algorithms with low learning rates can largely account for instrumental learning and performance. Prefrontal lesioned rats appear to mainly differ from control rats in their low rates of visits to the magazine after a lever press, and their inability to
A verification strategy for web services composition using enhanced stacked automata model.
Nagamouttou, Danapaquiame; Egambaram, Ilavarasan; Krishnan, Muthumanickam; Narasingam, Poonkuzhali
2015-01-01
Currently, Service-Oriented Architecture (SOA) is becoming the most popular software architecture of contemporary enterprise applications, and one crucial technique of its implementation is web services. Individual service offered by some service providers may symbolize limited business functionality; however, by composing individual services from different service providers, a composite service describing the intact business process of an enterprise can be made. Many new standards have been defined to decipher web service composition problem namely Business Process Execution Language (BPEL). BPEL provides an initial work for forming an Extended Markup Language (XML) specification language for defining and implementing business practice workflows for web services. The problems with most realistic approaches to service composition are the verification of composed web services. It has to depend on formal verification method to ensure the correctness of composed services. A few research works has been carried out in the literature survey for verification of web services for deterministic system. Moreover the existing models did not address the verification properties like dead transition, deadlock, reachability and safetyness. In this paper, a new model to verify the composed web services using Enhanced Stacked Automata Model (ESAM) has been proposed. The correctness properties of the non-deterministic system have been evaluated based on the properties like dead transition, deadlock, safetyness, liveness and reachability. Initially web services are composed using Business Process Execution Language for Web Service (BPEL4WS) and it is converted into ESAM (combination of Muller Automata (MA) and Push Down Automata (PDA)) and it is transformed into Promela language, an input language for Simple ProMeLa Interpreter (SPIN) tool. The model is verified using SPIN tool and the results revealed better recital in terms of finding dead transition and deadlock in contrast to the
ERIC Educational Resources Information Center
Chiou, Guo-Li; Lee, Min-Hsien; Tsai, Chin-Chung
2013-01-01
Background and purpose: Knowing how students learn physics is a central goal of physics education. The major purpose of this study is to examine the strength of the predictive power of students' epistemic views and conceptions of learning in terms of their approaches to learning in physics. Sample, design and method: A total of 279 Taiwanese high…
ERIC Educational Resources Information Center
Baeten, Marlies; Kyndt, Eva; Struyven, Katrien; Dochy, Filip
2010-01-01
This review outlines encouraging and discouraging factors in stimulating the adoption of deep approaches to learning in student-centred learning environments. Both encouraging and discouraging factors can be situated in the context of the learning environment, in students' perceptions of that context and in characteristics of the students…
ERIC Educational Resources Information Center
So, Hyo-Jeong; Bonk, Curtis J.
2010-01-01
In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…
ERIC Educational Resources Information Center
She, Hsiao-Ching
2005-01-01
This study investigates the potential of enhancing students' learning of difficult science concepts by exploring the interaction between teachers' four different instructional approaches and students' four different learning preference styles. Students' immediate performance and their retention for learning of buoyancy concepts serve to examine…
Amp: A modular approach to machine learning in atomistic simulations
NASA Astrophysics Data System (ADS)
Khorshidi, Alireza; Peterson, Andrew A.
2016-10-01
Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which
Machine learning: An artificial intelligence approach. Vol. II
Michalski, R.S.; Carbonell, J.G.; Mitchell, T.M.
1986-01-01
This book reflects the expansion of machine learning research through presentation of recent advances in the field. The book provides an account of current research directions. Major topics covered include the following: learning concepts and rules from examples; cognitive aspects of learning; learning by analogy; learning by observation and discovery; and an exploration of general aspects of learning.
JiFUNzeni: A Blended Learning Approach for Sustainable Teachers' Professional Development
ERIC Educational Resources Information Center
Onguko, Brown Bully
2014-01-01
JiFUNzeni blended learning approach is a sustainable approach to provision of professional development (PD) for those in challenging educational contexts. JiFUNzeni approach emphasizes training regional experts to create blended learning content, working with appropriate technology while building content repositories. JiFUNzeni approach was…
Blended learning in orthodontic diagnosis: an interactive approach.
Retrouvey, Jean-Marc; Finkelstein, Adam B A
2008-09-01
Interactive multimedia programs can provide an opportunity for authentic learning both inside and outside the classroom. McGill University designed an interactive Orthodontic Diagnosis program on CD-ROM that has been used successfully in the faculty of dentistry to provide undergraduate students with interactive tutorials and exercises to help them recognize developing malocclusions. Key aspects of this multimedia program are the use of an outside-in approach to diagnosis as well as sound instructional design that provides practice opportunities and feedback to students. The goal is to bridge the gap between theoretical knowledge and the practical skills needed to be a successful dentist.
Perspective: Codesign for materials science: An optimal learning approach
NASA Astrophysics Data System (ADS)
Lookman, Turab; Alexander, Francis J.; Bishop, Alan R.
2016-05-01
A key element of materials discovery and design is to learn from available data and prior knowledge to guide the next experiments or calculations in order to focus in on materials with targeted properties. We suggest that the tight coupling and feedback between experiments, theory and informatics demands a codesign approach, very reminiscent of computational codesign involving software and hardware in computer science. This requires dealing with a constrained optimization problem in which uncertainties are used to adaptively explore and exploit the predictions of a surrogate model to search the vast high dimensional space where the desired material may be found.
ERIC Educational Resources Information Center
Missouri State Dept. of Elementary and Secondary Education, Jefferson City.
This document is comprised of four publications of the early childhood section of the Missouri Department of Elementary and Secondary Education: (1) prekindergarten standards related to social and emotional development and approaches to learning; (2) a teacher's guide to early social and emotional development and approaches to learning; (3) a…
ERIC Educational Resources Information Center
Ellis, Robert A.; Goodyear, Peter; Brillant, Martha; Prosser, Michael
2008-01-01
This study investigates fourth-year pharmacy students' experiences of problem-based learning (PBL). It adopts a phenomenographic approach to the evaluation of problem-based learning, to shed light on the ways in which different groups of students conceive of, and approach, PBL. The study focuses on the way students approach solving problem…
Nanochaos and quantum information for a physical theory of evolvable semantic automata
NASA Astrophysics Data System (ADS)
Santoli, Salvatore
2000-05-01
The concept of "automaton" in its historical development, from the earlier attempts to mimic motions of men and animals to the recent ambitious goals of designing and building biomimetic, i.e., evolvable and self-reproducing machines, is very briefly outlined to stress the physical and logical differences between such conceptions and the main features through which we are able at present to identify and describe biosystems. It is argued that the merely "syntactic" aspect of information processing that is shared by all such approaches can hardly be considered biomimetic on the basis of evolutionary physics of biosystems and of their "semantic" and "pragmatic" information processing capabilities, that can stem from their structure-function (i.e., hardware-software) hierarchical dynamics from the nanometre (classical and quantum) up to the macroscopic (thermodynamic) level and make set-theoretic logic and Shannon-like information two stumbling blocks for a physical interpretation of life, evolution and biological intelligence. A classical and quantum nanoscale approach to the biophysical problem of describing the biosystems structure-function solidarity and its evolutionary properties beyond Gödelian and self-reference paradoxes is discussed as a path toward a physical theory of biomimetic evolvable automata which is based on nanochaos information processing through Hamiltonian and dissipative nonlinear dynamics, and on quantum coherence/entanglement. The envisaged nanostructured hierarchical "extralogical" and logical sequential architectures of such evolvable automata would be implemented through the emerging nanotechnological (nanoelectronic/supramolecular and nano-mechanical) miniaturization capabilities.
Juillet, N; Salzmann, C C; Scopece, G
2011-07-01
It has often been proposed that nectarless deceptive orchid species exploit naïve pollinators in search of food before they learn to avoid their flowers, and that intraspecific floral trait polymorphism, often noted in this plant group, could prolong the time needed for learning, thus increasing orchid reproductive success. We tested the importance of avoidance learning in a European deceptive orchid, Anacamptis morio, which has been reported to have a highly variable fragrance bouquet among individuals. We used an indirect approach, i.e. we facilitated pollinators' ability to learn to avoid A. morio by adding anisaldehyde to selected inflorescences, a scent compound that is easily perceived by the natural pollinators and produced in large quantities by the closely related, nectar producing Anacamptis coriophora, a species that shares pollinator species with A. morio. In a series of three experiments (in artificial arrays, in natural populations and in bumblebee behavioural observations), we consistently found no difference either of reproductive success of or visitation rates to scent-added versus control inflorescences. We also found that the decrease of reproductive success over time in artificial populations of this deceptive species was not as important as expected. Together, these data suggest that pollinators do not fully learn to avoid deceptive inflorescences, and that pollinator avoidance behaviour alone may explain the lower reproductive success usually found in deceptive orchids. We discuss the possible explanations for this pattern in deceptive orchids, particularly in relation to pollinator cognition and learning abilities. Lastly, in light of our results, the potential for higher average reproductive success in deceptive orchids with high phenotypic variability driven by avoidance learning thus appears to be challenged.
ERIC Educational Resources Information Center
Hung, Chun-Ming; Hwang, Gwo-Jen; Huang, Iwen
2012-01-01
Although project-based learning is a well-known and widely used instructional strategy, it remains a challenging issue to effectively apply this approach to practical settings for improving the learning performance of students. In this study, a project-based digital storytelling approach is proposed to cope with this problem. With a…
ERIC Educational Resources Information Center
Chan, Yiu-Kong
2016-01-01
Learning effectiveness requires an understanding of the relationship among extracurricular activities, learning approach and academic performance and, it is argued, this helps educators develop techniques designed to enrich learning effectiveness. Biggs' Presage-Process-Product model on student learning has identified the relationship among…
ERIC Educational Resources Information Center
Liu, Woon Chia; Wang, Chee Keng John; Kee, Ying Hwa; Koh, Caroline; Lim, Boon San Coral; Chua, Lilian
2014-01-01
The development of effective self-regulated learning strategies is of interest to educationalists. In this paper, we examine inherent individual difference in self-regulated learning based on Motivated Learning for Learning Questionnaire (MLSQ) using the cluster analytic approach and examine cluster difference in terms of self-determination theory…
Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning
ERIC Educational Resources Information Center
Akhmetova, Daniya Z.
2014-01-01
Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…
ERIC Educational Resources Information Center
Gorry, Jonathan
2011-01-01
A wide variety of British universities are expanding efforts to attract international students. This article argues that higher education's implicit claim to all-inclusive "universality" may hereby be challenged by subsequent issues of cultural particularity. Here I set to conceptualise possible differences in the learning culture of…
Translational Approach to Behavioral Learning: Lessons from Cerebellar Plasticity
Cheron, Guy; Dan, Bernard; Márquez-Ruiz, Javier
2013-01-01
The role of cerebellar plasticity has been increasingly recognized in learning. The privileged relationship between the cerebellum and the inferior olive offers an ideal circuit for attempting to integrate the numerous evidences of neuronal plasticity into a translational perspective. The high learning capacity of the Purkinje cells specifically controlled by the climbing fiber represents a major element within the feed-forward and feedback loops of the cerebellar cortex. Reciprocally connected with the basal ganglia and multimodal cerebral domains, this cerebellar network may realize fundamental functions in a wide range of behaviors. This review will outline the current understanding of three main experimental paradigms largely used for revealing cerebellar functions in behavioral learning: (1) the vestibuloocular reflex and smooth pursuit control, (2) the eyeblink conditioning, and (3) the sensory envelope plasticity. For each of these experimental conditions, we have critically revisited the chain of causalities linking together neural circuits, neural signals, and plasticity mechanisms, giving preference to behaving or alert animal physiology. Namely, recent experimental approaches mixing neural units and local field potentials recordings have demonstrated a spike timing dependent plasticity by which the cerebellum remains at a strategic crossroad for deciphering fundamental and translational mechanisms from cellular to network levels. PMID:24319600
Incremental Transductive Learning Approaches to Schistosomiasis Vector Classification
NASA Astrophysics Data System (ADS)
Fusco, Terence; Bi, Yaxin; Wang, Haiying; Browne, Fiona
2016-08-01
The key issues pertaining to collection of epidemic disease data for our analysis purposes are that it is a labour intensive, time consuming and expensive process resulting in availability of sparse sample data which we use to develop prediction models. To address this sparse data issue, we present the novel Incremental Transductive methods to circumvent the data collection process by applying previously acquired data to provide consistent, confidence-based labelling alternatives to field survey research. We investigated various reasoning approaches for semi-supervised machine learning including Bayesian models for labelling data. The results show that using the proposed methods, we can label instances of data with a class of vector density at a high level of confidence. By applying the Liberal and Strict Training Approaches, we provide a labelling and classification alternative to standalone algorithms. The methods in this paper are components in the process of reducing the proliferation of the Schistosomiasis disease and its effects.
A Concept Map Approach to Developing Collaborative Mindtools for Context-Aware Ubiquitous Learning
ERIC Educational Resources Information Center
Hwang, Gwo-Jen; Shi, Yen-Ru; Chu, Hui-Chun
2011-01-01
Recent advances in mobile and wireless communication technologies have enabled various new learning approaches which situate students in environments that combine real-world and digital-world learning resources; moreover, students are allowed to share knowledge or experiences with others during the learning process. Although such an approach seems…
What's Wrong with Learning for the Exam? An Assessment-Based Approach for Student Engagement
ERIC Educational Resources Information Center
Ito, Hiroshi
2014-01-01
It is now widely recognized that assessment and the feedback play key roles in the learning process. However, assessment-based learning approaches are not yet commonly practiced in Japan. This paper provides an example of an assessment-based approach to teaching and learning employed for a course entitled "English as an International…
ERIC Educational Resources Information Center
Cormas, Peter C.
2016-01-01
Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…
An approach towards problem-based learning in virtual space.
Freudenberg, Lutz S; Bockisch, Andreas; Beyer, Thomas
2010-01-01
Problem-based learning (PBL) is an established and efficient approach to sustainable teaching. Here, we describe translation of PBL into the virtual classroom thereby offering novel teaching aspects in the field of Nuclear Medicine. Our teaching approach is implemented on a "moodle" platform and consists of 2 modules: complementary seminar teaching materials and a virtual PBL-classroom, which can be attended via Skype.Over the course of 4 semesters 539 students have accessed our teaching platform. 21 students have participated in the PBL seminar (module 2). After resolving some minor technical difficulties our virtual seminars have evolved into a forum of intense studies, whereby the participating students have learned to become more independent along the workup of the teaching cases. This was reflected in the results of the intra-group presentations and discussions.Quantitative and qualitative evaluation of our moodle-based PBL platform indicates an increasing level of acceptance and enthusiasm by the students. This has initiated discussions about opening our PBL concept to a wider audience within the university and beyond the Nuclear Medicine specialty.
Predicting DPP-IV inhibitors with machine learning approaches.
Cai, Jie; Li, Chanjuan; Liu, Zhihong; Du, Jiewen; Ye, Jiming; Gu, Qiong; Xu, Jun
2017-02-02
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects. The scaffolds of existing DPP-IV inhibitors are structurally diversified. This makes it difficult to build virtual screening models based upon the known DPP-IV inhibitor libraries using conventional QSAR approaches. In this paper, we report a new strategy to predict DPP-IV inhibitors with machine learning approaches involving naïve Bayesian (NB) and recursive partitioning (RP) methods. We built 247 machine learning models based on 1307 known DPP-IV inhibitors with optimized molecular properties and topological fingerprints as descriptors. The overall predictive accuracies of the optimized models were greater than 80%. An external test set, composed of 65 recently reported compounds, was employed to validate the optimized models. The results demonstrated that both NB and RP models have a good predictive ability based on different combinations of descriptors. Twenty "good" and twenty "bad" structural fragments for DPP-IV inhibitors can also be derived from these models for inspiring the new DPP-IV inhibitor scaffold design.
Predicting DPP-IV inhibitors with machine learning approaches
NASA Astrophysics Data System (ADS)
Cai, Jie; Li, Chanjuan; Liu, Zhihong; Du, Jiewen; Ye, Jiming; Gu, Qiong; Xu, Jun
2017-02-01
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects. The scaffolds of existing DPP-IV inhibitors are structurally diversified. This makes it difficult to build virtual screening models based upon the known DPP-IV inhibitor libraries using conventional QSAR approaches. In this paper, we report a new strategy to predict DPP-IV inhibitors with machine learning approaches involving naïve Bayesian (NB) and recursive partitioning (RP) methods. We built 247 machine learning models based on 1307 known DPP-IV inhibitors with optimized molecular properties and topological fingerprints as descriptors. The overall predictive accuracies of the optimized models were greater than 80%. An external test set, composed of 65 recently reported compounds, was employed to validate the optimized models. The results demonstrated that both NB and RP models have a good predictive ability based on different combinations of descriptors. Twenty "good" and twenty "bad" structural fragments for DPP-IV inhibitors can also be derived from these models for inspiring the new DPP-IV inhibitor scaffold design.
Modeling pedestrian behaviors under attracting incidents using cellular automata
NASA Astrophysics Data System (ADS)
Chen, Yanyan; Chen, Ning; Wang, Yang; Wang, Zhenbao; Feng, Guochen
2015-08-01
Compared to vehicular flow, pedestrian flow is more complicated as it is free from the restriction of the lane and more flexible. Due to the lack of modeling pedestrian behaviors under attracting incidents (incidents which attract pedestrians around to gather), this paper proposes a new cellular automata model aiming to reproduce the behaviors induced by such attracting incidents. When attracting incidents occur, the proposed model will classify pedestrians around the incidents into three groups: the "unaffected" type, the "stopped" type and the "onlooking" type. The "unaffected" type represents the pedestrians who are not interested in the attracting incidents and its dynamics are the same as that under normal circumstances which are the main target in the previous works. The "stopped" type represents the pedestrians are somewhat interested in the attracting incidents, but unwilling to move close to the venues. Its dynamics are determined by "stopped" utility which can make the pedestrians stop for a while. The "onlooking" type represents the pedestrians who show strong interest in the attracting incidents and intend to move close to the venues to gain more information. The "onlooking" pedestrians will take a series of reactions to attracting incidents, such as approaching to the venues, stopping and watching the attracting incidents, leaving the venues, which have all been considered in the proposed model. The simulation results demonstrate that the proposed model can capture the macro-characteristics of pedestrian traffic flow under normal circumstances and possesses the fundamental characteristics of the pedestrian behaviors under attracting incidents around which a torus-shaped crowd is typically formed.
Validating Cellular Automata Lava Flow Emplacement Algorithms with Standard Benchmarks
NASA Astrophysics Data System (ADS)
Richardson, J. A.; Connor, L.; Charbonnier, S. J.; Connor, C.; Gallant, E.
2015-12-01
A major existing need in assessing lava flow simulators is a common set of validation benchmark tests. We propose three levels of benchmarks which test model output against increasingly complex standards. First, imulated lava flows should be morphologically identical, given changes in parameter space that should be inconsequential, such as slope direction. Second, lava flows simulated in simple parameter spaces can be tested against analytical solutions or empirical relationships seen in Bingham fluids. For instance, a lava flow simulated on a flat surface should produce a circular outline. Third, lava flows simulated over real world topography can be compared to recent real world lava flows, such as those at Tolbachik, Russia, and Fogo, Cape Verde. Success or failure of emplacement algorithms in these validation benchmarks can be determined using a Bayesian approach, which directly tests the ability of an emplacement algorithm to correctly forecast lava inundation. Here we focus on two posterior metrics, P(A|B) and P(¬A|¬B), which describe the positive and negative predictive value of flow algorithms. This is an improvement on less direct statistics such as model sensitivity and the Jaccard fitness coefficient. We have performed these validation benchmarks on a new, modular lava flow emplacement simulator that we have developed. This simulator, which we call MOLASSES, follows a Cellular Automata (CA) method. The code is developed in several interchangeable modules, which enables quick modification of the distribution algorithm from cell locations to their neighbors. By assessing several different distribution schemes with the benchmark tests, we have improved the performance of MOLASSES to correctly match early stages of the 2012-3 Tolbachik Flow, Kamchakta Russia, to 80%. We also can evaluate model performance given uncertain input parameters using a Monte Carlo setup. This illuminates sensitivity to model uncertainty.
Boolean linear differential operators on elementary cellular automata
NASA Astrophysics Data System (ADS)
Martín Del Rey, Ángel
2014-12-01
In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.
Cellular Automata Ideas in Digital Circuits and Switching Theory.
ERIC Educational Resources Information Center
Siwak, Pawel P.
1985-01-01
Presents two examples which illustrate the usefulness of ideas from cellular automata. First, Lee's algorithm is recalled and its cellular nature shown. Then a problem from digraphs, which has arisen from analyzing predecessing configurations in the famous Conway's "game of life," is considered. (Author/JN)
Return of the Quantum Cellular Automata: Episode VI
NASA Astrophysics Data System (ADS)
Carr, Lincoln D.; Hillberry, Logan E.; Rall, Patrick; Halpern, Nicole Yunger; Bao, Ning; Montangero, Simone
2016-05-01
There are now over 150 quantum simulators or analog quantum computers worldwide. Although exploring quantum phase transitions, many-body localization, and the generalized Gibbs ensemble are exciting and worthwhile endeavors, there are totally untapped directions we have not yet pursued. One of these is quantum cellular automata. In the past a principal goal of quantum cellular automata was to reproduce continuum single particle quantum physics such as the Schrodinger or Dirac equation from simple rule sets. Now that we begin to really understand entanglement and many-body quantum physics at a deeper level, quantum cellular automata present new possibilities. We explore several time evolution schemes on simple spin chains leading to high degrees of quantum complexity and nontrivial quantum dynamics. We explain how the 256 known classical elementary cellular automata reduce to just a few exciting quantum cases. Our analysis tools include mutual information based complex networks as well as more familiar quantifiers like sound speed and diffusion rate. Funded by NSF and AFOSR.
Quantum cellular automata and free quantum field theory
NASA Astrophysics Data System (ADS)
D'Ariano, Giacomo Mauro; Perinotti, Paolo
2017-02-01
In a series of recent papers [1-4] it has been shown how free quantum field theory can be derived without using mechanical primitives (including space-time, special relativity, quantization rules, etc.), but only considering the easiest quantum algorithm encompassing a countable set of quantum systems whose network of interactions satisfies the simple principles of unitarity, homogeneity, locality, and isotropy. This has opened the route to extending the axiomatic information-theoretic derivation of the quantum theory of abstract systems [5, 6] to include quantum field theory. The inherent discrete nature of the informational axiomatization leads to an extension of quantum field theory to a quantum cellular automata theory, where the usual field theory is recovered in a regime where the discrete structure of the automata cannot be probed. A simple heuristic argument sets the scale of discreteness to the Planck scale, and the customary physical regime where discreteness is not visible is the relativistic one of small wavevectors. In this paper we provide a thorough derivation from principles that in the most general case the graph of the quantum cellular automaton is the Cayley graph of a finitely presented group, and showing how for the case corresponding to Euclidean emergent space (where the group resorts to an Abelian one) the automata leads to Weyl, Dirac and Maxwell field dynamics in the relativistic limit. We conclude with some perspectives towards the more general scenario of non-linear automata for interacting quantum field theory.
Problem-Based Learning Approach for Science Teachers' Professional Development.
ERIC Educational Resources Information Center
Wang, HsingChi A.; Thompson, Patricia; Shuler, Charles; Harvey, LaNelle
This paper describes efforts to introduce teachers to three aspects of problem-based learning: (1) learning cases; (2) student-centered learning; and (3) small group cooperative learning. Problem-based learning was woven into the design of professional development institutes because of the organizers' idea that as teachers grow professionally in a…
NASA Astrophysics Data System (ADS)
Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.
2016-02-01
This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.
Free Quantum Field Theory from Quantum Cellular Automata
NASA Astrophysics Data System (ADS)
Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro
2015-10-01
After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).
A stochastic parameterization for deep convection using cellular automata
NASA Astrophysics Data System (ADS)
Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.
2012-12-01
Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in
Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults
NASA Technical Reports Server (NTRS)
Spikovska, Lilly; Iverson, David L.; Poll, Scott; Pryor, anna
2005-01-01
Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-11-22
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks
NASA Astrophysics Data System (ADS)
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-11-01
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.
Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks
Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez
2016-01-01
Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024
ERIC Educational Resources Information Center
Gallagher, Rosina Mena
This study evaluates the counseling-learning approach to foreign language instruction as compared with traditional methods in terms of language achievement and change in personal orientation and in attitude toward learning. Twelve students volunteered to learn Spanish or German under simultaneous exposure to both languages using the…
Finding accurate frontiers: A knowledge-intensive approach to relational learning
NASA Technical Reports Server (NTRS)
Pazzani, Michael; Brunk, Clifford
1994-01-01
An approach to analytic learning is described that searches for accurate entailments of a Horn Clause domain theory. A hill-climbing search, guided by an information based evaluation function, is performed by applying a set of operators that derive frontiers from domain theories. The analytic learning system is one component of a multi-strategy relational learning system. We compare the accuracy of concepts learned with this analytic strategy to concepts learned with an analytic strategy that operationalizes the domain theory.
Approaches to Studying and Students' Use of a Computer Supported Learning Environment
ERIC Educational Resources Information Center
Foster, Jonathan; Lin, Angela
2007-01-01
Although studies of students' study approaches in face to face learning environments are commonplace, studies investigating the role of students' study approaches in online learning environments is currently a less explored area. This paper presents the findings of a survey aimed at investigating the relationship between students' approaches to…
NASA Astrophysics Data System (ADS)
Ilyas, Muhammad; Salwah
2017-02-01
The type of this research was experiment. The purpose of this study was to determine the difference and the quality of student's learning achievement between students who obtained learning through Realistic Mathematics Education (RME) approach and students who obtained learning through problem solving approach. This study was a quasi-experimental research with non-equivalent experiment group design. The population of this study was all students of grade VII in one of junior high school in Palopo, in the second semester of academic year 2015/2016. Two classes were selected purposively as sample of research that was: year VII-5 as many as 28 students were selected as experiment group I and VII-6 as many as 23 students were selected as experiment group II. Treatment that used in the experiment group I was learning by RME Approach, whereas in the experiment group II by problem solving approach. Technique of data collection in this study gave pretest and posttest to students. The analysis used in this research was an analysis of descriptive statistics and analysis of inferential statistics using t-test. Based on the analysis of descriptive statistics, it can be concluded that the average score of students' mathematics learning after taught using problem solving approach was similar to the average results of students' mathematics learning after taught using realistic mathematics education (RME) approach, which are both at the high category. In addition, It can also be concluded that; (1) there was no difference in the results of students' mathematics learning taught using realistic mathematics education (RME) approach and students who taught using problem solving approach, (2) quality of learning achievement of students who received RME approach and problem solving approach learning was same, which was at the high category.
Learning approaches to physiology of undergraduates in an Indian medical school.
Abraham, Reem R; Kamath, Asha; Upadhya, Subramanya; Ramnarayan, Komattil
2006-09-01
Inventories monitoring students' learning approaches are widely used in medical education research. It is important that teaching interventions adopted in medical schools aim to develop a deep approach to learning in medical students. To study the changes in medical students' approaches to learning before and after the incorporation of clinically orientated physiology teaching (COPT) in the undergraduate physiology curriculum, using the Short Inventory of Approaches to Learning (SIAL). Medical students (n = 223) at Melaka Manipal Medical College (Manipal Campus) undertake a 9-week learning block of endocrine, reproductive and renal physiology in Year 1. During this period, COPT was incorporated along with regular didactic lectures with the intention of enhancing the use of the deep approach and decreasing the use of the surface and strategic approaches to learning taken by the students. The SIAL, which focuses on the learning approaches of students to physiology, was distributed both before and after COPT. The implementation of COPT seemed to affect the learning approaches of students as measured by the SIAL. After the introduction of COPT, there was a significant increase in the use of the deep learning approach, while the majority of subscales for the surface approach showed decreased use. Nevertheless, use of the strategic approach was found to have increased after COPT. The SIAL was found to be a fairly reliable tool with which to determine the learning approaches of medical students. Clinically orientated physiology teaching was successful in enhancing use of the deep approach to learning and reducing use of the surface approach among undergraduate medical students.
A hybrid ensemble learning approach to star-galaxy classification
NASA Astrophysics Data System (ADS)
Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias
2015-10-01
There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.
Machine learning approaches to personalize early prediction of asthma exacerbations.
Finkelstein, Joseph; Jeong, In Cheol
2017-01-01
Patient telemonitoring results in an aggregation of significant amounts of information about patient disease trajectory. However, the potential use of this information for early prediction of exacerbations in adult asthma patients has not been systematically evaluated. The aim of this study was to explore the utility of telemonitoring data for building machine learning algorithms that predict asthma exacerbations before they occur. The study dataset comprised daily self-monitoring reports consisting of 7001 records submitted by adult asthma patients during home telemonitoring. Predictive modeling included preparation of stratified training datasets, predictive feature selection, and evaluation of resulting classifiers. Using a 7-day window, a naive Bayesian classifier, adaptive Bayesian network, and support vector machines were able to predict asthma exacerbation occurring on day 8, with sensitivity of 0.80, 1.00, and 0.84; specificity of 0.77, 1.00, and 0.80; and accuracy of 0.77, 1.00, and 0.80, respectively. Our study demonstrated that machine learning techniques have significant potential in developing personalized decision support for chronic disease telemonitoring systems. Future studies may benefit from a comprehensive predictive framework that combines telemonitoring data with other factors affecting the likelihood of developing acute exacerbation. Approaches implemented for advanced asthma exacerbation prediction may be extended to prediction of exacerbations in patients with other chronic health conditions.
Machine Learning Approaches to Rare Events Sampling and Estimation
NASA Astrophysics Data System (ADS)
Elsheikh, A. H.
2014-12-01
Given the severe impacts of rare events, we try to quantitatively answer the following two questions: How can we estimate the probability of a rare event? And what are the factors affecting these probabilities? We utilize machine learning classification methods to define the failure boundary (in the stochastic space) corresponding to a specific threshold of a rare event. The training samples for the classification algorithm are obtained using multilevel splitting and Monte Carlo (MC) simulations. Once the training of the classifier is performed, a full MC simulation can be performed efficiently using the classifier as a reduced order model replacing the full physics simulator.We apply the proposed method on a standard benchmark for CO2 leakage through an abandoned well. In this idealized test case, CO2 is injected into a deep aquifer and then spreads within the aquifer and, upon reaching an abandoned well; it rises to a shallower aquifer. In current study, we try to evaluate the probability of leakage of a pre-defined amount of the injected CO2 given a heavy tailed distribution of the leaky well permeability. We show that machine learning based approaches significantly outperform direct MC and multi-level splitting methods in terms of efficiency and precision. The proposed algorithm's efficiency and reliability enabled us to perform a sensitivity analysis to the different modeling assumptions including the different prior distributions on the probability of CO2 leakage.
A dictionary learning approach for Poisson image deblurring.
Ma, Liyan; Moisan, Lionel; Yu, Jian; Zeng, Tieyong
2013-07-01
The restoration of images corrupted by blur and Poisson noise is a key issue in medical and biological image processing. While most existing methods are based on variational models, generally derived from a maximum a posteriori (MAP) formulation, recently sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, we propose in this paper a model containing three terms: a patch-based sparse representation prior over a learned dictionary, the pixel-based total variation regularization term and a data-fidelity term capturing the statistics of Poisson noise. The resulting optimization problem can be solved by an alternating minimization technique combined with variable splitting. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio value and the method noise, the proposed algorithm outperforms state-of-the-art methods.
New approaches to addiction treatment based on learning and memory.
Kiefer, Falk; Dinter, Christina
2013-01-01
Preclinical studies suggest that physiological learning processes are similar to changes observed in addicts at the molecular, neuronal, and structural levels. Based on the importance of classical and instrumental conditioning in the development and maintenance of addictive disorders, many have suggested cue-exposure-based extinction training of conditioned, drug-related responses as a potential new treatment of addiction. It may also be possible to facilitate this extinction training with pharmacological compounds that strengthen memory consolidation during cue exposure. Another potential therapeutic intervention would be based on the so-called reconsolidation theory. According to this hypothesis, already-consolidated memories return to a labile state when reactivated, allowing them to undergo another phase of consolidation-reconsolidation, which can be pharmacologically manipulated. These approaches suggest that the extinction of drug-related memories may represent a viable treatment strategy in the future treatment of addiction.
Student Approaches to Learning and Studying. Research Monograph.
ERIC Educational Resources Information Center
Biggs, John B.
A common thread in contemporary research in student learning refers to the ways in which students go about learning. A theory of learning is presented that accentuates the interaction between the person and the situation. Research evidence implies a form of meta-cognition called meta-learning, the awareness of students of their own learning…
Approach to Dynamic Assembling of Individualized Learning Paths
ERIC Educational Resources Information Center
Lubchak, Vladimir; Kupenko, Olena; Kuzikov, Borys
2012-01-01
E-learning students are generally heterogeneous and have different capabilities knowledge base and needs. The aim of the Sumy State University (SSU) e-learning system project is to cater to these individual needs by assembling individual learning path. This paper shows current situation with e-learning in Ukraine, state-of-art of development of…
A Computer-Assisted Approach to Conducting Cooperative Learning Process
ERIC Educational Resources Information Center
Tsai, Pei-Jin; Hwang, Gwo-Jen; Tseng, Judy C. R.; Hwang, Gwo-Haur
2008-01-01
Cooperative learning has been proven to be helpful in enhancing the learning performance of students. The goal of a cooperative learning group is to maximize all members' learning, which is accomplished via promoting each other's success, through assisting, sharing, mentoring, explaining, and encouragement. To achieve the goal of cooperative…
Constructive and problem-based learning using blended learning anchored instruction approaches
NASA Astrophysics Data System (ADS)
Mayer, M.
2012-04-01
Based on an anchored instruction approach, an enriched blended learning lecture course ("Introduction into GNSS positioning") was established in order to enable constructive and problem-based learning. The lecture course "Introduction into GNSS positioning" is a compulsory part of the Bachelor study course "Geodesy and Geoinformatics" and also a supplementary module of the Bachelor study course "Geophysics". Within the lecture course, basic knowledge and basic principles of Global Navigation Satellite Systems, like GPS, are imparted. The presented higher education technique "anchored instruction" uses a real and up-to-date and therefore authentic scientific paper dealing with a recent large-scale geodetic project (Fehmarn Belt Fixed Link) in order to introduce the topic of GNSS-based positioning to the students. In the beginning of the semester, the students have to read the paper individually and carefully. This enables them to realize a lot of not-known GNSS-related facts. Therefore, questions can be formulated focusing on new, unclear or not-understood aspects of the paper. The lecture course deals with these questions, in order to answer them throughout the semester. During the lecture course this paper is referred, e.g., in the middle of the semester, the paper has to be read again in order to check which questions have been answered; in addition, new question arise. At the end of the lecture course, the author of the scientific paper gave a concluding lecture. The framing anchor technique enables the students to anchor their GNSS knowledge. The presented case study uses a teaching resp. learning setting consisting of classroom lectures (given by teachers and learners), practical trainings (e.g., field exercises, students select topics individually), and online lectures (learning management system ILIAS is used as data, result, and asynchronous communication platform). The implementation and the elements of the anchoring technique, which enables student
E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education
NASA Astrophysics Data System (ADS)
Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.
2017-01-01
E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.
A full computation-relevant topological dynamics classification of elementary cellular automata.
Schüle, Martin; Stoop, Ruedi
2012-12-01
Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."
NASA Astrophysics Data System (ADS)
Vargas, David L.
Emerging quantum simulator technologies provide a new challenge to quantum many body theory. Quantifying the emergent order in and predicting the dynamics of such complex quantum systems requires a new approach. We develop such an approach based on complex network analysis of quantum mutual information. First, we establish the usefulness of quantum mutual information complex networks by reproducing the phase diagrams of transverse Ising and Bose-Hubbard models. By quantifying the complexity of quantum cellular automata we then demonstrate the applicability of complex network theory to non-equilibrium quantum dynamics. We conclude with a study of student collaboration networks, correlating a student's role in a collaboration network with their grades. This work thus initiates a quantitative theory of quantum complexity and provides a new tool for physics education research. (Abstract shortened by ProQuest.).
Rochmawati, Erna; Rahayu, Gandes Retno; Kumara, Amitya
2014-11-01
The aims of this study were to assess students' perceptions of their educational environment and approaches to learning, and determine if perceptions of learning environment associates with approaches to learning. A survey was conducted to collect data from a regional private university in Indonesia. A total of 232 nursing students completed two questionnaires that measured their perceptions of educational environment and approaches to learning. The measurement was based on Dundee Ready Education Environment Measurement (DREEM) and Approaches and Study Skills Inventory for Students (ASSIST). Five learning environments dimensions and three learning approaches dimensions from two measures were measured. The overall score of DREEM was 131.03/200 (SD 17.04), it was in the range considered to be favourable. The overall score is different significantly between years of study (p value = 0.01). This study indicated that the majority of undergraduate nursing students' adopt strategic approach (n = 139. 59.9%). The finding showed that perceived educational environment significantly associated with approaches to learning. This study implicated the need to maintain conducive learning environment. There is also a need to improve the management of learning activities that reflect the use of student-centered learning.
Checking Timed Büchi Automata Emptiness Using LU-Abstractions
NASA Astrophysics Data System (ADS)
Li, Guangyuan
This paper shows that the zone-based LU-extrapolation of Behrmann et al, that preserves reachability of timed automata, also preserves emptiness of timed Büchi automata. This improves the previous results by Tripakis et al who showed that the k-extrapolation preserves timed Büchi automata emptiness. The LU-extrapolation is coarser than k-extrapolation, allowing better state space reductions. A tool with LU-extrapolation for emptiness checking of timed Büchi automata has been implemented, and some experiments are reported.
Lessons Learned From Community-Based Approaches to Sodium Reduction
Kane, Heather; Strazza, Karen; Losby PhD, Jan L.; Lane, Rashon; Mugavero, Kristy; Anater, Andrea S.; Frost, Corey; Margolis, Marjorie; Hersey, James
2017-01-01
Purpose This article describes lessons from a Centers for Disease Control and Prevention initiative encompassing sodium reduction interventions in six communities. Design A multiple case study design was used. Setting This evaluation examined data from programs implemented in six communities located in New York (Broome County, Schenectady County, and New York City); California (Los Angeles County and Shasta County); and Kansas (Shawnee County). Subjects Participants (n = 80) included program staff, program directors, state-level staff, and partners. Measures Measures for this evaluation included challenges, facilitators, and lessons learned from implementing sodium reduction strategies. Analysis The project team conducted a document review of program materials and semi structured interviews 12 to 14 months after implementation. The team coded and analyzed data deductively and inductively. Results Five lessons for implementing community-based sodium reduction approaches emerged: (1) build relationships with partners to understand their concerns, (2) involve individuals knowledgeable about specific venues early, (3) incorporate sodium reduction efforts and messaging into broader nutrition efforts, (4) design the program to reduce sodium gradually to take into account consumer preferences and taste transitions, and (5) identify ways to address the cost of lower-sodium products. Conclusion The experiences of the six communities may assist practitioners in planning community-based sodium reduction interventions. Addressing sodium reduction using a community-based approach can foster meaningful change in dietary sodium consumption. PMID:24575726
ERIC Educational Resources Information Center
Sahin, Elif Adibelli; Deniz, Hasan; Topçu, Mustafa Sami
2016-01-01
The present study investigated to what extent Turkish preservice elementary teachers' orientations to teaching science could be explained by their epistemological beliefs, conceptions of learning, and approaches to learning science. The sample included 157 Turkish preservice elementary teachers. The four instruments used in the study were School…
ERIC Educational Resources Information Center
Khan, S.
2011-01-01
The purpose of this article is to report on empirical work, related to a techniques module, undertaken with the dental students of the University of the Western Cape, South Africa. I will relate how a range of different active learning techniques (tutorials; question papers and mock tests) assisted students to adopt a deep approach to learning in…
ERIC Educational Resources Information Center
Hsu, Ching-Kun; Hwang, Gwo-Jen
2014-01-01
Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…
ERIC Educational Resources Information Center
Arulselvi, Evangelin
2013-01-01
The present study aims at finding out the effectiveness of Mutual learning approach over the conventional method in learning English optional II among B.Ed students. The randomized pre-test, post test, control group and experimental group design was employed. The B.Ed students of the same college formed the control and experimental groups. Each…
ERIC Educational Resources Information Center
Brett, Paul; Nagra, Jas
2005-01-01
Provision of computers in universities for self-study is taken for granted and is seen as a must have educational resource, yet it is very expensive to fund. Students report that they use the Internet as their first stop in approaching research tasks. Learning theorists posit the important role of social interaction in contributing to learning.…
ERIC Educational Resources Information Center
Fuller, June L.
This study examined teachers' perceptions of changes in student learning and changes in their teaching strategies after implementing the Partners Advancing the Learning of Math and Science (PALMS) approach in an urban Massachusetts school district. PALMS was a cooperative statewide systemic initiative funded by the Massachusetts Department of…
ERIC Educational Resources Information Center
Wu, Ji-Wei; Tseng, Judy C. R.; Hwang, Gwo-Jen
2015-01-01
Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to…
The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent
ERIC Educational Resources Information Center
Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie
2017-01-01
Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…
Engaging in the Future of eLearning: A Scenarios-Based Approach
ERIC Educational Resources Information Center
Martin, Graeme; Pate, Judy
2005-01-01
eLearning has been heralded as a transforming influence on education and corporate training. Despite such rhetoric, the exploitation of eLearning has been slower than anticipated. We examine the future of eLearning by adopting a scenario planning approach. Our conclusions suggest the scenarios have been a valuable starting point in engaging in a…
ERIC Educational Resources Information Center
Linsey, Julie; Talley, Austin; White, Christina; Jensen, Dan; Wood, Kristin
2009-01-01
Active learning enhances engineering education. This paper presents rationale, curriculum supplements, and an approach to active learning that may be seamlessly incorporated into a traditional lecture-based engineering class. A framework of educational theory that structures the active learning experiences and includes consideration of learning…
ERIC Educational Resources Information Center
Önen, Emine
2015-01-01
This study aimed to examine connections between modes of thinking and approaches to learning. Participants were 1490 students attending to 9 high schools located in Ankara. The Style of Learning and Thinking-Youth Form and Revised Version of Learning Process Questionnaire were administered to these students. The connections between modes of…
A Comparison of the Learning Approaches of Accounting and Science Students at an Irish University
ERIC Educational Resources Information Center
Byrne, Marann; Finlayson, Odilla; Flood, Barbara; Lyons, Orla; Willis, Pauline
2010-01-01
One of the major challenges facing accounting education is the creation of a learning environment that promotes high-quality learning. Comparative research across disciplines offers educators the opportunity to gain a better understanding of the influence of contextual and personal variables on students' learning approaches. Using the Approaches…
The Development of a Robot-Based Learning Companion: A User-Centered Design Approach
ERIC Educational Resources Information Center
Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong
2015-01-01
A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…
A Cognitive Load Approach to Collaborative Learning: United Brains for Complex Tasks
ERIC Educational Resources Information Center
Kirschner, Femke; Paas, Fred; Kirschner, Paul A.
2009-01-01
This article presents a review of research comparing the effectiveness of individual learning environments with collaborative learning environments. In reviewing the literature, it was determined that there is no clear and unequivocal picture of how, when, and why the effectiveness of these two approaches to learning differ, a result which may be…
An Evaluation of Learning Objects in Singapore Primary Education: A Case Study Approach
ERIC Educational Resources Information Center
Grace, Tay Pei Lyn; Suan, Ng Peck; Wanzhen, Liaw
2008-01-01
Purpose: The purpose of this paper is to evaluate the usability and interface design of e-learning portal developed for primary schools in Singapore. Design/methodology/approach: Using Singapore-based learning EDvantage (LEAD) portal as a case study, this paper reviews and analyses the usability and usefulness of embedded learning objects (LOs)…
ERIC Educational Resources Information Center
Drago-Severson, Eleanor
2016-01-01
"What is happening in education today?" and "What is most needed for the future of teaching, learning and leading?" This article presents a developmental approach to learning, leadership and advancing professional learning--one that takes into account adults' diverse meaning making processes--that can help educators build the…
ERIC Educational Resources Information Center
Dixon, Helen; Hawe, Eleanor
2016-01-01
In this article we focus on how an experiential based approach to teacher learning about assessment for learning (AfL) provided opportunities for teachers to examine: their deep-seated beliefs about effective learning (and teaching); how these beliefs permeated their day-to-day actions and interactions with students, and the consequence of these…
Learning Biology through Innovative Curricula: A Comparison of Game- and Nongame-Based Approaches
ERIC Educational Resources Information Center
Sadler, Troy D.; Romine, William L.; Menon, Deepika; Ferdig, Richard E.; Annetta, Leonard
2015-01-01
This study explored student learning in the context of innovative biotechnology curricula and the effects of gaming as a central element of the learning experience. The quasi-experimentally designed study compared learning outcomes between two curricular approaches: One built around a computer-based game, and the other built around a narrative…
ERIC Educational Resources Information Center
Rebeschi, Lisa M.
2013-01-01
Professional nurses are challenged to provide high quality, evidence-based care in today's increasingly complex healthcare environment. Thus, nurses need to develop an appreciation for life-long learning. Understanding student approach to learning may provide nurse educators with empirical evidence to support specific teaching/learning strategies…
Autonomy in Science Education: A Practical Approach in Attitude Shifting towards Science Learning
ERIC Educational Resources Information Center
Jalil, Pasl A.; Abu Sbeih, M. Z.; Boujettif, M.; Barakat, R.
2009-01-01
This work describes a 2-year study in teaching school science, based on the stimulation of higher thinking levels in learning science using a highly student-centred and constructivist learning approach. We sought to shift and strengthen students' positive attitudes towards science learning, self-efficacy towards invention, and achievement.…
Learning in the Liminal Space: A Semiotic Approach to Threshold Concepts
ERIC Educational Resources Information Center
Land, Ray; Rattray, Julie; Vivian, Peter
2014-01-01
The threshold concepts approach to student learning and curriculum design now informs an empirical research base comprising over 170 disciplinary and professional contexts. It draws extensively on the notion of troublesomeness in a "liminal" space of learning. The latter is a transformative state in the process of learning in which there…
ERIC Educational Resources Information Center
Kliegel, Matthias; Altgassen, Mareike
2006-01-01
The present study investigated fluid and crystallized intelligence as well as strategic task approaches as potential sources of age-related differences in adult learning performance. Therefore, 45 young and 45 old adults were asked to learn pictured objects. Overall, young participants outperformed old participants in this learning test. However,…
Effect of Inquiry-Based Learning Approach on Student Resistance in a Science and Technology Course
ERIC Educational Resources Information Center
Sever, Demet; Guven, Meral
2014-01-01
The aim of this study was to identify the resistance behaviors of 7th grade students exhibited during their Science and Technology course teaching-learning processes, and to remove the identified resistance behaviors through teaching-learning processes that were constructed based on the inquiry-based learning approach. In the quasi-experimentally…
Learner-Centred Pedagogy for Swim Coaching: A Complex Learning Theory-Informed Approach
ERIC Educational Resources Information Center
Light, Richard
2014-01-01
While constructivist theories of learning have been widely drawn on to understand and explain learning in games when using game-based approaches their use to inform pedagogy beyond games is limited. In particular, there has been little interest in applying constructivist perspectives on learning to sports in which technique is of prime importance.…
Towards a New Learning: Play and Game-Based Approaches to Education
ERIC Educational Resources Information Center
de Freitas, Sara
2013-01-01
This position paper introduces the idea of a "new learning" which brings together elements of play and game-based learning approaches into education. The paper argues for a better understanding of the division between structured and unstructured play time in how one designs and delivers learning at all levels from primary to tertiary.…
ERIC Educational Resources Information Center
Scott, Sophia; Koch, Doug
2010-01-01
This article focuses on how technology educators can challenge students to "think" about technical problems. A key aspect of success in quality problem solving is understanding learning preferences and problem-solving approaches. The Learning Style Inventory (LSI) can be used to assess an individual's ideal way to learn, in essence, a…
An Outcome Evaluation of a Problem-Based Learning Approach with MSW Students
ERIC Educational Resources Information Center
Westhues, Anne; Barsen, Chia; Freymond, Nancy; Train, Patricia
2014-01-01
In this article, we report the findings from a study exploring the effects of a problem-based learning (PBL) approach to teaching and learning on learning outcomes for master's of social work (MSW) students. Students who participated in a PBL pilot project were compared with students who did not participate in 5 outcome areas: social work…
Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming
ERIC Educational Resources Information Center
Thota, Neena; Whitfield, Richard
2010-01-01
This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…
Demonstrating and Evaluating an Action Learning Approach to Building Project Management Competence
NASA Technical Reports Server (NTRS)
Kotnour, Tim; Starr, Stan; Steinrock, T. (Technical Monitor)
2001-01-01
This paper contributes a description of an action-learning approach to building project management competence. This approach was designed, implemented, and evaluated for use with the Dynacs Engineering Development Contract at the Kennedy Space Center. The aim of the approach was to improve three levels of competence within the organization: individual project management skills, project team performance. and organizational capabilities such as the project management process and tools. The overall steps to the approach, evaluation results, and lessons learned are presented. Managers can use this paper to design a specific action-learning approach for their organization.
Construction of living cellular automata using the Physarum plasmodium
NASA Astrophysics Data System (ADS)
Shirakawa, Tomohiro; Sato, Hiroshi; Ishiguro, Shinji
2015-04-01
The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.
Potential field cellular automata model for pedestrian flow.
Zhang, Peng; Jian, Xiao-Xia; Wong, S C; Choi, Keechoo
2012-02-01
This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.
A Learning-Based Approach for IP Geolocation
NASA Astrophysics Data System (ADS)
Eriksson, Brian; Barford, Paul; Sommers, Joel; Nowak, Robert
The ability to pinpoint the geographic location of IP hosts is compelling for applications such as on-line advertising and network attack diagnosis. While prior methods can accurately identify the location of hosts in some regions of the Internet, they produce erroneous results when the delay or topology measurement on which they are based is limited. The hypothesis of our work is that the accuracy of IP geolocation can be improved through the creation of a flexible analytic framework that accommodates different types of geolocation information. In this paper, we describe a new framework for IP geolocation that reduces to a machine-learning classification problem. Our methodology considers a set of lightweight measurements from a set of known monitors to a target, and then classifies the location of that target based on the most probable geographic region given probability densities learned from a training set. For this study, we employ a Naive Bayes framework that has low computational complexity and enables additional environmental information to be easily added to enhance the classification process. To demonstrate the feasibility and accuracy of our approach, we test IP geolocation on over 16,000 routers given ping measurements from 78 monitors with known geographic placement. Our results show that the simple application of our method improves geolocation accuracy for over 96% of the nodes identified in our data set, with on average accuracy 70 miles closer to the true geographic location versus prior constraint-based geolocation. These results highlight the promise of our method and indicate how future expansion of the classifier can lead to further improvements in geolocation accuracy.
What time is it? Deep learning approaches for circadian rhythms
Agostinelli, Forest; Ceglia, Nicholas; Shahbaba, Babak; Sassone-Corsi, Paolo; Baldi, Pierre
2016-01-01
Motivation: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken. Results: We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp. Availability and Implementation: All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu/. Contacts: fagostin@uci.edu or pfbaldi@uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307647
Learning Journeys: The Road from Informal to Formal Learning--The UK Open University's Approach
ERIC Educational Resources Information Center
Taylor, Josie
2013-01-01
Online learning is now achieving recognition as offering a way for learning to scale. However we need to learn from the experiences in distance learning institutions. The Open University was established over 40 years ago and offers a unique experience in building a distance learning organisation on innovative use of media, originally through…
Effects of Situated Mobile Learning Approach on Learning Motivation and Performance of EFL Students
ERIC Educational Resources Information Center
Huang, Chester S. J.; Yang, Stephen J. H.; Chiang, Tosti H. C.; Su, Addison Y. S.
2016-01-01
This study developed a 5-step vocabulary learning (FSVL) strategy and a mobile learning tool in a situational English vocabulary learning environment and assessed their effects on the learning motivation and performance of English as a foreign language (EFL) students in a situational English vocabulary learning environment. Overall, 80 EFL…
A Wiki Technology-Supported Seamless Learning Approach for Chinese Language Learning
ERIC Educational Resources Information Center
Wong, Lung-Hsiang; Chin, Chee-Kuen; Tay, Boon-Pei
2011-01-01
This paper reports an intervention study on Singapore primary five (fifth Grade) students' ICT (information and communication technology)-mediated Chinese idiom learning. We introduced "seamless learning" to the learning design, that is, the bridging of formal and informal learning, and individual and social learning, conforming to the…
The adaptive cruise control vehicles in the cellular automata model
NASA Astrophysics Data System (ADS)
Jiang, Rui; Wu, Qing-Song
2006-11-01
This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed.
A class of cellular automata modeling winnerless competition
NASA Astrophysics Data System (ADS)
Afraimovich, V.; Ordaz, F. C.; Urías, J.
2002-06-01
Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.
Supervisory control of (max,+) automata: extensions towards applications
NASA Astrophysics Data System (ADS)
Lahaye, Sébastien; Komenda, Jan; Boimond, Jean-Louis
2015-12-01
In this paper, supervisory control of (max,+) automata is studied. The synthesis of maximally permissive and just-in-time supervisor, as well as the synthesis of minimally permissive and just-after-time supervisor, are proposed. Results are also specialised to non-decreasing solutions, because only such supervisors can be realised in practice. The inherent issue of rationality raised recently is discussed. An illustration of concepts and results is presented through an example of a flexible manufacturing system.
An autonomous DNA model for finite state automata.
Martinez-Perez, Israel M; Zimmermann, Karl-Heinz; Ignatova, Zoya
2009-01-01
In this paper we introduce an autonomous DNA model for finite state automata. This model called sticker automaton model is based on the hybridisation of single stranded DNA molecules (stickers) encoding transition rules and input data. The computation is carried out in an autonomous manner by one enzyme which allows us to determine whether a resulting double-stranded DNA molecule belongs to the automaton's language or not.
Identifying patterns from one-rule-firing cellular automata.
Shin, Jae Kyun
2011-01-01
A new firing scheme for cellular automata in which only one rule is fired at a time produces myriad patterns. In addition to geometric patterns, natural patterns such as flowers and snow crystals were also generated. This study proposes an efficient method identifying the patterns using a minimal number of digits. Complexity of the generated patterns is discussed in terms of the shapes and colors of the patterns.
Origin of complexity and conditional predictability in cellular automata.
García-Morales, Vladimir
2013-10-01
A simple mechanism for the emergence of complexity in cellular automata out of predictable dynamics is described. This leads to introduce the concept of conditional predictability for systems whose trajectory can only be piecewise known. The mechanism is used to construct a cellular automaton model for discrete chimeralike states, where synchrony and incoherence in an ensemble of identical oscillators coexist. The incoherent region is shown to have a periodicity that is three orders of magnitude longer than the period of the synchronous oscillation.
An Operational Approach for Building Learning Environments Supporting Cognitive Flexibility
ERIC Educational Resources Information Center
Chieu, Vu Minh
2007-01-01
Constructivism is a learning theory that states that people learn by actively constructing their own knowledge, based on prior knowledge. A significant number of ICT-based constructivist learning systems have been proposed in recent years. According to our analysis, those systems exhibit only a few constructivist principles, and a critical problem…
Mobile Learning Approaches for U.S. Army Training
2010-08-01
or as lifelong learning tools requires that a learning management system (LMS) be developed to support the data from the assessments described above...Infantry Officer Basic Leadership Course LMS learning management system MEDEVAC medical evacuation MOS military occupation specialty NET
A Genetic Algorithm Approach to Recognise Students' Learning Styles
ERIC Educational Resources Information Center
Yannibelli, Virginia; Godoy, Daniela; Amandi, Analia
2006-01-01
Learning styles encapsulate the preferences of the students, regarding how they learn. By including information about the student learning style, computer-based educational systems are able to adapt a course according to the individual characteristics of the students. In accomplishing this goal, educational systems have been mostly based on the…
An Investigative, Cooperative Learning Approach to the General Microbiology Laboratory
ERIC Educational Resources Information Center
Seifert, Kyle; Fenster, Amy; Dilts, Judith A.; Temple, Louise
2009-01-01
Investigative- and cooperative-based learning strategies have been used effectively in a variety of classrooms to enhance student learning and engagement. In the General Microbiology laboratory for juniors and seniors at James Madison University, these strategies were combined to make a semester-long, investigative, cooperative learning experience…
A New Design Approach to Game-Based Learning
ERIC Educational Resources Information Center
Larsen, Lasse Juel
2012-01-01
This paper puts forward a new design perspective for game-based learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn--without the interference of teachers--whatever subject they wanted while sitting in front of a computer. This…
A Multidimensional Approach to E-Learning Sustainability
ERIC Educational Resources Information Center
Trentin, Guglielmo, Ed.
2007-01-01
The aim of the article is to outline the possible key elements related to the sustainability of e-learning. After analyzing trends in e-learning diffusion, a multidimensional model for sustainability of e-learning innovations is presented. The proposed model is characterized by eight dimensions that are closely and mutually interrelated:…
Flipped Learning in TESOL: Definitions, Approaches, and Implementation
ERIC Educational Resources Information Center
Bauer-Ramazani, Christine; Graney, John M.; Marshall, Helaine W.; Sabieh, Christine
2016-01-01
As the use of flipped learning spreads throughout educational disciplines, TESOL educators need to consider its potential for our field. This article, based on a computer-aided language learning (CALL) interest session at TESOL 2015, first looks at how best to describe and define flipped learning and examines the factors needed to make it…
An Analytical Model for Learning: An Applied Approach.
ERIC Educational Resources Information Center
Kassebaum, Peter Arthur
A mediated-learning package, geared toward non-traditional students, was developed for use in the College of Marin's cultural anthropology courses. An analytical model for learning was used in the development of the package, utilizing concepts related to learning objectives, programmed instruction, Gestalt psychology, cognitive psychology, and…
Designing Science Learning with Game-Based Approaches
ERIC Educational Resources Information Center
Liu, Min; Rosenblum, Jason A.; Horton, Lucas; Kang, Jina
2014-01-01
Given the growing popularity of digital games as a form of entertainment, educators are interested in exploring using digital games as a tool to facilitate learning. In this study, we examine game-based learning by describing a learning environment that combines game elements, play, and authenticity in the real world for the purpose of engaging…
Fostering Faculty Collaboration in Learning Communities: A Developmental Approach
ERIC Educational Resources Information Center
Stevenson, Catherine B.; Duran, Robert L.; Barrett, Karen A.; Colarulli, Guy C.
2005-01-01
Colleges and universities are adopting learning communities to increase student learning and build cohesion. As learning communities grow in popularity, institutions need to invest in faculty development (Oates, 2001) and understand faculty experiences (Mullen, 2001). The University of Hartford created a program that prepared faculty for…
Foreign Language Learning for Older Learners: Problems and Approaches.
ERIC Educational Resources Information Center
Roumani, Judith
An examination of some of the learning difficulties of Peace Corps volunteers 45 years of age and older who have attempted to learn a second language, combined with a review of research findings on the learning capacity of older learners, reveals areas in which the older learner can be helped to more complete success in foreign language study.…
Action Learning for Professionals: A New Approach to Practice
ERIC Educational Resources Information Center
Abbott, Christine; Mayes, Cathy
2014-01-01
Following on from the article "Building Capacity in Social Care: An Evaluation of a National Programme of Action Learning Facilitator Development" (Abbott, C., L. Burtney, and C. Wall. 2013. "Action Learning: Research & Practice" 10 (2): 168--177), this article describes how action learning is being introduced in Cornwall…
A Collaborative Action Research Approach to Professional Learning
ERIC Educational Resources Information Center
Bleicher, Robert E.
2014-01-01
The field of professional development is moving towards the notion of professional learning, highlighting the active learning role that teachers play in changing their knowledge bases, beliefs and practice. This article builds on this idea and argues for creating professional learning that is guided by a collaborative action research (CAR)…
A work-based learning approach for clinical support workers on mental health inpatient wards.
Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah
2016-09-14
Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary
ERIC Educational Resources Information Center
Fardanesh, Hashem
2006-01-01
In a conceptual-analytical study using a deductive classificatory content analysis method ten constructivist instructional design models were selected, and learning/teaching approaches within each model were appraised. Using the original writings of the originators of each design model, the learning and teaching approaches employed or permitted to…
An Interactive Approach to Learning and Teaching in Visual Arts Education
ERIC Educational Resources Information Center
Tomljenovic, Zlata
2015-01-01
The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts) teaching methods. The study uses quantitative…
ERIC Educational Resources Information Center
Dennehy, Edward
2015-01-01
With the advent of increasingly multinational student cohorts in many higher education institutes, the possible influence of 'national culture' on students' learning approaches has become a focal point of attention. In particular, the claim that Asian (Confucian) students adopt (primarily) surface learning approaches has attracted much debate…
Approaches to Learning and Age in Predicting College Students' Academic Achievement
ERIC Educational Resources Information Center
Cetin, Baris
2016-01-01
The aim of this study is to determine whether the approaches to learning and age are significantly correlated to grade point average (GPA) in early childhood education students. In addition, another purpose of this study is to determine whether approaches to learning and age predicted students' GPAs in the Early Childhood Education Department. The…
Differences in Perceived Approaches to Learning and Teaching English in Hong Kong Secondary Schools
ERIC Educational Resources Information Center
Mak, Barley; Chik, Pakey
2011-01-01
This paper investigates differences in approaches to learning and teaching English as a second language (ESL) as reported by 324 mixed-ability Grade 7 Hong Kong ESL students and 37 ESL secondary school teachers with different backgrounds. Information about participants' perceived approaches to learning/teaching English were collected through a…
ERIC Educational Resources Information Center
Yilmaz, Rezan
2014-01-01
This study aims to present the cognitive competences of the pre-service teacher about discovery learning approach in mathematical education. The study was conducted with 37 mathematics pre-service teachers who study Special Teaching Methods lesson in a state university in Turkey. Throughout the lesson, the approaches used in learning were examined…
Organizational Approach to the Ergonomic Examination of E-Learning Modules
ERIC Educational Resources Information Center
Lavrov, Evgeniy; Kupenko, Olena; Lavryk, Tetiana; Barchenko, Natalia
2013-01-01
With a significant increase in the number of e-learning resources the issue of quality is of current importance. An analysis of existing scientific and methodological literature shows the variety of approaches, methods and tools to evaluate e-learning materials. This paper proposes an approach based on the procedure for estimating parameters of…
ERIC Educational Resources Information Center
Imam, Boulent; Rafiq, M. Imran; Kumar, Prashant
2011-01-01
This article investigates the effectiveness of two distinct formative assessment methods for promoting deep learning and hence improving the performance amongst engineering students. The first method, applied for undergraduate students, employs a lecturer-led approach whereas the second method uses a student-led approach and e-learning for…
ERIC Educational Resources Information Center
Stephens, Ana; Fonger, Nicole L.; Blanton, Maria; Knuth, Eric
2016-01-01
In this paper, we describe our learning progressions approach to early algebra research that involves the coordination of a curricular framework, an instructional sequence, written assessments, and levels of sophistication describing the development of students' thinking. We focus in particular on what we have learning through this approach about…