DOCSLIB.ORG

Emergence Using Reinforcing Feedback: Quorum Sensing Bacteria Model Overview: What Is Emergence?

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Emergence Using Reinforcing Feedback: Quorum Sensing Bacteria Model Overview: What Is Emergence? Emergence Using Reinforcing Feedback: Quorum Sensing Bacteria Model Overview: This model introduces the concept of emergence and reinforcing feedback by using simulated bacteria as a platform. Using two types of agent-sets; bacteria and autoinducers, this model works as a proof of concept that demonstrates how individual bacteria (agents) may rely on reinforcing-feedback to work collectively in order to produce an emergent phenomena. What is Emergence? “Emergence may seem mysterious, but it is actually something that we experience every day. For example, a single water molecule of two hydrogen atoms and an oxygen atom does not feel wet (assuming you could feel a single molecule). But a few billion water molecules in a cup feel wet. That is because wetness is a collective property of the slippery interactions between water molecules in a particular temperature range… Similarly, what we call a symphony is a pattern of sound that emerges out of the playing of individual instruments, and what we call a kidney is a pattern of cells working together to provide a higher level function that none of the cells could do on its own.” Eric Beinhocker- Origin of Wealth1 Take a puzzle down from a dusty shelf and shake the contents onto a table. Now take a piece of the puzzle at random and inspect it. Note the color, shape, and presence of patterns on the piece. Now take another, and do the same. After awhile you may begin have some semblance of what certain differences there are between certain pieces, and you might notice certain trends in patterns. Now consider doing this process until you’ve looked at every single piece in the puzzle. Having considered each piece, would you have a clear understanding as to what the completed puzzle looked like? Perhaps, but certainly not as clearly as you would if you were to put all the pieces on the table, assemble them together, and see what as a whole they revealed. Like the picture of the completed puzzle, there are certain things that only become apparent or real to us when many other things interact with one another to form them. There appear to be many things that make a qualitative change or shift once a certain 1 Beinhocker, E. D. (2007). The origin of wealth: Evolution, complexity, and the radical remaking of economics. Century. quantitative boundary is crossed. Traffic jams2, flocking birds3, and even our own consciousness4 are examples of emergent properties that we experience in our day to day life. However, our understanding of exactly how these phenomena occur, and how to understand the significance of emergent properties is a challenging facet to the study of complex systems5. What is feedback? “All dynamics arise from the interaction of just two types of feedback loops, positive (or self-reinforcing) and negative (self-correcting) loops. Positive loops tend to reinforce or amplify whatever is happening in the system: The more nuclear weapons NATO deployed during the Cold War, the more the Soviet Union built, leading NATO to build still more....Negative loops counteract and oppose change... The larger the market share of dominant firms, the more likely is government antitrust action to limit their monopoly power. These loops all all describe processes that tend to be self-limiting, processes that seek balance and equilibrium.” John D. Sterman6 Feedback can be seen as the process by which an output is ‘fed’ ‘back’ into the initial input that created it. This can either be negative ( self-correcting) or positive ( self- reinforcing). These processes can be used as a tool to describe complex systems where a great many loops of reinforcement and correction work together to compose the dynamic behavior of a system. In the instance of quorum-sensing bacteria we see that the presence of autoinducers, which are produced by individual bacteria, encourages bacteria to produce even more autoinducers. Here we have a system that is composed of at least one self-reinforcing ( positive ) feedback loop; as more autoinducers are made, the higher the 2 Resnick, M. (1997). Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. Mit Press. 3 Cavagna, A., Cimarelli, A., Giardina, I., Parisi, G., Santagati, R., Stefanini, F., & Viale, M. (2010). Scale-free correlations in starling flocks. Proceedings of the National Academy of Sciences, 107(26), 11865-11870. 4 Baas, N. A., & Emmeche, C. (1997, February). On emergence and explanation. Santa Fe, NM: Santa Fe Institute. 5 Anderson, P. W. (1972). More is different. Science, 177(4047), 393-396. 6 Sterman, J. D. (2000). Business dynamics: systems thinking and modeling for a complex world (Vol. 19). New York: Irwin/McGraw-Hill. chance there will be to make even more, creating a higher chance that even more will be made! What is Quorum Sensing? The word quorum, having its etymological roots in Latin ( the genitive plural of qui meaning; of whom ) means in the larger sense; a particular group’s minimum amount individuals needed to make a decision. In regards to this model, our quorum is a group of bacteria. This raises the question; how do bacteria know there are enough individuals in their group (a quorum) to make a decision? And, what is the decision that they are making? In the late 60’s microbiologists observing bioluminescent bacteria7 surmised that there was some amount of collective effort done by individual bacteria that resulted in a bunch of bacteria lighting up all at once. The concept of a decentralized process guiding the group activity was expanded upon in the 70’s by another group of microbiologists8 showing that the bacteria were in fact inducing bioluminescence by means of a molecule called an autoinducer. Bacteria were sending out these autoinducers into their environment, and other bacteria of the same species were able to detect the presence of these molecules. In a sense, bacteria were communicating to each other by producing these little molecules. By being able to detect autoinducers bacteria were able to answer the question; how many other bacteria are around me right now? The purpose of answering the question of how many, has to do with the reaction a bacteria has when a certain number (threshold) of these autoinducer molecules are encountered. When a particular threshold of ‘how many’ is breached, bacteria begin transcribing genes that synthesize chemicals that, depending on the bacteria transcribing them, have a wide range of outcomes, “Quorum sensing is the regulation of gene expression in response to fluctuations in cell- population density. Quorum sensing bacteria produce and release chemical signal molecules called autoinducers that increase in concentrationas a function of cell density. The detection of a minimal threshold stimulatory concentration of an autoinducer leads to an alteration in gene expression....These processes include symbiosis, virulence, 7 Kempner, E.S. and Hanson, F.E. (1968) Aspects of light production by Photobacterium fischeri. J. Bacteriol. 95, 975-979. 8 Nealson, K.H., Platt, T. and Hastings, J.W. (1970) Cellular control of the synthesis and activity of the bacterial luminescence system. J. Bacteriol. 104, 313-322. competence, conjugation, antibiotic production, motility, sporulation, and biofilm formation.” 9 Consider this strange situation: Imagine yourself in a perfectly dark room. You stumble around the room looking for a light switch, but find there are none. Alas you take inventory of your situation. You hold in your hand an empty flashlight that seems to require an usual amount of batteries to turn on. You also have a bunch batteries filling all of your pockets. You try and fit each of the batteries you have in your flashlight, and find that for some reason they just don’t fit inside. Wandering around aimlessly you step on something strange and reach down to find that you’ve discovered a battery on the floor. You try this new battery and low and behold; it fits! You decide it would be a good idea to start getting rid of your other batteries, as they are of no obvious use to you, and you’re finding ones that seem to work a lot better anyway. As you walk around, each new battery you find encourages you to drop more and more of your batteries that you can’t use. Finally it seems, that every where you turn is a new battery that works with your light and you are dropping batteries left and right. Finally; you find the last battery you need to turn your light on, and just before you do so you notice all around this dark room other flash lights are lighting up, you turn yours on, and before you know it, the whole room is awash in the individual flashlights. Here you are the bacteria, the batteries are the autoinducers, and the light from the flashlight is the product of you transcribing genes. What is interesting about quorum- sensing and the dark room full of people walking around aimlessly with cumbersome flashlights, is that the collective action of bacteria, and the flashlight-holders isn’t regulated by any central figure; there is no master bacteria and there is no king of the flashlight holders. Nothing is telling each group to act all at once, it is only by means of using a shared environment, having a shared threshold and having a shared method of communication that allows each group of individuals to act collectively. It is this collective response that we describe as being an emergent property of the system. How the Model Works: The world is populated with a set number of bacteria that randomly wander around both reproducing and creating autoinducers. Each bacteria has a random chance of dying, and will never exceed the population size set by the carrying capacity in the model.
Load more

Recommended publications
  • What Is a Complex Adaptive System?
    PROJECT GUTS What is a Complex Adaptive System? Introduction During the last three decades a leap has been made from the application of computing to help scientists ‘do’ science to the integration of computer science concepts, tools and theorems into the very fabric of science. The modeling of complex adaptive systems (CAS) is an example of such an integration of computer science into the very fabric of science; models of complex systems are used to understand, predict and prevent the most daunting problems we face today; issues such as climate change, loss of biodiversity, energy consumption and virulent disease affect us all. The study of complex adaptive systems, has come to be seen as a scientific frontier, and an increasing ability to interact systematically with highly complex systems that transcend separate disciplines will have a profound affect on future science, engineering and industry as well as in the management of our planet’s resources (Emmott et al., 2006). The name itself, “complex adaptive systems” conjures up images of complicated ideas that might be too difficult for a novice to understand. Instead, the study of CAS does exactly the opposite; it creates a unified method of studying disparate systems that elucidates the processes by which they operate. A complex system is simply a system in which many independent elements or agents interact, leading to emergent outcomes that are often difficult (or impossible) to predict simply by looking at the individual interactions. The “complex” part of CAS refers in fact to the vast interconnectedness of these systems. Using the principles of CAS to study these topics as related disciplines that can be better understood through the application of models, rather than a disparate collection of facts can strengthen learners’ understanding of these topics and prepare them to understand other systems by applying similar methods of analysis (Emmott et al., 2006).
    [Show full text]
  • Organization, Self-Organization, Autonomy and Emergence: Status and Challenges
    Organization, Self-Organization, Autonomy and Emergence: Status and Challenges Sven Brueckner 1 Hans Czap 2 1 New Vectors LLC 3520 Green Court, Suite 250, Ann Arbor, MI 48105-1579, USA Email: [email protected] http://www.altarum.net/~sbrueckner 2 University of Trier, FB IV Business Information Systems I D-54286 Trier, Germany Email: [email protected] http://www.wi.uni-trier.de/ Abstract: Development of IT-systems in application react and adapt autonomously to changing requirements. domains is facing an ever-growing complexity resulting from Therefore, approaches that rely on the fundamental principles a continuous increase in dynamics of processes, applications- of self-organization and autonomy are growing in acceptance. and run-time environments and scaling. The impact of this Following such approaches, software system functionality trend is amplified by the lack of central control structures. As is no longer explicitly designed into its component processes a consequence, controlling this complexity and dynamics is but emerges from lower-level interactions that are one of the most challenging requirements of today’s system purposefully unaware of the system-wide behavior. engineers. Furthermore, organization, the meaningful progression of The lack of a central control instance immediately raises local sensing, processing and action, is achieved by the the need for software systems which can react autonomously system components themselves at runtime and in response to to changing environmental requirements and conditions. the current state of the environment and the problem that is to Therefore, a new paradigm is necessary how to build be solved, rather than being enforced from the “outside” software systems changing radically the way one is used to through design or external control.
    [Show full text]
  • Environmental Influences: Family Systems Theory
    Environmental Influences: Family Systems Theory Family Systems Theory provides a broad and comprehensive mechanism for understanding the core aspects of the Performance Competence Lifespan Framework — quality of life, member- ship, and a personal sense of competence. It also focuses on the most important component of environmental influences—home and family. From birth, a child’s Quality of Life is directly influ- enced by the kind of care, support, stimulation and education he or she receives from family mem- bers in the home. As infants begin to develop secure attachments with significant others, particu- larly family members, they begin to establish themselves as members of the first and most basic unit of society—the family, which forms the foundation for secure Membership in other groups throughout life. The infant begins to develop a Personal Sense of Competence when his mother responds consistently to his distress, when he takes his first step or says his first word, or when his father praises him for using the toilet. These early beginnings, then, are at the core of what each individual child will come to know and be able to do. As the PC Framework indicates, there are multiple environmental influences on performance and competence, but the family is the first and most important. The influence of family members on one another is not simple, but complex; it is not one-way, but reciprocal. The family, like a mechanical system, is made up of multiple parts that are interdependent. When one part does not function well, all other parts are impacted. Further, the family interacts with other systems, includ- ing those that provide direct services to the child—child care/preschools, schools and community agencies—and each system affects the other.
    [Show full text]
  • 1 Emergence of Universal Grammar in Foreign Word Adaptations* Shigeko
    1 Emergence of Universal Grammar in foreign word adaptations* Shigeko Shinohara, UPRESA 7018 University of Paris III/CNRS 1. Introduction There has been a renewal of interest in the study of loanword phonology since the recent development of constraint-based theories. Such theories readily express target structures and modifications that foreign inputs are subject to (e.g. Paradis and Lebel 1994, Itô and Mester 1995a,b). Depending on how the foreign sounds are modified, we may be able to make inferences about aspects of the speaker's grammar for which the study of the native vocabulary is either inconclusive or uninformative. At the very least we expect foreign words to be modified in accordance with productive phonological processes and constraints (Silverman 1992, Paradis and Lebel 1994). It therefore comes as some surprise when patterns of systematic modification arise for which the rules and constraints of the native system have nothing to say or even worse contradict. I report a number of such “emergent” patterns that appear in our study of the adaptations of French words by speakers of Japanese (Shinohara 1997a,b, 2000). I claim that they pose a learnability problem. My working hypothesis is that these emergent patterns are reflections of Universal Grammar (UG). This is suggested by the fact that the emergent patterns typically correspond to well-established crosslinguistic markedness preferences that are overtly and robustly attested in the synchronic phonologies of numerous other languages. It is therefore natural to suppose that these emergent patterns follow from the default parameter settings or constraint rankings inherited from the initial stages of language acquisition that remain latent in the mature grammar.
    [Show full text]
  • Clunio Populations to Different Tidal Conditions
    Genetic adaptation in emergence time of Clunio populations to different tidal conditions DIETRICH NEUMANN Zoologisches Institut der Universitiit Wiirzburg, Wiirzburg KURZFASSUNG: Genetische Adaptation der Schliipfzeiten yon Clunio-Populationen an verschiedene Gezeitenbedingungen. Die Schliipfzeiten der in der Gezeitenzone Iebenden Clunio-Arten (Diptera, Chironomidae) sind mit bestimmten Wasserstandsbedingungen syn- chronisiert, und zwar derart, dat~ die nnmittelbar anschlief~ende Fortpflanzung der kurz- lebigen Imagines auf dem trockengefallenen Habitat stattfinden kann. Wenn das Habitat einer Clunio-Art in der mittleren Gezeitenzone liegt und parallel zu dem halbt~igigen Gezeiten- zyklus (T = 12,4 h) zweimal t~iglich auftaucht, dann kann sich eine 12,4stiindige Schliipf- periodik einstellen (Beispiel: Clunio takahashii). Wenn das Habitat in der unteren Gezeiten- zone liegt und nur um die Zeit der Springtiden auftaucht, dann ist eine 15t~igige (semilunare) SchRipfperiodik zu erwarten (Beispiele: Clunio marinus und C. mecliterraneus). Diese 15t~igige Schliipfperiodik ist synchronisiert mit bestimmten Niedrigwasserbedingungen, die an einem Kiistenort alle 15 Tage jewqils um die gleiche Tageszeit auftreten. Sie wird daher dutch zwei Daten eindeutig gekennzeichnet: (1) die lunaren Schliipftage (wenige aufeinanderfolgende Tage um Voll- und Neumond) und (2) die t~igliche Schliipfzeit. Wie experimentelle Untersuchungen iiber die Steuerung der Schliipfperiodik zeigten, kiSnnen die Tiere beide Daten richtig voraus- bestimmen. Die einzelnen Kiistenpopulationen
    [Show full text]
  • Ophthalmology and the Emergence of Artificial Intelligence
    Perspectives Ophthalmology and the emergence of artificial intelligence Rapid advances in AI in ophthalmology are a harbinger of things to come for other fields of medicine he autonomous detection and triage of eye for retinopathy using retinal photography. This disease, or even accurate estimations of gender, vast demand for diabetic eye screening services Tage, and blood pressure from a simple retinal has stimulated the development of AI algorithms to photo, may sound like the realms of science fiction, identify sight-threatening disease. Several algorithms but advances in artificial intelligence (AI) have already have achieved performance that meets or exceeds that made this a reality.1 Ophthalmology is at the vanguard of human experts.4,5 Accordingly, in 2018, the United of the development and clinical application of AI. States Food and Drug Administration approved an AI Advances in the field may provide useful insights into system to detect referable diabetic retinopathy from the application of this technology in health care more retinal photographs, the first autonomous diagnostic broadly. system to be approved in any field of medicine.6 Advances in deep learning have extended to other Artificial intelligence imaging modalities that are commonly used in ophthalmology. Ocular coherence tomography is an Once described as the capacity of intelligent machines imaging technology that produces highly detailed, to imitate human intelligence and behaviour, AI now depth-resolved images of the retina. A recent describes many theories and practices used to achieve collaboration between researchers and clinicians computer intelligence (Box 1).2 Machine learning is at Google DeepMind, Moorfields Eye Hospital an application of AI that uses algorithms or statistical and University College London culminated in the models to make decisions or predictions.
    [Show full text]
  • Robustness of Multiloop Linear Feedback Systems
    WA1 - 10:45 ROBUSTNESS OF MJLTILOOP LINEAR FEEDBACK SYSTEMS* J. C. Doyle Consultant Honeywell Systems and Research Center 2600 Ridgway Parkway Minneapolis, Minnesota 55413 ABSTRACT critical role in evaluating system robustness. The Bode plot or scalar Nyquist or Inverse Nyquist This paper presents new a approach to the diagram (polar plots of the loop transfer function) frequency-domain analysis of multiloop linear feed-provides a meansof assessing these quantities at back systems. The properties of the return a glance. For multiloop systems, individual loops difference equation are examined using the conceptsmay be analyzed using scalar techniques, but these of singular values, singular vectors and the methods fail to capture the essentially multi- spectral norm of a matrix.A number of new tools variable nature of manysystem. For example, for multiloop systems are developed which are scalar methods may ignore variations which analogous to those for scalar Nyquist and Bode simultaneously affect multiple loops. analysis. These provide a generalization of the scalar frequency-domain notions such as gain, There are a number of other possible ways bandwidth, stability margins and M-circles, and to extend the classical frequency-domain tech- provide considerable insight into system robust- niques. One involves using compensation or feed- ness. back to decouple(or approximately decouple) a multiloop system into a set of scalar systems which may be treated w#th scalar techniques (i.e., 1. Introduction "Diagonal Dominance", bsenbrock[4]). Another A critical property of feedback systems is method uses the eigenvaluesof the loop transfer their robustness; that is, their ability to main-matrix (G(s) in Figure 1) as a function of fre- tain performance in the face of uncertainties.
    [Show full text]
  • Emergence in Psychology: Lessons from the History of Non-Reductionist Science
    Paper Human Development 2002;45:2-28 Human Development Emergence in Psychology: Lessons from the History of Non-Reductionist Science R. Keith Sawyer Washington University, St.louis, Mo., USA KeyWords Cognitive science. Emergence. History. Reductionism. Socioculturalism Abstract Theories of emergence have had a longstanding influence on psychological thought. Emergentism rejects both reductionism and holism; emergentists are scientific materialists, and yet argue that reductionist explanation may not always be scientifically feasible. I begin by summarizing the history of emergence in psy- chology and sociology, from the mid-19th century through the mid-20th century. I then demonstrate several parallels between this history and contemporary psy- chology, focusing on two recent psychological movements: socioculturalism and connectionist cognitive science. Placed in historical context, both sociocultural ism and connectionism are seen to be revivals of 19th and early 20th century emergen- tism. I then draw on this history to identify several unresolved issues facing socio- culturalists and connectionists, and to suggest several promising paths for future theory. Copyright @ 2002 S. Karger AG, Base! 1. Introduction Emergentism is a form of materialism which holds that some complex natural phe- nomena cannot be studied using reductionist methods. My first goal in this paper is to identify the historical roots of two emergentist paradigms in contemporary psychology: sociocultural psychology and cognitive science. My second goal is to draw on this histo- ry to explore several unresolved issues facing these contemporary paradigms. Sociocul- tural psychologists are sociological emergentists; they hold that group behavior is consti- KARG E R <92002 S. Karger AG, Basel R. Keith Sawyer, Washington University .OOI8-716X/02/0451-0()()2$18.50/0 Department of Education, Campus Box 1183 Fax+41613061234 St.
    [Show full text]
  • An Analysis of Power and Stress Using Cybernetic Epistemology Randall Robert Lyle Iowa State University
    Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1992 An analysis of power and stress using cybernetic epistemology Randall Robert Lyle Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Educational Psychology Commons, Family, Life Course, and Society Commons, and the Philosophy Commons Recommended Citation Lyle, Randall Robert, "An analysis of power and stress using cybernetic epistemology " (1992). Retrospective Theses and Dissertations. 10131. https://lib.dr.iastate.edu/rtd/10131 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely afreet reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from lefr to right in equal sections with small overlaps.
    [Show full text]
  • The Emergence of Artificial Intelligence in the Home: Products, Services, and Broader
    Western Oregon University Digital Commons@WOU Student Theses, Papers and Projects (Computer Department of Computer Science Science) 3-8-2017 The meE rgence of Artificial Intelligence in the Home: Products, Services, and Broader Developments of Consumer Oriented AI Bingqing Tang [email protected] Follow this and additional works at: https://digitalcommons.wou.edu/ computerscience_studentpubs Part of the Management Information Systems Commons Recommended Citation Tang, Bingqing, "The meE rgence of Artificial Intelligence in the Home: Products, Services, and Broader Developments of Consumer Oriented AI" (2017). Student Theses, Papers and Projects (Computer Science). 6. https://digitalcommons.wou.edu/computerscience_studentpubs/6 This Professional Project is brought to you for free and open access by the Department of Computer Science at Digital Commons@WOU. It has been accepted for inclusion in Student Theses, Papers and Projects (Computer Science) by an authorized administrator of Digital Commons@WOU. For more information, please contact [email protected]. The Emergence of Artificial Intelligence in the Home: Products, Services, and Broader Developments of Consumer Oriented AI Bingqing Tang IS642 MIS Graduate Project Dr. David Olson, Dr. John Leadley & Dr. Scot Morse March 15, 2017 Tang 1 Abstract Current home automation system merges a family's lifestyle with the latest technology & energy management tools to simplify people's lives. It allows users to easily manipulate a variety of home systems, including appliances, security systems, and environmental systems. Setting up a home automation system confuses many consumers. Multiple product lines and platforms make choosing the best system difficult. Basic requirements of setting up a home automations system and the comparison between different platforms are explained.
    [Show full text]
  • Artificial Intelligence: How Does It Work, Why Does It Matter, and What Can We Do About It?
    Artificial intelligence: How does it work, why does it matter, and what can we do about it? STUDY Panel for the Future of Science and Technology EPRS | European Parliamentary Research Service Author: Philip Boucher Scientific Foresight Unit (STOA) PE 641.547 – June 2020 EN Artificial intelligence: How does it work, why does it matter, and what can we do about it? Artificial intelligence (AI) is probably the defining technology of the last decade, and perhaps also the next. The aim of this study is to support meaningful reflection and productive debate about AI by providing accessible information about the full range of current and speculative techniques and their associated impacts, and setting out a wide range of regulatory, technological and societal measures that could be mobilised in response. AUTHOR Philip Boucher, Scientific Foresight Unit (STOA), This study has been drawn up by the Scientific Foresight Unit (STOA), within the Directorate-General for Parliamentary Research Services (EPRS) of the Secretariat of the European Parliament. To contact the publisher, please e-mail [email protected] LINGUISTIC VERSION Original: EN Manuscript completed in June 2020. DISCLAIMER AND COPYRIGHT This document is prepared for, and addressed to, the Members and staff of the European Parliament as background material to assist them in their parliamentary work. The content of the document is the sole responsibility of its author(s) and any opinions expressed herein should not be taken to represent an official position of the Parliament. Reproduction and translation for non-commercial purposes are authorised, provided the source is acknowledged and the European Parliament is given prior notice and sent a copy.
    [Show full text]
  • Adaptation of Elaborated Feedback in E-Learning
    Adaptation of Elaborated Feedback in e-Learning Ekaterina Vasilyeva1,2, Mykola Pechenizkiy2, and Paul De Bra2 1 Department of Computer Science and Information Systems, University of Jyväskylä, P.O. Box 35, 40351 Jyväskylä, Finland 2 Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, 5600MB Eindhoven, the Netherlands {e.vasilyeva,m.pechenizkiy}@tue.nl, [email protected] Abstract. Design of feedback is a critical issue of online assessment develop- ment within Web-based Learning Systems (WBLSs). In our work we demon- strate the possibilities of tailoring the feedback to the students’ learning style (LS), certitude in response and its correctness. We observe in the experimental studies that these factors have a significant influence on the feedback prefer- ences of students and the effectiveness of elaborated feedback (EF), i.e. stu- dents’ performance improvement during the test. These observations helped us to develop a simple EF recommendation approach. Our experimental study shows that (1) many students are eager to follow the recommendations on ne- cessity to read certain EF in the majority of cases; (2) the students more often find the recommended EF to be useful, and (3) the recommended EF helped to answer related questions better. Keywords: feedback authoring, feedback personalization, online assessment. 1 Introduction Online assessment is an important component of modern education. Nowadays it is used not only in e-learning for (self-)evaluation, but also tends to replace or comple- ment traditional methods of formal evaluation of the student’s performance in blended learning. Feedback is usually a significant part of the assessment as students need to be in- formed about the results of their (current and/or overall) performance.
    [Show full text]