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Published on September 13, 2007

Author: Sabatini

Source: authorstream.com

Authoring of Adaptive Hypermedia UPB RomaniaCourse 2:  Authoring of Adaptive Hypermedia UPB Romania Course 2 Dr. Alexandra Cristea a.i.cristea@tue.nl http://wwwis.win.tue.nl/~alex/ Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Sensory preferences treatment:  Sensory preferences treatment Adaptive presentations can switch between the following styles: textual (hyper-text) visual (image, diagrams, graphs, video, slideshows) auditory (sounds, streaming audio) kinaesthetic views (animations, simulations, puzzles) Dunn & Dunn model:  Dunn andamp; Dunn model Sensory preferences in AH:  Sensory preferences in AH CS388 (1996) Felder-Silverman learning styles model: global-sequential, visual-verbal, sensing-intuitive, inductive-deductive styles ARTHUR (1999) visual-interactive, auditory-lecture and text styles MANIC (2000) uses a Naïve Bayes Classifier to reason about the learner’s preferences in terms of explanations, examples and graphics iWeaver (2002) Dunn andamp; Dunn model; the application of a Bayesian network is planned to predict and recommend media representations to the learner. Slide7:  Slide8:  Auditory Interface, iWeaver:  Auditory Interface, iWeaver Visual Interface, iWeaver:  Visual Interface, iWeaver Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. FD vs. FI treatment:  FD vs. FI treatment FD learners prefer structures, social content, material relevant to own experience. AH systems respond by providing navigational support tools (CM, path indicator, advanced organizer): adaptive navigation support FD vs. FI treatment:  FD vs. FI treatment FI learners perceive analytically, make concept distinctions, prefer impersonal orientation. AH systems respond with learner control : arbitrary succession of course material. Sometimes: explicit switching between FI andamp; FD. Slide14:  AES-CS (2000) Adaptive Educational System base on cognitive styles http://www.vrc.gr/browse_en/ShowProduct.aspx?id=44 Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Slide16:  CS388 (1996) LSAS: Global or sequential learning style http://www.archives.ecs.soton.ac.uk/users/nb99r/intro_short/frame.htm Slide17:  Felder-Silverman:  Felder-Silverman 44 questions at: http://www.engr.ncsu.edu/learningstyles/ilsweb.html Index of Learning Styles (1991) Richard M. Felder, a chemical engineering professor at North Carolina State University, Barbara A. Soloman, then the coordinator of advising for the N.C. State First-Year College. The four learning style dimensions of the instrument were adapted from a model developed in 1987 by Dr. Felder and Linda K. Silverman, an educational psychologist then at the University of Denver. Slide19:  Slide20:  Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Learning styles & AH:  Learning styles andamp; AH ARTHUR, iWeaver, MANIC, CS388: sensory preferences AEC-ES: field-dependent (FD) independent (FI) LSAS, CS388: global-sequential (Felder-Silverman) Tangow: sensing-intuitive dimension (Felder-Silverman) INSPIRE: Honey and Mumford model etc.. Selected Model:Honey and Mumford model:  Selected Model: Honey and Mumford model Activist I like to have a go and see what happens Reflector I like to gather information and mull things over Theorist I like to tidy up and reach some conclusions Pragmatists I like tried and tested techniques that are relevant to my problems Presentation of MOT user guide to verbalizer :  Presentation of MOT user guide to verbalizer Slide26:  Presentation of MOT user guide to imager:  Presentation of MOT user guide to imager Slide28:  MOT:  MOT pronounced 'moh' like the French word for word My Online Teacher Site: http://wwwis.win.tue.nl/~acristea/mot.html Papers on MOT:  Papers on MOT implementation papers: first (educational) MOT paper (ITCC'03) ; http://wwwis.win.tue.nl/~acristea/HTML/Minerva/papers/ITCC03-cristea-mooij.doc MOT automatic linking paper (ITC'03) http://wwwis.win.tue.nl/~acristea/HTML/Minerva/papers/ITC03-cristea-mooij.doc MOT evaluation papers: URD evaluation (CATE'03) ; http://wwwis.win.tue.nl/~acristea/HTML/Minerva/papers/CATE-cristea-mooij.doc Student evaluations (SAC04, ATL journal ‘04); http://wwwis.win.tue.nl/~acristea/HTML/Minerva/papers/CristeaSAC04CameraReadyLast+2give.doc http://www.actapress.com/onlinejournals/208vol1,%202004/issue_2/208-0805.pdf MOT Download site:  MOT Download site http://wwwis.win.tue.nl/~acristea/HTML/USI/MOT/ LAOS:  LAOS based on AHAM supporting adaptive hypermedia authoring five layers: Domain Model (DM) Goal and constraints Model (GM) User Model (UM) Adaptation Model (AM) Presentation Model (PM) Creation of the LAOS Domain Model:  Creation of the LAOS Domain Model Domain Model in MOT is represented by a list of Domain Maps, called Concept maps Conceptmaps in MOT:  Conceptmaps in MOT each concept map corresponds roughly to a 'book' as is required by the LAOS model these books should describe different topics however, just as in reality, different books may treat a similar topic* * Please note that the current conversion system does not deal with this Steps to MOT system usage::  Steps to MOT system usage: Try-out steps: http://wwwis.win.tue.nl/~acristea/HTML/USI/MOT/help/steps2MOTsystemUsage.txt http://e-learning.dsp.pub.ro/mot/ MOT user guide MOT generalities andamp; installation Slide36:  Domain maps the author’s own maps author username other author’s maps MOT Conceptmap:  MOT Conceptmap Consists of a hierarchy of concepts and their attributes Slide38:  Conceptmap name Current concept attributes of the current concept Concept hierarchy Concept attributes in the Conceptmap:  Concept attributes in the Conceptmap Should contain ONLY domain-related content So: no prerequisites, no pedagogic information Concept attribute creation:  Concept attribute creation Current concept concept attribute Editing an attribute:  Editing an attribute text input window in the left hand panel cutandamp; paste any type of text you wish, including HTML/ XML !! Condition: you are the author of this conceptmap. Slide42:  Adding more attributes Adding children concepts Adding Relatedness relations LAOS:  LAOS based on AHAM supporting adaptive hypermedia authoring five layers: Domain Model (DM) Goal and constraints Model (GM) User Model (UM) Adaptation Model (AM) Presentation Model (PM) Creation of the LAOS Goal and Constraints Model:  Creation of the LAOS Goal and Constraints Model Goal and Constraints Model in MOT is represented by a list of Lesson Maps, called Lessons Lessons in MOT:  Lessons in MOT Lessons are filtered versions of the (domain) Conceptmaps they actually represent an overlay model with pedagogic information Lessons contain prerequisites Lesson contain ordering Lessons contain labels andamp; their respective weights Slide46:  Lessons by the current author Lessons by other authors Slide47:  Ordering of lessons Weights of sublesson Labels of sublesson Slide48:  Group of Sub- lessons Group alternatives Changing sub-lesson order:  Changing sub-lesson order Changing weights & labels for sublessons:  Changing weights andamp; labels for sublessons Note::  Note: The meaning of the weights andamp; labels is fixed in the application you will use, and is as follows: 0: everybody will see contents marked with it 35: visual learners 50: mixed learners 75: verbal learners MOT terms glossary:  MOT terms glossary http://wwwis.win.tue.nl/~acristea/HTML/USI/MOT/help/MOTterms-glossary.txt MOT Glossary extract::  MOT Glossary extract: adaptation assembly language: this language is the basis of adaptive hypermedia adaptation. It consists of IT-THEN constructs. adaptation strategy: adaptation strategies are equivalent to small programs telling the inference engine how to adapt to the student's needs. These strategies are written in MOT-ADAPT, in a special language developed, called adaptation language, or in adaptation assembly language. See adaptation language and adaptation assembly language. adaptation language: the adaptation language is a language for creating adaptation strategies. It borrows some language constructs from other programming languages, but also offers some structure dependent constructs, that use the MOT concept domain hierarchy. See also, for the actual programming constructs and grammar, the document: LAGgrammar.doc MOT Glossary extract::  MOT Glossary extract: adaptation map: all the information about the actual dynamics of the system is contained in the adaptation map. In MOT, the adaptation map is represented by an instantiated adaptation strategy. adaptation model: the adaptation model in MOT is based on the LAOS model. This model is also called the LAG model. The adaptation model is instantiated in the adaptation map. The instantiation takes place by creating adaptation strategies with the help of adaptation language. AM: same as adaptation map. MOT Glossary extract::  MOT Glossary extract: concept: a concept in MOT is built of a collection of attributes. A concept can have sub-concepts, if it is part of a hierarchy (hierarchical relation). A concept can belong to a domain model, a lesson model, a user model and a presentation model. A concept is instantiated in a concept instance. Conceptmap: This is a historical name for the domain map. See domain map. concept map: All the information in MOT is structured in concept maps. These are graph instances with nodes and links between them. Most links in MOT are directional. The most frequently used link type in concept maps in MOT is the hierarchical link type. See also Concept, Conceptmap. MOT Glossary extract::  MOT Glossary extract: domain concept map: same as domain map. domain map: The domain map is a concept map containing all the nodes, links and structures that correspond to the domain model. It is an instantiation of the domain model. Moreover, the domain map in MOT also links to the actual resources of the course. domain model: the domain model in MOT is based on the LAOS model. The domain model in MOT is instantiated in the domain map. See also DefinitionsLAOS.doc for the same item. MOT Glossary extract::  MOT Glossary extract: GM: same as goal and constraints map. goal and constraints model: the LAOS goal and constraints model is represented in MOT by the lesson model, and instantiated in the lesson maps. See also DefinitionsLAOS.doc for the same item. MOT Glossary extract::  MOT Glossary extract: LAG model: this is the 3-layered model of adaptation in LAOS. It is built of adaptation strategies, adaptation language and adaptation assembly language. LAOS model: the LAOS model is the theoretical framework of the MOT system. MOT doesn't implement at present the whole LAOS model. See also DefinitionsLAOS.doc for the same item. MOT Glossary extract::  MOT Glossary extract: lesson: same as lesson map. lesson map: the lesson map is an instantiation of the lesson model. The lesson map in MOT is a concept map containing all the nodes, attributes, links and structures that correspond to the pedagogical model. If the aim is not at education, than it contains goal related information and linking. Relations such as prerequisites appear in the lesson map. The lesson map will in future contain also attributes allowing narrative smoothing. lesson model: the lesson model is a goal and constraints model for educational purposes. It can, however, be streched for extended usage. LM: same as lesson map. MOT Glossary extract::  MOT Glossary extract: MOTadapt: same as MOT-ADAPT. MOT-ADAPT: This is actually a part of MOT, but it was developed later, and therefore has a different name for distinction. It refers only to the authoring of the adaptive strategies, based on adaptation language and adaptation assembly language. MOT: My Online Teacher, pronounced 'moh' like the French word for 'word'. It is an Authoring System for (Educational) Adaptive Hypermedia. It is built in Perl and works with MySQL databases. pedagogic strategy: this is an adaptation strategy with pedagogical purpose. See also adaptation strategy. MOT Glossary extract::  MOT Glossary extract: presentation map: the presentation map is an instantiation of the presentation model. The presentation map contains all the nodes, attributes, links and structures populated with the information that corresponds to the presentation on the screen. Attributes about the color of the background or forground, booleans about if something is presented or not, display dependent attributes are all in this map. MOT's presentation map will soon be available. At the moment, MOT features only two types of presentations: teacher view and student view. presentation model: this model is based on the LAOS model. See also DefinitionsLAOS.doc for the same item. MOT Glossary extract::  MOT Glossary extract: UM: same as user map. user map: the user map is an instantiation of the user model. The presentation map contains all the nodes, attributes, links and structures populated with the information that corresponds to the user. Such information can be user knowledge, preferences, learning style, but also access of different concepts in the domain maps or lesson maps, etc. This feature is not present in the current version of MOT. user model: this model is based on the LAOS model. See also DefinitionsLAOS.doc for the same item.

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