Mobile TWITTER pros & cons

Pros: 1)  simplistic user interface; 2)  easy to read.   Cons: 1)  limited tweets can be read, older tweets cannot be accessed; 2)  numerous features available in web Twitter are not available in mobile Twitter.   This blog entry also appear in http://mikeyeap.prodigits.co.uk/blog34.htm

 

Mobile Phone is more convenient than Notebook Computer

I arrived early at the client's place today and yesterday.  After switching on my wifi modem, I took out my mobile phone to access the internet.  It was convenient to make good use of this waiting time as I travelled early to avoid massive traffic congestion.  I read news articles, chatted with friends via Yahoo Messenger.  This was definitely more convenient than switching on my notebook computer which was in the car boot.   Mobile phone is light and small, and faster start-up as compared with notebook computer. The main downside of using mobile phone for internet access is the small screen size of mobile device.   This blog entry also appears in http://mikeyeap.prodigits.co.uk/blog33.htm

 

reading Bible on Mobile phone in church

Today, Sunday 28 Nov 2010, is my first time using Biblegateway on my mobile phone in church.  Instead of bringing my physical Bible to church, I brought my wifi modem and mobile phones.   When the Preacher quoted the bible verse, I read it from my mobile phone accessing m.Biblegateway.  I found this to be practical as the font size (which is adjustable) in mobile phone is bigger than font size in my physical Bible. I brought both the touchscreen and touchscreen+keyboard. I found keyboard to be useful and fast for entering bible verse to be searched.   This blog entry also appears in http://mikeyeap.prodigits.co.uk/blog32.htm   Future:  Will use mobile phone (accessing m.Biblegateway) instead of physical Bible in church and HF.   P.S. I haven't been to church for a long time. 2 signals that I should start to go to church again. a) Preacher today preached well using story-telling method. He drew my total attention throughout his sermon. (Downside: He quoted little from the Bible, only 2 verses.) b) Suny (in black outfit) was playing keyboard. (Still like the colors white-gray-black??)

 

20101127 - Conceptual/Theoretical Framework (wikipedia)

Conceptual Framework Comments: also known as Theoretical Framework. A conceptual framework is used in research to outline possible courses of action or to present a preferred approach to an idea or thought. For example, the philosopher Isaiah Berlin used the "hedgehogs" versus "foxes" approach;[1] a "hedgehog" might approach the world in terms of a single organizing principle; a "fox" might pursue multiple conflicting goals simultaneously. Alternatively, an empiricist might approach a subject by direct examination, whereas an intuitionist might simply intuit what's next.[2] Conceptual frameworks (theoretical frameworks) are a type of intermediate theory that attempt to connect to all aspects of inquiry (e.g., problem definition, purpose, literature review, methodology, data collection and analysis). Conceptual frameworks can act like maps that give coherence to empirical inquiry. Because conceptual frameworks are potentially so close to empirical inquiry, they take different forms depending upon the research question or problem. Several types of conceptual frameworks have been identified,[3][4] such as Working hypothesis Descriptive categories Practical ideal types Models of operations research Formal hypotheses These are linked to particular research purposes such as:[5] Exploration or Exploratory research Description or Descriptive research Gauging Decision making Explanation Prediction Proponents claim that when purpose and framework are aligned, other aspects of empirical research such as methodological choices and statistical techniques become simpler to identify. Source: http://en.wikipedia.org/wiki/Conceptual_framework Conceptual System A conceptual system is a system that is composed of non-physical objects, i.e. ideas or concepts. In this context a system is taken to mean "an interrelated, interworking set of objects". Overview A conceptual system is simply a conceptual model. There are no limitations on this kind of model whatsoever except those of human imagination. If there is an experimentally verified correspondence between a conceptual system and a physical system then that conceptual system models the physical system. "values, ideas, and beliefs that make up every persons view of the world": that is a model of the world; a conceptual system that is a model of a physical system (the world). The person who has that model is a physical system. In psychology and social work, when they talk about a conceptual system, they are referring to some person's model of the world, but if they try to understand that model, they end up making a model of that model, which is just a model of the person's behavior. In any case, this is exactly the purpose of the general term "conceptual systems". Examples Examples of conceptual systems are: Entity-relationship model Object-oriented programming: allows conceptual systems to be defined in a robust manner. Metalogic Unified Modeling Language Related topics Concept Main article: Concept A concept is an abstract idea or a mental symbol, typically associated with a corresponding representation in and language or symbology, that denotes all of the objects in a given category or class of entities, interactions, phenomena, or relationships between them. Concepts are abstract in that they omit the differences of the things in their extension, treating them as if they were identical. They are universal in that they apply equally to every thing in their extension. Concepts are also the basic elements of propositions, much the same way a word is the basic semantic element of a sentence. Unlike perceptions, which are particular images of individual objects, concepts cannot be visualized. Because they are not, themselves, individual perceptions, concepts are discursive and result from reason. They can only be thought about, or designated, by means of a name. Words are not concepts. Words are signs for concepts. Conceptual schema Main article: Conceptual schema A conceptual model is a representation of some phenomenon, data or theory by logical and mathematical objects such as functions, relations, tables, stochastic processes, formulas, axiom systems, rules of inference etc. A conceptual model has an ontology, that is the set of expressions in the model which are intended to denote some aspect of the modeled object. Here we are deliberately vague as to how expressions are constructed in a model and particularly what the logical structure of formulas in a model actually is. In fact, we have made no assumption that models are encoded in any formal logical system at all, although we briefly address this issue below. Moreover, the definition given here is oblivious about whether two expressions really should denote the same thing. Note that this notion of ontology is different from (and weaker than) ontology as is sometimes understood in philosophy; in our sense there is no claim that the expressions actually denote anything which exists physically or spatio-temporally (to use W. Quine's formulation). For example, a stochastic model of stock prices includes in its ontology a sample space, random variables, the mean and variance of stock prices, various regression coefficients etc. Models of quantum mechanics in which pure states are represented as unit vectors in a Hilbert space include in their ontologies observables, dynamics, measurement operators etc. It is possible that observables and states of quantum mechanics are as physically real as the electrons they model, but by adopting this purely formal notion of ontology we avoid altogether this question. Conceptual framework Main article: Conceptual framework A conceptual framework is used in research to outline possible courses of action or to present a preferred approach to a system analysis project. The framework is built from a set of concepts linked to a planned or existing system of methods, behaviors, functions, relationships, and objects. A conceptual framework might, in computing terms, be thought of as a relational model. For example a conceptual framework of accounting "seeks to identify the nature, subject, purpose and broad content of general-purpose financial reporting and the qualitative characteristics that financial information should possess".[1] Source: http://en.wikipedia.org/wiki/Conceptual_system Concept Map A concept map is a diagram showing the relationships among concepts. They are graphical tools for organizing and representing knowledge. Concepts, usually represented as boxes or circles, are connected with labeled arrows in a downward-branching hierarchical structure. The relationship between concepts can be articulated in linking phrases such as "gives rise to", "results in", "is required by," or "contributes to".[1] The technique for visualizing these relationships among different concepts is called "Concept mapping". An industry standard that implements formal rules for designing at least a subset of such diagrams is the Unified Modeling Language (UML). Overview A concept map is a way of representing relationships between ideas, images or words, in the same way that a sentence diagram represents the grammar of a sentence, a road map represents the locations of highways and towns, and a circuit diagram represents the workings of an electrical appliance. In a concept map, each word or phrase is connected to another and linked back to the original idea, word or phrase. Concept maps are a way to develop logical thinking and study skills, by revealing connections and helping students see how individual ideas form a larger whole.[2] Concept maps were developed to enhance meaningful learning in the sciences. A well-made concept map grows within a context frame defined by an explicit "focus question," while a mind map often has only branches radiating out from a central picture. There is research evidence that knowledge is stored in the brain in the form of productions (situation-response conditionals) that act on declarative memory content which is also referred to as chunks or propositions [3][4]. Because concept maps are constructed to reflect organization of the declarative memory system, they facilitate sense-making and meaningful learning on the part of individuals who make concept maps and those who use them. Concept mapping versus topic maps and mind mapping Concept maps are rather similar to topic maps (in that both allow to connect concepts or topics via graphs), while both can be contrasted with the similar idea of mind mapping, which is often restricted to radial hierarchies and tree structures. Among the various schema and techniques for visualizing ideas, processes, organizations, concept mapping, as developed by Joseph Novak is unique in philosophical basis, which "makes concepts, and propositions composed of concepts, the central elements in the structure of knowledge and construction of meaning."[5] Another contrast between Concept mapping and Mind mapping is the speed and spontaneity when a Mind map is created. A Mind map reflects what you think about a single topic, which can focus group brainstorming. A Concept map can be a map, a system view, of a real (abstract) system or set of concepts. Concept maps are more free form, as multiple hubs and clusters can be created, unlike mind maps which fix on a single conceptual center. History The technique of concept mapping was developed by Joseph D. Novak[6] and his research team at Cornell University in the 1970s as a means of representing the emerging science knowledge of students. It has subsequently been used as a tool to increase meaningful learning in the sciences and other subjects as well as to represent the expert knowledge of individuals and teams in education, government and business. Concept maps have their origin in the learning movement called constructivism. In particular, constructivists hold that learners actively construct knowledge. Novak's work is based on the cognitive theories of David Ausubel (assimilation theory), who stressed the importance of prior knowledge in being able to learn new concepts: "The most important single factor influencing learning is what the learner already knows. Ascertain this and teach accordingly."[7] Novak taught students as young as six years old to make concept maps to represent their response to focus questions such as "What is water?" "What causes the seasons?" In his book Learning How to Learn, Novak states that "meaningful learning involves the assimilation of new concepts and propositions into existing cognitive structures." Various attempts have been made to conceptualize the process of creating concept maps. Ray McAleese, in a series of articles, has suggested that mapping is a process of off-loading. In this 1998 paper, McAleese draws on the work of Sowa and a paper by Sweller & Chandler. In essence, McAleese suggests that the process of making knowledge explicit, using nodes and relationships, allows the individual to become aware of what they know and as a result to be able to modify what they know.[8] Maria Birbili applies that same idea to helping young children learn to think about what they know.[9]The concept of the Knowledge Arena is suggestive of a virtual space where learners etc. may explore what they know and what they do not know. Use Concept maps are used to stimulate the generation of ideas, and are believed to aid creativity. For example, concept mapping is sometimes used for brain-storming. Although they are often personalized and idiosyncratic, concept maps can be used to communicate complex ideas. Formalized concept maps are used in software design, where a common usage is Unified Modeling Language diagramming amongst similar conventions and development methodologies. Concept mapping can also be seen as a first step in ontology-building, and can also be used flexibly to represent formal argument. Concept maps are widely used in education and business for: Note taking and summarizing key concepts, their relationships and hierarchy from documents and source materials New knowledge creation: e.g., transforming tacit knowledge into an organizational resource, mapping team knowledge Institutional knowledge preservation (retention), e.g., eliciting and mapping expert knowledge of employees prior to retirement Collaborative knowledge modeling and the transfer of expert knowledge Facilitating the creation of shared vision and shared understanding within a team or organization Instructional design: concept maps used as Ausubelian "advance organizers" which provide an initial conceptual frame for subsequent information and learning. Training: concept maps used as Ausubelian "advanced organizers" to represent the training context and its relationship to their jobs, to the organization's strategic objectives, to training goals. Increasing meaningful learning Communicating complex ideas and arguments Examining the symmetry of complex ideas and arguments and associated terminology Detailing the entire structure of an idea, train of thought, or line of argument (with the specific goal of exposing faults, errors, or gaps in one's own reasoning) for the scrutiny of others. Enhancing metacognition (learning to learn, and thinking about knowledge) Improving language ability Knowledge Elicitation Assessing learner understanding of learning objectives, concepts, and the relationship among those concepts Source: http://en.wikipedia.org/wiki/Concept_mapping Conceptual Schema A conceptual schema or conceptual data model is a map of concepts and their relationships. This describes the semantics of an organization and represents a series of assertions about its nature. Specifically, it describes the things of significance to an organization (entity classes), about which it is inclined to collect information, and characteristics of (attributes) and associations between pairs of those things of significance (relationships). Overview Because a conceptual schema represents the semantics of an organization, and not a database design, it may exist on various levels of abstraction. The original ANSI four-schema architecture began with the set of external schemas that each represent one person's view of the world around him or her. These are consolidated into a single conceptual schema that is the superset of all of those external views. A data model can be as concrete as each person's perspective, but this tends to make it inflexible. If that person's world changes, the model must change. Conceptual data models take a more abstract perspective, identifying the fundamental things, of which the things an individual deals with are just examples. The model does allow for what is called inheritance in object oriented terms. The set of instances of an entity class may be subdivided into entity classes in their own right. Thus, each instance of a sub-type entity class is also an instance of the entity class's super-type. Each instance of the super-type entity class, then is also an instance of one of the sub-type entity classes. Super-type/sub-type relationships may be exclusive or not. A methodology may require that each instance of a super-type may only be an instance of one sub-type. Similarly, a super-type/sub-type relationship may be exhaustive or not. It is exhaustive if the methodology requires that each instance of a super-type must be an instance of a sub-type. Example relationships Each PERSON may be the vendor in one or more ORDERS. Each ORDER must be from one and only one PERSON. PERSON is a sub-type of PARTY. (Meaning that every instance of PERSON is also an instance of PARTY.) Each Employee may have the supervisor within Employee. Data structure diagram A data structure diagram (DSD) is a data model or diagram used to describe conceptual data models by providing graphical notations which document entities and their relationships, and the constraints that binds them. Source: http://en.wikipedia.org/wiki/Conceptual_schema Conceptual Model In the most general sense, a model is anything used in any way to represent anything else. Some models are physical objects, for instance, a toy model which may be assembled, and may even be made to work like the object it represents. However a conceptual model, may only be drawn on paper, described in words, or imagined in the mind. They are used to help us know and understand the subject matter they represent. Type and scope of conceptual models Conceptual models range in type from the more concrete, such as the mental image of a familiar physical object, to the formal generality and abstractness of mathematical models which do not appear to the mind as an image. Conceptual models also range in terms of the scope of the subject matter that they are taken to represent. A model may, for instance, represent a single thing (e.g. the Statue of Liberty), whole classes of things (e.g. the electron), and even very vast domains of subject matter such as the physical universe. The variety and scope of conceptual models is due to the variety of purposes had by the people using them. Metaphysical models A metaphysical model is a type of conceptual model which is distinguished from other conceptual models by its proposed scope. A metaphysical model intends to represent reality in the broadest possible way. This is to say that it explains the answers to fundamental questions such as whether matter and mind are one or two substances; or whether or not humans have free will. Epistemological models An epistemological model is a type of conceptual model whose proposed scope is the known and the knowable. Ethical models Logical models In logic, a model is a type of interpretation under which a particular statement is true. Logical models can be broadly divided into ones which only attempt to represent concepts, such as mathematical models; and ones which attempt to represent physical objects, and factual relationships, among which are scientific models. Mathematical models Main article: Mathematical model Mathematical models can take many forms, including but not limited to dynamical systems, statistical models, differential equations, or game theoretic models. These and other types of models can overlap, with a given model involving a variety of abstract structures. Scientific models Main article: Scientific model A scientific model is a simplified abstract view of the complex reality. A scientific model represents empirical objects, phenomena, and physical processes in a logical way. Attempts to formalize the principles of the empirical sciences, use an interpretation to model reality, in the same way logicians axiomatize the principles of logic. The aim of these attempts is to construct a formal system for which reality is the only interpretation. The world is an interpretation (or model) of these sciences, only insofar as these sciences are true.[1] Data models Domain Models A domain model is a type of conceptual model used to depict the structural elements and their conceptual constraints within a domain of interest (sometimes called the problem domain). A domain model includes the various entities, their attributes and relationships, plus the constraints governing the conceptual integrity of the structural model elements comprising that problem domain. A domain model may also include a number of conceptual views, where each view is pertinent to a particular subject area of the domain or to a particular subset of the domain model which is of interest to a stakeholder of the domain model. Social and political models Economic models Main article: Economic model In economics, a model is a theoretical construct that represents economic processes by a set of variables and a set of logical and/or quantitative relationships between them. The economic model is a simplified framework designed to illustrate complex processes, often but not always using mathematical techniques. Frequently, economic models use structural parameters. Structural parameters are underlying parameters in a model or class of models.[1] A model may have various parameters and those parameters may change to create various properties. Source: http://en.wikipedia.org/wiki/Model_(abstract)

Usability Framework (Shackel)

Human factors for informatics usability By Brian Shackel, Simon J. Richardson Chapter 2 Usability - Context, Framework, Definition, Design and Evaluation Brian Shackel http://books.google.com.my/books?hl=en&lr=&id=KSHrPgLlMJIC&oi=fnd&pg=PA21&dq=usability+framework&ots=ITWmRUSVB9&sig=5q50cAypuH-8I1LN4KPWtRRIoEs#v=onepage&q=usability%20framework&f=false

20101127 - concepts & defintions of Evaluation research (Stern)

2. Can evaluation be defined?   Stern, E. (2004).  Philosophies and types of evaluation research.  In Descy, P.; Tessaring, M. (eds), The foundations of evaluation and impact research.   There are numerous definitions and types of evaluation. There are, for example, many definitions of evaluation put forward in handbooks, evaluation guidelines and administrative procedures, by bodies that commission and use evaluation. All of these definitions draw selectively on a wider debate as to the scope and focus of evaluation. A recent book identifies 22 foundation models for 21st century programme evaluation (Stufflebeam, 2000a), although the authors suggest that a smaller subset of nine are the strongest. Rather than begin with types and models, this chapter begins with an attempt to review and bring together the main ideas and orientations that underpin evaluation thinking.   Indicating potential problems with 'definition' by a question mark in the title of this section warns the reader not to expect straightforward or consistent statements. Evaluation has grown up through different historical periods in different policy environments, with inputs from many disciplines and methodologies, from diverse value positions and rooted in hard fought debates in philosophy of science and theories of knowledge.   While there is some agreement, there is also persistent difference: evaluation is contested terrain. Most of these sources are from North America where evaluation has been established – as a discipline and practice – and debated for 30 or more years.   2.1. Assessing or explaining outcomes   Among the most frequently quoted definitions is that of Scriven who has produced an evaluation Thesaurus, his own extensive handbook of evaluation terminology: '"evaluation" refers to the process of determining the merit, worth or value of something, or the product of that process […]  The evaluation process normally involves some identification of relevant standards or merit, worth or value; some investigation of the performance of evaluands on these standards; and some integration or synthesis of the results to achieve an overall evaluation or set of associated evaluations.' (Scriven, 1991; p. 139).   This definition prepares the way for what has been called 'the logic of evaluation' (Scriven, 1991; Fournier, 1995). This logic is expressed in a sequence of four stages: (a) establishing evaluation criteria and related dimensions; (b) constructing standards of performance in relation to these criteria and dimensions; (c) measuring performance in practice; (d) reaching a conclusion about the worth of the object in question.   This logic is not without its critics (e.g. Schwandt, 1997) especially among those of a naturalistic or constructivist turn who cast doubt on the claims of evaluators to know, to judge and ultimately to control. Other stakeholders, it is argued, have a role and this changed relationship with stakeholders is discussed further below.   The most popular textbook definition of evaluation can be found in Rossi et. al.'s book Evaluation – a systematic approach: 'Program evaluation is the use of social research procedures to systematically investigate the effectiveness of social intervention programs. More specifically, evaluation researchers (evaluators) use social research methods to study, appraise, and help improve social programmes in all their important aspects, including the diagnosis of the social problems they address, their conceptualization and design, their implementation and administration, their outcomes, and their efficiency.' (Rossi et al., 1999; p. 4).   Using words such as effectiveness rather than Scriven's favoured 'merit worth or value' begins to shift the perspective of this definition towards the explanation of outcomes and impacts. This is partly because Rossi and his colleagues identify helping improve social programmes as one of the purposes of evaluation. Once there is an intention to make programmes more effective, the need to explain how they work becomes more important.   Yet, explanation is an important and intentionally absent element in Scriven's definitions of evaluation: 'By contrast with evaluation, which identifies the value of something, explanation involves answering a Why or How question about it or a call for some other type of understanding. Often, explanation involves identifying the cause of a phenomenon, rather than its effects (which is a major part of evaluation). When it is possible, without jeopardizing the main goals of an evaluation, a good evaluation design tries to uncover microexplanations (e.g. by identifying those components of the curriculum package that are producing the major part of the good or bad effects, and/or those that are having little effect). The first priority, however, is to resolve the evaluation issues (is the package any good at all, the best available? etc.). Too often the research orientation and training of evaluators leads them to do a poor job on evaluation because they became interested in explanation.' (Scriven, 1991, p. 158).   Scriven himself recognises that one pressure moving evaluation to pay greater attention to explanation is the emergence of programme theory, with its concern about how programmes operate so that they can be improved or better implemented. A parallel pressure comes from the uptake of impact assessment associated with the growth of performance management and other managerial reforms within public sector administrations.   The intellectual basis for this work was most consistently elaborated by Wholey and colleagues. They start from the position that evaluation should be concerned with the efficiency and effectiveness of the way governments deliver public services. A core concept within this approach is what is called 'evaluability assessment' (Wholey, 1981). The starting point for this assessment is a critical review of the logic of programmes and the assumptions that underpin them. This work constitutes the foundation for most of the thinking about programme theory and logical frameworks. It also prefigures a later generation of evaluation thinking rooted more in policy analysis that is concerned with the institutionalisation of evaluation within public agencies (Boyle and Lemaire, 1999), as discussed further below.   These management reforms generally link interventions with outcomes. As Rossi et al. recognise, this takes us to the heart of broader debates in the social sciences about causality: 'The problem of establishing a program's impact is identical to the problem of establishing that the program is a cause of some specified effect. Hence, establishing impact essentially amounts to establishing causality.' (Rossi et al., 1999).   The difficulties of establishing perfect, rather than good enough, impact assessments are recognised by Rossi and colleagues. This takes us into the territory of experimentation and causal inference associated with some of the most influential founders of North American evaluations such as Campbell, with his interest in experimental and quasi-experimental designs, but also his interest in later years in the explanatory potential of qualitative evaluation methods.   The debate about experimentation and causality in evaluation continues to be vigorously pursued in various guises. For example, in a recent authoritative text on experimentation and causal inference, (Shadish et al., 2002) the authors begin to take on board contemporary criticisms of experimental methods that have come from the philosophy of science and the social sciences more generally. In recent years, we have also seen a sustained realist critique on experimental methods led in Europe by Pawson and Tilley (1997). But, whatever their orientations to experimentation and causal inference, explanations remain at the heart of the concerns of an important constituency within evaluation.   2.2. Evaluation, change and values   Another important strand in evaluation thinking concerns the relationship between evaluation and action or change. One comparison is between 'summative' and 'formative' evaluation methods, terms also coined by Scriven. The former assesses or judges results and the latter seeks to influence or promote change.   Various authors have contributed to an understanding of the role of evaluation and change. For example, Cronbach (1982, 1989) rooted in policy analysis and education, sees an important if limited role for evaluation in shaping policy 'at the margins' through 'piecemeal adaptations'. The role of evaluation in Cronbach's framework is to inform policies and programmes through the generation of knowledge that feeds into the 'policy shaping community' of experts, administrators and policy-makers.   Stake (1996) on the other hand, with his notion of 'responsive evaluation', sees this as a 'service' to programme stakeholders and to participants. By working with those who are directly involved in a programme, Stake sees the evaluator as supporting their participation and possibilities for initiating change. This contrasts with Cronbach's position and even more strongly with that of Wholey (referred to earlier) given Stake's scepticism about the possibilities of change at the level of large scale national (or in the US context Federal and State) programmes and their management.   Similarly, Patton, (1997 and earlier editions) who has tended to eschew work at programme and national level, shares with Stake a commitment to working with stakeholders and (local) users. His concern is for 'intended use by intended users'.   Virtually everyone in the field recognises the political and value basis of much evaluation activity, albeit in different ways. While Stake, Cronbach and Wholey may recognise the importance of values within evaluation, the values that they recognise are variously those of stakeholders, participants and programme managers.   There is another strand within the general orientation towards evaluation and change which is decidedly normative. This category includes House, with his emphasis on evaluation for social justice and the emancipatory logic of Fetterman et al. (1996) and 'empowerment evaluation'. Within the view of Fetterman and his colleagues, evaluation itself is not undertaken by external experts but rather is a self-help activity in which – because people empower themselves – the role of any external input is to support self-help.   So, one of the main differences among those evaluators who explicitly address issues of programme and societal change is in terms of the role of evaluators, be they experts who act, facilitators and advocates, or enablers of self help.     Source:  http://www.cedefop.europa.eu/EN/Files/BgR1_Stern.pdf   Comments:  Boring. Reading thru all these concepts and definitions on Evaluation Research.