The power of feedback.

Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.

Standards for educational and psychological testing

Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user comprehensibility of the results, non-presumption of any canonical data distribution, and insensitivity to the order of input records. We present CLIQUE, a clustering algorithm that satisfies each of these requirements. CLIQUE identifies dense clusters in subspaces of maximum dimensionality. It generates cluster descriptions in the form of DNF expressions that are minimized for ease of comprehension. It produces identical results irrespective of the order in which input records are presented and does not presume any specific mathematical form for data distribution. Through experiments, we show that CLIQUE efficiently finds accurate cluster in large high dimensional datasets.

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Automatic subspace clustering of high dimensional data for data mining applications

What Video Games Have to Teach Us about Learning and Literacy

Conceptual clustering is an important way of summarizing and explaining data. However, the recent formulation of this paradigm has allowed little exploration of conceptual clustering as a means of improving performance. Furthermore, previous work in conceptual clustering has not explicitly dealt with constraints imposed by real world environments. This article presents COBWEB, a conceptual clustering system that organizes data so as to maximize inference ability. Additionally, COBWEB is incremental and computationally economical, and thus can be flexibly applied in a variety of domains.

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Knowledge acquisition via incremental conceptual clustering

Digital Technology is constantly improving as information becomes wireless. These advances demand more wearable and mobile form factors for products that access information. A product that is wearable should have wearability. This paper explores the concept of dynamic wearability, through design research. Wearability is defined as the interaction between the human body and the wearable object. Dynamic wearability extends that definition to include the human body in motion. Our research has been to locate, understand, and define the spaces on the human body where solid and flexible forms can rest-without interfering with fluid human movement. The result is a set of design guidelines embodied in a set of wearable forms. These wearable forms describe the three dimensional spaces on the body best suited for comfortable and unobtrusive wearability by design.

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Design for wearability

We report an experimental study on the effects of diagrams on deductive reasoning with double disjunctions, for example: Raphael is in Tacoma or Julia is in Atlanta, or both. Julia is in Atlanta or Paul is in Philadelphia, or both. What follows?We confirmed that subjects find it difficult to deduce a valid conclusion, such as Julia is in Atlanta, or both Raphael is in Tacoma and Paul is in Philadelphia.In a preliminary study, the format of the premises was either verbal or diagrammatic, and the diagrams used icons to distinguish between inclusive and exclusive disjunctions. The diagrams had no effect on performance. In the main experiment, the diagrams made the alternative possibilities more explicit. The subjects responded faster (about 35 s) and drew many more valid conclusions (nearly 30%) from the diagrams than from the verbal premises. These results corroborate the theory of mental models and have implications for the role of diagrams in reasoning.

How Diagrams Can Improve Reasoning

We already have too much medicine that is (cognitively) good for the 
patient-who will not take it-and medicine that patients fi nd delicious-but that contributes little to their cognitive abilities. (Simon, 
1995, p. 508)There is an enormous chasm between what kids do for fun and what they are 
required to do in school. School covers material we deem “important,” but 
kids, generally speaking, are unimpressed. These same kids, however, are highly 
motivated by what they do for fun (e.g., interactive, entertainment games). 
Imagine these two worlds united. Student engagement is strongly associated 
with academic achievement (e.g., Finn & Rock, 1997; Fredricks, Blumenfeld, 
& Paris, 2004; Fredricks & Eccles, 2006). Thus, combining school material 
with games has tremendous potential to increase learning, especially for lower 
performing, disengaged students.

Melding the Power of Serious Games and Embedded Assessment to Monitor and Foster Learning: Flow and Grow

In this paper we describe WITT, a computational model of categorization and conceptual clustering that has been motivated and guided by research on human categorization. Properties of categories to which humans are sensitive include best or prototypical members, relative contrasts between categories, and polymorphy (neither necessary nor sufficient feature rules). The system uses pairwise feature correlations to determine the “similarity” between objects and clusters of objects, allowing the system a flexible representation scheme that can model common-feature categories and polymorphous categories. This intercorrelation measure is cast in terms of an information-theoretic evaluation function that directs WITT'S search through the space of clusterings. This information-theoretic similarity metric also can be used to explain basic-level and typicality effects that occur in humans. WITT has been tested on both artificial domains and on data from the 1985 World Almanac, and we have examined the effect of various system parameters on the quality of the model's behavior.

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Conceptual Clustering, Categorization, and Polymorphy

This articles introduces the assessment and deployment contexts of the Networking Performance Skill System (NetPASS) project and the articles in this section that report on findings from this endeavor First, the educational context of the Cisco Networking Academy Program is described Second, the basic outline of Evidence Centered Design is described In the third section, the intersection of these two activities in the NetPASS project is described and the subsequent articles introduced

Malcolm Bauer

Papers

Design for wearability

How Diagrams Can Improve Reasoning

Melding the Power of Serious Games and Embedded Assessment to Monitor and Foster Learning: Flow and Grow

Conceptual Clustering, Categorization, and Polymorphy

Introduction to Evidence Centered Design and Lessons Learned From Its Application in a Global E-Learning Program