Anais do IHC'2001 - Departamento de Informática e Estatística - UFSC

More documents

Recommendations

Info

236 Anais do IHC’2001 - IV Workshop sobre Fatores Humanos em Sistemas Computacionais change from one stage to another. The path, as in ST, requires a set of representations that are increasingly more linguistic (and inferential) and less visual. This observation also suggests that DCM without RDCM may prevent learners from actually reaching the desired stages of knowledge embedded in learnware. Nevertheless, DCM and RDCM stand out as valuable stages of concept manipulation in the ST interface style. Euler Circles and Punnet Squares The use of images and diagrams as teaching aids is pervasive. In typical classroom situations, they are used as visualizations of specific aspects of contents being taught. Some visualizations can be easily used to elicit the correct responses in exercises and tests, whereas others can be used in cartoon-style sequences to depict different stages of transformations. Some are more concrete, and some more abstract. Some are quite conventional, and others are the products of a teacher’s imagination and talent. Therefore, saying that direct manipulation interfaces are bad for learnware is counter-intuitive. However, “graphics are frequently used in introductory teaching of abstract subjects, but are abandoned by students as they gain proficiency” [Stenning & Inder, 1995, p. 318]. Two examples of how diagrams can be used to support the teaching and learning of different topics illustrate some of the issues DCM and RDCM designers should be prepared to face. Euler Circles are a common graphical representation used in teaching syllogistic reasoning. For instance, the expression “all humans are breast-fed and some animals are not breastfed; therefore some animals are not human” is logically correct, although pragmatically strange (since our knowledge of the world tells us that no one animal is human). If Logic is taught based on a linguistic medium, the learning may be impaired by the interference of such factors as the one just exemplified. However, using circles (proposed by Euler in the XVIII century) can considerably improve learnability. Graphical representations of abstractions relative to quantification are more easily grasped than in the linguistic form (see Figure 4, adapted from Wang et al., 1995). The advantage of the diagram is that common-sense information that inevitably plays a role in linguistic formulation (where predication is interpreted as a cognitive category) is omitted in favor of more salient graphical properties (i.e. intersection and inclusion of circles). Therefore, if the idea is to lead learners to become proficient in interpreting and evaluating expressions such as: ((∀x H(x) → Bf(x)) ∧ (∃y⏐A(y) ∧ ¬ Bf(y))) → (∃y⏐A(y) ∧ ¬ H(y)) the diagrammatic representation is helpful as a mechanism to separate logic predication and propositional calculus from cognitive interpretations of the world and psychologically realistic information processing. Figure 4: Euler Circles representing the expression “all humans are breast-fed and some animals are not breast-fed; therefore some animals are not human” However, diagrammatic reasoning does pose problems. The interpretation of graphical constants is always affected by the emergence of cognizable elements that participate in the
Anais do IHC’2001 - IV Workshop sobre Fatores Humanos em Sistemas Computacionais 237 construction of the diagram [Wang et al., 1995]. A closer examination of Figure 4 might give elements to support the interpretation that some H are A, which is not a valid logic conclusion. An attempt to correct this representation by removing the intersection between circle H and circle A, as shown in Figure 5, would also lead to interpretations that are logically incorrect (i.e. that no A is H). Figure 5: An alternative representation for “all humans are breast-fed and some animals are not breast-fed; therefore some animals are not human” This situation has motivated research in different directions. Wang et al. (1995) have proposed a series of rules and constraints for constructing good diagrammatic representations. Stenning and Inder (1995) and Stenning and Oberlander (1995) have chosen another path and explored modes, media, and expressiveness of representation systems. The latter have proposed a hierarchy of representation systems (minimal abstraction systems, limited abstraction systems, and unlimited abstraction systems) and have provided experimental cognitive evidence that limited abstraction representation systems (LARS), which allow for representing indeterminacy are better as cognitive scaffolding in learning than minimal (MARS) and unlimited abstraction representation systems (UARS). It is interesting to notice that the problem with either Figures 4 or 5 is their excessive degree of (emergent) determination with respect to the relation between H and A. Stenning and Inder (1995) have also analyzed matrices and tables as graphic representations. They have concluded that these kinds of visual aids can only represent data that is fully specified on the dimensions present in the matrix. Partially determined data cannot be represented, for the assignment of data to a cell automatically specifies its value in all of the table’s dimensions. This observation has an interesting consequence for teaching Mendel’s laws of heredity with the use of Punnet Squares (see Figure 6). If we take the Law of Dominance, for example, we can use the Punnet Square to represent the principle that “when crossing parents with pure contrasting heredity traits, the next generation of individuals will exhibit the characteristic of only one of the contrasting traits”. The Punnet Square is a matrix (a table) where the traits of the female and male parents are displayed in the first column and first row. The possibilities of genetic combinations are displayed in the cells of the table, by the concatenation of codes used to represent each heredity trait. Figure 6 shows a Punnet Square for the crossing of two pure types: tall-stem pea (TT) and a short-stem pea (tt). The principle is represented by the fact that all genetic combinations of the offspring are Tt. Observably, this corresponds to the fact that the individuals show the characteristics of trait ‘T’, despite the presence of trait ‘t’ in their chromosomes. T T t Tt Tt t Tt Tt Figure 6: The Punnet Square representing Mendel’s Law of Dominance
Page 1 and 2:
De 15 a 17 de outubro de 2001 Flori
Page 3 and 4:
Sumário Apresentação............
Page 5 and 6:
Análise Ergonômica do Estado da A
Page 7 and 8:
de formidável coesão, denominado
Page 9 and 10:
Sociedade Brasileira de Computaçã
Page 11:
Fund. Educacional de Criciúma - FU
Page 15 and 16:
Palestras Internacionais Online Com
Page 17:
Objetivos: O objetivo deste mini-cu
Page 21 and 22:
Anais do IHC’2001 - IV Workshop s
Page 23 and 24:
Page 25 and 26:
Page 27 and 28:
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
Page 139 and 140:
Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
Page 161 and 162:
Page 163 and 164:
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177 and 178:
Page 179 and 180:
Page 181 and 182:
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
Page 191 and 192:
Page 193 and 194:
Page 195 and 196:
Page 197 and 198:
Page 199 and 200:
Page 201 and 202:
Page 203 and 204:
Page 205 and 206: Anais do IHC’2001 - IV Workshop s
Page 255: Anais do IHC’2001 - IV Workshop s
Page 289: IV Workshop sobre Fatores Humanos e
Page 292 and 293: 272 Anais do IHC’2001 - IV Worksh
Page 294 and 295: 274 4. Considerações Finais Anais
Page 306 and 307:
286 Anais do IHC’2001 - IV Worksh
Page 308 and 309:
Page 310 and 311:
Page 312 and 313:
Page 314 and 315:
Page 316 and 317:
Page 318 and 319:
Page 320 and 321:
Page 322 and 323:
Page 324 and 325:
Page 326 and 327:
Page 328 and 329:
Page 330 and 331:
Page 332 and 333:
Page 334 and 335:
314 Artigos Anais do IHC’2001 - I
show all

Anais do IHC'2001 - Departamento de Informática e Estatística - UFSC

Create successful ePaper yourself

Delete template?

Save as template?