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The Ubiquitous Patterns of Incorrect Answers to Science Questions 257have the same slope. Therefore, this is consistent with the hypothesis thatstudents answer according to the features of the question that capture themost attention. In the case of the crossed lines, the irrelevant dimension ofthe values of the lines captured attention and led many students to theincorrect response.One advantage of the hypothesis that bottom-up attentional allocationcan play a role in incorrect answering patterns is that it can potentially bemeasured and tested independent of student response choices. For example,one can operationally define overt eye gaze (as measured by an eyetracker) as a measure of attention (cf. Rehder & Hoffman, 2005).Specifically, the dimension that results in the first and longest fixationsis considered as the one capturing the most attention (and is the mostsalient). In the example in Figure 6, one would expect, for example, thatattention would be fixed on the intersection of the lines on the secondgraph.Note that the term salience is used in many contexts, and it is importantto use the term consistently. Informally speaking, the salience of a cue ordimension is usually defined as the quality of standing out or being morenoticeable compared to other cooccurring dimensions. Salience is oftenmore formally regarded empirically as a quality of a cue or dimension that,separate from relative predictiveness, affects attention to (e.g., Kim &Cave, 1999; Lamy, Tsal, & Egeth, 2003) and the learning of (e.g.,Edgell et al., 1992; Hall et al., 1977; Kruschke & Johansen, 1999;Trabasso & Bower, 1968) a cue relative to other present cues.Therefore, one may operationally define salience in a number of ways.For example, one may define the salient dimension as the one that attractsthe most attention, as measured by eye tracking.It is also important to keep in mind that the attention to a cue ordimension depends on the context. For example, the relative attention totwo given cues can depend on the presence or absence of other cues; thus,changing the perceptual or conceptual format of the context may changethe relative attention to two cues. Furthermore, attention (or salience)depends on bottom-up mechanisms operating at the level of perceptualfeatures as well as on top-down mechanisms operating at the level ofcognitive strategies, for example, controlling a search task (e.g., Egeth& Yantis, 1997). Therefore, our measures of relative attention to specificdimensions should be regarded as specific to particular questions and tasks.Nonetheless, the mechanism of attention to salient dimensions and itspossible effect on student answering is general.In a number of recent studies on enhancing multimedia learning, eyetracking results have shown that participants are distracted by irrelevantfeatures and tend to look at more relevant areas of diagrams after instruction(Canham & Hegarty, 2010) and at relevant areas of animations if theyare highlighted (Boucheix & Lowe, 2010), or if they are experts (Jarodzka,
258 Andrew F. HecklerScheiter, Gerjets, & Van Gog, 2010). Nonetheless, more studies areneeded that specifically focus on expert and novice attention to relevantand irrelevant features in physics problems known to elicit misconception-likeresponses. That is, the irrelevant features are more than justrandomly distracting. There may be previously learned attention to incorrectdimensions that must eventually be overcome. An example of arelated study is a study on spatial visualization ability and physics problemsolving ability by Kozhevnikov, Motes, and Hegarty (2007) who foundthat students who made ‘‘graph-as-picture’’ misconception-like descriptionstended to look at the axes less than those students who accuratelydescribe kinematics graphs questions; however, the eye tracking data weremore ambiguous about differences between students looking at the linesin the graphs.In sum, salient yet scientifically irrelevant features of a question competefor attention with less salient yet relevant features, and this may playan important role in incorrect student answering patterns. One may beable to observe the potential role of allocation of attention in the answeringof science questions by measuring attention via eye tracking duringthe course of responding to question tasks. Since allocation of attention iscontrolled by both bottom-up and top-down processes, the challenge willbe designing experiments to separate out these two kinds of processes inorder to determine the extent to which automatic attentional mechanismsmay be influencing response choices. Furthermore, there are a number ofmodels of attention and attentional learning that may be applicable tomisconception-like answering and may offer ways to test such models.8. SUMMARY AND GENERAL DISCUSSIONWhy do people often answer simple scientific questions incorrectlyin regular, patterned ways? This simply posed, powerful question is thedriving force behind this chapter. It is one of those simple yet deeplyimportant questions found in science like ‘‘what makes stars shine?’’ or‘‘what causes cancer?’’ It is a question that can lead to a deeper understandingof how people think and learn and how they interact with theworld.While there is general agreement on the existence of patterns ofincorrect answering to science concept questions, there is less agreementabout the causes of such patterns. The phenomenon of answering patternsis certainly not monolithic and likely arises from a number of mechanisms.As discussed in Section 2, a critical issue about incorrect answeringpatterns is that a cause for the patterns must first be assumed in order toidentify a practically relevant pattern, and then it must be based on
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Series EditorBRIAN H. ROSSBeckman I
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Academic Press is an imprint of Els
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viContents3. Science of Multimedia
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xContributorsHenry L. Roediger, III
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xiiPrefaceand there has been much e
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xivPrefaceInterventions for improvi
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26 Henry L. Roediger et al.feedback
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30 Henry L. Roediger et al.of some
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32 Henry L. Roediger et al.Benefit
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34 Henry L. Roediger et al.Hasher,
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36 Henry L. Roediger et al.Son, L.
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38 John Sweller1. INTRODUCTIONCogni
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40 John Sweller‘‘baby-talk.’
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42 John Swellerof cognitive or meta
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44 John SwellerTable 1Natural Infor
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46 John Swellerconfigurations. A ch
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48 John Swellerreproduction results
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50 John Swellerto mutation, without
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52 John Swellerusing a complex or,
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54 John SwellerThe human cognitive
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56 John Swellerepigenetic system ha
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58 John SwellerWe can determine lev
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60 John Swellerthan memorizing the
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62 John SwellerTable 2EffectVariabi
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64 John Swelleroccurs when students
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66 John Sweller3.3.3. The Split-Att
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68 John Swellermerely restates the
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70 John SwellerThe expertise revers
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72 John Swellerobtained a reverse m
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74 John Swelleractivities that othe
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76 John SwellerRenkl, A. (2005). Th
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78 Richard E. Mayercognitive theory
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80 Richard E. Mayerpictures beginni
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82 Richard E. MayerThe dualchannelp
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84 Richard E. Mayerlearner selects
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86 Richard E. MayerRosenthal, Rosno
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88 Richard E. MayerGenerative proce
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90 Richard E. Mayer4.2. Evidence-ba
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92 Richard E. Mayersituation could
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94 Richard E. Mayer(Moreno & Mayer,
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96 Richard E. Mayer4.3.1. Segmentin
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98 Richard E. Mayerpresenting the w
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100 Richard E. MayerThe multimedia
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102 Richard E. Mayergame in industr
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104 Richard E. MayerClark, R. C., &
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106 Richard E. MayerMayer, R. E., &
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108 Richard E. MayerSweller, J. (19
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110 Timothy J. Nokes and Daniel M.
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Incorporating Motivation into a The
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CHAPTERFIVEOn the Interplay of Emot
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Implications for Enhancing Academic
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CHAPTERSIXThere Is Nothing So Pract
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There Is Nothing So Practical as a
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CHAPTERSEVENThe Power of Comparison
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The Power of Comparison in Learning
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Page 242 and 243: CHAPTEREIGHTThe Ubiquitous Patterns
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Page 318 and 319: Index 303LLabor in vain, 28Language
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Index 307WWeb-delivered multimedia
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CONTENTS OF RECENT VOLUMESVolume 40
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Contents of Recent Volumes 311Under
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Contents of Recent Volumes 313Volum
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