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COMPREHENDING NON-LINEARTEXT: The Role of DiscourseCues and Reading StrategiesDavida CharneyDepartment of EnglishThe Pennsylvania State UniversityUniversity Park, PA 16802

ABSTRACTBy studying the structure of written discourse and the processes by which readersacquire information from texts, we have learned a great deal about how to design textsthat facilitate learning. However, recent advances in computer technology have enabledthe development of new forms of text that violate standard assumptions of what texts arelike. These new forms may pose serious problems for learning because they lackdiscourse features that readers rely on for assimilating new information. In particular,readers traditionally rely on the writer to determine the sequence of topics and toemploy conventional cues that signal relationships among topics, such as relativeimportance or chronology. However, on-line hypertext systems present textsnon-linearly, requiring readers to decide what information to read and in what order.This paper assesses the potential impact of non-linear texts on theories of discourse andon current cognitive theories of text processing. It also describes research in progresson readers sequencing strategies in hypertext. Research on the effect of hypertext onreading will have important practical implications for designing hypertext systems thatsatisfy readers needs.

PROBLEMS POSED FOR READERS BY NON-LINEAR TEXTSMost people think of a text as a collection of ideas that a writer has carefullyorganized into a coherent sequence or pattern. Discourse theorists have

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identified a host of stable patterns that writers employ on every level of text,from small units such as sentences and paragraphs, up to grand schemas thatoutline the structure of an entire text, such as a fairy tale, a resume or a policyargument [Ha1176], [Vand79], [Fahn83]. Indeed, as readers, we depend onstructural patterns to help us recognize the type of text we are reading andintegrate its parts. Empirical studies of reading comprehension confirm thatreaders understand and learn from texts more easily when the information isset out in well-defined structures and when the text provides clear signals ofshifts from one part to the next [Vand83], [Kier80], [Fras70]. But apart fromany natural disposition we may have to look for structure in a text, our view oftext as an ordered succession of concepts is strongly reinforced by theconstraints of the standard print medium: texts come to us on printed pagesthat we generally read in order, from the top down and from left to right.

Today, the constraints of the medium are being lifted by developments incomputer technology. Instead of storing texts on-line as large, monolithicblocks, software designers are developing systems that link individual piecesof text together into complex networks. For example, the referenceinformation for users of the text editor EMACS is stored on-line as ahierarchical network of facts that users can access in any order [Conk87]. Inaddition to serving a reference function, networks are also being developed toserve as sophisticated databases, as writing environments, and as instructionalmaterials. Recent examples of such networks include Carnegie-MellonUniversitys ZOG system [Robe791 , Xerox PARCs NoteCards [Hala87], BrownUniversitys INTERMEDIA [Yank85], and Tektronixs Neptune [Deli861 (for ageneral overview, see [Conk87]). These systems give readers much greatercontrol over the information they see and the sequence in which they see it.Instead of reading or skimming through a text from beginning to end, readersuse menus to order up the pieces of text they want .to read onto thecomputer screen. The most interesting systems link together informationfrom a variety of media and sources so the reader can access relateddocuments, graphics, and audio-visual displays at various points in the text.The texts become non-linear hvnertexts: each reader may choose to view adifferent selection of pieces in a different sequence; any given reader maychoose different sequences on different occasions.

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Along with greater control, of course, comes a greater burden for the readers,who must now locate the information they need and relate it to other facts inthe network, often without the aid of traditional structural cues. Mosthypertext designers recognize the problems such networks may present,especially for readers who are unfamiliar with the concepts in the textbase.They report informal evidence that users may be overwhelmed by the choiceamong menu items and by the difficulties of maneuvering through thenetworked text structure. As a result, readers can lose track of where they arein the network (and where they have been), and often read a great deal ofmaterial that is not relevant to their purpose [Yank85], [WhitU], [Trig83].While a fair amount of research is underway on the design andimplementation of hypertext systems, very little research has investigatedhow readers handle such unorthodox texts and how seriously these problemsinterfere with normal reading processes.ISSUES FOR RESEARCHGiven the growing interest in hypertext systems, it is important to assess theimpact of non-linear texts on theories of discourse and on current cognitivetheories of text processing. As in other areas of human-computer interaction,research can inform cognitive theory as well as practical system design.Three research issues appear especially important: (1) What strategies doreaders adopt for sequencing pieces of hypertext (i.e., constructing a paththrough the network)? (2) How do such strategies influence learning (i.e., themental representations readers build of the text)? (3) What strategies canhypertext designers employ to facilitate reading processes?

Readers Sequencing Strategies In HypertextSince little systematic evidence is available about the effects of non-linear texton reading, it is important to assess the seriousness of the absence of discoursecues, especially sequencing conventions. Although we know that presentinginformation in a poor order can impair learning from a text [Barn84], littleresearch has been conducted on how readers themselves choose to sequencethe pieces of a text and whether reader-chosen orders are generally poor.



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The most reasonable prediction is that readers new to the subject domain willhave trouble sequencing the pieces of a text in groupings that reflectmeaningful relationships. This prediction has not yet been tested directly, butit is supported by two kinds of evidence. First, there is empirical evidence thatmath students c lassify word problems by superficial similarities in thewording or the hypothetical problem situation rather than by deeprelationships. Similar strategies have been noted for novice computerprogrammers [Adel8 11. Second, there is anecdotal evidence that inexperiencedreaders of scientific articles and textbooks fail to look at figures or tables whenthey are referred to in the text. These results suggest that when readers aregiven the responsibility of selecting what text to read, they may sequence theinformation poorly or omit important information ahogether.

Other important sequencing questions include:

Information tvne: do readers consistently read certain types ofinformation (e.g., examples), while consistently skipping others (e.g.,definitions, historical background)?Prior knowlege: how does prior knowledge influence a readerssequencing strategy? Are domain experts better than novices atdeciding what to read? Determining when they have read enough?

Mental Representations of HypertextWhile it is important to know how readers construct a path through a hypertextsystem, the heart of the question is not what order they choose, but the effectof the chosen order on what they learn. In particular, how does the chosensequence affect the readers ability to grasp relationships between differentpieces of text, such as relative importance, spatial or chronological ordering,cause and effect, and so on?

A large body of research suggests that readers construct hierarchicalrepresentations of the text they read [Vand83]. Readers are much more likelyto remember general information at the top of the hierarchy than specific,low-level details. Crucially, the mental mechanism that Kintsch and van Dijk

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[Kint78] propose to explain this levels effect turns on the order in whichreaders encounter propositions in the text and the degree to which importantconcepts (i.e., arguments in the propositions) are repeated in successivesentences. Readers incorporate each new proposition in the text into theirinternal, hierarchical textbase by creating networks with chains of repeatedarguments. To the extent that the sentences in the text reuse the samearguments, the text is more coherent and the easier it is to create a mentaltextbase. When no explicit link to previous propositions is available in a localregion of text, readers must either recall earlier propositions from memory orinvent a link through inference processes. The memory advantage for highlevel propositions arises because these propositions are most likely to providelinks throughout the text. The model assumes that links are created betweenpropositions in working memory. Memory for a given proposition improves asthe number of times it cycles through working memory increases.

The advent of hypertext raises a number of interesting issues for this approachto text processing. First, Kintsch and van Dijks processing model [Kint78]assumes that a relatively stable textbase can be derived from a given text. Thisassumption seems to depend on a linear reading of a fixed amount ofinformation. Amost by definition, however, hypertext avoids imposing a fixedorder on information. Conklin [Conk871 distinguishes two types of linksbetween the nodes in a hypertext network: organizational links (which tend tocreate hierarchy) and referential links (which Conklin observes are trulycharacteristic of hypertext). Obviously, hypertexts that fully exploit thepotential of referential links raise interesting problems for the construction ofa textbase. For example, will readers taking different paths through thenetwork emerge with equivalent textbases? Second, some hypertext systemsprovide graphic displays of the information network. These displays may bequite important for helping readers construct a text base: by providingreminders of previous concepts and by providing an explicit guideline for aninternal representation of the network. However, such a guideline may onlybe useful to the extent that the hypertext network itself is strictly hierarchical.



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Hypertext Design: Reinventing Discourse Cues

Assuming that learners have trouble coping with the responsibility ofsequencing their reading, an important research goal will be to design andevaluate methods of adapting discourse cues for non-linear texts. For example,can the listing of menu items serve some of the same functions as sequencecues in standard texts? Will readers follow cues such as cross-references fromone piece of text to another when the referenced piece of text does not followthe current one?

Document designers have relied on the text processing literature to supporttheir recommendations to writers. For example, they tell writers to organizetext hierarchically (e.g., stating general information before specificinformation), to make presuppositions and transitions between sectionsexplicit, to use a small set of often repeated vocabulary items and to introducenew terms only in clause predicates [Felk81], [Kier85]. While theserecommendations have been found to facilitate reading, they may be quitehard to follow for writers of hypertext. How can hypertext writers interpretdocument design recommendations that incorporate notions of precedence orfirst mention?

At this point in the development of hypertext systems, it is not clear where todraw the line between system design decisions and *document design decisions.For example, constraints on the types of links in the network and the sizeand content of nodes are critical for planning the segmentation and labellingof text. However, these constraints may be imposed for a particular hypertextsystem or they may be left up to a given writer working with a flexiblehypertext system. System designers and document designers must thereforework together to define strategies for facilitating reading processes.SEQUENCING STRATEGIES: RESEARCH IN PROGRESSThis section describes a study that addresses some of the issues raised in theprevious section, specifically the issue of topic sequencing. While the study isstill in its initial stages, the design is presented to illustrate one approach tocollecting data for designing optimal hypertext databases and interfaces.


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Participants in this experiment will study on-line information about anunfamiliar software program (v iz., an electronic spreadsheet program). Thetext will be presented in a hypertext network (via Tektronixs Neptunesystem). The experiment will include a training phase and a test phase. In thetraining phase, subjects w ill study the procedures for using the spreadsheetprogram and their sequence of choices from the information network will berecorded. In the test phase, subjects will use the spreadsheet program to solvea series of problems that apply the studied procedures. The test is intended toreveal the effects of the sequencing choices on what subjects learn. The basicmethodology for the study has been used successfully in previous work onskill learning from texts [Rede86), [Char86].

In the training phase, subjects will read about Microsofts Multiplan program.This spreadsheet program involves a number of independent procedures thatusers can combine in various ways to solve problems. For example, someprocedures must be executed in a fixed sequence, some can be applied at thediscretion of the user, and some undo the effect of other procedures. Thisdiversity of procedures requires subjects to acquire a deep understanding ofwhat the procedures are for, as well as how to execute them.

SubjectsVolunteers from the PSU community (undergraduates and/or staff) will bepaid a fee to participate in the study. A questionnaire developed in previousresearch [Char861 will be used to assess previous computer experience. Thismeasure will be used primarily in the statistical analyses, rather than as ascreening device. However, no one who has prior experience with electronicspreadsheets will be allowed to participate.

Design and ProcedureAs described above, the research study will involve a training phase and a testphase. In the training phase, subjects will read the information contained inthe hypertext network. Subjects will be randomly assigned to study thenetwork in one of the following four conditions:



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Pre-Planned Seauencinq: subjects will be presented with a listing ofmenu choices and asked to rank them in the order in which they wouldlike to read them. Subjects will subsequently read the text in the chosenorder.Ounortunistic Seauencinq: subjects will be presented with a listing ofmenu choices and allowed to select and read topics in any order. Thiscondition should reveal the extent to which readers can use informationin one piece o f text as a cue to choosing the next piece.

Random Seauence: subjects will be told to read the topics in a prescribedrandom order (or perhaps in alphabetical order).

Guided Seauence: subjects will be told to read the topics in a prescribedlogical order, based on relationships between the topics. This conditionand the Random Sequence condition are intended to provide base-linesfor evaluating the sequences subjects devise themselves.

This design compares reader-chosen orders to two baselines. Previousexperiments on topic ordering have either enforced a random sequence orvarious guided sequences, but have not systematically compared the effects ofthese orders to those that learners choose for themselves [Bam84], [Maye76].This design tests the prediction that the orders subjects choose will be betterthan random orders, but worse than a logical guided sequence.

The sequence of topics that subjects choose in the Pre-Planned andOpportunistic Sequencing conditions will be recorded and analyzed. It is likelythat subjects with little computer experience will use superficial criteria toorder the topics. For example, they may group together topics that usesemantically related terms in the menu listings, regardless of whether or notthe topics have any actual bearing on each other. In any case, the subjectsorderings will be evaluated by several metrics. For instance, the relatednessof the topics in the network wiIl be judged by independent raters. Theseratings will be used to quantify how often subjects read unrelated topics insuccession.

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In the testing phase, subjects will attempt to solve problems using thespreadsheet that call on the procedures they studied in the training phase.The problems, which will be similar to those employed successfully inprevious research [Char86], will reveal whether subjects learned theprocedures and grasped the relationships between them. For instance,subjects should be able to carry out tasks that involve fixed sequences ofprocedures and they should be able to choose the more appropriate of similarprocedures. Subjects performance will be evaluated in terms of the numberof problems they can solve, how long it takes to solve them and the nature ofthe errors they make along the way. They most important analyses willcompare the performance of subjects in different training conditions. It isexpected that subjects who read topics in more logical sequences (whetherchosen by themselves or the experimenter) will learn more and thereforeperform better in the testing phase.IMPLICATIONS FOR FUTURE RESEARCHNon-linear text presents exciting opportunities for researchers in discourseanalysis, document design and cognitive science, From the practicalperspective, the need for good design is growing as rapidly as the increasinguse of computers for transmitting verbal information. More importantly,however, the electronic medium is shaking our assumptions of what texts areand can be. We can now re-evaluate current theories of discourse and textprocessing. Some of the important long-term questions include: what itmeans in cognitive terms for readers to get lost in networked text: how thepurposes readers bring to the text influence their selection strategies; andwhether different strategies are needed for different types of text.

Since hypertext systems are largely still under development or are just nowentering the marketplace, research on the effect of hypertext on reading willhave important practical implications for designing hypertext systems thatsatisfy readers needs.

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REFERENCES[Adelsl]

[Barn841

[Char861

[Conk871

[Deli861

[Fahn83]

[Felksl]

[Fras70]

[Hala87]

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Adelson, B. Problem solving and the development of abstractcategories in programming languages. Memory and Copnition, 9,422-433, 1981.

Barnard, P., MacLean, A., Hammond, N. User representations ofordered sequences of command operations. Paper delivered atINTERACT 84: the First IFIP Conference on Human-ComputerInteraction, 1984.

Chamey, D., Reder, L. Designing interactive tutorials for computerusers. Human-Comuuter Interaction, 2, 297-3 17, 1986.

Conklin, J. A survey of hypertext (MCC Technical ReportSTP-356-86, Rev. 1). MCC Software Technology Program, Austin, TX,February, 1987.

Delisle, N., Schwartz, M. Neptune: a hypertext system for CADapplications. SIGMOD Record, 15 (2), 132-143, June, 1986.Fahnestock, J., Secor, M. Teaching argument: a theory of types.College Comnosition and Communication, 34, 20-30, 1983.0.Felker, D., Pickering, F., Charrow, V., Holland, V., Redish, J.Guidelines for Document Designers. Washington, DC: AmericanInstitutes for Research, 1981.

Frase, L. The influence of sentence order and amount o f higherlevel text processing upon reproductive and productive memory.American Educational Research Journal, 307-3 19, 1970.

Halasz, F., Moran, R., Trigg, R. NoteCards in a Nutshell, submitted toCHI+GI 1987, Toronto, Canada, April 5-9, 1987.

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[Ha11761 Halliday, M., & Hasan, R. Cohesion in English. London: Longman,1976.

[Kier80] Kieras, D. Abstracting main ideas from technical prose (TechnicalReport 5). University of Arizona, Tucson, 1980.

[Kier85] Kieras, D., Dechert, C. Rules for comprehensible technical prose: asurvey of the psycholinguistic literature (Technical Report 21).University of Michigan, Ann Arbor, 1985.

[Kint78] Kintsch, W., van Dijk, T. Toward a model of text comprehension andproduction. PsvcholoPical Review, 85, 363-394, 1978.

[Maye76] Mayer, R. Some conditions of meaningful learning for computerprogramming: advance organizers and subject control of frameorder. Journal of Educational Psvchologv, 68, 143-150, 1976.

[Rede86] Reder, L., Chamey, D., Morgan, K. The role of elaborations inlearning a skill from an instructional text. Memorv & Cognition, 14,64-78, 1986.

[Robe793 Robertson, G., McCracken, D., Newell, A. The ZOG approach toman-machine communication (Computer Science Technical ReportCMU-CS-79-148). Carnegie-Mellon University, Pittsburgh, PA, Oct.,1979.

[Trig831 Trigg, R. A network-based approach to text handling for the onlinescientific community (Computer Science Technical Report TR- 1346).University of Maryland, November, 1983.

[Vand79] van Dijk, T. Relevance assignment in discourse comprehension.Discourse Processes, 2, 113-126, 1979.

[Vand83] van Dijk, T., Kintsch, W. Strategies of discourse comprehension.New York: Academic Press, 1983.

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[Whit851 Whiteside, J., Jones, S., Levy, P., Wixon, D. User performance withcommand, menu and iconic interfaces. In L. Borman & B. Curtis(Eds.), Human Factors in Computing Svstems: CHI 85 ConferenceProceedings. San Francisco: SIGCHI, April, 1985.

[Yank851 Yankelovich, N., Meyrowitz, N., and van Dam, A. Reading andwriting the electronic book. Computer, 18, 15-30, October, 1985.

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