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Stephen
W. Harmon, Ed.D. Technological innovation has necessarily kept pace with the expansion of readily accessible information. To be sure, the information explosion is directly attributable in large part to technological innovation. New technologies allow us to deal with more massive and disparate sources of information than ever before, and to do so more easily than we were able to deal with much smaller, more localized information just a few years ago. When microcomputers first became popular, almost everyone who owned one was a computer programmer; users almost had to be programmers in those days. But as time went on and computers became easier to use, they became more complicated to program. The number of amateur computer programmers dropped correspondingly. This decrease continued until the advent of object-oriented, natural language authoring systems in the late 1980's. Almost overnight, virtually anyone who had access to a microcomputer and wanted to create computer programs could - and many of them did. However, it is this very ease of programming that may be leading educators into trouble. The number of new computer programs available, particularly educational programs, has increased dramatically over the last five years. Since most software authors want their programs to be in the vanguard of educational theory and since one of the first widely distributed authoring systems dealt with an exciting new concept in cognitive theory, most of these new authors began making what they said were cutting edge programs. If you have followed computer-based education over the last few years you must be aware by now that it is hypermedia of which we speak. The promise of these hypermedia authoring systems was that "any expert on any subject should be able to produce . . . attractive, accessible, and powerful instructional applications with a moderate investment of time and energy" (Morariu, 1988, p. 17) With the advent of HyperCard in 1987 and Apple Computer Inc.'s decision to bundle it free with every new Macintosh computer they sold, the hypermedia bandwagon was off and rolling. What few people realized was that it was rolling down a pretty steep hill. Today, it is in some danger of rolling out of control. Hypermedia is a combination of text, sound, still pictures, graphics, and motion video arranged non-linearly in linked nodes so that a user can go directly from one node to any other. It should not be confused with multimedia, which combines text, sound, still pictures, graphics, and motion video but is unconcerned with the way nodes are linked together (Reeves & Harmon, 1991; Halasz & Conklin, 1989). What makes the concept of hypermedia exciting for educators is that it closely models semantic network theory (Jo nassen, 1989). Semantic network theory holds that people store information in linked web-like node structures (Anderson, 1973). People create networks by relating different nodes of information to each other in what becomes a meaningful way for them . For one person a node for the color green might be linked to nodes for grass, money, elves, and men from Mars. For another person green might be linked to eggs and ham, cheese, and a golf tournament. Cognitive psychologists and educational researchers believe that the best way to help learners acquire new knowledge is to present the knowledge in structures that the learner can easily relate to existing network within his or her own memory (Jonassen, 1989). As Dede and Palumbo (1991, p. 16) put it, "our adeptness in quickly storing and retrieving large amounts of information seems to stem from this property of associativity." So it is no wonder that developers of computer programs systems have embraced hypermedia wholeheartedly. In fact, development of hyperme dia systems has far outstripped research on them (Heller, 1990; Jonassen & Grabinger, 1990; Tsai, 1988). Most developers assume that because hypermedia ought to be good for instruction it is good for instruction. Those of us who have been involved in educational research for any length of time recognize this as a potentially dangerous assumption, just as surely as we recognize that common sense is neither. As Heller (1990, p. 436), so ably points out, "the problem areas within hypermedia and HAI [hypermedia-assisted instruction] are well documented but there needs to be more research done on how one comes to understand the extent and interconnections of the material represented in a hypermedia system." One method of arriving at some understanding of the innate instructional ability of hypermedia systems is to examine the ways in which learners actually use them. This study looks at how learners used a hypermedia system to form semantic associations among nodes of information that were not formally linked by the system designers in advance. Hypermedia proponents assume that learners will form semantic networks similar to those formed by experts, and many of today's educational hypermedia systems are based on this assumption (Fischer & Mandl, 1990). This study begins to examine the validity of that assumption. Methodology The s ubjects were asked to spend one hour browsing the system and constructing links between the topics in any way that made sense to them. In addition to having the subjects browse the hypermedia system and construct links, we asked questions occasionally about the reasoning behind a linkage. This data was collected to help determine the types of links they were constructing. In addition, subjects completed a pre-treatment survey, a post-treatment questionnaire and a post-treatment individual differences measurement test. Subjects Subjects were recruited by asking students in the two classes to volunteer to participate in a study of "Hypermedia and Learning". Initially, everyone in the two classes signed up, but due to scheduling conflicts, only 24 actually completed the study. Instrumentation The main screen (card) of the hypermedia system displayed the 25 available nodes as icons. The icons were purposefully presented as separate entities scattered on the screen in no pre-defined order. To view a node a subject simply clicked on the appropriate icon. Each node presented one card of information with options for viewing related video-clips or occasionally for getting more detailed information. Each node card also included a button for returning to the main system screen. ( Figure 1 ) The hypermedia system also included a very simple to use mechanism for setting up links between related nodes. Buttons for setting up the link appeared on the bottom of the main screen. The subject simply pressed the "link to " button followed by the icon for the first node to be linked. Next he or she pressed the icon for the second topic to be linked and pressed a second button to confirm the link. As each link was constructed, a line showing the link between the two node icons appeared on the main screen. The system was constr ucted in this manner, so that subjects could quickly alternate between browsing and linking and also keep track of the links they had established. (Figure 2 ) The hypermedia system was designed to record all the links that each subject made to ensure that complete, accurate data was available for analysis. Pre-treatment Survey Post-treatment Interview 1. What was your strategy for going through the system? Interaction Procedure When an hour had passed, the subject was told that time was up and was interviewed. The researcher recorded the subject's oral answers to the post-treatment questions, thanked him/her for participating, and finally gave a brief synops is of the purpose of the study. After the subject left, the researcher chose an option from the system to save a list of links that the subject had created. Results Statistics were also compiled for links by node. For the 25 different nodes combined,a mean number of 39.8 total links were created by participants, with a standard deviation of 13.99. Each node had a mean of 13.44 different links established, with a standard deviation of 3.94. Each node had a mean number of 3.8 instances in which it was not linked at all, with a standard deviation of 2.93. Table 1 presents the means and standard deviations obtained in the study. |
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| Category |
Mean
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Std. Dev.
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| Total Links per subject |
.20.7
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11.82
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| Total Links for All Nodes |
39.8
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13.99
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| Total Links per Individual Node |
.13.44
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3.94
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| Instances Where Nodes Were Left Unlinked per Node |
3.8
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2.93
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Table 1 Means and Standard Deviations of Links by Subjects
and Nodes Node Total # Links Links to Different Nodes Instances of No Links to Any Node
More interesting themes emerged from the qualitative analysis of the interview and verbal report data. Eight different types of links were identified by the subjects. This sort of emic (subject generated) categorization is of particular interest since as Franz Boas remarks "If it is our serious purpose to understand the thoughts of a people the whole analysis of experience must be based on their concepts, not ours" (Boas, 1943, p. 314). In each case the term used here to describe the type of link was used by at least one subject. In many of the instances subjects used different but equivalent expressions to identify a particular type of link. We have chosen the words we feel best describe the types of links subjects made and have occasionally changed case of the words used as links types in order to maintain consistency. To increase inter-rater reliability, each investigator coded links separately, before combining to discuss and resolve discrepant cases. In the few instances where we disagreed, the disagreement was caused by different, but synonymous terms used to describe a particular link. Note that no attempt was made to determine the frequency of occurrence of any particular link type; we were interested primarily in identifying the different types. Comparative Causal Sequential Associative Exemplary Componential Accidental Although subjects weren't always able to classify every link that they made, of the 497 total links made by subjects, all were either immediately placed into one of the seven categories (combining similar and opposite into comparative) by the subjects themselves or in retrospect by the researchers. It is important to remember that these seven link types may not represent every possible link type. They only represent every link type made in this study with this particular set of nodes. Further research with different subjects and subject matter is needed to find the limits of the utility of this categorization. Higher and Lower Order Links One example of a higher order link was made by a subject when he in rapid succession linked "Arafat and the UN" to "PLO Violence", "PLO Violence" to "Terrorism," then "Arafat and The UN" to "Terrorism." In another example that same subject liked "Sanctuary" to "PLO Violence" because in his words "countries around the world give sanctuary to the PLO." He then linked "Sanctuary" to "Terrorism" because since PLO violence is most often expressed as terrorism, "those same countries are supporting terrorism when they give sanctuary." Interestingly, this subject had read several books about the content area. This subject made 69 links overall, 4 standard deviations above the mean. Higher-order linking appears to indicate a greater degree of assimilation of information than direct linking, hence the higher and lower order distinction. Video Nodes General Conclusions Dansereau (1978, & Dansereau et al., 1979) advocates a general schema training approach called "networking." In networking he suggests that learners be trained to recognize six types of links between nodes of information. These are: Part links, Type links, Leads-to links, Analogy links, Characteristic links, and Evidence links. Learners read a passage of text, then create a "node-link map" on paper. They can then relate or link information nodes on the map by classifying them as one of these link types. Links represent the way the ideas represented by the nodes are interrelated. Clearly this strategy relates closely to the link types identified in this study. It may be that experts in a content domain or in working in hypermedia environments would exhibit link types more closely related to those suggested by Dansereau. Although McKeachie (1984) suggests that this networking strategy is dif ficult and time-consuming to learn and employ, it would be well worthwhile to examine how well it works in hypermedia environments. This study suggests that training in networking is highly applicable to work in hypermedia environments, and should be researched. Subjects in this study had no training in networking. Whereas Dansereau's link types are etic, the types identified in this study are emic, coming from the subjects, not the researchers. At the time analysis of the data for the this study was conducted, neither researcher was familiar with Dansereau's work. However, we feel that the results of our study also suggest that caution should be used before choosing hypermedia to address some educational goals. Based on our observations of the subjects, their answers to our questions, and the linkages they established, it is clear to us that there is no way to guarantee that specific learning objectives will be met with a completely non-linear, unstructured system such as that used in this study. Based on p ost-treatment interviews, we felt that some subjects left the study with an incomplete and/or inaccurate understanding of some of the facts presented in the system. (One subject left the study thinking Camp David was a concentration camp in World War II.) Because of this finding, we believe that we can only say that these systems allow learners to construct their own world views, and that there is no evidence that these newly constructed views will be consistent with the norm. More research must performed before it is clear what features hypermedia systems must incorporate in order to allow learners to achieve more specific learning objectives. This study gave us the opportunity to observe subjects actually using a hypermedia system and to gain some new insights into potential advantages and disadvantages of non-linear, learner-controlled instructional systems. One aspect of that observation was eye-opening for us and we believe should be considered caref ully in the development and implementation of hypermedia instructional systems (HIS). To be precise, subjects occasionally mentioned during their interaction that they were avoiding particular topics (like violence and terrorism) because although they knew things like that happened, they didn't like to hear or see the details. This suggests that allowing students to choose the topics they review in a hypermedia system could actually allow them to bias their learning because they are unwilling to explore certain topics. Much emphasis has been placed on giving students access to raw information so that their learning is not biased by the opinions held by their teacher, however, we have not seen anyone mention this equally unsettling prospect of students censoring their own learning due to personal preferences. While most hypermedia proponents extol the virtues of students being able to come to their own conclusions based on raw, uncensored data, we wonder if they have considered how valid those conclusions might be if t he learner refuses to expose himself/herself to certain facts or theories. Further, the size of a hypermedia system may turn out to be a critical factor in its success. Although much emphasis has been placed on how we can develop hypermedia systems which encompass great volumes of information, we believe that too large a system might actually hamper the hypermedia learning process. Our system used only 25 nodes of information taken from a larger system of over 400 nodes. The subjects had a difficult time reviewing that much information in the one hour allotted and some of them said they had difficulty maneuvering among that many options. Limitations Evident within the Study Due to the limited time available for the study, the subjects were artificially limited to one hour to explore the topics. This limitation possibly precluded the viewing of many videodisc clips and /or the careful reviewing of data nodes. This time limitation therefore could have impacted our findings. Subjects often found it difficult to verbalize link types. This difficulty may have had two impacts on the study, 1) in identifying all of the different link types subjects made, and 2) in interfering with the subjects' progress through the system. Being forced stop and verbalize reasons for links may have caused the subjects to progress through the system in a manner different than they might have otherwise. The verbalization may have also affected the number of links subjects made. The video-clips available often were too big to be single nodes, often containing information about more than the topic they represente d. This was distracting to subjects in some cases and possibly caused confusion in what nodes were appropriate to link. The structure of the system utilized video-clips as part of the nodes (or topics) rather than as separate entities. One other major consideration is that subjects had no extrinsic motivation for learning about this particular topic area. They were rewarded for participating in the study by being given extra credit in their courses, but they had no reason to want to learn about the Israeli/Palestinian conflict. Findings may have been different given a sample already studying this content area. Suggestions for Further Research First, extensive research into the active versus passive hypermedia instructional systems is needed. Many proponents of hypermedia in education are emphasizing the virtues of hypermedia as a teacher presentation tool. While it may be more than multimedia due to its non-linear capabilities, it still amounts to relatively passive learning for students. In other cases, hypermedia systems are designed for use by individual students but still do not promote active learning by students. We feel that hypermedia systems which promote active learning by forcing learners to construct their own links between nodes of information will prove to be the most beneficial. However, we feel that more research is needed into how active versus passive hypermedia instructional systems will impact learning. Second, our research results indicate that subjects with a richer prior knowledge of the subje ct created more links between nodes. We expect that there will be a difference between the way domain experts and novices create links between nodes. We feel that there is a need for further research to examine the way learners at different levels construct links in hypermedia systems compared to the way experts in the field construct them. If a goal of instruction is for learners to become experts in whatever area they are studying, every stop on the path to expertise should be mapped out and road signs put up for the travellers. Hypermedia-based instructional systems have the potential to become the vehicle that carries education into the twenty-first century. They also have the potential to become the out-of-control bandwagon that plummets off a cliff, sending computer-based instruction to a much deserved grave in a jaded public's eye. It's time to take control of hypermedia before it gets away from us. Let's send it where we want it to go, letting r esearch be our guide. References Bloom, B. S. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York: Longman. 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Dansereau (Eds.), Spatial learning strategies: Techniques, applications, and related issues (pp. 301 - 312). Orlando, FL: Academic Press. Morariu, J. (1988). Hypermedia in instruction and training: The power and the promise. Educational Technology, 28(11), 17 - 20. Reeves, T. C., & Harmon, S. W. (1991). What's in a name: Hypermedia vs. multimedia. Interact, In Press. Trujillo, I. (1989). Academic Computing: The los andes project. , Summer. Tsai, C. J. (1988). Hypertext: Technology, applications, and research issues. Journal of Educational Technology Systems, 17(1), 3-14. |
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