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Constructing and maintaining an effective hypertext-based learning environment Web-based learning and cognitive style
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Martin Graff Department of Psychology and Education, University of Glamorgan, Pontypridd, UK Abstract Purpose – This paper aims to review the literature on the utility of employing the construct of cognitive style in understanding behaviour in web-based learning environments. Design/methodology/approach – The paper initially examines whether the web architecture may be matched to an individual’s cognitive style in order to facilitate learning, before progressing to assess whether different architectures influence a web users’ internal representations of web-based learning systems, as measured by concept map drawings. Other issues explored are users’ web navigation and users’ sense of learning community when receiving instruction via web-based learning environments. Findings – The studies reviewed indicate that cognitive style is a pertinent factor for consideration when assessing the success with which users engage with web-based learning systems. Research limitations/implications – Some of the studies reviewed here are small-scale and caution is urged in generalising the findings. Practical implications – In terms of the practical implications, however, it is suggested that web-based systems should be designed with consideration to individual differences in user characteristics, as this is related to the success with which users learn, navigate and interact socially in an online environment. However, it is concluded that more research is required in order to produce general rules relating cognitive style to the use of web-based learning systems. Originality/value – The findings from the numerous studies on the implications of considering the function of individual differences in using web-based learning are notable and useful in the context of web-based instruction. Keywords Learning styles, Cognitive mapping, Data handling, Worldwide web, Architecture, Navigation Paper type General review
1. Background Web-based learning environments are constructed from a system known as hypertext from which there are various historical derivations. For example the Memex system developed by Bush (1945), Randall Trigg’s NoteCard system (Trigg, 1983; Halasz et al., 1987) and Doug Englebart’s oN Line System (NLS). The revolutionary point about hypertext is that it brings something extra to the learning situation in the way of providing an explicit structure to the material to be learned, which should theoretically be advantageous to the learner. Computerised hypertext may be considered to be a user-driven medium, where individuals feel a necessity to move actively around the system. In other words, individuals want to feel that they are active when using computer-based hypertext. This viewpoint is supported by Landow (1992), who
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suggests that learners in a hypertext environment are active by choosing which links to follow. He quotes Jonassen and Grabinger (1990, quoted in Landow, 1992, p. 121), who stated that “hypermedia users must be mentally active while interacting with the information”. Therefore it is important to analyse and synthesise the results from individual studies examining the relationship between hypertext architecture and learning in order to design effective web-based learning environments. This is one of the aims of the paper. 2. Hypertext architecture and learning Mohageg (1992) looked at question answering performance using three hypertext architectures, namely: (1) hierarchical, where the information was arranged so that superordinate pages were linked to lower order pages; (2) network, where one page may be connected to any other page to form a complex structure with many links; and (3) mixed, which was a combination of the two other structures. Mohageg found that performance was poorest in the network condition, however he found no performance differences between the mixed and hierarchical conditions. The mixed hypertext condition contained more links than the other conditions, which may have had the effect of increasing performance in this condition. The results provide support for the facilitative instructional effects of a mixed hypertext architecture in computer-based learning. In a further study assessing the benefits of learning from hypertext, McDonald and Stevenson (1998) employed 30 undergraduate and postgraduate students and three hypertext architectures: hierarchical, non-linear (which was where the nodes were connected to form a network based on a large number of links) and mixed (which was hierarchical with lateral links). Participants read the hypertext document and then used it to answer ten questions. They found that participants in the mixed condition found the information quicker than those in each of the other two conditions. The result is explained in terms of the mixed hypertext condition facilitating the ease with which participants grasped the conceptual structure of the material. Findings from the above studies suggest that a mixed hypertext architecture would appear to be the most effective way of structuring learning material. However, no consideration was given in the above studies to individual differences between users in the ways in which they engaged with the hypertext. One relevant individual difference factor that may potentially have an important influence on the way in which users learn from hypertext is cognitive style. Cognitive style, hypertext and learning Cognitive style refers broadly to the way in which people process information, for example how they perceive, remember and use information from their surrounding environment. There are numerous models of cognitive style, many of which define style as opposite extremes of a particular dimension, for example reflective-impulsive (Kagan et al., 1964), convergent-divergent (Guildford, 1959), leveller-sharpener (Holzman and Klein, 1954) and serialist-holist (Pask, 1972). However, one of the most extensively used models of cognitive style is that referred to as field
dependent-independent, which developed from the work of Herman Witkin in the late 1940s (Witkin and Goodenough, 1979). This model of cognitive style suggests that people perceive entities either in discrete units (field independent approach) or as complete wholes (field dependent approach). Subsequent evidence suggested that differences in learning strategies are apparent between field independent (FI) and field dependent (FD) individuals (Witkin et al., 1977). This is because FI individuals have the ability to impose or extract structure from material to be learned, whereas FDs must rely on external information to organise information. Accordingly then it is likely that a highly structured hypertext instructional architecture would provide an organisational aid to learning that would benefit FD individuals. In contrast, a less structured environment, where organisation would need to be provided by the learner would be less facilitative to FDs. FIs on the other hand would be able to learn from less structured environments due to the manner in which they organise information internally. In summary then it would be expected that instructional methods involving greater structure or organisation should be more beneficial to FD individuals, and less important for FI individuals. However, the evidence does not fully support this reasoning. For example, Lin and Davidson-Shivers (1996) investigated the effect of hypertext architecture and cognitive style as measured by the Group Embedded Figures Test (GEFT) on recall of verbal information with 139 undergraduate college students. Five hypertext architectures were used, which corresponded to linear, hierarchical, hierarchical-associative, associative and random. All hypertext architectures featured the same informational content. Overall, their results showed that students with higher scores on the GEFT and labelled as field-independent, outperformed those with lower scores, labelled as field-dependent. They also found that the FI students had more favourable attitudes to using hypertext than FD students. Furthermore, they observed that hypertext architecture did not influence performance. Lin and Davidson-Shivers (1996) explain the effects of cognitive style in terms of FI individuals being more self-motivated and having greater expectations of achievement. A further study by Korthauer and Koubek (1994) looked at the difference between 40 FD and FI participants’ ability to answer questions following a session of hypertext browsing. They found that FD participants who were experienced in the subject matter of the hypertext document performed less well than experienced FI participants. They account for these findings by suggesting that the existing knowledge of the experienced FD participants and the way in which these individuals represented this knowledge internally conflicted with the explicitly structured hypertext. However, tests of disembedding figures have been found to be correlated with standard tests of spatial ability (McKenna, 1984, 1990). Therefore it is possible that the superior performance of FI individuals in the studies of Lin and Davidson-Shivers, and Korthauer and Koubek may be more a function of differences in spatial ability rather than individual differences in the strategies individuals employ for organising information. Accordingly, there is a need to test learning from hypertext employing a cognitive style measure that is independent of individual attitudes to computer-based delivery and independent also of spatial ability. Self-report measures of style and learning from hypertext Melara (1996) used Kolb’s (1976) Learning Style Inventory to assess learning style and related this to a task delivered via hypertext. A total of 40 participants who were
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students in computer science, engineering or mathematics were employed in the study. The learning styles of the participants were assessed, and each participant was classified as possessing an active or reflective style. Participants were then randomly assigned to one of two hypertext conditions corresponding to a hierarchical architecture or a network architecture. The network structure was described as one which linked together related concepts to form a web. Participants were required to answer ten questions on the information included in the hypertext. Melara found no difference in performance between participants of different learning styles in either hypertext condition. However, the results were approaching significance (p ¼ 0:06), with superior performance from participants in the hierarchical condition. In addition, individuals with both learning styles, activist and reflective, displayed superior performance when using the hierarchical structure. Melara suggests that the results indicate a consistent difference between the two structures, and that learning style made no difference. However, it is important to note that participants in the hierarchical condition took significantly longer to complete the task than those using the network structure, which is a possible explanation for the superior performance of participants in this condition. The studies cited so far have sought to measure learning by using tests of simple recall of information. Recall is synonymous with knowledge or comprehension at the lower levels of Bloom’s (1968) Taxonomy of Educational Objectives, and it could be argued that this does not reveal whether learning has occurred on a deeper level, which would involve an understanding of the structure of interrelationships between concepts and procedures in a particular domain, and how they are organised into a unified body of knowledge. Accordingly, an assessment of an individual’s understanding of how the information contained within a hypertext document may be combined into a unified whole is required in order to test learning at a deeper level. 3. Learning assessed by description Shapiro (1998) used an essay test in an attempt to investigate how effectively learners had gained an overall understanding of the structure of the information in a hypertext. This investigation employed three hypertext architectures conforming to: hierarchical, with some lateral links; unstructured, which provided the same links and documents as the hierarchical condition, but with no explicit information about the hypertext structure; and linear, where there was no inter-connectivity between the pages apart from those which were next to each other, rather like a book. The 72 participants employed were instructed to write an essay that required them to integrate the material from the hypertext. The essays were rated on four criteria: (1) integration of the material in the essay; (2) how well the participant understood the topic about which they were writing; (3) the clarity of the participant’s essay; and (4) the overall quality of the essay. Shapiro found that on all criteria, participants in the unstructured hypertext condition scored higher than those in the hierarchical and linear conditions. Shapiro interpreted this finding by arguing that the lack of explicit information in the unstructured condition required a deeper level of processing of the information in order for participants to understand it, which resulted in a higher level of performance.
Graff (2003a) investigated whether different hypertext architectures could be matched to an individual’s cognitive style in order to facilitate learning as measured by essay questions. Three hypertext architectures were employed, which were linear, hierarchical and relational. Each architecture condition represented the way in which the information in the hypertext was arranged. In the linear condition, one piece of information followed another; in the hierarchical condition, superordinate pieces of information were provided before more detailed information; whereas in the relational condition, users of the hypertext could move freely between pieces of information, which were conceptually related. Cognitive style was assessed using the Cognitive Styles Analysis (Riding, 1991), and essay scores were measured by number of words and amount of detail included. The findings revealed that in the relational architecture condition, intermediates (i.e. individuals between wholist and analytic) obtained superior scores, whereas in the hierarchical condition, bimodals (i.e. individuals between imager and verbaliser) obtained superior scores. The findings were explained not in terms of ease of use of the hypertext, but rather by specific architectures being more suited to the cognitive styles of particular users. To conclude this section briefly, the findings would appear to suggest that a consideration of cognitive style is pertinent to the design of hypertext learning environments. However, what is evident is that the findings are derived from an array of cognitive style measures, and evidently more research is needed here with a view to unifying the study of cognitive style research and hypertext-based learning. Nevertheless, the findings reported above reveal that a consideration of cognitive style is important for simple learning, such as recalling information, and for essay writing tasks. However, also worthy of consideration is the application of cognitive style testing to more complex cognitive tasks within hypertext. 4. Concept mapping of hypertext Concept mapping is a technique whereby individuals are required to reproduce diagramatically the relationship between the concepts belonging to a particular subject domain. The technique was developed by Joseph Novak at Cornell University in the 1960s, and is appropriate as a means of testing a user’s understanding of hypertext. Shapiro (1998 (described above)), compared the performance of participants in three hypertext architectures on a concept mapping task. She asked participants to freely recall the structure of the hypertext on paper and used a measure of link density, which was derived by dividing the total number of links in each concept map by the total number of nodes, in order to assess the complexity of the participants’ conceptualisation of the material. Shapiro found no significant effect of hypertext architecture on concept map link density. Further analysis to try to assess the amount of detail present in each map revealed that participants in the linear condition recalled less detail than those in the other hierarchical and unstructured conditions. This was explained by the fact that participants in the two non-linear conditions visited the same pages in the hypertext many more times than those in the linear condition, thus mere exposure to the information may have caused the differences in amount of detail recalled. Finally, Shapiro also reported that the presence of system links affected participants’ internal representations of the hypertext, in that participants who were exposed to the hierarchical and unstructured conditions produced concept maps that largely reflected the system links in each of these structures. A slightly different finding to this was reported by McNamara et al. (1989), who observed that when
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producing maps of the environments in which they had worked, individuals’ representations tended to be hierarchical in form even when the environment had no predefined hierarchy. McNamara et al. (1989) account for this by proposing that certain types of information tend to be organised hierarchically by individuals in order to facilitate efficient recall. It is also conceivable that cognitive style may account for differences in the types of concept maps produced by learners, and this issue was investigated by Graff (2002a, 2005a). In one study 55 participants were assigned to one of three hypertext conditions (linear, hierarchical and relational, described above) and were required to recall information and produce maps of the hypertext (Graff, 2005a). Cognitive style was assessed using the “analysis-intuition” dimension of cognitive style (Allinson and Hayes, 1996). The findings confirmed earlier research that individuals possessing different cognitive styles differed in recall performance when using different hypertexts. Those with an analyst style scored highest in the hierarchical condition, intermediates scored highest in the relational condition and intuitives scored highest in the linear condition. For assessment of concept map density, (the degree to which users are able to integrate the concepts in the hypertext), participants in the hierarchical architecture condition produced the least dense maps with little difference between the relational and linear architectures. The higher density scores produced by participants in the relational architecture was explained by the fact that the intricate relational architecture encouraged participants to produce dense maps purely because of the impression that this architecture gave them. This finding differs from that of Shapiro (1998) who found no difference in density scores between participants performing in different architectures. No significant effects were observed for cognitive style; however, the greatest variation in density scores between conditions occurred for the intermediates, with little variation for the analytics and intuitives. Assessments of complexity (the degree of representation of map breadth) revealed that participants performing in the relational architecture produced the most complex maps, followed by those in the linear condition, with those in the hierarchical condition producing the least complex maps. The findings here are explained partly as being due to differences between individuals’ perceived ease of use of the hypertext. In conclusion, the findings from the studies cited above suggest that awareness of an individual’s cognitive style has utility also for predicting success at more cognitively complex tasks within a hypertext environment. 5. Segmentation of hypertext In terms of the design of hypertext, one further question to address is the degree to which the hypertext should be segmented. The issues of the degree of segmentation which is appropriate to apply in a web structure and whether the provision of an overview is appropriate have been addressed by Dee-Lucas and Larkin (1995) who found that providing an overview makes a hypertext easier to use, directing readers to different aspects of the system. However, again it is feasible that the degree to which segmentation of a hypertext and provision of guidance is beneficial may be contingent on an individual’s cognitive style. Graff (2003c) employed 50 participants who were assigned to one of two web-based instructional systems on the subject of psychological ethics. The information in one system was more segmented than the other, and half the participants were given an overview of the system and half were not. Following a period of time using the system participants were requested to
answer questions. The findings here suggest that cognitive style and segmentation had an effect on learning from the system, with analytics showing superior learning performance in the less segmented condition, whereas wholists showed superior learning performance in the more segmented condition. However, the provision of the overview of the system had no effect; a similar finding to this was observed by Graff and Byrne (2002). Further information on an individual’s ability to apprehend effectively the structure of a hypertext document may be derived from an analysis of the way in which he/she navigates hypertext. It is likely that the route followed through an environment, physical or virtual, will influence an individual’s internal or mental representation of that space. Maglio and Matlock (1999) reported that the way people navigate hypertext has implications for the way in which they think about it. Using data from interviews with participants, they argue that people think of hypertext as a kind of physical space in which they move, and see it in terms of a cognitive map. They remember only a few places they visit, but they remember landmarks and routes and they also remember key information. They also rely on personal routines when trying to find information. As with maps of physical space, personal routines correspond to the routes that individuals use to get from one point to another. The suggestion is that navigation will influence an individual’s internal representation of the hypertext. The following section examines first, the types of hypertext navigational strategies that have been identified in the literature, and then assesses how these relate to cognitive style. 6. Hypertext navigation Numerous distinctions have been made between the terms “navigation” and “browsing” with regard to using hypertext (Batley, 1989; Hammond and Allinson, 1988; Hildreth, 1982), and it is important to distinguish between these terms. The broad differentiation would appear to be that browsing is considered a more casual non-goal-related task, whereas navigating is considered as targeted towards some distinct end goal. Both are characterised by the manner in which an individual moves around the hypertext system, and it is this style of movement that is of interest in the present review. Navigational strategies This review continues with an analysis of the types of navigational strategies that have been identified and classified in the literature. For example, in their research into the way in which users navigate through a hypertext document, Batra et al. (1993) noted differences in navigational behaviour according to hypertext architecture. They used two architectures, which were hierarchical and hypertorus (nodes are arranged in a rectangular pattern), and the effect of each architecture on participants’ ability to answer ten questions, the answers to which were located within the hypertext. Their findings suggest that the hypertorus structure fostered more exploratory browsing, but participants found it significantly easier to locate information using the hierarchical structure. Batra et al. (1993) explain the results in terms of the differences in the number of links in each hypertext architecture, which motivated different browsing strategies. Canter et al. (1985) classified navigational strategies in terms of the functions each serves when a user engages with hypertext. They devised a series of indices for the navigational routes chosen by users:
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pathiness, where users follow long linear paths; loopiness, where users navigate in circles around the document; ringiness, which are small loops or circles; and spikeness, where users follow paths to dead ends.
They also looked at the number of nodes and pages users visited, and the ratio of the number of different pages visited to the total number visited. Using this information, they derived five discernible navigational strategies: scanning (covering a large area without depth), browsing (following a path until a goal is reached), searching (striving to find an explicit goal), exploring (finding out the extent of the information system) and wandering (purposeless and unstructured globe-trotting). Canter et al. (1985) further concluded that each of these strategies, except for the last, has an appropriate function in navigating hypertext. Scanning and exploring are used to get an overview of an application. Browsing is following a train of thoughts, and searching is following to a dead end. Other investigations of navigational strategies include an analysis of search strategies, (Hill and Hannafin, 1997) and also time spent navigating through selected pages (Korthauer and Koubek, 1994). The above studies provide useful classifications of navigational behaviour, although a consideration of cognitive style and how this could influence navigational behaviour would also seem appropriate. Studies that have examined navigational behaviour according to cognitive style differences are examined in the following section. Cognitive style and hypertext navigation One study which examined this issue was undertaken by Ellis et al. (1992), who looked at individual differences in cognitive style and hypertext navigational behaviour. They tested students using a Study Preference Questionnaire (SPQ) a non-standardised test developed by the authors to assess holist and serialist study strategies. Navigation tools were provided for using the hypertext document in this study which were: . a self-orienting global concept map; . keyword index menus; and . a backtracking facility. The subject matter of the hypertext document was the European Single Market. A total of 40 postgraduate students were assigned the task of using the system to answer a number of questions requiring first, specific factual recall and, second, generalisation using information from more than one location in the hypertext. It was found that participants with a holist strategy made use of a map whereas participants with a serialist strategy made use of an index. A further study by Chen and Ford (1998) tested 20 postgraduate students who learned from a hypertext system designed to give an introduction to the field of artificial intelligence In this study cognitive style was tested using the Cognitive Styles Analysis (Riding, 1991). It was found that wholists made use of the main menu for navigation, whereas analytics made more use of the “previous” or “next” buttons on the browser software. However, it is possible that the sample size was too small to generalise navigational tendencies to either style. Furthermore, both of the above studies provided the user with a variety of navigational aids, and therefore tell us more about the user’s selection of such aids rather than the navigational strategies employed by users with different cognitive styles.
Two further studies addressing the issue of a relationship between cognitive style and browsing strategy are worthy of note. Stanton and Stammers (1990) employed 60 participants who used a structured hypertext architecture and completed the Embedded Figures Test in order to assess their cognitive styles. Results indicated that FD participants tended to use bottom-up navigational strategies, progressing from the more basic information upwards, whereas FI participants tended to use top-down strategies, which meant that they looked at the most important information first. This is consistent with the notion that FI individuals who are able to apprehend the structure on the hypertext use a top-down strategy, while FD individuals who characteristically approach tasks more sequentially use a bottom-up strategy. It was also reported that the FI individuals viewed fewer pages than the FD individuals. Stanton and Stammers explained this by suggesting that FI individuals use top-down strategies so that they can make greater inferences about the content of the lower order pages. Verheoj et al. (1996) used the Dutch Inventory of Learning Styles developed by Vermunt and Van Rijswijk (1987) that identifies individuals as deep or surface processors. The study involved asking participants to search for information within a hypertext environment. Verheoj et al. (1996) found that there were differences in strategy between the two learning styles, with the individuals identified as deep processors adopting a global strategy to navigate through the text, while surface processors adopted a more step-by-step approach. However, a major problem with this type of self-report instrument is its reliance on retrospectively reported information. Graff (2002b, 2005b) investigated differences in web browsing strategies between individuals displaying verbaliser and imager cognitive styles. Graff (2005b) employed 58 participants who were allowed ten minutes to read information in either a hierarchical or relational hypertext with the expectation of answering questions on this information. Browsing strategies were assessed firstly by using three indices of browsing patterns, (number of pages visited, proportion of pages visited and pages revisited) and secondly by analysing assessments of browsing strategies given by independent judges. Cognitive style was assessed using the Cognitive Styles Analysis (Riding, 1991), which revealed the extent to which participants possessed an imager or verbaliser cognitive style. Differences were found between imagers and verbalisers for the indices of browsing patterns, with verbalisers visiting more pages in the hierarchical architecture and imagers visiting more pages in the relational architecture. However, no differences were observed between verbalisers and imagers for the independent judge’s ratings of browsing strategy. The evidence cited above is encouraging in as much as they appear to illustrate that distinctive hypertext navigational strategies are identifiable, and furthermore that such strategies are related to various cognitive style models. The ability to predict how an individual may navigate a hpertext learning system is of paramount importance to the overall design of such systems. 7. Social behaviour and sense of online community Finally it must be noted that using hypertext for learning is now seen as a more dynamic activity, with learners engaging more actively with such systems, and communicating with each other online. One concept which describes this interactive behaviour is referred to as “sense of community” which more precisely may be described as the sense of trust and interaction between groups of learners.
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As well as proving useful in explaining differences in educational attainment, the construct of cognitive style has also been found to be related to social behaviour. Graff (2003b) investigated the relationship between cognitive style as measured by the Cognitive Styles Index (CSI) (Allinson and Hayes, 1996) and sense of classroom community as measured by the Classroom Community Index (Rovai, 2002) in a group of students pursuing courses which featured a mixture of face-to-face and online instruction, typically referred to as a blended learning environment. The findings indicated that the participants with intuitive cognitive styles reported a lower sense of community than students with intermediate or analytic styles. This finding is interpreted by the fact that intuitive individuals, being more outgoing in social orientation, need to feel a greater sense of community than analytics in the same interactive environment. 8. Summary This review has looked at various studies assessing the use of hypertext as an instructional instrument, which have generated an array of findings in several areas: the effectiveness of hypertext in facilitating learning (Mohageg, 1992; McDonald and Stevenson, 1998), the navigational strategies employed by users (Batra et al., 1993; Canter et al., 1985) and social behaviour and sense of online community (Graff, 2003b). However several further research questions emerge from the studies reviewed in this paper. For example, differences in hypertext architecture have revealed that the most facilitative structure for learning, in terms of a user’s ability to answer recall questions was a hierarchical structure with lateral connections. Further investigation also revealed that individual differences in cognitive style can influence the effectiveness of learning from hypertext (Korthauer and Koubek, 1994; Lin and Davidson-Shivers, 1996). However, both of these studies using the field dependence-independence construct found field-independent individuals to be superior to FDs in performance at learning across all hypertext architectures. This finding fails to support the rationale that an explicitly structured hypertext architecture should be of more benefit as an instructional aid to field dependent individuals and alludes to the suggestion that FDI cognitive style as assessed with tests of disembedding shapes is merely a test of ability (McKenna, 1984). A further research question concerns the assessment of learning. Learning in most of the studies reviewed in the early part of this paper, were assessed by means of simple recall questions, which assess learning on a lower level. Deeper levels of learning involve an understanding of the structure of interrelationships within a particular domain which can, according to Shapiro (1998), be assessed by an analysis of responses to essay questions. According to Shapiro, performance on essay questions reveals whether a learner has comprehended the overall structure of the learning material. Furthermore, the manner in which an individual navigates a hypertext document may influence his/her ability to effectively apprehend its structure, in as much as the route followed through an environment, physical or virtual, will influence an individual’s internal or mental representation of that space. Batra et al. (1993) and Canter et al. (1985) sought to classify navigational strategies and suggested that they were dependent firstly on the hypertext architecture, and secondly on the tasks which users were asked to perform. Graff (2002b, 2005b) has also demonstrated that cognitive style is useful to consider in assessing hypertext navigation.
9. Implications The evidence reviewed in this paper suggests that numerous research questions regarding use of hypertext and cognitive style still need to be addressed. First, whether the wholist-analytic and verbailser-imager cognitive style constructs prove to be more appropriate in assessing style differences in learning from hypertext; second, whether essay questions provide a more realistic measurement of learning performance than recall questions; and third, whether navigational behaviour and the amount of disorientation experienced by users is influenced by cognitive style. The overall conclusion to be drawn however, is that differences in hypertext architecture have revealed that the most facilitative structure for learning, in terms of a user’s ability to answer recall questions was a hierarchical structure with lateral connections. Furthermore, it seems also that individual differences in cognitive style can influence the effectiveness of learning from hypertext. Indeed, the manner in which an individual navigates a hypertext document may influence his/her ability to effectively apprehend its structure, in as much as the route followed through an environment, physical or virtual, will influence an individual’s internal or mental representation of that space. Finally, some tentative findings suggest that online interactive behaviour may be related to cognitive style. Overall, the findings reported in this paper indicate that individual differences in cognitive style are a pertinent factor for consideration in the design and implementation of hypertext-based instructional systems, and this consequently will have implications for the practice of education and training, in environments that utilise hypertext as an instructional tool.
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