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THE EFFECT OF PRIOR KNOWLEDGE ON LEARNERS’ NAVIGATION STRUCTURE

THE EFFECT OF PRIOR KNOWLEDGE ON LEARNERS’ NAVIGATION STRUCTURE. Gökhan AKÇAPINAR Arif ALTUN Dept. of Computer Education and Instructional Technologies, Ankara, Turkey. Outline. Introduction Purpose of the study Navigation Structure Compactness Stratum Method Participants

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THE EFFECT OF PRIOR KNOWLEDGE ON LEARNERS’ NAVIGATION STRUCTURE

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  1. THE EFFECT OF PRIOR KNOWLEDGE ON LEARNERS’ NAVIGATION STRUCTURE Gökhan AKÇAPINAR Arif ALTUN Dept. of Computer Education and Instructional Technologies, Ankara, Turkey

  2. Outline • Introduction • Purpose of the study • Navigation Structure • Compactness • Stratum • Method • Participants • Data collection • Design and procedure • Findings • Conclusion Gökhan Akçapınar, Arif Altun

  3. Introduction • In a written text information is structured linearly and hierarchically but in hypermedia information can also be presented non-linearly and connectively. • This flexible structure provides learners with great browsing freedom (Botafogo, et al., 1992). • Nevertheless, there is a risk for some learners, as they can become “lost in hyperspace” (Chen and Macredie, 2002). Gökhan Akçapınar, Arif Altun

  4. Introduction • Lostness or Disorientation is one of the most important issues in user experience during browsing hypertext environment (Conklin, 1987; Edwards and Hardman, 1999; Herder, 2003b). • Studies show that individual differences such as prior knowledge, cognitive skills, cognitive loads etc. play important roles on this behavior or perception. Gökhan Akçapınar, Arif Altun

  5. Purpose of the study • This study was carried out to investigate the effect of prior knowledge (high vs. low; HPK and LPK) on learners’ navigation in network structured hypermedia systems. Gökhan Akçapınar, Arif Altun

  6. Navigation Structure • Navigation strucrure was measured by two metrics: compactness and stratum. • Although compactness and stratum were originally developed to assess the structure of hypertext networks (Botafogo, et al., 1992), they have been adapted by McEneaney (2001) to measure user navigational behaviors. Gökhan Akçapınar, Arif Altun

  7. Compactness • Compactness refers to the connectedness of a navigation, of which values close to zero for sparsely linked navigation and values close to one for densely connected navigation. Gökhan Akçapınar, Arif Altun

  8. Stratum • Stratum refers to the degree of linearity of a navigation, close to one for more linear navigation while close to zero for less linear ones. Gökhan Akçapınar, Arif Altun

  9. Participants • Thirteen prospective high school computer teachers from Computer Education and Instructional Technologies Department of Hacettepe University (6 females and 7 males) participated to this study. • Their mean age was 21.5 years (SD=1,05). They were also registered Database course at same semester. Gökhan Akçapınar, Arif Altun

  10. Data collection: Learning material • Course content was designed by researches related to learning task. In this content, basic SQL queries (Select, Update, Delete, Insert) were introduced and how to use these queries with ActiveX Data Object (ADO) to connect MS Access database from Visual Basic programming language was explained. • A networked structure was used to present information consisting of 12 web pages (about 1000 words) and 53 cross-reference links between pages. Gökhan Akçapınar, Arif Altun

  11. Learning material Gökhan Akçapınar, Arif Altun

  12. Data collection: Navigation data • Students’ navigation data were recorded in a log file to calculate their compactness and stratum scores. • Date, time, page name, IP address and visit duration were recorded in these files. • Each navigation data logged in a separate file. Gökhan Akçapınar, Arif Altun

  13. Users’ log files Gökhan Akçapınar, Arif Altun

  14. Data collection: Navigation data • A tool was developed by researches to automatically analyze these files. • With the help of this tool when user select a log file, its compactness and stratum scores were calculated and also navigation graph was drawn automatically. Gökhan Akçapınar, Arif Altun

  15. Navigation Analyzer Gökhan Akçapınar, Arif Altun

  16. Data collection: Prior knowledge test • Students’ prior domain knowledge about database systemswere assessed by the four open ended questions which were prepared by researches as content experts. • Based on the score of these questions, they were split into two groups. High prior knowledge group (HPK, N=7) and low prior knowledge group (LPK, N=6). Gökhan Akçapınar, Arif Altun

  17. Design and procedure • The prior knowledge test was administered one day before the learning task. • Both HPK and LPK learners perform learning task in network structure hypermedia. • While they are performing the task navigation data were recorded into log files. They had given maximum 10 minutes to learn the materials. Gökhan Akçapınar, Arif Altun

  18. Findings: Prior knowledge and navigation • A Mann Whitney U test, was used to determine whether there were significant differences in students’ stratum and compactness scores based on levels of prior knowledge. • Table 1 shows the result of the Mann-Whitney U test statistics. Table 1. Mann Whitney U test result related to users’ compactness and stratum scores Gökhan Akçapınar, Arif Altun

  19. Findings: Prior knowledge and navigation • As seen in Table 1 there was significant differences between users’ levels of prior knowledge and Stratum scores (U=1.50, p<.05). HPK learners (Mean Rank = 3.75) navigated more linear than LPK learners (Mean Rank = 9.79). • There was also significant differences between users’ levels of prior knowledge and Compactness scores (U=6.00, p<.05). HPK learners (Mean Rank = 4.50) navigated more connectively than LPK learners (Mean Rank = 9.14). Gökhan Akçapınar, Arif Altun

  20. Navigation pattern: HPK (Left) vs. LPK (Right) Stratum: 0.22 – Compactness: 0.17 Stratum: 0.7 – Compactness: 0.48 Stratum: 0.16 – Compactness: 0.25 Stratum: 0.58 – Compactness: 0.45 Gökhan Akçapınar, Arif Altun

  21. Conclusion • Based on these findings we can conclude that HPK and LPK learners navigate significantly different from each other in network structure hypermedia systems. • These results indicated that HPK learners have higher compactness values and higher stratum values while LPK learners have lower compactness values and lower stratum values. • Analyzing users’ navigation pattern showed that HPK learners’ navigation was better structured than LPK learners. Gökhan Akçapınar, Arif Altun

  22. Thank You!

  23. THE EFFECT OF PRIOR KNOWLEDGE ON LEARNERS’ NAVIGATION STRUCTURE Gökhan AKÇAPINAR Arif ALTUN Dept. of Computer Education and Instructional Technologies, Ankara, Turkey

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