Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library

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(1)圖書與資訊學刊 3:4=79(Nov. ’11)1-11 ISSN 1023-2125. Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library Hsing-Yu Hou Assistant Professor, Department of Business Administration, Transworld University E-mail: yue@twu.edu.tw. 【Abstract】 Social intelligence plays an important role in multiple intelligences. Despite its significance, in the field of library and information science, there have been few researches on the practice of social intelligence evaluation on digital library designers. The objective of this study is to adopt the Tromsø Social Intelligence Scale (TSIS) to evaluate social intelligence and design performance of digital library guide designers. In addition to TSIS, a computer self-efficiency scale is also applied to measure the designers’ computer skill. Moreover, Kepner-Tregoe Analysis (KTA) is used to score designs and select the best digital library guide. Analyses reveal that the correlation among TSIS, computer skill efficiency, and KTA is high: if the designer is good at basic computer skill, he or she is also generally evaluated as equipped with better social intelligence and as capable of designing better digital library guides.. Keyword Social intelligence;Computer self-efficiency;Kepner-Tregoe Analysis;Digital library guide design. 1.

(2) 圖書與資訊學刊. 第 3 卷第 4 期(第 79 期). behavioral intelligence. Daniel Goleman (2007). Introduction. demonstrated that social intelligence included social (1993). awareness and social facility. Social awareness is. were. composed of primal empathy, attunement, empathic. linguistic intelligence, musical intelligence, logical-. accuracy and social cognition. Social facility mixed. mathematical. synchrony, self-presentation, influence and concern.. According multiple. to. Howard. intelligent. Gardner’s. measurement,. intelligence,. spatial. there. intelligence, interpersonal. Although there are different ways to measure. intelligence, intrapersonal intelligence, and naturalist. social intelligence, psychologists always consider. intelligence. Social intelligence has played an. that the pencil-and-paper format tests are the most. important role in multiple-intelligence in recent. convenient tool to evaluate social intelligence. And. research. Goleman (1995), Hatch and Gardner (1993). cognition is the basis that experts pay most attention. proved that emotional intelligence or interpersonal. to in this method.. bodily-kinesthetic. intelligence,. intelligence were close to social intelligence.. The Tromsø Social Intelligence Scale. Furthermore, Lazear (2000) showed that social intelligent measurement could be divided into verbal. Silvera,. Martinussen. and. Dahl. (2001). skill, history, mathematics, science or health, global. constructed a Tromsø Social Intelligence Scale (TSIS). research, life skill and art. Social intelligence in the. including social information processing, social skills. computer science field means that each team or. and social awareness. Gini (2006) applied this scale. members in the class can teach or guide others how. to an Italian adolescent population and found good. to learn the relative items in the computers. Therefore,. correlation. social intelligence in computer science field belongs. suggested that different factors such as culture,. to life skill measurement. In recent years, many. perceived self-efficacy and self-esteem could be. researchers had divided social intelligence into a. discussed with social intelligence. However, there is. multifaceted construct. Kosmitzki and John (1993). few research about social intelligence evaluation in. indicated seven components of social intelligence: (a). Taiwan. The goal of the present study was to adapt. perceptiveness of others’ internal states and moods;. the Tromsø Social Intelligence Scale to the digital. (b) general ability to deal with other people; (c). library guide designers to evaluate their social. knowledge about social rules and social life; (d). intelligence and their design.. insight and sensitivity in complex social situations; (e). perspective tasking and (g) social adaptation. Osterman,. and. Kaukiainen. social. intelligence.. The. author. Self-efficiency. use of social techniques to manipulate others; (f). Bjorkqvist,. in. Bandura’s (1986) theory of self-efficiency. (2000). meant an estimation of one’s ability to successfully. indicated that social intelligence had three different. perform target behaviors to produce outcomes. Owen. components: perceptual, cognition-analytical and. (1986) suggested that self-efficiency could be easily. 2.

(3) Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library. eliminated.. and reliably measured and it could be used to assess a composite of affection, cognition, and performance in. 6. Score each alternative on each “Want”.. the attainment of program and course objectives.. 7. Multiply each alternative’s score on each. Murphy, Coover and Owen (1989) developed the. criterion by the importance weighting of that. computer. criterion.. self-efficiency. scale. to. measure. 8. Sum up all the weighted scores for each. self-efficiency scores. They found that three factors. alternative.. including beginning level computer skills, advanced. 9. Select the alternative with the highest score.. level computer skills and mainframe computer skills were reliable in estimating computer self-efficiency.. Objective of the Research. Kepner-Tregoe Technique. Lazear (2000) showed that social intelligence in. Founded in 1958 by Dr. Charles Kepner and Dr.. the computer science field meant each team or. Benjamin Tregoe, Kepner-Tregoe, Inc., is a global. members in the class could teach or guide others how. organization providing consulting and. training. to learn the relative items in the computers. Besides,. services around problem solving, decision making. library guides on the web are very important and. and. convenient for the users to understand how to use the. project. Kepner-Tregoe's. execution trademark. methodologies.. technique,. library,. Rational. such. as. borrowing. books,. searching. Process, which is commonly referred to as the KT. magazines, operating databases and enjoying movies,. Process, is the creation of structured, systematic. etc. Therefore, good digital library guides have to be. processes which are used to maximize the critical. designed patiently and the designers have to be. thinking skills of key stakeholders in a particular. organized as a project team. A project team could. situation, problem (potential or real), decision or. consist of two or three members in charging of. opportunity. The advantages of Kepner-Tregoe. editing the script, operating visual or verbal flash and. Analysis (KTA) are: (a) it provides explicit decision. dealing with the functional guide. During the digital. model; (b) it accounts for mandatory criteria; (c) it. library guide design process, the team member. accounts for varying importance of criteria; and (d) it. involve with intensive social intelligence. Therefore,. provides a single score for each alternative.. all the team members will answer the TSIS and. KTA includes the following procedures:. computer self-efficiency questionnaires to reveal. 1. Identify mandatory criteria “Musts”.. their relationships between social intelligence and. 2. Identify other evaluation criteria “Wants”.. self-efficiency perception. Finally, KTA is used to. 3. Weight wants by importance (usually 1-10. collect digital library guide movies scores from experts and users’ voting to decide the final digital. weights). 4. Score each alternative on each “Must”.. library guide design among all the alternatives. The. 5. Any alternative not meeting a “Must” is. reliability of the TSIS and computer self-efficiency. 3.

(4) 圖書與資訊學刊. 第 3 卷第 4 期(第 79 期). Methods. for digital library guide designers in Taiwan will be investigated. The correlation between TSIS and. Participants. computer self-efficiency will be analyzed. The relationship between the designers’ TSIS score and. Forty three subjects participated in the digital. their design score will be discussed.. library guide designing program in Transworld. The following sections are arranged as follows:. University (TWU) (see Figure 1). Each subject spent. methods include the research methods of participants,. one week in learning to edit, capture, discuss, design. questionnaires design, procedure and evaluation.. and upload the digital library guide movies. Because. Results present the results of reliability, correlation. group cooperation could evaluate social intelligence,. and KTA analysis. In discussion, we discuss and. each participant was assigned to a group which. analyze the scores between TSIS and KTA. Finally,. included two or three members.. conclusions are drawn in conclusions.. Figure 1 TWU Digital Library Guide Movies Designing Project. Questionnaires Design. questionnaire including 32 items was also tested to investigate the relationship between different social. The TSIS questionnaire was given to the. intelligence and self-efficiency perception. The. participants to measure their social intelligence,. self-efficiency questionnaire is a five-point scale. including three factors and 21 items in total. The. measurement.. TSIS is a seven-point scale measurement. Scale 1. Scale 1. means extremely poor. confidence, and scale 5 means extremely well. means extremely poor, and scale 7 means extremely. confidence. Participants were asked to answer the. well. Participants were asked to answer the scale.. scale.. Furthermore, a personal computer self-efficiency. 4.

(5) Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library. Procedures. 15%, 15% and 20% respectively. In evaluation of the content of digital library. Each group proceeded the digital library guide. guide design, each expert had his own evaluation. system by using the following stages:. criteria and percentage weights. Regarding to the. 1. The instructor taught the digital library editing software,. Ulead. Video. 11. to. all. other 50% weights of “Wants”, the first expert. the. considered that completely structure, creativity and. participants.. objects matching level were needed in project. 2. The participants in each group went to the. contents, and their percentage weights were 15%,. TWU library to collect images.. 20% and 15% respectively. The second expert. 3. The group members discussed the digital. thought that difficulty level, creativity and interface. library guide contents in order to design the. design. digital library guide system.. (visual. and. verbal. presentation). were. important in a design, and their percentage weights. 4. The group members cooperated to make the. were 15%, 20% and 15% respectively. Finally, the. digital library guide movies and upload the. third expert thought that fluent expression, creativity. final work to the instructor on the web.. and guide logic were the main items in expressive. Evaluation. functions, and their percentage weight were 15%, 20% and 15%.. After each group finished uploading their. In this research, reliability, correlation and KTA. system, three experts evaluated each digital library. analysis results will be discussed. Using reliability. guide design. According to the KTA decision models,. can confirm the TSIS and computer self-efficiency. the alternative with the highest score from three. questionnaires. experts’ evaluation and 60 digital library users. suitable. to. the. designers.. The. correlation coefficient between factors of TSIS and. evaluation was selected. The percentage weights. computer self-efficiency can reveal significant effects. were 30% for each instructor and 10% for the users.. and relationship. In order to select the best digital. The three experts had plentiful experience in activity. library guide, KTA was applied in this paper. Because. projects, multimedia design, and news reporting.. the TSIS has been applied only in Norway and Italy,. Regarding to KTA Decision Analysis Worksheets. the contribution of this paper might be to promote. (Table 1), total percentage weight of the “Must” was. TSTS to the designers’ social intelligence in TWU. 50%. In “Must”, the percentage weight of project. digital library in Taiwan.. contents, design skills, and expressive functions are. 5.

(6) 圖書與資訊學刊. 第 3 卷第 4 期(第 79 期). Table 1 Decision Analysis Worksheets Must. Expert 1. Contents Skills Functions Wants. Expert 2. 15% 15% 20% completely structure creativity objects matching level. 15% 20% 15%. Expert 3. 15% 15% 20% difficulty level creativity interface design. 15%. 15% 15% 20% fluent expression. 15%. 20% 15%. creativity guide logic. 20% 15%. Total weighted Score. Results. eigenvalue at 5.52. They explain 19.88%, 18.72% and 17.81% of the variance, respectively.. Results of Factor Analysis. Results of Reliability analysis. A principal component analysis, with varimax rotation, was conducted on the 21 items of the TSIS.. In TSIS there are three factors such as SP, SS,. Similar to the results of the Silvera, Martinussen. and SA. Internal reliability for each of the three. and Dahl (2001) and Gini (2006), three factors were. factors. extracted. The social information process (SP) had. coefficients.. its eigenvalue at 4.39, the social skill (SS) had its. and acceptable levels of reliability for the three. eigenvalue at 3.89 and the social awareness (SA). factors of TSIS: SP (α=0.80), SS (α=0.64) and SA. had its eigenvalue at 3.40. The three factors. (α=0.71). In addition, the reliability of the three. explained 20.92%, 18.52% and 16.19% of the. subscales in computer self-efficiency is also. variance, respectively. The factor analysis was also. acceptable (see Table 3). Table 3 shows the factors. applied. computer. loadings and acceptable levels of reliability for the. self-efficiency. Three factors were extracted. The. three factors of computer self-efficiency: Basicski. beginning level computer skills (Basicski) had its. (α=0.92),. eigenvalue at 6.16, the advanced level computer. (α=0.61). Because the the reliability of the item 8:. skills (Advanski) had its eigenvalue at 5.80, and the. Logging off the mainframe computer system was. mainframe computer skills (Mainfram) had its. lower than 0.6, it was deleted at this stage.. on. the. 32. items. of. the. 6. is. evaluated. using. Cronbach’s. alpha. Table 2 shows the factors loadings. Advanski. (α=0.91). and. Mainfram.

(7) Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library. Table 2 Reliability analysis of The Tromsø Social Intelligence Scale TSIS Items. Loading. SP subscale. Alpha 0.80. 1. I can predict other peoples’ behavior.. .799. 2. I know how my actions will make others feel.. .788. 6. I understand other peoples’ feelings.. .719. 9. I understand others’ wishes.. .741. 14. I can often understand what others are trying to accomplish without the need for them. .739. to say anything. 17. I can predict how others will react to my behavior.. .481. 19. I can often understand what others really mean through their expression, body. .641. language, etc. SS subscale. 0.64. 4. I often feel uncertain around new people who I don’t know.. .491. 7. I fit in easily in social situations.. .587. 10. I am good at entering new situations and meeting people for the first time.. .733. 12. I have a hard time getting along with other people.. .775. 15. It takes a long time for me to get to know others well.. .512. 18. I am good at getting on good terms with new people.. .468. 20. I frequently have problems finding good conversation topics.. .737. SA subscale. 0.71. 2. I often feel that it is difficult to understand others’ choices.. .542. 5. People often surprise me with the things they do.. .564. 8. Other people become angry with me without me being able to explain why.. .577. 11. It seems as though people are often angry or irritated with me when I say what I think.. .737. 13. I find people unpredictable.. .647. 16. I have often hurt others without realizing it.. .767. 21. I am often surprised by others’ reactions to what I do.. .606. 7.

(8) 圖書與資訊學刊. 第 3 卷第 4 期(第 79 期). Table 3 Reliability analysis of Computer Self-Efficiency subscales Computer Self-Efficiency Items. Loading. Beginning Level. Alpha 0.92. 5. Using the directory.. .568. 20. Adding and deleting information from a data file.. .862. 7. Escaping/ Exiting from the program/ software.. .534. 19. Coping an individual file.. .845. 18. Coping a disk.. .808. 15. Making selections from an onscreen menu.. .688. 21. Moving the cursor around the monitor screen.. .836. 17. Using a printer to make a “hardcopy” of my work.. .702. 23. Using the computer to write a letter or essay.. .646. 12. Handling a floppy disk correctly.. .730. 6. Entering and saving data (numbers or words) into a file.. .504. 27. Storing software correctly.. .518. 30. Getting rid of files when they are no longer needed.. .638. 1. Working on a personal (microcomputer).. .781. 2. Getting the software up and running.. .710. 9. Calling-up a data file to view on the monitor screen. 31. Organizing and managing files.. .522 .686. Advanced Level. 0.91. 28. Explaining why a program(software) will or will not run on a given computer.. .741. 32. Troubleshooting computer problems.. .688. 22. Writing simple programs for the computer.. .623. 24. Describing the function of computer hardware (keyboard, monitor, disk drives,. .475. computer processing unit). 10. Understanding terms/ words relating to computer hardware.. .670. 11. Understanding terms/ words relating to computer software.. .652. 25. Understanding the three stages of data processing: input, processing, output.. .620. 13. Learning to use a variety of programs (software).. .685. 26. Getting help for problems in the computer system.. .636. 14. Learning advanced skills within a specific program (software).. .572. 29. Using the computer to organize information.. .814. 16. Using the computer to analyze number data.. .620. Mainframe Computer Skills. 0.61. 3. Logging onto a mainframe computer system.. .556. 4. Working on a mainframe computer.. .338. 8.

(9) Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library. Results of Correlation. significantly correlated with Advanski, and Advanski is correlated with Mainfram. Most especially, the. Correlation coefficients among TSIS subscales. magnitude of the correlation is high (r=0.74 between. and between TSIS subscale and Basicski are shown. Basicski and Advanski). In short, the TSIS and. in Table 4. This table shows that the TSIS subscales. computer self-efficiency can be reliably applied to. are significantly correlated with each other and with. digital library designers in Taiwan. When the. the Basicski. Correlation coefficients among the. designers are good at the basic computer skill, they. computer self-efficiency subscales are shown in. have good social intelligence.. Table 5. This table shows that Basicski is. Table 4 Correlation coefficients among TSIS subscales and the Basicski scale Basicski. SP. SS. SA. SP. .225. 1.0. .652**. .437**. SS. .311*. .652**. 1.0. .687**. SA. .092. .437**. .687**. 1.0. Basicski= beginning level computer skills; N=43.* p<.05, ** p<.01 (two-tailed test).. Table 5 Correlation coefficients among subscales of Computer Self-Efficiency. Basicski. Basicski. Advanski. 1.000. .739**. .227. 1.000. .381*. Advanski Mainfram. Mainfram. 1.000. Basicski= beginning level computer skills; Advanski =advanced level computer skills; Mainfram=mainframe computer skills; N=43. * p<.05, **p<.01 (two-tailed test).. Results of KTA technique. project and 60 users’ voting were added to decide the best library guide design. Three experts and digital. After designers finished their digital library. library users’ scores are shown in Table 6.. guide work, three experts evaluated 12 groups’. 9.

(10) 圖書與資訊學刊. 第 3 卷第 4 期(第 79 期). Table 6 KTA scores of the twelve digital library design Group. Experts average. Users evaluation. Total score. Rank. 1. 59. 1. 60. 12. 2. 65. 3. 68. 8. 3. 83. 10. 93. 1. 4. 73. 6. 79. 5. 5. 70. 5. 75. 6. 6. 82. 9. 91. 2. 7. 77. 7. 84. 3. 8. 74. 8. 82. 4. 9. 64. 2. 66. 9. 10. 61. 1. 62. 10. 11. 60. 1. 61. 11. 12. 67. 4. 71. 7. digital library designers is higher than the average,. Discussion. the group will produce better digital design work.. From Table 6 it appears that group 3 is the best. Conclusions. digital library guide designer. Furthermore, the performance of group 3 is 10% higher than the other. This research applied TSIS and computer. 10 groups (except the group 6). Thus, the final library. self-efficiency to the digital library designers in an. guide selected by using KTA is group 3.. university library in Taiwan. The KTA analysis was. Because the performance of group 3 was 10%. applied to select the best digital library design. The. higher than the other 10 groups, this research tried to. factor analysis, reliability analysis and correlation. investigate the relationship between TSIS and KTA. analysis were applied. The factor analysis used the. scores. The average scores of the SP, SS and SA. same factors with that of previous researches in TSIS. subscales for the 12 groups were calculated, and the. and computer self-efficiency. The reliability analysis. average values generated from regression factor. showed good reliability in subscale of the TSIS and. scores by using SPSS 10 were 0.058, 0.196 and 0.183. computer self-efficiency. The correlation analysis. respectively. The score of the group 3 for the SP, SS,. showed the positive correlated among the TSIS. and SA subscales were 0.243, 0.486 and 0.395. The. subscales and between the basic level of computer. TSIS scores of group 3 were better than the average. self-efficiency and the three TSIS subscales. Finally,. values. Therefore, if the social intelligence of the. the KTA was applied to collect digital library guide. 10.

(11) Adaptation of the Tromsø Social Intelligence Scale to the Digital Library Guide Designers: A Case Study of the Transworld University Library. movies scores to decide the final alternative design.. digital library guide.. The result shows that if all the designers are good at (收稿日期:2011 年 7 月 7 日). the basic computer skill, they have good social intelligence, and therefore they can design better. References Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. NJ: Prentice-Hall, Inc. Bjorkqvist, K., Osterman, K., & Kaukiainen, A. (2000, March). Social intelligence – empathy = aggression? Aggression and Violent Behavior, 5 (2), 191-200. Gardner, H. (1993). Frames of mind: The theory of multiple intelligences. New York: Basic Books. Gini, G. (2006). Brief report: Adaptation of the Italian version of the Tromsø Social Intelligence Scale to the adolescent population. Journal of Adolescence,29 (2), 307-312. Goleman, D. (1995). Emotional intelligence. New York, NY: Bantam Books. Goleman, D. (2007)。SQ-I-You共融的社會智能(Social Intelligence: The New Science of Human Relationships) (閻紀宇 譯)。臺北市:時報出版。 Hatch, T., & Gardner, H. (1993). Finding cognition in the classroom: An expanded view of human intelligence. In G. Salomon (Ed.), Distributed cognitions: Psychological and educational considerations (pp.164-187). Cambridge: Cambridge University Press. Kosmitzki, C., & John, O. P. (1993). The implicit use of explicit conceptions of social intelligence. Personality and Individual Differences, 15 (1), 11-23. Lazear, D. (2000)。落實多元智慧教學評量(Multiple Intelligence Approaches to Assessment: Solving the Assessment Conundrum)(郭俊賢、陳淑惠譯)。臺北市:遠流。 Murphy, C.A., Coover, D., & Owen, S.V. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49 (4), 893-899. Owen, S. V. (1986). Using self-efficiency in program evaluation. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA. Silvera, D. H., Martinussen, M., & Dahl, T.I. (2001). The Tromsø Social Intelligence Scale, a self-report measure of social intelligence. Scandinavian Journal of Psychology, 42 (4), 313-319.. 11.

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