October 2011 Volume 14 Number 4 - Educational Technology ...

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the outcome satisfaction. Although the counter-arguments interrupt the decision-making process by allowing decision makers to consider both positive and negative opinions suggested by the system, the decision maker is predicted to report satisfaction toward their decision. Therefore, we hypothesize the following: Research methods H2a: Subjects who use DSS with computer-mediated counter-argument will feel less satisfied about the decision-making process. H2b: Subjects who use DSS with computer-mediated counter-argument will feel more satisfied about the decision-making outcome. An experiment was conducted to test the listed hypotheses. Participants were assigned randomly into two groups, with/without computer-mediated counter-argument. They were asked to accomplish a stock-investment task using the DSS provided by the authors. A stock-investment task was selected because DSS are intensively adopted to support stock investment decision making to cope with high uncertainty and process data in large quantities. In general stock-investment decision-making tasks, subjects are allowed to invest certain amounts of money in one or more selected investing targets. Real decision making is more complex, and the final investment portfolio may contain several combinations of investments. Since this study focuses on understanding learning effects only, a simplified investment environment was constructed. That is, people were requested to invest their money in two companies belonging to different industries instead of among all available companies in the open market. The stock-investment task used in this paper was modified from Melone, McGuire, Hinson, and Yee (1993). Subjects were requested to put the given amount of money into two different stocks. To maximize their return, subjects allocated that money into two different options (a company in the financial holding industry or high-tech industry) based on whatever subset they deemed appropriate. DSS with “what if” analysis was provided as a decision aid. The system provided basic market information and current market status (with news format). Basic market information included the name of company, capital, business scope, expected ROI in the next five years, and stock price for the past five years. Current market status included positive and negative information about these two companies and the industries in which they belong. Information was summarized from articles published in investing-related journals and magazines. Although the investment information presented in this experiment was collected from real financial news, events, and reports, the content was reviewed and modified by two business-school PhD candidates. We removed the names and brand names that appeared in the original news report to avoid any inappropriate connection between the experiment and real-world events. Further, we refined the wording of news titles and news content. The length of the presented news headlines and story bodies were condensed to 10–20 words and 150–200 words, respectively. The content validity was then assured by eight financial professionals, including professors, experienced investors, senior managers in the high-tech industry, and accountants. News with ambiguous titles or content was dropped or modified. The direction (positive or negative) and importance of each piece of news and the accompanying headline was determined based on opinions provided by the above eight financial professionals. Measurement User satisfaction includes two major dimensions: satisfaction toward the system and toward the decision making (Sanders and Courtney, 1985). Since this study focused on the new function, namely counter-argument provided by the DSS, several questions were used to understand users’ attitude toward the DSS. A total of three questions adopted from Sanders and Courtney (1985) were used to measure subjects’ satisfaction with the DSS. On the other hand, three questions adopted from Green and Taber (1980) were used to measure satisfaction toward the decisionmaking process. 115
Learning in this study refers to, with regard to DSS use, participants’ using the information to challenge their assumptions or using the information to maintain their initial beliefs. A total of six questions obtained from (Vandenbosch & Higgins, 1996) were used to measure learning effects: three for mental-model maintenance and three for mental-model building. The measurement uses a seven-point Likert scale ranging from 1 (strong disagree) to 7 (strong agree). Manipulation check Since we wanted to manipulate the effect of with and without counter-argument, we asked subjects whether or not they were aware of the pop-up window showing counter-argument information during the experiment. We found that 90 subjects in the group with CMCA were aware and only two subjects were not; and that 86 subjects in the group without CMCA were not aware (or could not recall) and only nine subjects were. The result of subjects’ awareness is shown in Table 1. Table 1. Results of subjects’ awareness Yes Awareness No Could not recall Total number Computer-mediated w/o 9 71 15 95 Counter-argument w 90 1 1 92 Total number 99 72 16 187 According to a reading-behavior study by using eye-tracking machines, in a two-column condition, people tend to focus on content that appears on the left-hand side first. Since the information for these two companies appeared in a two-column format, we randomized the location of the messages to avoid the possible confounding effect. As shown in Table 2, the location of the news and whether or not there was CMCA are independent. Table 2. Results of subjects in different information displayed location Location of displayed information Computer-mediated counter-argument w/o w Total number of subjects IT-related news on the left-hand side 51 45 96 IT-related news on the right-hand side 44 47 91 Total number of subjects 95 92 187 Table 3. DSS functions (Hung et al., 2007) Menu Function Market summary Detailed information on the stock market, including stock quotes, change, day’s range, volume, etc. Industry quotes Detailed information on the specific industries. Company information Provided information on six companies used for trading in the experiment, including basic information, historical prices, news, and streaming charts. Technical analysis Analyzed technical aspects, such as the moving average, relative strength index, and stochastic line indicators. Recent news Provided three categories of news: political, international, and financial. Calculator Calculated investment returns and more. System A GUI-based DSS, with 4GL programming language and a relational database management system, was developed for the experiment. The system was able to support Simon’s decision processes, which allow people to perform intelligence, design, and choice activities. Actual design activities followed Hung, Ku, Liang, and Lee’s recommendations (2007), and the detail system tools are shown in Table 3. Furthermore, the purpose of this study was to understand how users’ information-reading behaviors affected their final decision. To support this, a total of 5 to 15 positive and 5 to 15 negative message titles about each company were displayed on the main page for the noninformation-loading group. After users clicked on the message title, the system popped up an “always on top” screen, 116
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October 2011 Volume 14 Number 4
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Supporting Organizations Centre for
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Time-Quality Tradeoff of Waiting St
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Ibáñez, M. B., García, J. J., Ga
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Situated learning. It states that k
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executed in the client, the server
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The participants were twelve non-na
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Huang, H. M., Rauch, U., & Liaw, S.
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Theoretical background Feedback, is
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There are already a number of tools
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output used were blogs, written by
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Question Table 2: Perceived Relevan
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Black, P., & Wiliam, D. (2009). Dev
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detection, and analysis of affectiv
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experience is a suitable method of
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Collins, 1998). The appraisal theor
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encompasses the finer shades of an
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and can also track faces with glass
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Acknowledgements This research was
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Merill, D. C., Reiser, B. J., Traft
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to the above-discussed issues of th
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The annotation part of the SDM onto
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that enables the office users to ac
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Figure 4. Semantic document browser
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to the group’s shared semantic do
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participants performed less mouse c
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Bastili, V.R., Gianluigi, C., & Rom
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esource contribution, enabling conv
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Semantic Search In contrast to the
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Participation: P i i i NiVadd Vde
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and comment on each page as well. T
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Table 1. Questionnaire results (N=2
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propose for him, as well as calenda
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Discussion and Conclusion Collabora
Page 69 and 70: Sampson, D. G., & Zervas, P. (2011)
Page 71 and 72: Obtaining: the first step of the li
Page 73 and 74: process (Palmer & Richardson, 2004)
Page 75 and 76: and ratings (the use of star rating
Page 77 and 78: (K1) is the number of non-reusable
Page 79 and 80: Case 3: The process of reusing a se
Page 81 and 82: Washizaki, H., Yamamoto, Y. & Fukaz
Page 83 and 84: to examine determinants for pre-ser
Page 85 and 86: Overview of the model The first res
Page 87 and 88: significance of relationships. All
Page 89 and 90: Discussion This study represents a
Page 91 and 92: Davis, F., Bagozzi, R., & Warshaw,
Page 93 and 94: Ko, C.-C., Chiang, C.-H., Lin, Y.-L
Page 95 and 96: Interestingly, the Universal Design
Page 97 and 98: Figure 1. Framework of the TriAcces
Page 99 and 100: Experiment This experiment aimed to
Page 101 and 102: Table 2. Descriptive statistics for
Page 103 and 104: Foulds, R., & Camacho, C. (2003). T
Page 105 and 106: answer. However, students can choos
Page 107 and 108: Hartley & Collins-Brown, 1999; Morl
Page 109 and 110: Subjects Figure 4. Partial misconce
Page 111 and 112: correct for a four-option MC item i
Page 113 and 114: from −3 to 3 for any four-option
Page 115 and 116: Kansup, W. (1973). A comparison of
Page 117 and 118: The theory of mental models explain
Page 119: computer-mediated counter-arguments
Page 123 and 124: the experiment process was anonymou
Page 125 and 126: supported. However, significant dif
Page 127 and 128: Cannon-Bowers, J. A., Salas, E., &
Page 129 and 130: Lee, Y.-H., Hsieh, Y.-C., & Hsu, C.
Page 131 and 132: Many researchers have conducted emp
Page 133 and 134: Trialability Some studies have empi
Page 135 and 136: Results Instrument validation Two c
Page 137 and 138: In this study, Amos 6.0 was employe
Page 139 and 140: Our results strongly supported the
Page 141 and 142: Fornell, C., & Larcker, D. F. (1981
Page 143 and 144: Kimmerle, J., Moskaliuk, J., & Cres
Page 145 and 146: What becomes clear from this short
Page 147 and 148: Figure 1. Distribution of informati
Page 149 and 150: Results In order to test the hypoth
Page 151 and 152: esults of the present study with th
Page 153 and 154: Kolbitsch, J., & Maurer, H. (2006).
Page 155 and 156: A conceptual framework of this stud
Page 157 and 158: eveal positive effects on students
Page 159 and 160: learning resources; and able to acc
Page 161 and 162: Discussion This study suggests that
Page 163 and 164: 146). Also, role of constructivist
Page 165 and 166: eform strategy, namely, the MOE-Int
Page 167 and 168: McNaughton, S. (2002). Meeting of m
Page 169 and 170: Wu, T.-T., Sung, T.-W., Huang, Y.-M
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Ubiquitous English-Reading Learning
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include the number of times and ran
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initial value for the predetermined
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The following Eq. (18) expresses th
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Limitations This experiment adopted
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Table 3 shows the analysis of the p
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enhance learning outcomes, it impor
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Ogata, H., & Yano, Y. (2004a). Cont
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Communication seems to be more effe
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the audience only listened, one whe
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Step 5) Writing the story On the ba
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As indicated in Table 2, the differ
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References Armstrong, S. (2003). Th
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Goh, T.-T. (2011). Exploring Gender
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OPAC has been transformed into AirP
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Perceived Self-Efficacy Figure 3. H
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were asked to rate their confidence
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(2001). The correlation table begin
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Discussion and Implications Note. S
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will become important to identify i
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Parker, A. (2007). SMS - Its use in
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Find the perimeter of the rectangle
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Wait Time Management Issues related
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Precision Reduced_Precision ( T T0
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learning concept. If the Specialty
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Two criteria have been adopted to e
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Reduced Recall 0.07 0.06 0.05 0.04
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In this work, both recall-oriented
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Tsai, C.-C., Chuang, S.-C., Liang,
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confidence and self-belief in their
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Peng et al. (2006) To explore ISE &
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Torkzadeh, Chang, and Demirhan (200
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educational level, locus of control
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Internet-based learning self-effica
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Though Lee and Lee (2008) did not d
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Regarding the category of ISE resea
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Bandura, A. (1997). Self-efficacy:
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Pintrich, P. R., & de Groot, E. V.
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In formal learning, Safran, Helic,
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that culture is essential when user
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Table 3. Analysis of usage frequenc
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7 1.16 137.73 0.25 0.29 0.25 Social
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discussions freely. So Korean stude
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Johnson, L., Levine, A., & Smith, R
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Figure 1. The UE Faculty Web Portal
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2006), and consistency (Sindhuja &
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Independent Variables Dependent Var
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Meanwhile, as shown in Table 4, Ava
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design methods in the development o
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Pearson, J. M., & Pearson, A. (2008
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Clewley, N., Chen, S. Y., & Liu, X.
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As shown in this Table, Holists wil
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satisfaction or dissatisfaction wit
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8 I would prefer to learn from huma
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the examples need to be more practi
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Brotherton, J. A,. & Abowd, G. D. (
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Cobos, D. L. (2011). Book review: T
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