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AWERProcedia Information Technology & Computer Science Vol 03 (2013) 1198-1203

3rd World Conference on Information Technology (WCIT-2012)

Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method Ecem Basak *, Istanbul Technical University, Istanbul, 34367, Turkey. Cigdem Kadaifci, Istanbul Technical University, Istanbul, 34367, Turkey. Fethi Calisir, Istanbul Technical University, Istanbul, 34367, Turkey. Suggested Citation: Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-education-center.org/index.php/P-ITCS rd Proceedings of 3 World Conference on Information Technology (WCIT-2012), 14-16 November 2012, University of Barcelon, Barcelona, Spain. Received 9 Feburary, 2013; revised 14 May, 2013; accepted 18 September, 2013. Selection and peer review under responsibility of Prof. Dr. Hafize Keser ©2013 Academic World Education & Research Center. All rights reserved. Abstract Personal digital assistant (PDA) is a miniaturized portable hand-held computer that helps to compute and store information for personal or business use. PDAs help medical students to use their time more efficiently and accurately. In this paper, we propose a modified technology acceptance model (TAM) to identify the factors shaping the acceptance of PDA technology by medical students in Turkey. In order to analyze the model, we suggest using the Fuzzy DEMATEL method. The proposed model provides a causative representation of the technology acceptance in an uncertain environment and the results illustrate the strongest determinants that influence medical students into accepting PDA technology for medical education. Keywords: Personal Digital Assisstant (PDA), Technology Acceptance Model (TAM), fuzzy DEMATEL;

* ADDRESS FOR CORRESPONDENCE: Ecem Basak, Istanbul Technical University, Istanbul, 34367, Turkey, E-mail address:

[email protected]

Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-educationcenter.org/index.php/P-ITCS

1. Introduction Personal digital assistant (PDA) is a miniaturized portable hand-held computer that helps to compute and store information for personal or business use [1]. They have become a useful resource for medical students, residents, and faculty physicians due to the increase of complex and vast amounts of information in medical education [2]. Because of the need to reach medical information rapidly and review the updated data at any moment, medical education relies heavily on mobile technology in today’s world [3]. PDAs provide different ways of learn and practice medicine. In medical education, they are being commonly used as an electronic library, for patient tracking, drug prescribing and clinical decision making [2–4]. Hence, it is estimated that PDAs help medical students to use their time more efficiently and accurately. Consequently, PDA technology may increase medical students’ performance in both theoretical learning and real-time practice. In this paper, we identify the critical factors shaping the acceptance of PDA technology by medical students in Turkey. Technology acceptance model (TAM) [5] is proposed as our research model in this study to understand the acceptance of PDA technology. The classical TAM is well established for the determination of relationships among perceived usefulness (PU), perceived ease of use (PEU), attitude toward use (AU), and behavioral intention to use (BI) a new technology. However, we modify the original TAM by introducing external variables because of the needs of advanced research. Later, in order to analyze the critical factors playing a key role in the acceptance of PDA technology, we suggest using Fuzzy DEMATEL method, which provides a model and a visualization of complex network of cause-effect relationships in fuzzy environment. In conclusion, this study may further play a role in the implementation of PDA technology in medical schools and reveal the remarkable facts that affect PDA usage of medical students. 2. Research Model TAM which is an adaptation of Theory of Reasoned Action (TRA) [6], is developed in order to determine the user’s perspective of the acceptance of information technology [5]. TAM is formed by the PEU, the PU, the AU, and the BI. The PEU is defined as “the degree to which a person believes that using a particular system would be free of effort,” while the PU is defined as “the degree to which a person believes that using a particular system would enhance his or her performance” [7]. According to the model, the PEU and the PU are key estimators of BI through the AU. If users think that a particular technology is easy to use and that it plays a significant role in increasing their job performance, they will show a better attitude about using that technology [7]. When medical students see that PDA technology facilitates learning in a theoretical setting and helps them to provide a better healthcare in a practical setting, they may tend to adopt PDA technology in medical education. Apart from classical TAM, we propose extending the model in this study by introducing external variables, as mentioned in the introduction. Among these external variables, subjective norm (SN) is one of the major factors that determine user behavior. Subjective norm is “the person’s perception that most people who are important to him think that he should or should not perform the behavior in question” [6]. If a colleague or a friend suggests that PDA technology in education is beneficial, students may believe that use of PDA is actually positive in medical training and they may intend to use it. During educational stage, students are commonly influenced by the opinions of their professors. They may feel that their professors expect them to use the PDA technology for educational purposes and that expectation may motivate students to start using a PDA. Another external variable is perceived enjoyment (PE) that refers to “the extent to which the activity of using the computer is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated” [8]. Students may have a favorable attitude if they enjoy while using a PDA but they may also feel lack of enjoyment if they perceive the use of PDA as requiring more effort. Therefore, it may 1199

Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-educationcenter.org/index.php/P-ITCS

be asserted that PE affects the AU and gets affected by PEU. Compatibility (C) is an another external variable represented in the literature and is defined as “the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters” [9]. If students have an experience of PDA technology in the past, they will easily adapt to new technology. Moreover, the students will be more likely to use PDA if they regard it as being compatible with their medical education. Result demonstrability (RD) also plays a role in the acceptance of a new technology. It refers to “the tangibility of the results of using the innovation” [10]. RD may have a positive effect upon PU, because even if PDA technology is an effective system in medical education, students perceive inconvenience when they do not experience the advantages of using a PDA. Hence, if the results of PDA technology are easily apparent to the medical students, they may better see the benefits of using that technology and may tend to use it. Finally, computer anxiety (CA) is the last external variable in our research model. It is “a form of state anxiety and is an irrational emotional distress which is experienced by an individual when using or considering the use of computer technology” [11]. If students feel uncomfortable while using a PDA, their perception about the complexity of that technology is more likely to be increased. Their discomfort level causes lower degree of ease of PDA usage. Figure 1. gives the illustrative representation of relationships among factors.

SN

RD

PU

C

CA

AU

PEU

BI

PE

Figure 1. Research model

3. Fuzzy DEMATEL The decision-making trial and evaluation laboratory (DEMATEL) method, developed by the Science and Human Affairs Program of the Battelle Memorial Institute of Geneva between 1972 and 1976 [12] was aimed at the fragmented and antagonistic phenomena of world societies and searched for integrated solutions [13]. The model is used for presenting the complex structure of causal relationships between factors with diagraphs or matrices [14] without considering the assumption that factors are mutually exclusive [15]. Since we suggest using the fuzzy DEMATEL method, which extends the classical method using crisp values to an uncertain linguistic environment, its main steps are summarized as follows [12–14, 16]; Step 1: Defining the decision goal and forming a committee of experts. Step2: Determining the factors of model and designing the fuzzy linguistic scale indicating the degree of direct influence. The linguistic terms used to represent the six different levels of influence 1200

Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-educationcenter.org/index.php/P-ITCS

are “No Influence” (No), “Very Low Influence” (VL), “Low Influence” (L), “Moderate Influence” (M), “High Influence” (H), and “Very High Influence” (VH). Step 3: Calculating the average matrix à which is an nxn matrix includes the view of experts related to the influence and direction between factors. à is also called the initial direct-relation matrix and all ãij elements are triangular fuzzy numbers, such as ãij = (lij, mij, uij). Step 4: Obtaining the normalized direct relation matrix maximum row total of à matrix.

through Equation 1 where s is the (1)

Step 5: The total relation fuzzy matrix is obtained through Equation 2 where I is the identity matrix. , which is the sum of the normalized ith column of matrix , represents the sum of the influence that the factor i receives from other factors. (2)

Suppose that

then, (3)

Step 6: Calculating the sum of rows

and the sum of columns

of total relation matrix .

Step 7: Drawing the causal map by using the calculated and values represent the horizontal axis and vertical axis, respectively. The calculated and values are turned into crisp values (denoted by def) by using the CFCS (Converting Fuzzy data into Crisp Scores) method. If the value of is positive, then the factor belongs to the cause group. If the value of is negative, then the factor belongs to the effect group. shows how important the factor is. 4. Analysis

AU

BI

PEU

PE

C

SN

CA

RD

PU AU BI PEU PE C SN CA RD

PU

Table 1. Factors and their pairwise relations in terms of aggregate linguistic assessment data.

No No VH No H H No H

H No H VH No No No No

H No No H No H No No

No No No No H No M No

No No No H No No No No

No No No No No No No No

No No No No No No No No

No No No No No No No No

No No No No No No No No -

As explained above, in this study, we aim to explore the factors shaping the acceptance of PDA technology by medical students in Turkey. To do this, experts who have the knowledge and experience of PDA technology for medical education were involved in the assessment of the strength of 1201

Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-educationcenter.org/index.php/P-ITCS

influences by means of fuzzy linguistic terms. In Table 1, the direct causal relationships among factors including the strengths are indicated. The overall influence and dependence values of the factors are determined by applying the equations (1)-(3) and the CFCS method. As represented in Table 2, D values representing the cause, which is the sum of impacting other impacting variables, and R values representing the effect, which is the sum of being impacted by other variables, are calculated by utilizing the total relation matrix, T. Table 2. The results of Fuzzy DEMATEL.

1,000 1,338 5,149

-2,770 -0,538 1,379

1,990

-0,558

0,680 0,975 4,334

-3,104 -0,975 0,550

1,570

-1,008

0,583 0,842 4,192

-2,962 -0,842 0,647

1,438

-0,895

0,863 1,190 4,800

-1,360

0,490 2,577

1,818

0,449

0,538 0,720 3,875

-1,446

0,180 1,892

1,288

0,158

0,437 0,648 3,775

-0,793

0,648 2,545

1,206

0,649

0,345 0,480 3,471

-0,885

0,480 2,241

1,011

0,493

0,161 0,276 3,006

-1,068

0,276 1,776

0,746

0,269

0,195 0,280 3,046

-1,035

0,280 1,816

0,758

0,284

Figure 2. The causal diagram of factors.

After summing up the prominence and the relation , divided by the 9 variables to receive the mean, the means are 1.32 and 0.018, respectively. By dividing the causal diagram Figure 2. into four quadrants, the factors can be separated into four different areas in order to evaluate their role in our system. On the one hand, the PEU can be seen in the first quadrant, and is the only key factor in terms of both influence and dependence. On the other hand, with high prominence, but low relation, the PU, the BI, and the AU are the core factors impacted by other conditions. The results also indicate that in the long run, the acceptance of the PDA usage in medical education may largely depend on the PU. The C, the SN, the PE, the CA, and the RD are the cause factors in quadrant II, with lower prominence. It means that these variables impact other variables. Quadrant III includes the factors with the lowest importance and impact, and for the proposed model, there is no factors in this quadrant. 5. Conclusions TAM suggests that the BI is affected by the external variables, the PU, the PEU and the AU. TAM provides a further understanding of the casual relationship and mutual effects among variables related to technology acceptance. Therefore, this study reveals the dominant factors influencing the acceptance of PDA usage by medical students in Turkey. It is demonstrated that Fuzzy DEMATEL analyzes the complex structure of acceptance of PDA and provides a more efficient decision-making process for the integration of PDA technology into medical schools. References [1] [2] [3]

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Basak, E., Kadaifci, C. & Calisir, F. Analysis of Factors That Affect PDA Use Among Medical Students in Turkey using Fuzzy DEMATEL Method, AWERProcedia Information Technology & Computer Science. [Online]. 2013, 3, pp 1198-1203. Available from: http://www.world-educationcenter.org/index.php/P-ITCS

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