Understanding the values of mobile technology in education

Understanding the Values of Mobile Technology in Education: A Value-Focused Thinking Approach

Hong Sheng Department of Business and Information Technology Missouri University of Science and Technology Keng Siau College of Business Administration University of Nebraska-Lincoln Fiona Fui-Hoon Nah College of Business Administration University of Nebraska-Lincoln

Abstract

Mobile technology has mobilized the human interaction in all dimensions by supporting mobile collaboration. As collaboration is key to learning in today’s educational environment, mobile technology has tremendous potential in supporting and improving education and its delivery. Given that mobile technology for education is a new phenomenon that is gaining popularity, the values of using mobile technology to support education need to be further researched and better understood. In this research, we used the Value-Focused Thinking approach to interview students and instructors to identify the values of education that are enabled by mobile technology. These values are represented in the form of a means-ends objective network that not only captures the values of education facilitated by mobile technology but also depicts the relationships between these values. The means-ends objective network derived from this research can serve as a conceptual foundation for future studies and provide useful guidelines to practitioners for implementation of mobile technology in education.

ACM Categories: C.1.3 Cellular Architecture; K.3.1 Collaborative learning.

Keywords: mobile technology, collaborative learning, means-ends network, value-focused thinking

Introduction

Rapid advancements in mobile technology have accelerated the use of wireless networks and handheld devices in educational settings and presented tremendous opportunities to both educators and students (Massey et al., 2006; Hoppe et al., 2003; Farooq et al., 2002; Milrad et al., 2002). Mobile technology can extend access for desktop-based online environment to handheld devices to support delivery of education anytime and anywhere. This phenomenon is called “mobile education” or “M-Education” (Farooq et al., 2002). Mobile education can be defined as “using any service or facility to provide a learner with general electronic information and educational content that aids in the acquisition of knowledge regardless of location and time” (Lehner & Nosekabel, 2002, p.103).

Utilizing wireless networks and handheld devices, mobile education presents a lot of promise in supporting and improving teaching and learning (Eschenbrenner & Nah, 2007). Educational materials can be delivered via SMS (Short Message

The DATA BASE for Advances in Information Systems 25 Volume 41, Number 2, May 2010

Service) using mobile devices (Hoppe et al., 2003); handheld devices such as PDA (Personal Digital Assistant) can be connected through a wireless network in the classroom to enable cooperative learning (Davis, 2002); mobile technology can be implemented to create ad hoc and mobile classrooms where learning can take place either indoor or outdoor, even while students are traveling (Chang et al., 2005; Chen et al., 2002).

The delivery of educational materials through mobile technology can eliminate time and space constraint in learning and provide more freedom for learners. Mobile education, therefore, has the potential to bridge the gap between mobile and desktop computing and enable learning to take place anytime and anywhere (Farooq, et al., 2002). Mobile technology not only provides features and functions that support communication, collaboration, and knowledge exchange (Davis, 2002) but also provides opportunities to discover and exchange ideas through the wireless medium, thus greatly facilitating collaborative learning (e.g., Farooq et al., 2002; Milrad et al., 2002).

Mobile education has also received much attention from the academics. Prior research has examined the design of mobile education systems (e.g., Chang et al., 2005), reported on various mobile education projects across the world (e.g., Eschenbrenner & Nah, 2007; Mitchel & Race, 2005; Milrad et al., 2002; Smordal et al., 2002), and evaluated the impact of using mobile technologies to support teaching and learning (e.g., Siau et al., 2006; Relan et al., 2004; Crawford & Vahey, 2002).

As the success of any information technology application relies on users’ attitudes and perceptions towards the application (e.g., Davis et al., 1989; Taylor & Todd, 1995), we need to understand the benefits, problems, and limitations of using mobile technology in educational settings to discover issues that are important for the adoption and diffusion of mobile education applications as well as to provide implications and guidelines for future development of mobile education applications. In addition, we need to gain a better understanding of how mobile technology can be used to facilitate and support collaborative learning. Collaboration and teamwork have been shown to be keys to effective learning (Alavi, 1994; Mayers, 1995).

The paper is organized as follows: Section 2 presents the literature review on learning models and the learning process, the use of technology in education, as well as mobile technology and its impact on learning. Section 3 explains the research

methodology – Value-Focused Thinking Approach (VFT), which originated from the means-ends chain theory and laddering technique, and provides justification for the use of this methodology. Section 4 describes the process of data collection and analysis. Section 5 presents the research results. Section 6 discusses the research findings. Section 7 discusses the implications of the study. Section 8 highlights the contributions of this research. Section 9 concludes the paper.

Literature Review

Learning Models and Learning Process

The traditional view of learning is represented by the behaviorism model and cognitivism model. The behaviorism model, which is derived from the stimulus and response theory, suggests that learning is a change in the behavioral disposition of an organism that can be shaped through reinforcement (Jonassen, 1993). From the perspective of cognitivism, learning refers to the processing and transfer of new knowledge into long-term memories. The mind is perceived as an information processor with short-term and long-term memories. Knowledge is a storehouse of representations (patterns) which can be called upon for use in reasoning and translated into language (Hung, 2001). Stimulus can be provided by instructors to improve recall and retention of knowledge.

Recently, education has shifted the focus of learning from the behaviorism and cognitivism models to the constructivism model. The constructivism model of learning stresses that knowledge is created or constructed by each learner. According to the constructivism model, learning involves an active process of constructing rather than acquiring knowledge. Hence, knowledge has to be constructed by the learner through discovery with a focus on the process of assimilation and accommodation of the knowledge. Individuals can learn better when they discover things themselves and when they control the pace of learning (Leidner & Jarvenpaa, 1995). The constructivist model of learning implies that learning must be learner-centered with the instructors providing support rather than directions.

Social orientations of constructivism have gained wide popularity. The general view of social constructivism is that human knowledge is socially constructed, and the interpretation of knowledge is dependent on the social and cultural context through which the knowledge was constructed (Hung, 2001).


For example, Vygotsky’s (1978) sociocultural theory emphasizes the critical importance of interaction with people in learning and thinking.

The constructivism model of learning emphasizes problem solving, collaboration, and interaction. To understand how the constructivism model of learning can be applied to develop instructions that promote learning, Mayers (1995) drew on research findings from cognitive psychology to argue that: (1) learning is a by-product of understanding; (2) understanding occurs best through performing tasks; and (3) learning is largely social in nature. Mayers (1995) then suggested that learning is a circle of action, feedback, and reflection. He emphasized the need to put new information into new contexts for the learner to apply it in practice and believed that discussions with fellow learners and instructors could promote the process of feedback and reflection.

Alavi (1994) also identified three attributes of effective learning process. The first attribute is active learning and construction of knowledge. Learning is best accomplished by actively involving students in construction of knowledge and understanding through acquisition, generation, analysis, and manipulation of information. The second attribute is cooperation and teamwork in learning. Learning can be viewed as a social process that could occur more effectively through cooperative interpersonal interactions. The third attribute is learning through problem solving. Through the process of problem solving, knowledge of specific domains and strategies for solving problems can be acquired.

The constructivism model of learning suggests that education should focus on active construction of knowledge by the learners through effective communication, problem solving, and collaboration.

Information Technology in Education

Information technologies have been adopted to enrich learning, increase the efficiency of learning, provide wider access to education, and contain the costs of education. Information technology can help to deliver learning activities more efficiently and facilitate engaging and participatory activities for students (Niederman & Rollier, 2001).

Leidner and Jarvenpaa (1993) examined the use and outcomes of computer-based instructional technology in the context of graduate business education. They identified four primary uses of computer-based technology: (i) as a means of interactive, guided learning of technical procedures

necessary for mastering the analysis of a subject, (ii) as a means of real-time manipulation and analysis of data to provide the basis for conceptual and exploratory learning during classes, (iii) as tools in a lab where students can work individually or in pairs until they need the instructor’s help, and (iv) as a display mechanism – a replacement of transparencies, slides, or blackboards.

In another paper by Leidner and Jarvenpaa (1995), they reviewed the different models of learning, identified assumptions of information technology, and related those assumptions to the different learning models. From their perspectives, information technology can be used in education for: (i) automating the delivery of information in the classroom, (ii) facilitating information access to instructors, (iii) facilitating information access to students, and (iv) transforming to virtual continuous learning spaces.

While Leidner and Jarvenpaa (1993, 1995) identified the general impact of information technology on education, other researchers have evaluated the use of information technology in some specific contexts.

In particular, many information and communication technologies are used to facilitate collaboration and collaborative learning (Karsten, 1999). Communication-focused technologies such as email and course-management software (e.g., Blackboard, WebCT) support collaborative work among students and quick references to databases of knowledge (Goodman & Darr, 1998) while also making communications available to faculty and staff at any time or place. Information technologies can facilitate collaboration by bridging discontinuities in time, geography, and compositions of groups/teams (Chudoba et al., 2005). The capabilities of information technologies to automate routine tasks, allow flexible input, and integrate multiple communication modes make them well suited to support teamwork and group collaboration in the educational context (Wegerif, 2005).

Alavi (1994) investigated the impact of an information technology – a group decision support system (GDSS) – on collaborative learning in a field setting. The results of the study indicated that GDSS-supported collaborative learning led to higher levels of perceived skill development, self-reported learning, and evaluation of classroom experience. Another study by Alavi et al. (1995) also suggested that distant students equipped with desktop video-conferencing exhibited higher critical-thinking skills than local students.


These prior studies have investigated the usage of computer technology in learning, the general impact of computer technology in education, as well as the benefits of using information technology to support collaborative learning.

Mobile Technology and its Impact on Learning

Human interaction can be characterized in terms of three dimensions – spatial, temporal, and contextual (Kohlrausch & van de Par, 2005). These three dimensions of human interaction have been dramatically mobilized by the use of information technology, especially mobile technology, in both our social lives and working environments (Kakihara & Sorensen, 2001; Sheng et al., 2008). Chatterjee and Sarker (2007) reviewed the literature and further extended mobility into five dimensions: (i) intrinsic nature (e.g., seamless temporal, spatial, and contextual accessibility), (ii) purpose (e.g., perpetual availability of information and need for social inclusion), (iii) modalities (e.g., travelling, wandering, and visiting), (iv) physical manifestation (e.g., mobility of users, devices, and services), and (v) implications (i.e., the effects of mobility).

Mobile technology has extended computing and the Internet to the wireless medium, thus providing more freedom to individuals in their personal lives and at work (Jarvenpaa et al., 2003). The most touted advantage of mobile technology is mobility (Sarker & Wells, 2003), which enables anytime, anywhere computing (Varshney & Vetter, 2000; Davis, 2002). Anytime, anywhere computing can remove time and space constraints in accessing critical information and enhance capabilities for communication, coordination, collaboration, and knowledge exchange (Davis, 2002). Users of mobile technology can have access to the Internet and mobile applications whenever the need arises, such as when “traveling, wandering, and visiting” (Sarker & Wells, 2003).

Mobility is the main building block of mobile collaboration. Mobile technology, with “mobility” as the key characteristic, supports mobile collaboration. Mobile collaboration can be defined as “cooperative work, towards a special goal, by individuals who are spatially and/or contextually dispersed and the relevant loci of the individuals change with time during the cooperative act” (Chatterjee & Sarker, 2007, p.4). Collaboration is an active process that allows a work group to develop an atmosphere of sharing where members can contribute their knowledge to solve the problems (Patnayakuni et al., 2006). Collaboration can create multiple synergies in the workplace (Griffith et al., 2003) and

thus, has become an increasingly important practice in industry. To better accommodate the needs of future professionals, learning has been re-examined as a constructivist activity, where knowledge is actively reconstructed by learners rather than being passively transferred to learners (Rohde et al., 2007). Learning is an iterative, evolutionary process and is generated through social participation in a group context (Rohde et al., 2007). Therefore, collaboration is the central element in the constructivism model of learning. Mobile collaboration has also become an important part of mobile education, which relies on mobile technology to aid the acquisition of knowledge of a learner regardless location and time (Lehner & Nosekabel, 2002).

The use of mobile technology in education can revolutionize the processes of learning and teaching, and change the learning environment (Erickson & Siau, 2003; Chen et al., 2002; Plummer et al., 2008). The information provided through mobile technology can be based on the learner’s request, i.e., learning on-demand. Learning practices can also take place anytime and anywhere. Students are no longer confined to learning at specific locations such as classrooms and libraries. Mobile technology also enables students to learn as and when the need arises and when the time is right. Learning can take place no matter where they are through portable mobile devices and multi-media functions provided by the devices. With mobile technology, collaboration and interaction are facilitated. Students can communicate and interact with peer students, instructors, and experts even when they are on the move (Chen et al., 2002). Applications of mobile technology to learning can facilitate student learning in a more dynamic and complex learning environment.

Despite numerous benefits of using mobile technology in education, research in this area is sparse. Mobile technology is still a new and evolving research area. Furthermore, the use of mobile technology in education is in its infancy at best. Research is needed in the area to inform practice and set directions for future research effort. Thus, this research presents one of the pioneering efforts in understanding the values of mobile education for students and instructors. It uses a qualitative research approach to understand the “values” of mobile education, i.e., what people want and desire in mobile education, and developed a means-ends objective network that depict those values and their relationships.


Research Methodology

Values

According to Rokeach (1973), a value is “an enduring belief that a specific mode of conduct or end-state of existence is personally or socially preferable to an opposite or converse mode of conduct or end-state of existence” (p.5). Gutman (1982) also suggested that “values are special kinds of preferences for modes of conduct or end-states of existence” (p.63). To put it simply, values are what one desires to achieve (Keeney, 1992). They are principles used for evaluation by customers (Keeney, 1992).

Reynolds and Gutman (1987) defined two different kinds of values: terminal and instrumental values. Terminal or “end” values are concerned with preferred states of existence (i.e., happiness, security, or accomplishment), and instrumental or “means” values are related to modes of behavior (i.e., honest, courageous, or broad-minded) which are instrumental in achieving these end-states. The interaction between these “means” and “ends” values is referred to as a value system.

Means-Ends Chain Theory

The Means-Ends Chain (MEC) theory proposes that knowledge held in consumers’ memories is represented as hierarchical cognitive structures at various levels of abstraction (e.g., Gutman, 1982; Gutman, 1997). The lowest level describes an object’s attributes, i.e., those that are typically physical or concrete, although they can sometimes be abstract. The higher level refers to the psychological or social consequences of consuming the product or service, which is then followed by the consumers’ instrumental values and terminal values (Gutman, 1982).

The MEC theory focuses on the linkages between the attributes that exist in products (the lower-level “means”), the consequences for the consumers provided with the attributes (the higher-level “means”), and the personal values (the “ends”) (Reynolds & Gutman, 1988). Means are objects (products) or activities in which people engage with. Ends are valued states of being (such as happiness, security, or accomplishment). Achieving a valued state is brought about, facilitated, or caused by consequences at the lower levels of abstraction (Gutman, 1997). Consequences can be defined as results (e.g., physiological or psychological) accruing directly or indirectly to a consumer from his/her behavior. Consequences can be desirable or

undesirable. Consequences may be physiological in nature (e.g., satisfying hunger, thirst, or other physiological needs), psychological (e.g., self-esteem, improved outlook for the future), or sociological (e.g., enhanced status, group membership). Consumers choose actions that produce desired consequences and minimize undesired consequences (Gutman, 1982).

Therefore, the MEC theory suggests that there is a flow toward desired ends in successively higher levels of abstraction – extending from the product to consumers’ values (Gutman, 1997). A means-ends chain is a model that explains how a product or service facilitates the achievement of desired end states (Gutman, 1982).

The MEC theory has been widely applied in marketing research. Researchers have successfully applied MEC to study consumer market segmentation, brand positioning, communication strategy development, and testing of commercials and ads (Pieters et al., 1998). Researchers have also used MEC in the domain of consumer behavior. For example, using the MEC theory, Pieters et al. (1998) developed a hierarchical model of customers’ expectations about service employees and the motivations underlying their expectations.

Laddering Technique

Laddering is a frequently used technique for eliciting means-ends chains. Laddering refers to an in-depth, one-to-one interviewing technique used to develop an understanding of how consumers translate the attributes of products into consumers’ personal values. Laddering uses a series of directed probes such as “Why is that important to you?” to determine linkages between attributes of the products (A), consequences (C), and end values (V). The combination of these connected elements, or ladder, represents the linkage between the product and the perceptual process of consumers, which offers a more direct and useful understanding of the consumers (Reynolds & Gutman, 1988).

The laddering technique usually involves two steps. The first step is to elicit salient criteria used to discriminate between products, which can be done using triadic sorting tasks (Kelly, 1955) or simply through direct questioning. The salient attributes that are elicited from the first step then serve as the starting point for the laddering probes to identify the means-ends structure. Probing questions such as “Why is that important to you?” are used to help in deriving the ladder of abstraction. The response at each level is used as a basis for further questioning.


This process is repeated until the highest level abstraction of value has been reached.

The complete chain of product attributes (A), consequences (C), and values (V) elicited from one subject constitutes a ladder. For example, the following ladder was derived from a subject in a salty-snack study by Reynolds and Gutman (1988): flavored chip (A) strong taste (A) eat less (C)

don’t get fat (C) better figure (C) self-esteem (V). These elements were sequentially elicited from the subject using the laddering technique, which enables the respondent to think critically about the connections between the product’s attributes and, in this case, his/her personal motivations.

Analysis of laddering data across subjects first involves summarizing the key elements by standard content-analysis procedures, while bearing in mind the levels of abstraction, that is Attributes – Consequences – Values. A summary table can then be constructed to represent the number of connections between the elements. From this summary table, dominant connections can be graphically represented in a tree diagram, named a hierarchical value map, which is a cognitive map. This structured cognitive map represents the consensus mental model of the subjects.

Value-Focused Thinking Approach

The Value Focused Thinking (VFT) approach (Keeney, 1992) provides a systematic way to identify values and organize the values. The MEC theory and the laddering technique provide the conceptual foundation to understand VFT. The VFT approach, which is fundamentally about deciding “what” is important and “how” to achieve it, defines essentially what the decision maker cares about (Keeney, 1992).

VFT focuses on identifying the fundamental values the decision maker cares about in a certain decision context and determining how the fundamental values can be achieved through a hierarchical structure, that is, linkages between the fundamental values and means to achieve these values. The goal of VFT is to identify the means-end value structure in a certain decision context.

Keeney (1992) defined values as principles used for evaluation by customers/users. Values that are of concern are made explicit by the identification of objectives. An objective is a statement of something that one desires to achieve (Keeney, 1992). An objective is characterized by three features: a decision context, an object, and a direction of

preference. The result of a VFT study is a means-ends objective network, which not only depicts the fundamental objectives and means objectives, but also the relationships between the objectives.

The steps of VFT are as follows (as shown in Figure 1):

(1) Develop an initial list of objectives and convert them into a common form. Several popular and recommended techniques that can help stimulate the identification of possible objectives include “wish lists”, problems and shortcomings, alternatives, and consequences (Keeney, 1992).

(2) Structuring objectives – fundamental objectives versus means objectives. After collecting the list of objectives, this step distinguishes between fundamental objectives and means objectives. Fundamental objectives concern “the ends that decision makers value in a specific context” whereas means objectives are “methods to achieve ends” (Keeney, 1992). To separate means objectives from fundamental objectives and to establish their relationships, Keeney (1992) suggested using the “Why Is That Important?” test. For each identified objective, asking “Why Is That Important?” yields two types of possible responses. One is that this objective is one of the essential reasons for interest in the situation and is fundamental for decision making. This is called a fundamental objective. The other response is that an objective is important because of its implication for some other objective(s). This is called a means objective.

(3) Building the means-ends objective network. The final step in the VFT approach is to build the means-ends objective network. This network provides a model of the specific interrelationships among the means objectives and their relationships to fundamental objectives. The relationships depicted in the means-ends objective network allow analysts to better understand the complexities of the decision maker’s value system, and select alternatives that are designed to achieve these fundamental objectives via their effects on one or more means objectives.

Applicability of Value-Focused Thinking Approach

The research question for this study is: What are the values of mobile education for students and instructors? The aim of the research is to inductively identify the users’ value system in the context of mobile education.


Figure 1: Steps involved in Value-Focused Thinking Approach

The VFT approach focuses on identifying what users desire to achieve in a certain decision context. VFT not only uncovers the fundamental values and objectives that are usually hidden, but also provides a systematic way of identifying relationships among the objectives. VFT is, therefore, appropriate for this research.

As mentioned earlier, the MEC theory and the laddering technique provide the theoretical underpinning for VFT. The MEC theory is widely accepted and applied in marketing and consumer behavior research. The laddering technique is also an established research method to elicit means-ends structures. Therefore, VFT is a systematic yet flexible research method that has strong theoretical basis.

The VFT approach has been applied in many research areas such as creativity in decision making

(Keeney, 1994), strategic decision making (Keeney & McDaniels, 1992), value-focused assessment of privacy and security (Dhillon & Torkzadeh, 2001; Dhillon et al., 2002), value focused assessment of trust in mobile commerce (Siau et al., 2004), and values of mobile applications (Nah et al., 2005; Sheng et al., 2005).

Table 1 is a summary of prior literatures that have applied the VFT approach.

Data Collection And Analysis

Subjects

Using the VFT approach, we interviewed a total of 33 subjects regarding the values of mobile technology in education. Among the 33 subjects, 18 of them are university students and 15 of them are instructors at a large mid-western university.

Table 1: Summary of Research Using VFT Approach

Literature Applications of VFT

Keeney & McDaniels (1992) • Strategic Decisions at British Columbia Hydro and Power Authority

Keeney (1994) • Decision making at Conflict Management, Inc. Keeney (1999a) • Foundation for Seagate to identify its vision and mission

statement Keeney (1999b) • Values of Internet commerce to the customer Dhillon & Torkzadeh (2001) • Value focused assessment of information system security

in organizations Dhillon et al. (2002) • Value focused assessment of individual privacy concerns

for Internet commerce

Torkzadeh & Dhillon (2002) • Develop instruments that measure factors that influence the success of Internet commerce

Siau et al. (2004) • Values of trust in mobile commerce

Nah et al. (2005); Sheng et al. (2005)

• Values of mobile applications in organizations

Develop an initial list of objectives and convert them into a common form

Structuring objectives – fundamental objectives versus means objectives

Build means-ends objective network


As our research is focusing on the use of mobile technology in the educational context, interviewing students and instructors allows us to focus on the technology in its use context. We also recruited the subjects based on their experience with mobile technology. All subjects own mobile devices and have used mobile devices for at least a year, and hence, they have a good understanding of mobile technology, such as its capability, benefits, and limitations.

Deriving Fundamental and Means Objectives

Two techniques were used to identify the values: “benefits and problems” and “wish list” (Keeney, 1992). As our subjects are university students and instructors who are also mobile technology users, they have sufficient knowledge and experience to understand the benefits and problems mobile technology could bring to education. Also, considering that mobile technology is still a relatively new phenomenon and few applications are available at present in educational settings, “wish list” is an appropriate way to elicit subjects’ values regarding mobile technology in education.

Following the VFT approach, probing questions that were used in the interviews include:

“What are the benefits of using mobile technology for learning/teaching?”

“What problems or concerns can arise in using mobile technology in education?”

“If there is no limitation at all, what are the features or functions of mobile education applications you wish to have?”

Using these probing questions, we collected an initial list of values that are relevant to mobile education. This initial list of values serves as the basis for further probing to develop a means-ends objective network in mobile education. The “Why Is That Important” test was employed to distinguish between means objectives and fundamental objectives, as discussed earlier. Asking “Why Is That Important” forced the subjects to think critically about the relationships between objectives. The probing was repeated until fundamental objectives were reached. That is, when asked “Why Is That Important?”, the subject’s answer was something like “I think the objective is important because itself is important”. Such a response indicates that a potential fundamental value has been identified.

The interviews were conducted face-to-face using the VFT approach. Each interview lasted

approximately 30-45 minutes. The interviews were audio-recorded and notes were taken by the researcher during each interview. Each interview session continued until no further values could be elicited from the subject via various probing questions.

Data Analysis

The means and ends objectives were derived from the transcript of each interview. Values derived from the transcripts were converted into a common form – in the form of objectives which includes a decision context, an object, and a direction of preference.

Two researchers individually coded six of the interviews – identifying a list of means objectives and fundamental objectives. The inter-rater reliability of 93% was computed based on the number of matches between the two coders. Hence, there is a high degree of consistency and agreement between them. The discrepancies were discussed and consensus was reached on the mismatches, which were mainly related to naming and phrasing of the concepts. Through the discussion, the researchers came to an agreement on how to identify concepts from the transcripts, and on the naming and phrasing of concepts. One researcher continued coding the rest of the interviews.

After the initial list of objectives was identified, two researchers carefully reviewed the objectives list: redundant objectives were removed and similar objectives were grouped together. The final set of objectives includes 30 means objectives and 8 fundamental objectives (as shown in Table 2). The means-ends relationships between the objectives were derived based on the subjects’ responses to the “Why Is That Important?” test.

The means-ends objective network was constructed based on the list of 38 unique objectives identified as well as the relationships between the objectives. For example, when one subject mentioned that “I would like to have better coverage area for the wireless network”. The researcher followed up with “Why Is That Important?”. The participant then mentioned, “so that I could have access to the Internet and other educational services from any place”. After being asked “why?” again, the participant responded, “I can have access to course websites, class notes, and other resources from any place”. When asked “why?”, the participant then answered, “Then I will be able to have access of educational materials when I need them, and I can learn at my own pace when I have time.”


Table 2: Fundamental Objectives and Means Objectives

Fundamental Objectives:

Overall Objective: Maximize Values of Education Using Mobile Technology

Maximize convenience of education Example: Maximize time flexibility in educational activities Minimize location-specific constraints for education

Maximize efficiency in learning Example: Accelerate learning procedures Maximize time management

Maximize effectiveness in learning Example: Maximize acquisition of knowledge Maximize understanding of education materials

Maximize usability of mobile education services Example: Maximize ease of use of mobile education services Maximize ease of navigation on mobile education websites

Maximize individual privacy Example: Prevent invasion of personal life Ensure private space of instructors

Minimize cost of education Example: Minimize need to commute to campus Reduce cost of education through virtual learning

Ensure academic honesty Example: Minimize opportunities for dishonest conduct Prevent plagiarism in educational activities

Maximize security of student/instructor information Example: Maximize confidentiality of personal information Maximize confidentiality of students’ performance ( e.g., grades)

Means Objectives:

Maximize coverage area of wireless services Example: Maximize wireless access points Maximize area of coverage

Maximize accessibility of mobile education services Example: Maximize access to mobile education services at any time

Maximize access to mobile education services while on the move

Maximize mobility of mobile devices Example: Maximize portability of mobile devices Mobile devices work at any place or condition

Maximize availability of education resources Example: Maximize access to educational websites via wireless

Internet Maximize availability of information from the field

Maximize education on demand Example: Ability to access course materials from any place Education is not constrained to locations

Maximize customized learning Example: Students can learn at their own pace Provide personalized learning materials

Maximize information/idea sharing Example: Maximize info. exchange with students/instructors Maximize ability to beam data/ideas to team members

Maximize virtual collaboration among students Example: Maximize collaborative learning among students Maximize collaboration support for project teams

Enable virtual meetings Example: Enable virtual classroom meetings via mobile

devices Enable virtual study groups

Maximize flexibility in teamwork/meeting Example: Teams need not meet face-to-face Ability to carry out asynchronous meetings

Maximize tracking of education activities Example: Availability of To-Do list Ability to track work done by team members

Maximize scheduling of education activities Example: Availability of scheduling features for mobile education Ability to check team members’ availability for scheduling meeting

Maximize organization of education activities Example: Provide project management features for education Ability to plan education activities

Maximize availability of instructors Example: Instructors are more readily available to students Instructors can be accessed outside classroom

Enable mobile-testing Example: Students can take test on mobile devices at any

time Students can take self-assessment test rom any place

Increase bandwidth of mobile services Example: Increase bandwidth of downloading course material Increase bandwidth of wireless services

Table continued


Table 2: Fundamental Objectives and Means Objectives Means Objectives:

Maximize multi-media capabilities of mobile devices Example: Maximize the availability of multi-media functions

on mobile devices Maximize the use of video and audio conferencing

Maximize interaction in education Example: Improve interaction between students and instructors Improve interaction among students

Maximize immediate feedback Example: Maximize students’ ability to get immediate

answer Maximize instructors’ ability to offer real-time

question/answering

Enable capturing of information from the field Example: Ability to take pictures during field trip Ability to video tape sessions

Maximize enjoyment of learning Example: Learning should be fun Mobile education should make learning enjoyable

Maximize student involvement in learning Example: Maximize students’ participation in learning Maximize students’ engagement in learning

Minimize distraction of mobile devices in classroom Example: Minimize interruption from mobile devices Ability to block distractions (e.g., beaming, instant

messaging) from mobile devices in classroom

Enhance user-interface of mobile devices Example: Improve input mechanism of mobile devices Enlarge screen size of mobile devices

Maximize ease of use of mobile education devices Example: Maximize ease of input Maximize ease of navigation

Maximize readability of display Example: Enhance screen resolution Use legible font size

Maximize security features of wireless services Example: Maximize encryption of data Ensure authentication of students

Minimize cost of mobile devices Example: Minimize cost of purchasing mobile devices Ensure mobile devices are affordable

Minimize cost of wireless services Example: Minimize cost of wireless Internet access Minimize cost of monthly service fees

Prevent cheating with mobile devices Example: Disable beaming during exam Prevent plagiarism using mobile devices

When the researcher asked “Why Is That Important?”, the participant stated, “It is more effective for me to learn at my own pace”. The example suggests the following means-ends chain: “maximize coverage area of wireless service” → “maximize accessibility of mobile education service” → “maximize availability of educational resource” → “maximize education on demand”, “maximize customized learning” → “maximize effectiveness in learning”.

A means-ends relationship is included in the means-ends objective network only if it was elicited from at least four subjects. This was done to ensure that the means-ends objective network indicates only the main and common relationships identified by the subjects. This cutoff value is recommended by Reynolds and Gutman (1988) in constructing the hierarchical value maps using the laddering technique. They suggested that a cutoff value of four relations with 50 respondents would account for as many as two thirds of all relations among the elements. Although there are only 33 subjects in our study, the focus and intensive nature of the interviews allowed us to identify more than five paths (or ladders using the terminology from the laddering technique) from each subject. Typically, only two or three ladders

can be obtained from a respondent interviewed using the laddering approach (Reynolds & Gutman, 1988). Given that we were able to identify more than five paths using VFT, we argue that the comprehensiveness and intensiveness of our interviews can compensate for the relatively smaller number of subjects and justify for the cutoff value of four in determining the relationships in the means-ends objective network.

Research Results After interviewing the 33 subjects, we derived a list of fundamental objectives as well as means objectives (see Table 2). We also developed a means-ends objective network to depict the objectives and relationships between objectives (see Figure 2). The results are discussed below.

Discussion Fundamental Objectives and Means Objectives

The overall objective for mobile applications and technology in education is to maximize the values of education.


Figure 2: Means-ends Objective Network (Gray boxes highlight the instructors concerns)


We identified eight fundamental objectives in this study – maximize convenience of education, maximize efficiency in learning, maximize effectiveness in learning, maximize usability of mobile education services, maximize security of student/instructor information, maximize individual privacy, minimize cost of education, and ensure academic honesty. These eight objectives represent the fundamental values of mobile applications in education from the students’ and instructors’ perspectives and determine the “principles” (Keeney, 1992) for assessments concerning the use of mobile technology for education. These objectives are the fundamental reasons that drive mobile application development for education purposes.

The goals of education are to increase students’ knowledge and their ability to acquire and apply knowledge. Thus, it is not surprising that the fundamental objectives for using mobile technology to support education include “effectiveness” (Can mobile technology produce better learning outcomes than traditional education?) and “efficiency” (Can mobile technology expedite the learning process?). Nevertheless, mobile technology provides new means to achieve “effectiveness” and “efficiency” by utilizing features and functions available through mobile technology in the learning environment. For example, mobile technology enables students to communicate and collaborate more easily across time and space, thus facilitating team learning. Mobile technology also enables access to educational materials anytime and anywhere, which increases the availability of educational resources such that learning can take place based on students’ needs and demands. These means objectives lead to an increase in the effectiveness of learning. Mobile technology also enables mobile-testing, which can result in immediate feedback, and hence, improve “efficiency” in learning.

“Convenience”, as stated by subjects during the interviews, is one of the key advantages of using mobile technology for education. This advantage is primarily derived from the mobility features of mobile devices and the “anytime and anywhere” ability of wireless services. For instance, “anytime and anywhere” access allows students to hold virtual meetings with other students to carry out group assignments or projects, and to hold virtual discussions with their instructors, thereby, increasing flexibility in teamwork and meetings (i.e., resolving problems of time conflict and eliminating location constraints). This increased flexibility makes it more convenient for students to carry out group projects and to interact with instructors more easily or frequently.

“Usability” is a fundamental objective because of the limitations of mobile devices. Current mobile devices have far from ideal user interface, which makes it difficult to use and navigate, and this affects the readability of information display (Tarasewich et al., 2008). Therefore, research and development must be undertaken to improve usability and user-friendliness of mobile devices.

“Security” is important for mobile education where information is transferred through the wireless medium, which is perceived to be more vulnerable to hacking or interception (Tarasewich et al., 2008). The subjects in our study felt that more and better security features must be provided, such as encryption and authentication.

“Individual privacy” must be ensured when mobile technology is used in educational settings. Privacy refers to the right to preserve one’s personal time and space. This is in line with the definition of privacy by Laudon and Traver’s (2001, p.467) as “the moral right of individuals to be left alone, free from surveillance or interference from other individuals or organizations, including the state”. The “anytime, anywhere” accessibility of mobile technology makes instructors more readily available and reachable, which, in turn, may intrude into instructors’ private time or space.

“Cost” refers to the cost of mobile devices and services. Although mobile devices are considerably cheaper than desktop computers, higher monthly fees are charged for accessing the Internet from mobile devices. For mobile technology to be widely employed in education, the subjects stressed that cost is an issue that must be taken into account.

“Ensure academic honesty” is another fundamental objective of mobile education. Students can use mobile devices to transmit information during an exam or plagiarize by copying from Internet resources more easily. Although mobile technology has the potential to transform education, academic honesty must be ensured and plagiarism must be prevented.

The means objectives derived from this study as well as the relationships between them illustrate how the fundamental objectives can be achieved. The means objectives not only include features or functions of mobile technology, but they also highlight possible mobile applications for education. Based on the means objectives derived, we identified the following ways where mobile technology can contribute to education:

I. Maximize education on demand. With the ability to access educational materials anytime and anywhere, mobile technology


makes educational resources more accessible. Therefore, students can gain access to the educational resources based on their personal needs. Since the availability of educational resources are not constrained or confined to certain places and times (unlike traditional education), knowledge acquisition can be facilitated based on the learners’ needs and requests (Chen et al., 2002).

II. Maximize virtual collaboration among students. Virtual meetings through mobile devices and wireless services provide new means for student collaboration. Students can attend virtual classes using their mobile devices or form virtual study groups with peer students. Mobile technology allows students to collaborate with peer students in less time and without geographical constraints.

III. Maximize customized learning. Educational resources can be tailored based on the students’ personal preferences or abilities. Educational materials can be provided to the students at the appropriate level and students can learn those materials at their own pace.

IV. Maximize organization of education activities. Mobile devices usually have “personal digital assistant” functions which include scheduling, to-do list, and tracking. These functions make it easier for students and instructors to keep up with educational activities such as meetings and assignments, and help them to be more organized.

V. Maximize immediate feedback. Mobile testing or quizzes allow students to take tests using mobile devices to assess their understanding of the course materials. Software applications can evaluate and analyze students’ performance, and provide feedback immediately to both the instructors and students. Also, enhanced interaction using mobile technology enables students to ask instructors questions whenever the need arises regardless of their locations (such as when they encounter a problem while commuting on a train) and to potentially receive instantaneous feedback from instructors.

VI. Maximize student involvement in learning. Students’ participation and engagement are very important for effective and efficient learning. Mobile technology provides faster and more frequent interactions between

students and educators, thereby, increasing students’ willingness to participate and engage in learning. This idea is in line with the “interactivity of learning process” feature of mobile learning environment suggested by Chen et al. (2002).

To realize these mobile technology enabled objectives, there are some “necessary conditions” that must be met. They are:

I. Mobility and coverage area are the two key enablers of mobile technology in education. Mobility is the primary advantage of mobile devices as compared with desktop computers. Being portable, mobile devices can be carried around anywhere. The network coverage area determines whether a mobile device has access to the Internet or other educational databases and resources from a specific location. These two enablers, mobility and coverage area, when combined, make it possible for students to access educational resources anytime and anywhere.

II. Accessibility is key for the application of mobile technology in education. Anytime and anywhere accessibility of mobile technology makes educational resources more readily available, enables information and idea sharing, maximizes virtual collaboration, maximizes tracking and scheduling of education activities, enables mobile testing, maximizes students’ interactions with educators, and enables capture of data from the field. For mobile technology to offer these objectives and benefits to education, accessibility is a necessary condition. As noted by Watson and Straub (2007), the values of IT/IS lie in the accessibility of information.

In DeLone and McLean’s IS success model (2003), they pointed out the importance of system quality, information quality, and service quality for IS success. The necessary conditions identified in our means-end objective network, mobility, coverage area, and accessibility, highlight the importance of the quality of mobile devices and wireless connections for success in mobile education. These conditions correspond to system quality and service quality in DeLone and McLean's IS success model. Information quality, on the other hand, is manifested through means objectives such as ‘maximize information/idea sharing’, ‘maximize availability of education resources’ and ‘maximize availability of instructors’.


Differences between Students and Instructors

In this study, we identified a list of objectives and developed a means-ends objective network that depicts the objectives and the relationships between them. Interestingly, the objectives identified by students and by instructors are similar. Both sets are driven by the purpose of education, which is to facilitate students’ learning. Learning involves knowledge transfer from instructors to students (i.e., the views of behaviorism and cognitivism) as well as the discovery and construction of knowledge through interactions with peer students and instructors (i.e., the views of constructivism and social constructivism). Therefore, students and instructors are two integrated parties in education; each party views the values of education by taking into account of the other party.

Although the aggregated values of mobile education are the same for both students and instructors, the qualitative nature of this study yields very rich, in-depth, and narrative data that implicates some differences between students and instructors in terms of their emphasis of some objectives. Both students and instructors highlighted the potential of mobile technology in education; instructors, though, are more concerned about potential problems of using mobile technology in educational settings. The grayed boxes in the means-ends objective network (see Figure 2) highlight the instructors’ concerns.

“Individual privacy” has been expressed by many instructors during the interviews. Because of the mobility features of mobile technology, instructors can be reached anytime, anywhere, and will become more readily available to students. Although this increased availability provides greater opportunity for real-time interactions between students and instructors, it may, at the same time, intrude into instructors’ private time and space, which may affect instructors’ personal lives.

“Academic honesty” is another concern raised by instructors concerning the use of mobile technology in educational settings. When students are equipped with mobile devices that can provide them instant access to educational resources, inappropriate use of mobile technology can damage academic honesty. For example, students may use mobile devices to transmit information during exams. Instructors, therefore, want to make sure that mobile technology is used appropriately in educational settings.

The use of mobile devices in the classroom can possibly distract students’ attention during lectures. The “distractions” caused by using mobile devices in the classroom poses challenges in classroom management by instructors.

The above objectives, though also mentioned by students during interviews, did not receive as much attention from students. Students are more focused on the benefits that mobile technology can bring to them. Some possible explanations for these differences include: (1) instructors are responsible for managing and monitoring the education process; and (2) instructors are more concerned about personal time and space.

Rigor of Study

The rigor of the study is important in order to generate credible and trustworthy results (Creswell, 1998; Strauss & Corbin, 1998; Yin, 1994). The rigor in this study is achieved in the following ways.

First, we followed the standard procedures of the VFT approach to collect and analyze data. VFT is an established research method that has been applied in various disciplines. In addition, we incorporated the guidelines for data analysis from the laddering technique to decide on the cutoff value for relations to be included in the means-ends objective network. By following the guidelines of VFT and the laddering technique, we ensure the reliability and validity of the results.

Second, we used multiple coders to assess the reliability and validity of the coding. Two coders were used and their degree of agreement (i.e., based on matches) was 93%, indicating a very high level of consistency.

Third, we maintained interview notes and audio recorded the interviews for documentation purposes. These notes and documentations allow an outsider or external observer to trace the chain of evidence in the study. We followed the steps of the VFT approach for articulating the interviews and organizing the results. The chain of evidence leads up to the means-ends objective network.

Fourth, we used prior literature for “supplemental validation”, a verification step suggested by Creswell (1998, p.209). The use of VFT in this study is aimed to inductively identify the values of mobile education to students and instructors. In discussing the results, we also use prior literature as additional sources for validation of the study results.

Fifth, we adopted a standard “stopping rule” for qualitative research with respect to the sample size. As recommended by qualitative researchers (Glaser & Strauss, 1967; Strauss & Corbin, 1998), the sample size was decided by the results gathered from the interviews. As Glaser and Strauss (1967) indicated, the researcher “cannot state at the outset


of his research how many [subjects] he will sample during the entire study; he can only count up the [subjects] at the end” (p.61). When subsequent interviews did not yield any new objectives, we concluded that the “point of saturation” was reached. That is, additional interviews would not provide any added insights to the study. This is a standard “stopping rule” for qualitative research (Glaser & Strauss, 1967; Strauss & Corbin, 1998; Eisenhardt, 1989).

Similar arguments were also put forth by Tan and Hunter (2002) for the Repertory Grid technique where a sample size of 15 to 25 is usually sufficient. In a study by Dunn et al. (1986), they reached the point of saturation after the tenth interview. The repertory grid technique is a qualitative method that provides a systematic approach to articulate and organize individuals’ personal constructs (Kelly, 1955). Similar to the VFT approach, the repertory grid technique is an inductive approach that develops higher-level concepts/constructs from raw data. Because of the similarities between the two techniques (e.g., both are qualitative techniques, both use interviews as the main data collection method, and both follow a semi-structured approach to data analysis), we argue that we can infer the “point of saturation” from other repertory grid studies to this study.

In our research, we reached the point of saturation after the 15th interview. To ensure that all objectives were gathered, we continued the interviews until the 33rd subject.

Implications

Implications for Research

As Tokzadeh and Dhillon (2002) stated in their study to develop instruments to measure factors that influence the success of Internet commerce, “the ultimate question about the success of Internet commerce depends on how customers perceive its values” (p.199). Mobile technology, as an emerging technology, has shown great promises and potential for education. However, for mobile technology to be well received and used in educational settings, it is essential to understand how the users, namely, students and instructors, perceive the values of mobile education. This is in line with the view of Benbasat and Zmud (2003) that information technology artifacts should be central to theory development in information systems, as the more context-specific model provides greater explanatory power and more actionable guidance to practitioners.

This research identifies the values of mobile education from the perspectives of students and instructors using the VFT approach. The VFT approach, which is grounded in the MEC theory and the laddering technique, has been shown to be effective in uncovering users’ values and understanding users’ behaviors. The results of this study, presented in the form of a means-ends objective network, not only enhance our understanding in mobile education, but also offer directions for future research in mobile education.

From an academic research perspective, the means-ends objective network provides many interesting questions waiting to be answered. For example, research is needed to analyze the relative importance of each fundamental objective in maximizing the values of mobile education. Research is also warranted to examine the relative importance of each means objective in achieving each fundamental objective. In addition, future research can study the longitudinal effects of learning using mobile technology and the change in values of mobile education over time. For example, this research can be replicated in the near future when mobile education becomes more widely available. The results of this research can also be operationalized to develop a set of instruments to measure the values of mobile education.

From a research and development perspective, the means-end objective network derived from this research identifies unresolved issues for future development. For example, the usability of mobile devices has been raised by many subjects. The limited screen size of mobile devices is an area that needs to be addressed. Security of wireless transmission and data encryption also need to be enhanced. The means-end objective network also highlights the issues that software companies need to take into account when designing mobile education applications. For example, mobile education software needs to work around the current limited screen size of mobile devices to maximize readability of display.

From the perspective of learning and education, the results of this research highlight the importance of collaboration in education and suggest that mobile technology can be used in education to facilitate collaboration and knowledge transfer/exchange. Although collaboration has become an increasingly important practice in industry, traditional forms of education that focus primarily on individual assignments and fact-based lectures are still the norm (Felder and Brent, 2005). More pedagogical research is needed to explore ways to incorporate


collaboration in learning and to promote collaborative learning.

Future research can examine the role of information technology, in particular mobile technology, for supporting and facilitating the use of social constructivist learning approach in educational settings. Information technologies can help to bridge the discontinuities (of time, geography, and group composition) (Chudoba et al., 2005) in virtual teams. Prior research on technology innovation has pointed out the importance of fit between information technologies and the tasks to be supported as a precursor to technology use and its subsequent benefits (Goodhue & Thompson, 1995). Task-technology-fit (TTF) model, which was proposed by Goodhue and Thompson (1995), suggests that a fit between the features and functions provided by the technology and the tasks to be supported will result in increased use intentions and better performance. Future research can examine the interplay between the tasks and technology features in collaborative learning.

This research is also a step towards developing a theory in the context of mobile education. It answers the call for theory in information systems research where it is recommended that researchers focus on “generating ideas, theories, and hypothesis, rather than simply testing them” (Fitzgerald et al., 1995; Klein & Lyytinen, 1995). Value-Focused Thinking, which provides a systematic approach to elicit and organize values, has proven to be an effective method of developing constructs in relatively new and under-studied areas.

Implications for Practice

Constructivism focuses on the discovery and construction of knowledge by learners. Mobile technology can enable “education on demand” and “customized learning”, which are learner-centered and allow students to learn at their own pace. The greater availability of educational resources provides greater opportunity for students to “discover” new knowledge and to “construct” knowledge.

Constructed in the social and cultural context, interpersonal interactions are very important. The ability of mobile technology to enable any place and any time communication can provide more opportunities for students to interact with instructors, as well as collaborate among students. Mobile technology can also facilitate collaborative learning by supporting virtual meetings and instant messaging. Students can work on group assignments or team projects in a more flexible and efficient way without the need to meet face-to-face. If a student works full

time or travels a lot, he/she can use mobile technology to catch up with school work, lectures, individual assignments, or group projects during slack time. Our findings are in line with prior literature, which argues that mobile technology mobilizes human interaction in terms of spatial, temporal, and contextual dimensions (Kakihara & Sorensen, 2001; Chatterjee & Sarker, 2007), and facilitates collaboration by bridging discontinuities (of time, geography, and group composition) (Chudoba et al., 2005).

As learning is considered to be cycles of action, feedback, and reflection (Mayers, 1995), mobile technology can hasten these cycles by enabling immediate feedback from instructors, and facilitating virtual meetings with peer students and instructors, as well as supporting virtual collaboration among peer students.

The means-end objective network also identifies ways of addressing the attributes of effective learning process identified by Alavi (1994): (1) enables active learning by allowing students to learn anytime, anywhere; (2) facilitates cooperation and teamwork by providing functions such as virtual meetings and virtual collaboration; and (3) improves learning through problem solving by facilitating teamwork and group projects, as well as the capability to capture data or information from the field.

The means-end objective network also points out the limitations of current mobile technologies such as limited screen size, accessibility, coverage issues, high costs, and security concerns. Thus, instructors and institutions contemplating the adoption and implementation of mobile education need to be aware of the current constraints and shortcomings of mobile technology. A careful analysis of the benefits and costs (including limitations) need to be weighed before embarking on mobile technology implementation. If the costs or limitations outweigh the benefits, the implementation could be deferred while mobile technology continues to advance rapidly. Some of these constraints or costs could be resolved or alleviated fairly quickly and hence, the right timing could be crucial for success. The means-ends objective network presented in this research can be used to provide guidance on the key factors in the analysis.

Contributions Given the rapid advancement of mobile technologies, this research addresses a current and important topic on mobile education. This research elicits the values of mobile technology in education using the Value-Focused Thinking approach. It allows us to identify


the values of mobile technology from the students’ and instructors’ perspectives and develop a means-ends objective network that depicts relationships between these values. The results suggest that mobile technology can enable some unique activities in educational settings and provide added values to students. The fundamental and means objectives are discussed in terms of their implications for education.

This research also opens up new directions for future research. For example, the results of this study suggest important means and ways of facilitating mobile education, including maximizing education on demand, maximizing virtual collaboration among students, maximizing customized learning, maximizing organization of education activities, maximizing immediate or rapid feedback in learning, and maximizing student involvement in learning. Empirical studies can be conducted to examine (i) how mobile technology can support these means; (ii) how these means will impact on students’ learning outcomes.

As one of the pioneering research in the area of mobile education, this research is of significance to both academic researchers and education practitioners. The value model (i.e., means-ends network) derived from this research can serve as a conceptual foundation for future research in mobile education. This research is also relevant to practice. It provides directions for improving education and highlights potential areas for mobile application development. It also extends the perspectives of DeLone and McLean’s (2003) model of IS success by expanding on IS success factors from the perspective of mobile education. The fundamental objectives derived in this study can serve as key factors in evaluating the success of mobile applications to education, while the means objectives highlight the antecedents that can contribute to success in mobile education.

Conclusions Collaboration is becoming an important and common practice in industry. For this reason, learning has been re-examined as a constructivist activity where collaboration is the key to learning in today’s educational environment. Mobile technology has tremendous potential in supporting and improving education and its delivery. In this research, we used the Value-Focused Thinking approach to interview students and instructors to identify the values of education that are enabled by mobile technology. These values are represented in the form of a means-ends objective network that not only captures the values of education facilitated by

mobile technology but also depicts the relationships between these values. The means-ends objective network derived from this research can serve as a conceptual foundation for future studies and provide useful guidelines to practitioners for implementation of mobile technology in education.

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About the Authors

Hong Sheng is an Assistant Professor in Information Science and Technology (IST) at the Department of Business and Information Technology in the Missouri University of Science and Technology (Missouri S&T) (former University of Missouri-Rolla). She is co-directing the Laboratory of Information Technology Evaluation (LITE lab) at Missouri S&T. Dr. Sheng received her Ph.D. and master degrees from the University of Nebraska-Lincoln with a specialization in Management Information Systems (MIS), and her bachelor degree is from Shanghai Jiaotong University, China. Her research interests include mobile commerce and ubiquitous commerce, trust and privacy issues in information systems, use of IT to support teaching and learning, and human-computer interaction. She has published research papers in journals such as Journal of Association for Information Systems, Information Systems Journal, Journal of Strategic Information Systems, Communications of the ACM, IEEE Transactions on Education, Journal of Database Management, and International Journal of Electronic Business.

Keng Siau is the E. J. Faulkner Professor of Management Information Systems (MIS) and Full Professor of Management at the University of Nebraska-Lincoln (UNL). He is the Director of the UNL-IBM Global Innovation Hub, Editor-in-Chief of the Journal of Database Management, and North America Regional Editor of the Requirements Engineering journal. He received his Ph.D. degree from the University of British Columbia (UBC). His master and bachelor degrees are in Computer and Information Sciences from the National University of Singapore. Professor Siau has over 200 academic publications. He has published more than 100 refereed journal articles, and these articles have appeared (or are forthcoming) in journals such as Management Information Systems Quarterly, Journal of the Association for Information Systems, Communications of the ACM, IEEE Computer, Information Systems Journal, Journal of Strategic Information Systems, Information Systems, ACM

SIGMIS’s Database, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Professional Communication, IEEE Transactions on Information Technology in Biomedicine, IEICE Transactions on Information and Systems, Data and Knowledge Engineering, Journal of Information Technology, and International Journal of Human-Computer Studies. He served on the organizing committees of AMCIS 2005, ER 2006, AMCIS 2007, EuroSIGSAND 2007, EuroSIGSAND 2008, and ICMB 2009. Professor Siau has received numerous research, teaching, and service awards. He received the International Federation for Information Processing (IFIP) Outstanding Service Award in 2006. He is also a recipient of the IBM Faculty Award in 2006 and 2008.

Fiona Fui-Hoon Nah is an Associate Professor at College of Business Administration, University of Nebraska-Lincoln. Her research interests include human-computer interaction, virtual worlds, mobile and ubiquitous commerce, computer-supported collaborative work, knowledge-based and decision support systems, and enterprise resource planning. She has published her research in journals such as Journal of the Association for Information Systems, Journal of Strategic Information Systems, Communications of the ACM, Communications of the Association for Information Systems, International Journal of Human-Computer Studies, International Journal of Human-Computer Interaction, Behaviour & Information Technology, Journal of Electronic Commerce Research, Journal of Computer Information Systems, and Information Resources Management Journal. She is Associate Editor of AIS Transactions of Human-Computer Interaction, and Journal of Electronic Commerce Research. She also serves on the editorial boards of several other MIS journals including Journal of Association for Information Systems, Information & Management, Information Resources Management Journal, and Journal of Global Information Management. Dr. Nah is a co-founder and past chair of AIS Special Interest Group on Human-Computer Interaction (SIGHCI). She received an Outstanding Service Award from SIGHCI in 2005. She received her Ph.D. in MIS from the University of British Columbia, and M.Sc. and B.Sc. (Honors) in Computer and Information Sciences from National University of Singapore. She has previously served on the faculty at Purdue University.


Documents

Understanding the values of mobile technology in education