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Digital media are known to have a differentiated impact upon consumer transactions, information gathering and citizen participation (Long, Webber and Li, 2008). As Frand (2000) points out, many business sectors like banking and publishing, are facing an uncertain scenario with the rise of the new generation of Digital Natives: will anyone go to a "bank" anymore? Will textbooks still be printed? Will libraries be online electronic collections?
As mentioned in the introduction of this study, the Digital Natives are an important target for marketers because of their size and spending power, but their consumption patterns are nowadays far from being fully understood (Noble, Haytko, Phillips, 2009). Furthermore, this generation will soon be part of the workforce and it is a central issue for internal market oriented employers to find the best strategies to motivate them in the workplace, by improving the company's internal marketing (Raines, 2002).
Digital Natives behaviours and preferences, like their scarce tolerance for delays, ubiquitous connectivity and preference for typing over writing, are important to firms who want to offer a good service to Digital Natives customers. In the era of eBay, online banking 24/7 and Amazon, Digital Natives expect high level of responsiveness from companies, as well as from self-service technologies.
Studies by Long and McMellon (2004) proved that confused definitions of customers' expectations are one of the most important causes for electronic services to fail in meeting quality requirements. It has also been proved that a consumer's overall technology beliefs have an influence on their propensity to adopt new technology (Parasuraman et al. 2000). In other words, "customer specific attributes might influence, for instance, the attributes that customers desire in an ideal web site and the performance levels that would signal superior e-Service Quality" (Parasuraman et al. 2000, p.216). The list of Digital Natives attributes employed in this study is a first step to help developing a new set of preferences and beliefs among Generation Y consumers that might be need to be considered when designing effective web sites and e-services.
Digital Natives skills are essential to employers (Raines, 2002) and the other articles on their management....add bullshit here.
It has been argued that as information is becoming more and more a commodity (Openshaw and Goddard 1987), the lack of knowledge on how to use information technology is a significant barrier to employment (Long, Webber and Li, 2008). Investigating the motivation and the school results of students who possess an Information age mindset is therefore essential as those skills, needed in the workplace, might need to be leveraged by colleges and universities to better the students' employability records and prepare them to fulfil the needs of modern organization. If the simple accumulation of knowledge is becoming less important and college dropouts such as Bill Gates become icons of the new generations, perhaps Digital Native sustainers are right in calling for an educational reform that taps into the students' new skills.
Lack of skills with technology might also bring to social exclusion
Acadamic performances of their students by tapping into their new digital skills could also help to fill the Digital Divide that
As information becomes increasingly commodified the lack of access to a computer, or a lack of knowledge of how to use it, may in time become as significant a source of disadvantage as for example access to or lack of access to a car or access to or lack of access to central heating. Arguably, in terms of employability, a lack of competence in the use of information technology may become as significant a barrier as a lack of higher educational qualifications
The Digital Natives and the Information Age Mindset
Literature on e-Service quality measurement introduce several dimension like Access (the ability to get on a website quickly and to reach the company when needed), Responsiveness (i.e. quick response and the ability to get help if there is a problem or a question) and Ease of navigation (Zeithaml, Parasuraman, and Malhotra, 2000) that are related
Today's students are defined by Prensky (2001a, p.1) as 'Digital Natives' i.e. "native speakers of the digital language of computers, video games and the Internet". As a result of the fact that these students have grown up immersed in technology and never knew a time without the Internet, e-mail and mobile telephones, Prensky theorizes that they think and process information in a different way from previous generation. To sustain this argument, he relies on neuroplasticity theories, which suggest that the brain is flexible and able to adapt to changes in the environment. Therefore, he argues, young student's brains are completely different from adults who grew up without technologies.
Following this linguistic metaphor, in Prensky's terms today's adults and teachers are Digital Immigrants "who speak an outdated language" (2001a, p.2). They might be able to learn the new language, but they will always retain their immigrant 'accent'.
The Immigrant/Natives dichotomy is believed to have serious negative consequences on student motivation, attention spans, satisfaction (Oblinger, 2003, Prensky, 2001a; Levin and Arafeh, 2002). For Prensky, teachers are struggling to teach these new generations, while students "cry out" for new approaches to education.
Prensky's definition of Digital Natives is partly derived from Frand (2000) who identifies ten attributes of what he defines the Infomation Age Mindset. These attributes are used in this study as a base for an operational definition of the construct of 'Digital Nativeness' and therefore are worth a further examination.
The first attribute ascribed to Digital Natives by Frand is that they view computers as a normal part of life, rather than as "technology". If technology is considered as "anything that isn't around when you were born" (Frand, 2000 p.16) it's easy to tell why computers are not seen as technology by the young generations. Rather than being impressed by new, highly sophisticated gadgets, the Natives tend to have a "what took so long?" reaction instead.
A second characteristic of Digital Natives is the belief that Internet is better than Television. Frand states that the Natives are using the web as their primary source of information. On one hand the Internet is a more interactive media compared to the TV and this should partly overcome one of the TV major flaws. On the other hand, the information overload and the rudimentary search techniques adopted by the majority of them makes it difficult to distinguish facts and fiction, reliable and unreliable sources. Information overload and lack of time might also be some of the reason why students' engage in a trial and error approach rather than using traditional problem solving techniques (see the Nintendo over Logic attribute).
The third feature of the Digital Natives is named by Frand Reality no longer real. This attribute refers to the problem of content authenticity on the Internet. Many Internet resources are not reliable and personal identities can be stolen or cloned. Distinguishing between what is real and what is not has become one of the major challenges for the Digital Natives.
A fourth quality of the Digital Natives is their preference for Doing an activity rather than knowing the theories behind it. This attribute is central to this study as it is directly related with student's achievement goal orientation (mastery or performance oriented students). Frand observes that in a world dominated by digital technologies, where drastic changes occur, the life span of information is measured in months. Therefore, knowing many facts is becoming less and less important, while the ability to deal with complex and ambiguous information is fundamental for students entering the workforce.
Another learning preference is the one that involves the adoption of a "Nintendo" approach to learning, that is, using trial-and-error, to achieve desired result rather than careful research. Frand describes this style as typical of the new generation of students, born with videogames, that tend to approach problems in a trial and error fashion rather than using the scientific method approach, i.e. careful evaluation of the consequences before attempting a solution. Whether this might affect students' capacity of in-depth analysis is a much debated question. Prensky (2001b) also considers that Digital Natives have lost in reflection and critical thinking while they have enhanced parallel processing skills (see the Multitasking attribute).
The sixth Digital Natives attribute identified by Frand is a classic of the Digital Natives literature and it describes their preference for Multitasking, with no task receiving full attention from the student. Along with the trial and error approach, this is one of the most common strategy adopted by Digital Natives to cope with the information overload and the lack of time for deep problem evaluation. According to Prensky (2001b), children are now capable of distributing their attention strategically while attending two tasks at a time. The problem with this new skill, enhanced by digital technologies, seems to be that Digital Immigrants educators, who just do not believe that students can learn while listening to music, ignore it.
Observing Digital Natives, Frand came to the conclusion that they prefer Typing on a keyboard rather than writing on paper. The power of word-processing goes beyond improvements in spelling and legibility and allows brand new way of playing with ideas, allowing non-linear thinking. Similarly, spreadsheet and databases enable to solve problem and make decision in a new fashion.
The typical Digital Natives student is always connected, no matter what. Here the power of networking is considered as a function of the number of people that take part to that network. The more people, the more that network will be useful to its users. Love for team work and networking is a trait of the Digital Natives that is well know and recognized by many studies (e.g Howe and Strauss, 2000).
According to Frand, Digital Natives are also impatient, showing "zero tolerance" for delays. The cyberage has modified our need for immediacy. We have already discussed that the time to produce accurate in-depth analyses is a luxury that few people can afford and we mentioned multitasking as well as trial and error as strategies used by the Digital Natives to cope with time constraints. As consequence, the new generation of students also expect zero delays when accessing to services or information. 24/7 banking services, instant messaging, ubiquitous broadband connectivity are just useless technical means if the human component of the service act as a bottleneck in the information delivery processes. The "zero tolerance for delay" attribute is more evident when we think about e-mails: people tend to apologize if they are not responding immediately and adopt a much less formal language to speed up the communication.
The last consideration made by Frand is that the traditional distinction between creator and consumer of information is blurring. This trend is almost ubiquitous: User Generated Contents, Mash-Ups, Creative Commons licenses, open-source movements, social bookmarking. Everywhere users are getting involved in producing, sharing and improving contents, without copyright restrictions. Where in traditional media the users where involved in co-create the meaning of the content by interpreting it, now they are capable of modifying the content itself and share it back with the audience. This is consistent with the "doing rather than knowing attribute" that already takes into account the Digital Natives preference for taking part into productive processes rather than being passive learners.
Similar views on Digital Natives are shared by other authors (Oblinger, 2003; Oblinger and Oblinger, 2005, Tapscott, 1998; Rainie 2006; Gibbons, 2007). These studies confirm that students nowadays show distinct learning preferences such as team working, multitasking, use of technology and experiential activities.
Underwood (2007) stress on the existence of a Natives / Immigrants Digital divide and quote evidence from Hargittai (2002) that showed how young generations are more skilled in searching the web than people over 30s. However this dichotomy has been heavily criticized by many commentators: while it is undoubtedly true that young people have familiarity with a greater range of ICTs in their household, tend to use the Internet as a first port of call and multi-task more (Cheong, 2008; Dutton, Helsper and Gerber 2009; Helsper and Eynon, 2010), significant differences found within cohorts of young people undermine the idea of homogeneity that lie at the base of the Natives / Immigrants opposition.
The Digital Natives Debate
When it comes to quantitative evidence, the Digital Natives definition becomes a controversial topic: Kvavik, Caruso and Morgan (2004) for example, surveyed 4,374 students across 13 institutions in the United States. On one hand they found high level of technology ownership (93,4% for personal computers and 82% for mobile phones) and high levels of academic and recreational activities based on Information Technologies (99.5% users used word-processing, e-mailing and Internet browsing for pleasure). On the other hand, students showed only a moderate preference for the use of technology in classroom and as Kvavik (2005, p.98) points out, "ironically, many of the students most skilled in the use of technology had mixed feelings about technology in the classroom". A much more extensive follow up to this study among 18,000 university students (Caruso and Kvavik, 2005) seems to confirm the fact that no significant correlation exists between use and skill of technology and preferences for increased use of technology in the classroom.
Some authors refuse the Digital Natives arguments radically: Facer and Furlong (2001) point out that the distinction between natives and immigrants is not backed up by any empirical evidence. The authors also warn about the possible dangers coming from teachers who assume a level of digital knowledge that is not accurate for all students. Similar arguments are made by Bennett et al. (2008) who quote several quantitative surveys assessing that a significant proportion of young people do not hold the access or the technologic skills predicted by Digital Natives sustainers. She deducts therefore that "It may be that there is as much variation within the digital native generation as between generations" (p.779). This is confirmed by Krause (Krause 2007; Kennedy et al. 2008) who conducted a study on 2,000 first year university students in Australia whose result shows that the patterns of access and use of a range of technologies and tools (e.g. computers, mobile telephones, e-mail) change sensibly across the student populations (according to socio-economic background, age and gender). She concludes stating that the "assumption of homogeneity is misleading and dangerous" (2007, p138).
Significant differences in how and why students use information technologies have been also highlighted recently by a number of writers (Livingstone and Helsper,2007; Hargittai and Hinnart, 2008). More recently, Helsper and Eynon (2010) analyzed secondary data on UK students coming to the conclusion that generation is not the only predictor of Digital Nativeness. From their research it seems clear that many other variables such as gender, education, experience and breadth of use concur to explain this behaviour.
Since generation seem to be not the only antecedent to Digital Nativeness, it is not surprising that many researchers criticized the Natives-Immigrants dichotomy (Bayne and Ross, 2007) or introduced additional categories based on a continuum (Currant et al., 2008), to better reflect the variation in Digital Nativeness that is considered to be cross-generational.
In the light of the many studies showing lack of homogeneity within the student population, the research design of this study is assuming that the chosen sample (a class of undergraduate students belonging, therefore, to the same generation) is showing significant variation in the degree of acquaintance with technology (i.e "Digital Nativeness"), measured using Frand's (2000) definition of the Informational Age Mindset. A further confirmation that a variation in the construct is to be observed comes from Frand itself, who states that his ten attributes are broad generalizations, not all of which apply to each individual.
The above considerations have led the critics to be cautious about rethinking established teaching methods and a call for a more measured debate between sceptics and advocates of the Digital Natives idea has been made (Bennett et al. 2008). To shed more light into the Digital Natives debate, this research is looking at the motivational implications of the Digital Nativeness attribute, investigating whether students who respond to the Digital Natives definition show amotivated or work-avoidant behaviour.
Motivation can be defined as "the physiological process involved in the direction, vigor and persistence of behaviour" (Bergin, Ford and Hesse, 1993, p.437). As Prensky (2003, p.1) puts it "a sine qua non of successful learning is motivation: a motivated learner can't be stopped." Research reporting on high school students' motivation to learn argued that motivation is a key factor in the success or failure of education (National Research council, 2004). The motivated learner status is often depicted as an ideal condition, where students are enthusiastic, focused and persistent. Constructivist learning theorists (e.g. Piaget, Papert) have always stressed on the need of engaging and motivating students, a task whose difficulties seems to be increased by the rise of new technologies and videogames (Carstens and Beck, 2005).
Digital Native sustainers typically support the Immigrant/Native opposition as based on age differences (Prensky 2001a; Gibbons 2007; Underwood, 2007). One of their most debated claims is that the gap between the technological skills of the new students and the limited use of technology adopted nowadays by teachers has a negative impact on student motivation, causing disaffection, alienation and disappointment (Prensky, 2005; Levin & Arefeh, 2002; Oblinger, 2003).
"It generally isn't that Digital Natives can't pay attention, it's that they choose not to" (Prensky, 2001b, p.4).
Students' lack of motivation and alienation from school has received some degree of attention from educational researchers that recognize it as one of the most prominent academic problems (Legault et. al 2006). According to the self-determination theory (SDT, Deci and Ryan, 1985), amotivation is a class of behaviours that are either performed for unknown reasons or not executed at all. Amotivation is a state in which the person cannot perceive the link between their behaviour and the outcome of that behaviour.
As a consequence, amotivated individuals perceive their behaviour as caused by forces that are not under their control. They feel detached from their action and therefore will invest little effort or energy in its effectuation (Legault et.al 2006). Traditional SDT approach defines amotivation as a one-dimensional construct and in this form it has been used for measuring students orientation toward the academic environment (Vallerand et. al., 1992). However further studies (Pelletier et. al. 1999) showed the multidimensional nature of amotivation. Legualt et.al (2006), in a series of studies, developed a taxonomy of reasons that give rise to academic amotivation, comprising of four dimensions: ability beliefs, effort beliefs, characteristic of the task and value placed on the task.
For the purpose of this study, characteristic of task and value placed on task are the only relevant amotivation dimensions that are included in the conceptual model.
The characteristics of task dimension "denotes the specific features of the academic task that may lead to amotivation" (Legault et. al. 2006, p.569). Unappealing tasks are likely to be neglected, leading to disengagement.
The value placed on task evaluates the acceptance of an activity from the students. It has been proved that when a task is not important to the student, amotivation is likely to arise (Ryan and Deci 1999; 2000).
Sustainers of the Digital Natives/Immigrants opposition claim that new generations, born with videogames, should be engaged through the use of multimedia or instructional games (e.g. Carstens and Beck, 2005; Garris et al. 2002) and are not paying attention because of the way tasks are actually presented in class (Prensky, 2001b). The following hypothesis is therefore included in this study:
H1: Students with a higher degree of 'Digital Nativeness' will be more amotivated than students with a lower degree of 'Digital Nativeness'
From a conceptual viewpoint, amotivation subtypes are associated with negative outcomes such as poor academic performances, low academic self-esteem and intent to withdraw from high-school (Legault et. al., 2006). As a consequence it will be hypothesised that the amotivated Digital Natives students will show poor academic performances.
H2: Students with a higher degree of 'Digital Nativeness' will show worse exam performances than students with a lower degree of 'Digital Nativeness'
Academic amotivation is not the only construct that has been examined by motivational researcher interested in detrimental behaviour. Within the Achievement Goal stream of motivational research, the work avoidance goal (also named "academic alienation") received a considerable amount of attention (Meece et al 1988; Nolen, 1988; Nicholls et al 1985; Elliot and Harackiewicz, 1996; Seifert and O'Keefe, 2001).
Work avoidance goal is defined as an attempt to get away with putting as little work or effort as possible into achievement tasks (Elliot, 2005). Similarly to amotivated students, students with a work avoidance goal are likely not attempt to do their work. Their main concern is to get the work done with a minimum amount of effort (Meece et. al, 1988). However, work avoidant students unlike amotivated ones, have a motivation: which is to put little effort on work. Work avoidant students therefore do not perceive the lack of contingency between behaviour and outcome, typical of amotivated students (Seifert, 2004).
Work avoidant goals are also to be distinguished from performance goals. In performance goals, success with little effort is a prove of ability whereas failure with little effort does not provide a proof of low ability. In work avoidance goals, alienated students have their interest and source of self-esteem outside of the classroom and so lack of effort is not used as a way to conceal lack of ability (Archer, 1994).
The idea that Information and Communication Technologies are, in general, generating alienation in human learning and social exchange has been sustained by many authors (Cooper, 1995; Rintala, 1998). Some educators like Tell (2000) described Digital Natives as an alienated youth, surfing the internet in social isolation. As Knapp (1998) points out, the "computer-based information technologies separate and alienate people from direct experience with nature and community [...] and lead to inadequate curricula" (p.7)
Digital Natives sustainers support the idea that the Natives/Immigrants divide, combined with lack of technology in classroom, is the cause of student alienation, whereas these commentators ascribe alienation to Information Technologies and contemporary society. While the latter views are partly surpassed with the breaking of the Social Web, they offer a post-modernist explanation for the students' adoption of work-avoidant goals. Whatever the reason for this behaviour might be, the literature offers enough evidence to hypothesise that students with high degree of Digital Nativeness will show amotivated and work-avoidant behaviours.
H5: Students with a higher degree of 'Digital Nativeness' will be more work-avoidant than students with a lower degree of 'Digital Nativeness'
Achievement Goal Orientation
In their review of the effects of computer based instruction (CBI) on motivation, Moos and Marroquin (2009) show that while a number of studies investigated effects of CBI on Interest, Intrinsic/Extrinsic motivation and self-efficacy, there is a lack of research within the goal-theory framework. Recognizing the central role of the achievement goal orientation on academic performances, this study is filling this gap with a deep investigation of students' goal-oriented behaviour.
As mentioned in the review of the Digital Natives literature, many commentators, based on research evidence, made a call for a measured debate on the Digital Native idea before rethinking the whole educational system. In fact, far from craving for a complete digital experience, students seem to recognize the motivational role of teachers in education. Qualitative research from Oblinger and Oblinger (2005, p.14), for example, reports the following students' considerations:
Teachers are vital to the learning process. Tech is good, but it is not a perfect substitute.
Computers can never replace humans.
Learning is based on motivation, and without teachers that motivation would cease to exist.
Similar considerations can be done looking at Kvavik, Caruso and Morgan (2004) quantitative research: if many of the students most skilled in the use of technology have mixed feelings about technology in the classroom, they have less reason to show the amotivated or work-avoidant behaviour theorized by Digital Natives sustainers.
Further doubts on Prensky's idea of amotivated students (Prensky, 2001a) may rise looking at the students traits as depicted by Howe and Strauss in many of their works (Howe and Strauss, 1993; Strauss and Howe, 1997; Howe and Strauss, 2000). It emerges a picture of students perceiving themselves as special and highly expectant. Ambitious, even though directionless (Schneider and Stevenson, 1999), they are also described as very confident and have been encouraged to believe in themselves from parents and teachers (Lancaster and Stillman, 2002).
Howe and Strauss also point out that their parents have pushed Digital Natives to be the best they can, pressuring them to perform and excel. As students, they feel the pressure to conform to these expectations and have developed one of their primary characteristics that is their need for achievement. They expect high grades as a reward for conformity to academic standards, they like to have constant feedback; they are competitive and goal-oriented.
This kind of achievement, goal-oriented behaviour has been analyzed extensively within the motivation literature associated with the study of academic achievement. The achievement goal orientation is defined as "a set of behavioural intentions that determine how students approach and engage in learning activities" (Meece, Blumenfeld and Hoyle, 1988, p.514). For Dweck, "Achievement goals must lie at the heart of any analysis of achievement motivation" (quote)
Authors like Nicholss (1984) and Dweck (1986) identified two types of goals that have received great theoretical and empirical attention in the motivation literature:
Mastery goal (also called learning goal) defined as a desire to gain competence or master a new set of skills or knowledge (Archer, 1994);
Performance goal (also called proving goal) defined as desire to perform better than others, demonstrating one's competence or avoiding to show incompetence (Elliott, 2005).
It was initially hypothesized that mastery goals led to positive outcomes (e.g. persistence in the face of failure, deep processing of study material, enhanced task enjoyment), while performance goal led to deleterious one (withdrawal of effort, surface processing, decreased task enjoyment) (Nicholls, 1989; Nolen 1988; Dweck and Leggett, 1988). A closer examination at research studies however, indicated that while mastery goal seemed to lead to positive outcomes, mixed result were obtained when looking at performance goals (Harackiewicz and Elliot, 1993).
As a consequence, Elliott (1994) suggested the incorporation of another distinction (approach/avoidance) to explain the variation in results for performance goals. "In approach motivation, behaviour is instigated or directed by a positive or desirable event or possibility, whereas in avoidance motivation, behaviour is instigated or directed by undesirable event or possibility" (Elliot, 1999, p.170).
A first, trichotomous achievement goal model was introduced by Elliot and Church (1997) including mastery goal, performance-approach and performance-avoidance goal. Performance-approach goal focus on the attainment of potential positive outcome (e.g. performing better than other students), whereas performance-avoidance goal focus on the avoidance of potential negative outcome (e.g. avoiding performing worse than other students) (Elliot, 2005). A vast majority of empirical studies based on this model (over 60 by the end 2003 according to Elliot (2005)) clearly documented that the majority of negative consequences of performance goals were to due to performance-avoidance goal orientation.
Successively Elliot and McGregor (2001) extended the approach/avoidance distinction to the mastery-goal, resulting in the 2x2 Achievement goal framework and in the development of the Achievement Goal Questionnaire (AGQ) employed in this research.
Mastery-approach goals entail striving to develop one's skill and abilities (Elliot, 2005) and are similar to the mastery goal as previously defined in the literature. But as Elliot and McGregor point out, approach is not the only form regulation for mastery oriented students. For example, students might strive to avoid misunderstanding or failing to learn course materials, or avoid forgetting what they have learned. This is an avoidance form of regulation, typical of perfectionists, who avoid making mistakes or doing anything wrong (Elliot and McGregor, 2001).
It is possible to argue that the performance/mastery distinction relates with many of the attributes pertaining to the Digital Natives as described by Frand (2000), including the "doing rather than knowing" approach that is central to this study, as it should directly impact the achievement goal that students will set. Furthermore, the performance-approach goal orientation (that is related to performing better than other students) is rather consistent with the competitive and confident traits described by Howe and Strauss (2000). By being confident of their competence, students are more likely to favour a performance-approach over a performance-avoidance or work-avoidant goals. These considerations lead to the following hypothesis:
H3 Students with a higher degree of 'Digital Nativeness' will show a preference for performance-approach goals
In the light of the approach/avoidance distinction a new pattern became clear and it is that mastery-approach goals often did not predict positively performance attainment as originally believed, whereas performance-approach goals did, on more consistent basis (Elliot, 2005). Therefore the following hypothesis will be tested:
H4: Students with a higher degree of 'Digital Nativeness' will show better exam performances than students with a lower degree of 'Digital Nativeness'
Additional arguments against the Natives/Immigrants opposition come from cognitive researchers that argue against the idea that young people's brains have changed in recent times (see Herther, 2009 for a review). But whether or not we are facing a revolution in brain structures, it is nonetheless true that experience is able to alter our cognitive capabilities. What is still to be established is whether technologies are making us smarter, like Digital Natives sustainers claims, or lazier and less able, like some commentators (Carr, 2008; 2010) suggest. Obviously there is no clear answer, but both Carr and Prensky agree on the fact that something got lost with the diffusion of Digital Technologies and the list includes deep processing, reflection and critical thinking. Similar observations are made by Frand (2000) in his analysis of the consequences of the trial and error approach. The author expresses concerns whether students who cannot derive an answer from using trial and error are prepared to engage in deep analyses. The following hypothesis is therefore stated:
H6: Students with a higher degree of 'Digital Nativeness' will show a lower degree of Critical Thinking
Literature suggests that Digital Natives thrive when multitasking, parallel processing and surface thinking. In a fast-paced world, these skills might perhaps be more important, as is suggested by Digital Native sustainers. Are the current examination and teaching methods tapping those skills? To find out, this study is also looking at the correlation between the Digital Nativeness construct and the students' Academic performances.
Academic Performances (Grade Point Average)
There is a whole body of literature that investigated the relationship of academic motivation with academic performance. Different motivational approaches have been used by different authors: expectancy value theory (e.g. Berndt and Miller, 1990) goal theory (e.g. Meece and Holt, 1993) self-efficacy theory (e.g. Zimmerman et al., 1992), and self-determination theory (e.g. Grolnick et al., 1991). In general, such researches reveal that academic motivation positively influences academic performances.
In this study both the Self determination theory (for the Amotivation construct) and the goal theory (for the achievement goal orientation and work avoidance constructs) frameworks are employed.
Amotivation has been proved to be an excellent indicator of GPA (Karsenti and Gilles, 1995) and to be related with negative outcomes (Deci and Ryan, 1985, Vallerand 1997). Similarly, work avoidant student are likely not to engage with classroom work and impact negatively their achievement. Furthermore, learning alienation has been proved to have an inverse relation to academic achievement (Johnson, 2005).
Within the achievement goal orientation framework, performance-approach goals, as previously stated, have been proved to predict positively performance attainment. Harackiewicz et al. (2002) provide a review of a series of research that consistently demonstrates that performance-approach goals are the only achievement goals that are positively related to actual performance (e.g. semester GPA, exam performance and final grade). This means that instead of favouring content mastery, educators could actually encourage students to follow performance-approach goals in order to motivate them to succeed.
Regarding the direct relationship between Digital Nativeness and GPA, Kvavik (2005) found no significant relationship between computer skills and GPA. Similarly, in the same study no relationship between GPA and preference for technology in the classroom was found. Unsurprisingly, students with lowest GPAs were found to spend more time playing computer games, whereas student with highest GPAs spend more time using the computer in support of classroom activities (Kvavik, 2005).
However, the effects that the Digital Natives' mindset and study preferences have on GPA have never been considered before. By including the mediator effect of amotivation, work-avoidance, critical thinking and performance-approach goal orientation, this relationship is investigated, resulting in the following theoretical model:
As the model shows, competing hypothesis H2 and H4 are a result of the ongoing Digital Natives debate and the opposite views dividing sceptics and enthusiasts. Rather than accepting one hypothesis over another, this study investigates whether technology is going to have a positive (H4) or a negative impact (H2) on Academic performance, as a result of the considered mediators (Amotivation, Work Avoidance and Performance Approach Orientation).
Achievement goal orientations have been proved to be related with job
Engaging worker through Digital Technologies = Internal Marketing Orientation.
Technology spontaneously delight customers
Herzberg's two-factor theory , Maslow's hierarchy of needs , and McGregor's theories
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A.H. Maslow, Motivation and Personality. Harper & Row,
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D. McGregor,The Human Side of Enterprise. McGraw-Hill,
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The theoretical grounding includes also the work