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    1. Digital Natives + Others = First Year Students Dr Gregor Kennedy Biomedical Multimedia Unit with colleagues: Dr Kerri-Lee Krause, Dr Terry Judd, Ms Anna Churchward & Dr Kathleen Gray

    2. They [digital natives] have spent their entire lives surrounded by and using computers, videogames, digital music players, video cams, cell phones and all the other toys and tools of the digital age It is now clear that as a result of this ubiquitous environment and the sheer volume of their interaction with it, todays students think and process information fundamentally differently from their predecessors. It is very likely that our students brains have physically changed - and are different from ours - as a result of how they grew up. The starting point for this research project was Marc Prenskys (2001) two commentary pieces on the Digital Natives. Prensky, M. (2001a). Digital Natives, Digital Immigrants. On the Horizen, 9 (5). Prensky, M. (2001b). Digital Natives, Digital Immigrants, Part II. Do they really think differently? On the Horizen, 9 (6). This slide contains direct quotes from Prensky. These quotes not only highlight the context or environment in which the so-called Digital Natives have grown up, but also what Prensky says are the results of this upbringing - namely that Digital Natives think differently and it is likely that their brains have a changed physically. For me, this represents a bold claim about the structural and functional changes evident across one generation; this alone makes Prenskys claims worthy of closer attention. The starting point for this research project was Marc Prenskys (2001) two commentary pieces on the Digital Natives. Prensky, M. (2001a). Digital Natives, Digital Immigrants. On the Horizen, 9 (5). Prensky, M. (2001b). Digital Natives, Digital Immigrants, Part II. Do they really think differently? On the Horizen, 9 (6). This slide contains direct quotes from Prensky. These quotes not only highlight the context or environment in which the so-called Digital Natives have grown up, but also what Prensky says are the results of this upbringing - namely that Digital Natives think differently and it is likely that their brains have a changed physically. For me, this represents a bold claim about the structural and functional changes evident across one generation; this alone makes Prenskys claims worthy of closer attention.

    3. Digital Natives = Net Generation = Y Generation = Millennials Born roughly between 1980 and 1994 Characterised by their familiarity with and reliance on information and communication technologies (ICTs). prefer multi-tasking and quick, non-linear access to information; are adept at processing information rapidly; have a low tolerance for lectures; prefer active rather than passive learning; rely heavily on communications technologies to access information and to carry out social and professional interactions. This slide presents how commentators have characterised the Digital Natives. The new references are: Gros, B. (2003). The impact of digital games in education. First Monday. Available at: http://www.firstmonday.org/issues/issue8_7/xyzgros/index.html. Oblinger, D. (2003). Boomers, Gen-Xers & Millennials. Understanding the new students. Educause Review, July-August, 37-47. Frand, J.L. (2000). The information-age mindset. Changes in Students and implications for higher education. Educause Review, September-October, 15-24. This slide presents how commentators have characterised the Digital Natives. The new references are: Gros, B. (2003). The impact of digital games in education. First Monday. Available at: http://www.firstmonday.org/issues/issue8_7/xyzgros/index.html. Oblinger, D. (2003). Boomers, Gen-Xers & Millennials. Understanding the new students. Educause Review, July-August, 37-47. Frand, J.L. (2000). The information-age mindset. Changes in Students and implications for higher education. Educause Review, September-October, 15-24.

    4. Digital Immigrant University staff are ill-equipped to educate Digital Natives, whose sophisticated use of emerging technologies is incompatible with current teaching practice. Prensky (2001) suggests that this disparity is the the biggest single problem facing education today (p. 2). Commentators say educators need to adjust their pedagogical models to suit the preferences of this new generation of students. This slide presents the problem statements that underpin this research project and, again, these are based largely on the original commentary made by Prensky. According to Prensky, the issue is not only that a new generation of students are entering University with a fundamentally different set of attitudes, skills and beliefs; the issue is also that University teachers are Digital Immigrants and are ill-equipped to deal with the Digital Natives. This is regarded by Prensky as a serious problem and the implication of the proposed mismatch a number of commentators have suggested this is that university educators need to adjust the way they carry out their teaching and learning practices in order to accommodate this new generation of students. This slide presents the problem statements that underpin this research project and, again, these are based largely on the original commentary made by Prensky. According to Prensky, the issue is not only that a new generation of students are entering University with a fundamentally different set of attitudes, skills and beliefs; the issue is also that University teachers are Digital Immigrants and are ill-equipped to deal with the Digital Natives. This is regarded by Prensky as a serious problem and the implication of the proposed mismatch a number of commentators have suggested this is that university educators need to adjust the way they carry out their teaching and learning practices in order to accommodate this new generation of students.

    5. The Problem with the Problem Assumptions underlying Prenskys view on students in Higher Education: All incoming University students are Digital Natives. These Digital Natives are an homogenous group. These Digital Natives are more adept with technology than their teachers. Everyday skills with technology will easily translate into beneficial technology-based learning. The difficulty that we have with this line of reasoning is that it seemed to us that many of problems that Prensky and his followers were foreshadowing in Higher Education were based on a number of largely untested assumptions. The first three assumptions are about the technological experiences of students and teachers in higher education which underpin the characterisations of Digital Native and Digital Immigrant The fourth bullet point outlines an assumption sometimes explicitly and often implicitly made by educational technology commentators. It is assumed that if students are embracing mobile phones, iPods, MySpace, etc then not only should we use these technologies in learning, but they will be easy to adopt and students learning will be enhanced in some way. Even if the majority of students WERE in MySpace, the other proposition doesnt necessarily follow. The first two assumptions outlined on this slide are the real drivers for this project. The difficulty that we have with this line of reasoning is that it seemed to us that many of problems that Prensky and his followers were foreshadowing in Higher Education were based on a number of largely untested assumptions. The first three assumptions are about the technological experiences of students and teachers in higher education which underpin the characterisations of Digital Native and Digital Immigrant The fourth bullet point outlines an assumption sometimes explicitly and often implicitly made by educational technology commentators. It is assumed that if students are embracing mobile phones, iPods, MySpace, etc then not only should we use these technologies in learning, but they will be easy to adopt and students learning will be enhanced in some way. Even if the majority of students WERE in MySpace, the other proposition doesnt necessarily follow. The first two assumptions outlined on this slide are the real drivers for this project.

    6. While there are plenty of case studies, and some evidence, of the successful application of technology in Higher Education, there is little empirical research on the Digital Natives per se. Kvavik (2005) and Kvavik & Caruso (2005) ICT permeates all aspects of students lives. Students are comfortable with core technologies; less comfortable with specialised technologies. High levels of use and skill did not necessarily translate into preferences for increased use of technology in the classroom. Students prefer technology to a moderate degree and as a supplement in courses. While there is little evidence in Australia about the characteristics of the Digital Natives, there have been a couple of recent, large studies carried out in the United States. Kvavik, R.B. (2005). Convenience, communications, and control: How Students Use technology. In D. Oblinger & J. Oblinger (Eds.) Educating the Net Generation (pp. 7.1-7.20). EduCause. Kvavik, R. B., & Caruso, J. B. (2005). ECAR study of students and information technology 2005: Convenience, connection, control, and learning (Volume 6). Boulder, CO: Educause. My presentation does not allow the time to go into the results of these studies in detail and this slide is selective in what it reports from the executive summaries and conclusions of these projects. One clear message I get from these US-based studies is that while ICT is integral to students lives, there is variation in its use and there are complexities associated with what students want and expect with regards to the use of ICT in teaching and learning at University. While there is little evidence in Australia about the characteristics of the Digital Natives, there have been a couple of recent, large studies carried out in the United States. Kvavik, R.B. (2005). Convenience, communications, and control: How Students Use technology. In D. Oblinger & J. Oblinger (Eds.) Educating the Net Generation (pp. 7.1-7.20). EduCause. Kvavik, R. B., & Caruso, J. B. (2005). ECAR study of students and information technology 2005: Convenience, connection, control, and learning (Volume 6). Boulder, CO: Educause. My presentation does not allow the time to go into the results of these studies in detail and this slide is selective in what it reports from the executive summaries and conclusions of these projects. One clear message I get from these US-based studies is that while ICT is integral to students lives, there is variation in its use and there are complexities associated with what students want and expect with regards to the use of ICT in teaching and learning at University.

    7. This slide presents the aim of the study reported in this paper. The research team was keen to obtain empirical evidence on the characteristics of incoming first year students and determine the degree to which the characteristics of the first year cohort accorded with the stereotypical Digital Native presented by Prensky. The research team wanted to extend the US studies by examining more specifically students everyday use of emerging technologies and technology-based tools. The boxed note on this slide highlights that this project only sought to tackle one aspect of the proposed defining features of the Digital Natives (their sophisticated experiences with technology); it did not tackle the question of whether incoming cohort of students cognitive structure and function has changed in the last 20 years. This slide presents the aim of the study reported in this paper. The research team was keen to obtain empirical evidence on the characteristics of incoming first year students and determine the degree to which the characteristics of the first year cohort accorded with the stereotypical Digital Native presented by Prensky. The research team wanted to extend the US studies by examining more specifically students everyday use of emerging technologies and technology-based tools. The boxed note on this slide highlights that this project only sought to tackle one aspect of the proposed defining features of the Digital Natives (their sophisticated experiences with technology); it did not tackle the question of whether incoming cohort of students cognitive structure and function has changed in the last 20 years.

    8. 1,973 first year students surveyed. Orientation week and first week of Semester 1, 2006. Good representation across faculties. 62.4% females 37.5% males. 23.4% International 75.2% Local students. This slide provides the general details about the studys method, particularly the sample. First year students who were commencing their studies at Melbourne University in 2006 were surveyed using a four page questionnaire (see next slide). The questionnaire data were collected in students orientation and introductory sessions during orientation week and the first week of Semester 1, 2006 (20 sessions in total). A total of 2120 students returned the survey and of this number 1973 surveys were used in this analysis as they represented students who were born after 1980. Most of the students who participated in the study were born between 1985 and 1988 (accounting for 94.4% of the sample); thus the vast majority of students were between the ages of 17 and 21. More females than males responded to the survey (62.4% females; 37.5% males), approximately a third of the sample were from a non-English speaking background (34.9% NESB; 64.8% ESB) and approximately a quarter of the sample were International students (23.4% International; 75.2% Local students).This slide provides the general details about the studys method, particularly the sample. First year students who were commencing their studies at Melbourne University in 2006 were surveyed using a four page questionnaire (see next slide). The questionnaire data were collected in students orientation and introductory sessions during orientation week and the first week of Semester 1, 2006 (20 sessions in total). A total of 2120 students returned the survey and of this number 1973 surveys were used in this analysis as they represented students who were born after 1980. Most of the students who participated in the study were born between 1985 and 1988 (accounting for 94.4% of the sample); thus the vast majority of students were between the ages of 17 and 21. More females than males responded to the survey (62.4% females; 37.5% males), approximately a third of the sample were from a non-English speaking background (34.9% NESB; 64.8% ESB) and approximately a quarter of the sample were International students (23.4% International; 75.2% Local students).

    9. Demographics (11 items) Access to hardware and the Internet (16 items) Use of tech-tools Computer (10 items) Web (22 items) Mobile (7 items) Skills with tech-tools (39 items) Preferences for tech-tools in University studies (34 items) This slide provides the general details about the studys method, particularly the questionnaire. The questionnaire asked students about their access to hardware and the internet, use of and self-reported skills with 39 technology-based tools in three general areas - general computing, the Internet and mobile phones. The final question in the survey asked students to reflect on the degree to which they wanted to be able to use a series of technology-based tools to assist with their university studies. It is important to note that these incoming first year students were asked to report on their experience with technology across the previous year - that is, they were not reporting on their university experience. This slide provides the general details about the studys method, particularly the questionnaire. The questionnaire asked students about their access to hardware and the internet, use of and self-reported skills with 39 technology-based tools in three general areas - general computing, the Internet and mobile phones. The final question in the survey asked students to reflect on the degree to which they wanted to be able to use a series of technology-based tools to assist with their university studies. It is important to note that these incoming first year students were asked to report on their experience with technology across the previous year - that is, they were not reporting on their university experience.

    10. This slide shows a selection of results for students access to hardware and the internet (not all results can be shown in the time available in this presentation and the interested reader should download a copy of the report at: http://www.bmu.unimelb.edu.au/research/munatives/natives_report2006.pdf) The figures presented in this table refer to the percentages of students in each of the categories of access. Four findings are noted: The very high percentage of incoming first year students who have unrestricted access to mobile phones The array of technologies that the majority of students are reporting unrestricted access to The variation in access to technologies is evidenced by the majority of students having unrestricted access to MP3 players and Portable computers but at the same time close to a quarter of the students sampled have no access to these technologies at all. The majority of students have no access to some technologies (like the PDA). (It is possible that some of the functions of a PDA are now included in the feature sets of mobile phones, and as a result the reported access to this technology is lower). This slide shows a selection of results for students access to hardware and the internet (not all results can be shown in the time available in this presentation and the interested reader should download a copy of the report at: http://www.bmu.unimelb.edu.au/research/munatives/natives_report2006.pdf) The figures presented in this table refer to the percentages of students in each of the categories of access. Four findings are noted: The very high percentage of incoming first year students who have unrestricted access to mobile phones The array of technologies that the majority of students are reporting unrestricted access to The variation in access to technologies is evidenced by the majority of students having unrestricted access to MP3 players and Portable computers but at the same time close to a quarter of the students sampled have no access to these technologies at all. The majority of students have no access to some technologies (like the PDA). (It is possible that some of the functions of a PDA are now included in the feature sets of mobile phones, and as a result the reported access to this technology is lower).

    11. Mobile phone (96%) Desktop computer (90%) Digital camera (76%) Broadband Internet (73%) MP3 player (69%) Laptop computer (63%) This slide really reiterates the figures presented on the previous slide. The point being made here is that there certain technologies being used by students are regarded as core or are becoming so. This slide really reiterates the figures presented on the previous slide. The point being made here is that there certain technologies being used by students are regarded as core or are becoming so.

    12. Sending or receiving email (94%) Mobile phone voice calls (92%) Mobile phone text messaging (93%) Creating documents (88%) Playing digital music files (84%) Web-searching for general information (83%) Communicating via instant messaging (80%) Web-searching for study (76%) Similarly, the analysis of the data relating to the frequency with which students use technologies and technology-based tools shows that there are core technology-based activities that the majority of students are engaging with on a daily or weekly basis. They are listed here and many are not surprising; but is it is nice to have evidence of what students are doing. Similarly, the analysis of the data relating to the frequency with which students use technologies and technology-based tools shows that there are core technology-based activities that the majority of students are engaging with on a daily or weekly basis. They are listed here and many are not surprising; but is it is nice to have evidence of what students are doing.

    13. Mobiles to take digital photos or movies (57%) Mobiles to send digital photos or movies (33%) Web-based file sharing - music (38%) - photos (31%) Blogs - reading (38%) - commenting (27%) - maintaining (21%) We also determined from our analysis of the results that there are a series of emerging technology-based activities.These activities, while not at all universal, are embraced by a small but significant proportion of students on a daily or weekly basis (as shown by the percentages on this slide). The use of mobiles to take and send digital content; file sharing via the web; blogging and relatively recent forms of web-based communication were all technology based activities that between one fifth and one-third of students were engaging with on a daily or weekly basis. It was a surprise to many academics in the University community that 21% of students reported maintaining their own blog on a weekly basis. We also determined from our analysis of the results that there are a series of emerging technology-based activities.These activities, while not at all universal, are embraced by a small but significant proportion of students on a daily or weekly basis (as shown by the percentages on this slide). The use of mobiles to take and send digital content; file sharing via the web; blogging and relatively recent forms of web-based communication were all technology based activities that between one fifth and one-third of students were engaging with on a daily or weekly basis. It was a surprise to many academics in the University community that 21% of students reported maintaining their own blog on a weekly basis.

    14. In order to make the data more manageable for inferential tests, a factor analysis was conducted using students reports of how frequently they used technology based tools. A initial principal components factor analysis with a varimax rotation was conduced and this was restricted at nine factors. The next three slides simply outline the factor loadings of individual items on the nine factors that emerged in this analysis. In general, the factors that emerged from this solution were conceptually distinct and they are labelled at the top the the table. The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting). In order to make the data more manageable for inferential tests, a factor analysis was conducted using students reports of how frequently they used technology based tools. A initial principal components factor analysis with a varimax rotation was conduced and this was restricted at nine factors. The next three slides simply outline the factor loadings of individual items on the nine factors that emerged in this analysis. In general, the factors that emerged from this solution were conceptually distinct and they are labelled at the top the the table. The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting).

    15. The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting).The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting).

    16. The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting). The nine factors shown in this set of three slides are: Web Publishing: Publishing blogs and other web based material. Advanced Mobile Use: Using the advanced features of mobile phones (more than calling and texting). MP3, Pics & IM: This factor captures some of students Web 2.0 activities: hooked on MP3s, IM and flickr. Advanced Web Use: This factor captures some of the more sophisticated web uses, particularly in the area of communication. Standard Web Use: This factor captures the now more standard uses of the web as a reference source, for email, etc. Standard PC Use: This factor captures standard uses of a personal computer. Use of Web Services: While build a website a bit out of place, this factor is dominated by accessing web services and buying and selling. Use of Digital Games: Games, games, games; web, console, PC. Standard Mobile Use: Using the standard features of mobile phones (calling and texting).

    17. Gender Females > Males for: - Web Publishing - Advanced Mobile Males > Females for: - Web Services - Games The nine factors that emerged from the previous analysis were used as dependent variables in a three-way multivariate analysis of variance (MANOVA). The independent variables used were gender, residency (whether students were international or local) and Faculty (Facultys of the University). The result presented on this slide show that apart from the often reported difference between males and females with regard to the use of games, other gender differences emerged. Notably female students engaged in more web publishing (blogging, social networking) and advanced mobile phone use (taking and sending pictures, accessing the web via mobile) than males. The nine factors that emerged from the previous analysis were used as dependent variables in a three-way multivariate analysis of variance (MANOVA). The independent variables used were gender, residency (whether students were international or local) and Faculty (Facultys of the University). The result presented on this slide show that apart from the often reported difference between males and females with regard to the use of games, other gender differences emerged. Notably female students engaged in more web publishing (blogging, social networking) and advanced mobile phone use (taking and sending pictures, accessing the web via mobile) than males.

    18. Very clear residency differences emerged from the MANOVA. International students were engaging in a series of technology-based activities more frequently than local students. The six factors for which this was the case are reported on this slide. Local students were only engaging in the use of web services more frequently than international students.Very clear residency differences emerged from the MANOVA. International students were engaging in a series of technology-based activities more frequently than local students. The six factors for which this was the case are reported on this slide. Local students were only engaging in the use of web services more frequently than international students.

    19. The table on this slide shows the factors for which there were significant univariate effects for Faculty. The acronyms used in this table refer to the faculties of interest (ABP = Architecture, Building and Planning; ENG = Engineering; LFR = Land and Food Resources; Arts = Arts; E&C = Economics and Commerce; MDHS = Medicine, Dentistry and Health Sciences). Rather than report all possible contrasts for each factor and showing where specific significances lie, the data for High and Low users of each technology based activity is reported. This is where the most marked differences were apparent. It can be seen that the Faculties of Architecture, Building and Planning (ABP) and Engineering (ENG) are regularly represented in the high user group for the significant factors. While there is more variation in the low user group, Arts is represented on three occasions. These results are simple summaries of the data that are meant to show that there is significant faculty-based variation in the degree to which students use technology-based tools. The table on this slide shows the factors for which there were significant univariate effects for Faculty. The acronyms used in this table refer to the faculties of interest (ABP = Architecture, Building and Planning; ENG = Engineering; LFR = Land and Food Resources; Arts = Arts; E&C = Economics and Commerce; MDHS = Medicine, Dentistry and Health Sciences). Rather than report all possible contrasts for each factor and showing where specific significances lie, the data for High and Low users of each technology based activity is reported. This is where the most marked differences were apparent. It can be seen that the Faculties of Architecture, Building and Planning (ABP) and Engineering (ENG) are regularly represented in the high user group for the significant factors. While there is more variation in the low user group, Arts is represented on three occasions.

    20. The final set of analyses asked students to rate the degree to which they wanted to be able to use a series of technology-based tools to assist with their University studies. The data in this table represents a subset of the 34 questions asked in this area and is meant to highlight two points: There are technologies and tools that the vast majority of students indicate they would like to assist with their university studies and, conversely, few students indicate they would not be useful. The second pattern of results reflects technologies and tools for which there is more divergence in students responses. For some technologies and tools, a significant proportion of students (30%-40%) indicate they want to be able to use them in their studies but a commensurate proportion (20-30%) indicate they do not want to use them. The final set of analyses asked students to rate the degree to which they wanted to be able to use a series of technology-based tools to assist with their University studies. The data in this table represents a subset of the 34 questions asked in this area and is meant to highlight two points: There are technologies and tools that the vast majority of students indicate they would like to assist with their university studies and, conversely, few students indicate they would not be useful. The second pattern of results reflects technologies and tools for which there is more divergence in students responses. For some technologies and tools, a significant proportion of students (30%-40%) indicate they want to be able to use them in their studies but a commensurate proportion (20-30%) indicate they do not want to use them.

    21. Computer for digital document creation and multimedia presentations, learning portal, web searches and Uni services, instant messaging and SMS. This slide really just reiterates the figures presented on the previous slide. The point being made here is that there are some technologies that most students want to use and for other technologies student endorsement is more polarised. This slide really just reiterates the figures presented on the previous slide. The point being made here is that there are some technologies that most students want to use and for other technologies student endorsement is more polarised.

    22. While there are clearly many tech-savvy first year students; - there is substantial diversity among this cohort - particularly when one moves beyond core technologies. Any technology-based learning and teaching strategies need to consider student equity (access and skill levels). There are essential technologies expected by students. While the use of some technologies is widely endorsed by students; other technologies clearly dont enjoy this endorsement. This slide attempts to pull together some ideas about what the implications of this study are for Higher Education: particularly with regards to how the use of technology dovetails with our - staff, students, institutions - learning and teaching strategies. The utility of this project is that it allows us to ground discussions about how we use technology in teaching and learning in higher education in concrete information about students experiences. Clearly many of our incoming students at the University of Melbourne are highly tech-savvy. But substantial diversity exists among this cohort of students when one moves beyond core technologies and tech-based tools. Not all students have an MP3 player, not all students produce and share digital content, not all students want to blog as part of their studies. There are clear differences between students from different faculties and backgrounds in terms of their experiences with technology. The implications of this are that any teaching and learning strategy that involves technology - particularly emerging ones - needs to consider the degree to which particular student groups are familiar with, have access to and have skills with that technology. This data from this study also suggest there are technologies and tools that students expect in their university studies It is clear that institutions need to continue to support this technological infrastructure and technology-related student services. Finally, we cannot assume that just because many students use a particular technology based tool in their everyday lives, it will be endorsed by them as an educational tool. This slide attempts to pull together some ideas about what the implications of this study are for Higher Education: particularly with regards to how the use of technology dovetails with our - staff, students, institutions - learning and teaching strategies. The utility of this project is that it allows us to ground discussions about how we use technology in teaching and learning in higher education in concrete information about students experiences. Clearly many of our incoming students at the University of Melbourne are highly tech-savvy. But substantial diversity exists among this cohort of students when one moves beyond core technologies and tech-based tools. Not all students have an MP3 player, not all students produce and share digital content, not all students want to blog as part of their studies. There are clear differences between students from different faculties and backgrounds in terms of their experiences with technology. The implications of this are that any teaching and learning strategy that involves technology - particularly emerging ones - needs to consider the degree to which particular student groups are familiar with, have access to and have skills with that technology. This data from this study also suggest there are technologies and tools that students expect in their university studies It is clear that institutions need to continue to support this technological infrastructure and technology-related student services. Finally, we cannot assume that just because many students use a particular technology based tool in their everyday lives, it will be endorsed by them as an educational tool.

    23. The assumptions underpinning Prenskys rhetoric about a new generation of Digital Native students dont quite hold. The sheer volume of their interaction with their technologically ubiquitous environment They have spent their entire lives using videogames, digital music players, video cams, cell phones and all the other toys and tools of the digital age. Its true for some, Its not true for others Not only does the data from this study have important implications for teaching and learning at university, they also have implications for the Digital Natives argument that is currently quite popular. In this slide I have gone back to the assumptions about students experiences with technology that underpin Prenskys original argument. It seems clear from the data we have collected that, at Melbourne University at least, these statements dont hold. There are some Digital Natives and there are some Not-So-Digital-Natives in our First Year cohort (thus, the reason for the title of this talk). Not only does the data from this study have important implications for teaching and learning at university, they also have implications for the Digital Natives argument that is currently quite popular. In this slide I have gone back to the assumptions about students experiences with technology that underpin Prenskys original argument. It seems clear from the data we have collected that, at Melbourne University at least, these statements dont hold. There are some Digital Natives and there are some Not-So-Digital-Natives in our First Year cohort (thus, the reason for the title of this talk).

    24. Rather than scrambling to react to the so-called Digital Natives and changing our curricula in response to what we think they might be like (or like) we need to think carefully about how we can use particular core and emerging technologies to support learning in higher education, given the known diversity of experiences, attitudes and expectations of all students. We need to know more about how emerging technologies particularly can be used appropriately - from both teachers and the learners perspectives - to best support learning experiences in higher education. We need to know more about how emerging technologies particularly can be used appropriately - from both teachers and the learners perspectives - to best support learning experiences in higher education.

    25. The ECAR Framework: Students ICT expectations and preferences This slide presents one perspective on the challenge we as educators face on how to use technology, and picks up on the conference theme of Pushing Boundaries This first phase of this slide presents an adapted - truncated really - form of the EDUCAUSE Center for Applied Research (ECAR) framework that was developed as part of Kvavik and Carusos (2005) work. The ECAR framework is a useful map of students expectations of and preferences for the use of ICT in higher education: Convenience, Connection, Control and Learning. These quadrants are not regarded as mutually exclusive. Technology can simultaneously fulfill a variety of important and valuable roles in higher education as these all are. What is interesting to me is that the first three quadrants of the model are very closely associated with the management, administration and technical support of the information and communication technology in Higher Education, while the fourth quadrant is the only one directly related to student learning per se. When this observation is overlayed by Kvavik and Carusos (2005) findings about what students see as the most valuable benefit of ICT in their university courses, part of the challenge we as educators face with regards how we how should we be using technology becomes more apparent. [The percentages in the second phase of the slide refer to proportion of students who regard that purpose as the most valuable benefit of using ICTs in their courses.] The implication of this for me is that in the area of technology enhanced higher education, the boundaries we need to be pushing beyond are those of convenience, connection, infrastructure, information provision, administration and access. Technology has been - and will continue to be - a wonderful tool in these areas in higher education and we need to ensure that staff and students are supported and their expectations are being met in these areas. But the real challenge is to make new and emerging technologies more relevant and valuable to students LEARNING experiences. Despite the rhetoric about how technology can enhance student learning, implementations often do not directly target learning per se, and as a result they are not perceived as being valuable in student learning by students at least. So in the context of the Digital Natives debate: The issue is not that todays incoming university students are all techno-whizzes (the data in this paper suggests that while some are, many are not). The issue is not that incoming students may think differently (currently there is little empirical evidence to support or refute this idea). The issue is not that lecturers should change their teaching strategies to suit the hypothesised characteristics of a New Generation of students. (Will they be expected to do this for every new generation of students?) The issue - and challenge - for me is an old one: As educators we should try to be aware of the (often diverse) characteristics of our student cohorts. Armed with an idea of who our students are, we should think carefully about how we can use the tools at our disposal to create rich and engaging learning experiences for them. As implied by the bullet points in the fourth quadrant, this is achieved through considered educational design of learning activities - with and without technology. There are numerous examples of how this has been done well, with many different types of technology, over very many years. This slide presents one perspective on the challenge we as educators face on how to use technology, and picks up on the conference theme of Pushing Boundaries This first phase of this slide presents an adapted - truncated really - form of the EDUCAUSE Center for Applied Research (ECAR) framework that was developed as part of Kvavik and Carusos (2005) work. The ECAR framework is a useful map of students expectations of and preferences for the use of ICT in higher education: Convenience, Connection, Control and Learning. These quadrants are not regarded as mutually exclusive. Technology can simultaneously fulfill a variety of important and valuable roles in higher education as these all are. What is interesting to me is that the first three quadrants of the model are very closely associated with the management, administration and technical support of the information and communication technology in Higher Education, while the fourth quadrant is the only one directly related to student learning per se. When this observation is overlayed by Kvavik and Carusos (2005) findings about what students see as the most valuable benefit of ICT in their university courses, part of the challenge we as educators face with regards how we how should we be using technology becomes more apparent. [The percentages in the second phase of the slide refer to proportion of students who regard that purpose as the most valuable benefit of using ICTs in their courses.] The implication of this for me is that in the area of technology enhanced higher education, the boundaries we need to be pushing beyond are those of convenience, connection, infrastructure, information provision, administration and access. Technology has been - and will continue to be - a wonderful tool in these areas in higher education and we need to ensure that staff and students are supported and their expectations are being met in these areas. But the real challenge is to make new and emerging technologies more relevant and valuable to students LEARNING experiences. Despite the rhetoric about how technology can enhance student learning, implementations often do not directly target learning per se, and as a result they are not perceived as being valuable in student learning by students at least. So in the context of the Digital Natives debate: The issue is not that todays incoming university students are all techno-whizzes (the data in this paper suggests that while some are, many are not). The issue is not that incoming students may think differently (currently there is little empirical evidence to support or refute this idea). The issue is not that lecturers should change their teaching strategies to suit the hypothesised characteristics of a New Generation of students. (Will they be expected to do this for every new generation of students?) The issue - and challenge - for me is an old one: As educators we should try to be aware of the (often diverse) characteristics of our student cohorts. Armed with an idea of who our students are, we should think carefully about how we can use the tools at our disposal to create rich and engaging learning experiences for them. As implied by the bullet points in the fourth quadrant, this is achieved through considered educational design of learning activities - with and without technology. There are numerous examples of how this has been done well, with many different types of technology, over very many years.

    26. The Project Team: Kerri-Lee Krause, Terry Judd, Anna Churchward, Kathleen Gray. The Project Sponsor: Associate Professor Sue Elliott, Pro Vice-Chancellor (Teaching, Learning and Equity). Students and staff who assisted with data collection. Billy Lee for this presentation. Barney Dalgarno and Sue Bennett.