Scholarly article on topic 'Investigating the ICT Needs of ‘Digital Natives’ in the Learning of English in a Public University in East Malaysia'

Investigating the ICT Needs of ‘Digital Natives’ in the Learning of English in a Public University in East Malaysia Academic research paper on "Educational sciences"

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{"Digital Natives" / "ICT needs" / "learning English" / "technology use" / "East Malaysia university"}

Abstract of research paper on Educational sciences, author of scientific article — Kean Wah Lee, Siew Ming Thang, Choon Keong Tan, Shi Ing Ng, Sook Jhee Yoon, et al.

Abstract This paper examined the undergraduates‟ patterns and perceptions of technology use in the teaching and learning of English in an attempt to throw further light into the current debate of the need to change the knowledge content and method of delivery in universities to cater to the needs of “digital natives.” A questionnaire survey was used to collect data and was analysed quantitatively through the use of descriptive and inferential statistics. Findings revealed a large majority of the university students surveyed are comfortable with the use of technology, and are incorporating a range of traditional and emerging technologies in their daily and academic lives. However, areas where the use of and familiarity with technology based tools are far from universal or uniform among the students, implying that any effort to optimise the use of technology in language teaching and learning in the university has to be appropriate to the learning environment.

Academic research paper on topic "Investigating the ICT Needs of ‘Digital Natives’ in the Learning of English in a Public University in East Malaysia"

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Procedia - Social and Behavioral Sciences 118 (2014) 242 - 250

SoLLs.INTEC.13: International Conference on Knowledge-Innovation-Excellence: Synergy in Language

Research and Practice

Investigating the ICT needs of 'Digital Natives' in the learning of English in a public university in East Malaysia

Kean Wah Leea*, Siew Ming, Thangb, Choon Keong, Tanc, Shi Ing, Ngd, Sook Jhee, Yoone, Yong Wei, Chuaf, Nadin, Shelly Shirlennag

a School of Education and Social Development, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu, 88400, Malaysia b School of Language Studies & Linguistics, Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia

Abstract

This paper examined the undergraduates' patterns and perceptions of technology use in the teaching and learning of English in an attempt to throw further light into the current debate of the need to change the knowledge content and method of delivery in universities to cater to the needs of "digital natives." A questionnaire survey was used to collect data and was analysed quantitatively through the use of descriptive and inferential statistics. Findings revealed a large majority of the university students surveyed are comfortable with the use of technology, and are incorporating a range of traditional and emerging technologies in their daily and academic lives. However, areas where the use of and familiarity with technology based tools are far from universal or uniform among the students, implying that any effort to optimise the use of technology in language teaching and learning in the university has to be appropriate to the learning environment.

© 2013 TheAuthors.PublishedbyElsevier Ltd.

Selection and peer-reviewunderresponsibilityofUniversiti KebangsaanMalaysia.

Keywords: Digital Natives; ICT needs; learning English; technology use; East Malaysia university

* Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . E-mail address: keanwah@gmail.com

1877-0428 © 2013 The Authors. Published by Elsevier Ltd.

Selection and peer-review under responsibility of Universiti Kebangsaan Malaysia. doi:10.1016/j.sbspro.2014.02.033

1. Introduction

The extent to which technology should be used in teaching and learning in institutions of higher learning is an issue that has been much debated upon in academic circles. This dispute stems from the belief by certain quarters that the current generation of students, born between 1980 and 1994, is highly attuned with technology and possesses sophisticated knowledge and skills in Information Communication Technologies (ICT). Prensky (2001) has labelled them as "digital natives' and Tapscott (1988) called them the 'Net generation' (Tapscott, 1998). In line with this belief it is further argued that there is dire need to change the knowledge content and method of delivery in universities to cater to the needs of these "digital natives". Although this argument has attracted much attention in the West there has not been much research related to it in the Malaysian context. Hence, this study was carried out to address this gap in knowledge by undertaking a study in a public university in East Malaysia, quintessentially viewed as less developed and infrastructurally more challenged and culturally different in terms of ethnicity, religion, and tradition. It examined the undergraduates' patterns and perceptions of technology use in the teaching and learning of English. This study intends to address this gap in knowledge by undertaking a study of the ICT needs of Malaysian undergraduates from an East Malaysia university in Borneo. The study attempts to throw more light into the patterns and perceptions of technology use in the teaching and learning of English. It is hoped findings obtained will enable language instructors to "fine-tune" the knowledge content and method of delivery in the university to cater to the needs of these "digital natives".

1.1. Background of Study

In Universiti Malaysia Sabah (UMS), the adoption of technologies to enhance teaching and learning has been gaining momentum. This is reflected in the increasing number of campus-based courses adopting the blended approach to teaching and learning registered under its Moodle-based learning management system (LMS) called 'SmartUMS' (Tan et al., 2012). Based on Tan et al. (2012) studies, more than 485 lecturers from the 12 academic schools have created 1186 (30%) blended academic courses in SmartUMS. In an effort to further consolidate adoption of technologies in teaching and learning across the university, UMS has drawn up its e-learning Strategic Plan 2013-2015 and earmarked a number of initiatives as its Key Performance Indicators. For instance, the Strategic Plan outlines that by 2013, fifty percent (50%) of all academic courses on offer in the campus should be run on a blended format and by 2015, all courses (100%) should be blended in nature (UMS e-learning Coordinating Committee, 2012).

2. Literature Review

Prensky (2001) and Tapscott's (1988) delineation of a generic term to describe digital natives stems from observing young users displaying a certain aptitude towards technology. This is further compared to users from a previous generation struggling to grasp the skills needed to function in this fast-paced digital environment or "digital immigrants" (Prensky, 2001, p. 2).

Digital Settlers

Digital Immigrant

Digital Native / Net generation

Figure 1: Dichotomy of digital users

Nonetheless, the dichotomy suggests there are only two extreme ends of the continuum and discounts users who progress from basic to near proficient digital literacy skills. "Digital settlers" are users graduating from an analog driven generation to achieve sophistication in their digital skills without discarding their need of analog forms of communication (Palfrey & Gasser, 2008, p. 3 - 4). Despite the widely-accepted terms, the homogenous representation of each category has come under criticism as a superficial assumption based on empirical findings from current research (Bennet & Maton, 2010, Jones et al, 2010, Jones & Healing, 2010, Kennedy et al, 2010).

Current research on identifying the extent of HEI learners' technological prowess demonstrate demographic features, the university environment and learners as important factors in determining the concept of 'digital natives' or 'Net generation'. A survey research conducted between three HEI in Australia identified four types of undergraduate technology users (Kennedy et al, 2010). The usage of eclectic choice of technology equipment and online activity could be influenced by key demographic characteristics i.e. age, gender, cultural background (Kennedy et al, 2010, Corrin et al, 2010). The four types of users are:

Table 1: Categories of four types of learner technology users from Kennedy et al (2010: 337).

Category Types of learner technology users

Power users Use a wide range of technologies in a significant manner.

Ordinary users Use standard Web and mobile technologies, on a monthly average, and tend to not engage in web

publishing and file sharing through Web 2.0 activities.

Irregular users Use standard Web and mobile technologies only on a less frequent basis compared, relatively low

users of all other technologies with the exception of Web 2.0publishing.

Basic users Extremely infrequent use of new and emerging technologies but regular users of standard mobile

features (i.e. call and text people).

One of the major findings indicated by Kennedy et al (2010) is 15% of the respondents fall under the power users category compared to 45% under the basic users category. Corrin et al (2010) similarly report that first-year undergraduates demonstrate a higher percentage of mobile phone use as compared to a lower percentage of employing Web 2.0 tools i.e. blogging as a communication medium. Corrin et al (2010) findings support Kennedy et al (2010) distinction of technology users. The findings denote current homogenous representation of 'digital natives' or 'Net generation' should include various elements ensuring an encompassing representation of advance users of technology. It should be reiterated that 'digital natives' "exist beyond the person...not relying on motives and motivation. but enforced by collective sanctions that can be physical, economic and moral" (Jones & Healing, 2010, p. 354).

3. Research Design

The design adopted for this study is one of a descriptive survey type. According to Fraenkel, Wallen & Hyun (2012), a descriptive survey is a non-experimental design which measures the characteristics of a sample at one point in time. A total of 657 subjects from 3 academic disciplines, i.e. Sciences, Social Sciences, and Economics responded to self-constructed questionnaire aimed at eliciting undergraduates use of technology in the university setting. The breakdown of respondents based on disciplines is shown in Table 2 below:

Table 2: Respondents according to disciplines

Faculty Frequency %

Sciences 218 33.2

Social Science 214 32.6

Economics 225 34.2

Total 657 100

There two major sections that made up the questionnaire used for this survey. Section 1 contained items that gathered the students' demographic data. Section 2 is made up of two parts. The first part aims to gather information on students' ownership and use of technological tools. Respondents were asked to rate their usage of technologies in the contexts of leaning of English and recreation. The second part is aimed at eliciting students' perceptions on the usage of technologies in English language teaching and learning. To ensure all respondents are able to complete the questionnaire, the national language (Bahasa Malaysia - Malay Language) was used. Data collated was analysed using Statistical Package for social Sciences (SPSS) version 20. To get a clearer description of each item, the mean score and standard deviation were computed and compared. In addition to that, the following statistical procedures were also conducted: frequency analysis, item analysis, reliability analysis and ANOVA.

4. Data analysis

Findings obtained is presented based on the following three dimensions, namely 1) ownership and usage of tools; usage of technology in learning English; and 3) opinions on the use of technology in the learning of English.

4.1. Ownership and usage of tools

Table 3 below summarises the distribution of the frequency analysis in terms of ownership and tools used.

Table 3: Ownership of tools (general)

Ownership Mobile Phone % Camera Phone % Music Phone % 3G Phone %

95.4 97.9 89.5 68.8

Ownership Desktop % Laptop % Handheld computer % Portable Media Player %

50.8 91.2 26.8 44.3

Ownership Digital Camera % Games Console % Portable Games Console %

49.4 23.2 21.7

As can be seen, the frequency analysis revealed that phone ownership is generally high, where 95.4% of the respondents own a mobile phone, follow by camera phone (97.7%), music phone (89.5%) and 3G phone (68.8%). A majority of them also possess a laptop (91.2%). Tools that many of them do not have are games console (23.2%), handheld computers (26.8%) and portable games console (21.7%).

In order to have a clearer description, item analysis was carried out to identify the tools that are most and least used by the respondents (see Tables 4 and 5 below). The three most used tools are mobile phones, camera phone and laptops. The least used tools are games consoles, handheld computers and portable media players. A probable reason for this is that the most used tools are mostly multi-functional in themselves and they incorporate many of the features found in games consoles, media players, and digital cameras.

Table 4: Usage of Tools - Items with the highest mean scores

No. Items Sciences Social Sciences Economics

1 Mobile phone 3.90 3.95 3.95

2 Camera phone 3.57 3.49 3.54

3 Laptop 3.55 3.81 3.88

4 Music phone 3.29 3.40 3.45

5 Desktop 2.50 - 2.74

3G phone

Kean Wah Lee et al. / Procedía - Social and Behavioral Sciences 118 (2014) 242 - 250 2.50 2.39 3.46

Table 5: Usage of Tools - Items with the lowest mean scores

No. Items Sciences Social Sciences Economics

1 Portable media player 2.09 2.17 2.13

2 Digital camera 2.08 2.33 2.32

3 Handheld computers 1.87 1.71 1.67

4 Games console 1.50 1.60 1.82

5 Portable games console 1.39 1.51 1.70

4.2. Usage of technology in learning English

In the case of the usage of technological tools in learning English, this section examines findings based on item analyses on tools with the highest and lowest mean scores.

Table 6 shows the technological tools that have the highest mean scores for each discipline. Two main tools seem to be more popular than others - Email and Facebook. The mean scores for Facebook and emails for all three disciplines hover around the 3 region, implying that students from all three disciplines sometimes used emails and Facebook for their English coursework. Other technological tools that are moderately used across the three disciplines include digital online self-tests/quizzes/practices, online assessment submission, subject website and learning management system. The mean scores of all the other technological tools are around 2 and below such as blogging, Twitter, and Skype, implying that these tools are seldom used in the academic contexts.

Table 6: Students' use of tools in English coursework- Items with the highest mean scores

No. Items Sciences Social Sciences Economics

1 Email 3.09 2.85 3.16

2 Facebook 2.98 2.99 3.22

3 Digital videos in lectures 2.50 - -

4 A subject website 2.44 2.31 -

5 A learning management system 2.27 - 2.34

6 Online self-tests/ quizzes/ practices - 2.55 2.79

7 Online assessment submission - 2.46 2.31

Table 7 ': Students' use of tools in English coursework Items with the lowest mean scores

No. Items Sciences Social Sciences

1 Discussion lists/ online forums 2.06 2.15 2.07

2 Online self-tests/ quizzes/ practices 1.95 - -

3 Blogging 1.81 1.79 1.87

4 Twitter 1.72 1.56 1.80

5 Skype 1.61 1.59 1.87

6 A learning management system - 2.09 -

7 A subject website - - 2.26

Rating scale: 1=never; 2=seldom; 3=sometimes; 4=frequently

4.2.1. Opinion on which technology should be used in teaching and learning of English

Table 8 below shows the technologies that are favoured by the students in learning English. As can be seen, the mean scores for most of the tools are hovering around 3 or about which suggest that students from all disciplines agree that all these tools should be sometimes used to teach and learn English. However, there are slight differences in the technologies preferred based on disciplines. For Sciences, the favoured technologies for learning of English are digital videos in lectures and learning management system, but for Social Sciences and Economics the preferred tools are email and Facebook. A probable reason for this could be due to the nature of learning involved where teaching and learning is more didactic in Science.

Table 8: Opinion on which technology should be used in teaching and learning of English Items with the highest mean scores

No. Items Sciences Social Sciences Economics

1 Digital videos in lectures 3.25 3.00 2.85

2 A learning management system 3.22 - 2.91

3 Discussion lists/ online forums 3.13 2.97 -

4 Email 3.04 3.31 3.35

5 Facebook 2.96 3.15 3.00

6 Online self-tests/ quizzes/ practices - 3.01 3.03

Rating scale: 1=never; 2=seldom; 3=sometimes; 4=frequently

4.2.2. The extent to which students use technology for recreation

According to Table 9 the students, regardless of their disciplines, appear to have similar tendency in the usage of technology tools for recreation purposes. Facebook appears to be the most frequently used tool, followed by emails and blogs which are used sometimes. The likely reason for the frequent used of Facebook might be attributed to the students' current lifestyle of connecting and communicating with one another on a regular basis. When compared to the earlier section which examines tools for learning English (Section XX), it is evident that the students in general used Facebook more frequently for recreation purposes than for English Language learning (e-mail).

Table 9: The extent to which students use technology for recreation- Items with the highest mean scores

No. Items Sciences Social Sciences Economics

1 Facebook 3.44 3.49 3.60

2 Email 2.61 2.79 3.03

3 Blogging 2.48 2.39 2.40

4 A subject website 2.25

5 Digital videos in lectures 2.24 2.17

6 Skype 2.15 2.46

7 Online self-tests/ quizzes/ practices 2.45

Rating scale: 1=never; 2=seldom; 3=sometimes; 4=frequently

The mean scores of all other items are below 2.5 which suggest that the students only used blogs or Skype occasionally for recreation purposes. When both set of data (using technology for learning English and/or for recreation purpose) are further analysed using Kennedy et al. (2010) schematisation of technology users, i.e. whether UMS university students are power users, ordinary users, irregular users, or basic users, it can be deduced that our findings thus far (based on ownership of technological tools and usage of those tools in language learning) seem to point towards the presence of a large group of basic and irregular users, as evidenced by their lack of use of new merging technologies in their daily lives (such as blogging and creating subject websites) and a relatively low use of other technologies other than Web 2.0 publishing (Facebook). There is no denying that power users (characterised by their wide range of use of technologies in a significant manner) and ordinary users (characterised by their standard use of Web and mobile technologies, on a monthly average, and tend to not engage in web publishing and file sharing through Web 2.0 activities) are also present, but their

numbers are limited. However, caution need to be exercised in reading too much into this schématisation, as data obtained did not investigate the issue of frequency of use and accessibility to merging technologies).

4.3. Opinions on the use of technology in the learning of English

Besides investigating students' ownership and usage of technologies in English language learning, students' opinions on the use of technology in the learning of English were also elicited. Students' were asked to give their opinions on three dimensions: (1) Effects of technology on learning, (2) effects of technology on affects, and (3) Opinion of teachers' use of technology.

An item analysis was undertaken to determine the top three and bottom three items. As shown in Table 10, the top three items belong to Category 1 and each of them has a mean score above 3 suggesting that students (regardless of disciplines) believed that technology makes learning of English easier.

Table 10: Items with the highest mean scores

No. Items Sciences Social Sciences Economics

1 Using technology enables me to learn many new 3.65 3.70 3.69

things.

2 Technology has made learning English easier 3.49 3.58 3.63

today.

3 It is easier to search for suitable English materials 3.48 3.53 3.61

online than looking for suitable printed texts.

However, when contrasted with the bottom three items, as shown in Table 11 below, their opinions seem to vary across disciplines. The items listed came from all three categories, implying variability in opinions about what is least helpful for the students involved.

Table 11: Items with the lowest mean scores

No. Items Sciences Social Sciences Economics

2 I am not comfortable to use digital tools for 2.21 2.00 1.86 1.86

4 learning English. The use of technology in learning English has burdened me further. 2.02 2.03

5 It is a waste of time and energy to use 1.92 1.71 1.62 1.82

6 technology in learning English. My English teachers/lecturers are not 1.90 2.09

competent in using technology

Rating scale: 1=Strongly disagree; 2=disagree; 3=Agree; 4=Strongly Agree

The results presented in Tables 3 through to 11 show that a large majority of UMS university students surveyed in this study are 'tech-savvy' and are incorporating a range of traditional and emerging technologies in their daily lives. However, there are clearly areas where the use of and familiarity with technology based tools is far from universal or uniform among the students. Thus while there are a great majority who claimed technology helped made language learning easier, there are still a number of students who opined that they "are not comfortable to use digital tools", "felt burdened by", and that it was "a waste of time to use technology". The findings also revealed that while most students regularly use established technologies such as email and Facebook, only a small subset of students use more advanced or newer Web 2.0 tools and technologies for language learning.

4.4 Verifying reliability and validity of findings

Finally, inferential statistical analysis was undertaken to determine the reliability and validity of the findings. Before carrying out a one-way analysis of variance (ANOVA) to compare the opinions of the students, the Cronbach's Alpha reliability test was undertaken to verify the internal consistency of the items in each category. The Cronbach's Alpha reliability values for Category 1 and 2 is 0.78 and 0.75 respectively. Since the values exceed 0.7, it can be surmised that the items have internal consistency. In the case of Category 3, the Cronbach's Alpha value is only 0.52, indicating they lacked internal consistency.

The ANOVA results (see Table 12) support that of the item analysis. The mean scores for Category (1) are the highest (all approaching strongly agree) regardless of disciplines which suggest that the students believed that technology makes learning of English easier. The mean scores of Category (2) and (3) both approach "agree" which suggest that they have positive views on the affective effects of technology and their teachers' use of technology.

Table 12: ANOVA based on category

Descriptives

95% Confidence Interval for Mean

N Mean Std. Deviation Std. Error Lower Bound Upper Bound Min Max

Category 1 Sciences 218 3.2803 .41754 .02828 3.2245 3.3360 2.29 4.00

Social Sc 214 3.4404 .37643 .02573 3.3896 3.4911 2.29 4.00

Economics 225 3.5110 .38534 .02569 3.4604 3.5616 2.00 4.00

Total 657 3.4114 .40469 .01579 3.3804 3.4424 2.00 4.00

Category 2 Sciences 218 2.7645 .38148 .02584 2.7136 2.8154 1.50 4.00

Social Sc 214 2.9900 .47481 .03246 2.9261 3.0540 1.00 4.00

Economics 225 2.9270 .55180 .03679 2.8545 2.9995 1.00 4.00

Total 657 2.8936 .48400 .01888 2.8565 2.9307 1.00 4.00

Category 3 Sciences 218 2.7378 .39280 .02660 2.6853 2.7902 1.67 4.00

Social Sc 214 3.0494 .39985 .02733 2.9955 3.1033 1.67 4.00

Economics 225 2.9096 .36542 .02436 2.8616 2.9576 1.83 4.00

Total 657 2.8981 .40571 .01583 2.8670 2.9292 1.67 4.00

5. Discussion and conclusion

As in Thang et al. (2011) studies, the findings in this study reveal that the students use more technology for in their daily lives than for academic purposes. Also, based on Kennedy et al (2010) technology users categorisation, it appears that UMS respondents are basic and irregular users, as evidenced by their lack of use of new merging technologies in their daily lives (such as blogging and creating subject websites) and a relatively low use of other technologies other than Web 2.0 publishing (Facebook). There are a number of power users (characterised by their wide range of use of technologies in a significant manner) and ordinary users (characterised by their standard use of Web and mobile technologies, on a monthly average, and tend to not engage in web publishing and file sharing through Web 2.0 activities) but their numbers are limited. It was also found that while a large majority of UMS university students surveyed in this study are comfortable with the use of technology, and are incorporating a range of traditional and emerging technologies in their daily and academic lives, there are, however, clearly areas where the use of and familiarity with technology based tools is far from universal or uniform among the students. Thus while there are a great majority who claimed technology helped

make language learning easier, there are still a number of students who opined that they "are not comfortable to use digital tools", "felt burdened by", and "a waste of time to use technology".

The findings obtained in this study seem to lend support to related studies conducted in the Western contexts, which on the whole point to the use of less technology in academic settings (Corrin et al., 2010) and limited range of use (Margaryan et al., 2011) in teaching and learning in Higher institutions of learning (HEIs). Nevertheless, an interesting finding that emerged is that the majority of the students surveyed seem to like to see more technology used in the classroom. They opined that technology is crucial and helpful to language learning. Thus, despite the lack in diversity and sophistication in the use of technology exemplified in this study, and as corroborated in the studies conducted in Western context, there are sufficient optimisms in the data collated to suggest that technology can enhance the teaching and learning of English in Malaysian universities as the students are very receptive to this mode of learning. Such positive indications are evidenced in the findings found in Wong et al. (2012), Thang et al. (in press) and Thang and Bidmeshki (2010). Its limited use and its lack of exploitation in the present context should not deter the full potential of optimising the use of technology in language teaching and learning in this university in particular and Malaysia in general. If the appropriate learning environment is provided, our undergraduates can become "digital natives" in the true sense of the word.

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