Internet and Higher Education 14 (2011) 137–141

Contents lists available at ScienceDirect

Internet and Higher Education

College students’ conceptions of context-aware ubiquitous learning: Aphenomenographic analysis

Pei-Shan Tsai a,⁎, Chin-Chung Tsai a,b, Gwo-Haur Hwang c

a Graduate Institute of Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., Taipei, 106, Taiwanb Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology,#43, Sec.4, Keelung Rd., Taipei, 106, Taiwanc Department of Information Technology, Ling Tung University, 1, Lingtung Rd., Taichung, 408, Taiwan

⁎ Corresponding author.E-mail addresses: D9622305@mail.ntust.edu.tw (P.-S

cctsai@mail.ntust.edu.tw (C.-C. Tsai), ghhwang@mail.ltu

1096-7516/$ – see front matter © 2011 Elsevier Inc. Aldoi:10.1016/j.iheduc.2011.01.004

a b s t r a c t

a r t i c l e i n f o

Article history:Accepted 26 January 2011Available online 2 February 2011

Keywords:Context-aware ubiquitous learningConceptions of learningPhenomenographic methodTree of conceptions of learning

The purpose of this studywas to explore students’ conceptions of context-awareubiquitous learning (u-learning).The students participated in a u-learning exercise using PDAs equippedwith RFID readers. Thedatawere collectedfrom individual interviewswith eachof the students by a trained researcher, and the responsesof the intervieweeswere further analyzed using the phenomenographic method. The analysis revealed five categories of concep-tions of u-learning, including “u-learning as the application of technology,” “u-learning as a platform for attaininginformation,” “u-learning as a timely guide,” “u-learning as increase of knowledge” and “u-learning as activelearning.” There conceptions are viewed as a hierarchy, from less advanced to more sophisticated. An in-depthanalysis of the students’ conceptions of learning indicated that students held multiple conceptions of u-learning.This study further suggests that inquiry practices (such as allowingopen-endedexploration for the learning topic)should be addressed in u-learning activities, as these practices may foster more sophisticated conceptions ofu-learning.

. Tsai),.edu.tw (G.-H. Hwang).

l rights reserved.

© 2011 Elsevier Inc. All rights reserved.

1. Introduction

The rapid development of information technologies has potential-ly promoted the growth of diverse learning approaches and globaleducation, such as e-learning, m-learning and blended learning(Brew, 2008; Harrison, Kostic, Toton, & Zurek, 2010; Nichols & Levy,2009). Context-aware ubiquitous learning (u-learning) is one of theinnovative learning approaches. The usage of the technologiesunderlying u-computing, wireless communication, mobile devicesand context-aware technologies in education contexts has beendefined as u-learning (Hwang, Tsai, & Yang, 2008). The importantfeatures of u-learning have also been addressed in the studies ofHwang et al. (2008), Ogata and Yano (2004), and Yang, Okamoto, andTseng (2008), including mobility, location awareness, seamlessness,situation awareness, adaptability, immediacy, and accessibility. Forexample, in u-learning environments, students can integrate theinformation and learning materials from the real world and the digitalworld through the learning system and context-aware technology atthe right time and in the right place. It is expected that u-learningenvironments can support students to learn in the real world (Joiner,Nethercott, Hull, & Reid, 2006).

Previous studies of u-learning have focused on the development ofu-learning systems (El-Bishouty, Ogata, & Yano, 2007; Peng et al.,2009; Tan, Liu, & Chang, 2007). El-Bishouty et al. (2007) found thatthe effectiveness of a u-learning system, PERsonalized KnowledgeAwareness Map (PERKAM), was demonstrated by college studentsthrough evaluating the system usage, efficacy and their satisfaction.However, students may not benefit from merely integrating tech-nology into instruction. Gopal et al. (2010) found that selectingtechnology for use in various learning environments should becarefully assessed to ensure effective teaching. This finding indicatesthat the benefits of integrating technology into instruction partiallydepend on how students learn during the processes, such as students’behavior in the learning activities (Hershkovitz & Nachmias, in press),their usage of e-portfolios (Wang, 2010) and their attitudes (Cohen &Nachmias, in press). However, just a few studies have focused on thestudents’ learning processes and performance in u-learning environ-ments (Chu, Hwang, & Tsai, 2010; Peng, Chou, & Chang, 2008). Thus,exploring students’ learning processes and performance is animportant issue for those educational researchers who encouragestudents to persistently learn in u-learning environments.

Moreover, students’ conceptions of learning, as well as students’interpretations of learning itself, have been investigated by educa-tional research (Tsai, 2009). Benson and Lor (1999) indicated thatstudents’ conceptions of learning relate to what they believe thepurpose and process of learning are. Pioneering research work intostudents’ conceptions of learning was conducted by Sälijö (1979), and

138 P.-S. Tsai et al. / Internet and Higher Education 14 (2011) 137–141

the conceptions were identified through a so-called “phenomeno-graphic” method. Richardson (1999) indicated that the “phenomeno-graphic” method is a qualitative methodology, and is often used toidentify students’ qualitatively different, hierarchically related con-ceptions of learning. In Sälijö's (1979) study, five hierarchicallydifferent conceptions of learning were identified using a phenomeno-graphic method, including “increase of knowledge,” “memorizing,”“acquisitions of facts or procedures that can be retained and/orutilized in practice,” “abstraction of meaning” and “an interpretativeprocess aimed at the understanding of reality,” with these categoriesrepresenting the conceptions from lower to higher levels. FollowingSälijö's study (1979), using the phenomenographic method, severalstudies have explored different groups of students’ conceptions oflearning in various educational contexts or majoring in differentsubjects, and found that they showed different conceptions indifferent educational contexts, such as science subjects (Tsai, 2004;Tsai & Kuo, 2008), engineering subjects (Marshall, Summer, &Woolnough, 1999), and management (Lin & Tsai, 2008).

Recently, some studies were undertaken to explore students’ andteachers’ conceptions of learning via the usage of technology, such asonline discussion (Ellis, Goodyear, Prosser, & Ohara, 2006), online peerassessment (Yang & Tsai, 2010), web-based learning (Tsai, 2009), andblended learning (Ellis, Steed, & Applebee, 2006). For example, Tsai(2009) compared college students’ conceptions of learning in generaland those particularly relating to web-based learning, and revealedsimilar categories of aforementioned conceptions, such as “memoriz-ing,” “increase,” “applying,” “understanding,” and “seeing inanewway.”An interesting finding of his study is that the conceptions of web-basedlearning are more sophisticated than those of learning in general. Thissuggests the potential role of web-based learning in education, whichmay promote students’ conceptions of learning. Ellis et al. (2006)explored the relationships between students’ conceptions of learningthrough online and face-to-face discussions, their approaches tolearning through online and face-to-face discussions, and their learningoutcomes.Nevertheless, in their study, students’ conceptions of learningthrough discussionswere not differentiated into online and face-to-facecontexts.

The issue of conceptions of learning in u-learning environments has,however, received limited attention among educational researchers(Tsai, Tsai, Hwang, Hwang, & Yang, 2009). Therefore, this study used thephenomenographic method to explore students’ qualitatively differentconceptions of u-learning. Through the analysis of students’ qualita-tively different conceptions of u-learning, it was expected that thefindings can assist researchers to develop more adaptive u-learningsystems and environments for enhancing students’ learning perfor-mance, and encourage students to use better approaches to learning.The research questions of this study are presented as below:

• What are the students’ conceptions of u-learning gained from thephenomenographic method?

• What are the distributions of students’ conceptions of u-learning?

2. Method

2.1. Participants

The participants of this study included 22 college students (10malesand 12 females; 8 juniors and 14 seniors) in central Taiwan. All of thestudentsweremajoring in informationmanagement. The students’ agesranged from 20 to 22, with an average of 21.64. The studentsparticipated in a u-learning exercise using PDAs equipped with RFIDreaders. In the numismatic museum, according to the students’ visittime and their prior knowledge of the history of coins, the u-learningsystem provided adaptive in-time guidance and contents for eachstudent to construct their knowledge about coins. The data for this studywere gathered in 2009. In addition, the students had also previously

participated in projects of designing u-learning systems for elementaryschool students in their library and campus (Hwang, Ye, Lin, Peng, & Lyu,2008; Hwang et al., 2009).

2.2. Data collection

The data were gathered by interviewing the sample students toexplore their interpretations of u-learning. Each student was inter-viewed individually by a trained researcher. The guiding interviewquestions were mainly modified from the studies conducted byMarshall et al. (1999), Tsai (2004) and Yang and Tsai (2010), as follows:

(1) Based on your experiences, what do you understand by“u-learning”?

(2) When your friends ask you about the u-learning activities, whatwill you tell them?

(3) What do you do and think regarding u-learning activities?

All of the individual interviews were undertaken in Chinese andaudio-recorded. The verbatim transcripts of these students’ interviewswere the major data for revealing their conceptions of u-learning.

2.3. Data analysis

The transcripts of the student interviews were analyzed by tworesearchers following the phenomenographic method based on thestudies of Lin and Tsai (2008), Marshall et al. (1999), Tsai (2004), andYang and Tsai (2010), which can identify qualitative relationships andclassify the responses in ordered categories. After verbatim transcriptsof each student's interview were made, the researchers first read all ofthem, selected the most significant sentences, and marked the mainideas expressed by the students about learning. Following this, theresearchers compared the selected sentences and the main ideas tosummarize the similarities and differences between the students’perspectives of learning. Hence, the researchers explored the consis-tencies and differences across the interviewed students’ responses toconstruct qualitatively different categories about the conceptions oflearning held by the interviewed students.

After the initial classifications, the students’ interview responseswere classifiedagainby two researchers, independently. Thepercentageof agreement was applied to calculate the reliability of these tworesearchers’ coding, showing an initial 82% agreement between them.Those responses without agreement were resolved by discussionbetween the researchers.

3. Findings

3.1. The categories of conceptions of u-learning

By comparing the content-specific similarities and differences acrossthe responses of different students, this study found some majorcategories of u-learning as presented by the students. A framework offive hierarchical categories is presented, including u-learning as theapplication of technology, a platform for attaining information, a timelyguide, increase of knowledge, and active learning. A detailed descriptionof the students’ interview responses for the five categories is presentedbelow, from less advanced to more sophisticated:

(1) U-learning as the application of technology (A). In the firstcategory, the students conceptualize u-learning as the applica-tion of technology in the learning process, such as the applying ofthe voice function and the focus on the role of the PDAs orcontext-aware technology. For these students, the purpose ofu-learning was conceptualized as applying novel technology inan effective way. For example, the students stated that:

S02: In my view, u-learning is a practical tool, such asapplying PDAs and sensors to the process of learning.

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S09: In u-learning environments, PDAs have the voice func-tion that helps me learn something without reading.

S10: In u-learning environments, the voice function of PDAs isa convenient tool, rather than looking at printed words.

S15: By u-learning, learners can take PDAs to react to tags,and the PDAs will show the information and images.

S17: In u-learning environments, learners can learn out-doors because they hold mobile devices, such as PDAs.

S18: By u-learning, learners can take sensors to react totags, and the contents will be shown on the PDAs.

S21: U-learning helps me to learn how to operate a PDA, andprovides a convenient way to learn.

This category probably regards u-learning as an application ofnovel technology. In this way, the studentsmay focus on the roleof technology such as the interaction of PDAs and/or context-aware technology in their u-learning activity.

(2) U-learning as a platform for attaining information (P). In thiscategory, the acquisition of information was considered as themain feature of u-learning. The attainment and collection ofinformation constituted the major component of u-learning. Inthis category, the students viewed u-learning as a convenientway to attain information to achieve their goals. For example, thestudents replied that:

S03: U-learning involves a lot of relevant information. Wecan get the information more immediately throughPDAs, not just by reading printed words.

S06: Based on the information of location, environment andlearner, u-learninghelpsme to get the learningmaterialsI need.

S11: In u-learning environments, I can getmore information.For example, I can attain relevant information about acoin, not just by looking at the coins and printed wordsin the coin museum.

S12: By u-learning, I can browse the information everywhere.S14: In u-learning environments, I can get learningmaterials

or information everywhere.S16: U-learning helps me to get the information to solve my

questions.S17: In u-learning environments, I can get the information I

want to know immediately, not just in a computer class.S20: By u-learning, I can obtain something immediately

through PDAs instead of using computers at home.In this category, students highly emphasized the attainment andcollection of information to achieve their goalswhen learning in au-learningactivity. Their viewsalso indicated that they viewedu-learning as a platform to obtain more relevant information.

(3) U-learning as a timely guide (T). In the third category, the studentsview u-learning as a timely guide for having a direction in thelearning process. For these students, u-learning was to apply themobile devices to provide directions for learning. For example,the students responded that:

S02: U-learning is practical in that I can check the PDAinterface and follow the illustrations to use the PDA…Following the steps of the PDA, I can learn with itsguidance.

S04: In u-learning environments, I can know clearly what Ishould learn. For example, in the numismaticmuseum, Ican know thedetailed backgroundor learningmaterialsof a coin which I should learn about.

S07: U-learning provides the information I need, and I canget the information through PDAs at the right timeand in the right way.

S08: I do not need to visit anywhere; the PDA is so con-venient to take me to look around.

S14: In u-learning environments, through PDAs, whichrecognize learners’ locations and situations automat-

ically, learners can know what they should payattention to or what they should do.

This category addressed the timely guidance of u-learningactivities. Students’ perspectives implied that u-learninginvolved a timely guide to provide them with the adaptivedirections of learning.

(4) U-learning as increase of knowledge (I). In the fourth category,the students conceptualized increasing knowledge as themajorfeature of u-learning. Moreover, the students in this categorystressed an extension of prior knowledge and assimilated ideas.For example, the students stated that:

S05: U-learning helpsme to keep learning, and promotesmyabilities.

S11: In u-learning environments, learners can acquire moreknowledge through mobile devices rather thanencyclopedias.

S13: U-learning helps me to acquire more knowledge in anadaptive way, not just reading printed words.

S14: By u-learning, I can learn something which I want tounderstand.

In this category, the students emphasized an increase ofknowledge as a result of the u-learning activities. Their viewsimplied that u-learning extended their prior knowledge andhelped them to assimilate many ideas.

(5) U-learning as active learning (L). In thefinal category, the studentsviewed u-learning as away of allowing them to engage in inquirypractices, such as allowing open-ended exploration for thelearning topic. Having chances for engaging in inquiry practiceswas the major feature of u-learning. For example, the studentsstated that:

S01: In u-learning environments, I can learn something bymyself.

S05: By u-learning, I can keep learning, whether we are indifferent times, seasons, locations or not.

S07: In u-learning environments, I can learn something Iwant to know.

S20: U-learning helpsme to learn something Iwant to know.S22: In u-learning environments, I can learn everything

through mobile devices.These students believe that u-learning provides ubiquitouslearning methods to engage them in inquiry practices, andpromotes their abilities and the knowledge acquisition theywant.

3.2. The distribution of students’ conceptions of u-learning

Marton, Dall’ Alba, and Beaty (1993), Lin and Tsai (2008), and Tsaiand Kuo (2008) indicated that many students show mixed concep-tions of learning across different categories. To provide a more directand clear analysis of each student's conceptions of u-learning, thisstudy applied the method, developed by Lin and Tsai (2008), ofrepresenting the variations in students’ conceptions. For example, if astudent presented ideas in the categories of “a timely guide” and “aplatform for attaining information,” he/she would be marked intothese two categories. According to their conceptions of u-learning,each student was allowed to be categorized in one or more categories.

This study focuses on the variations in the interviewed students’conceptions of u-learning. Therefore, according to their conceptions ofu-learning, each student was permitted to be included in one or morecategories. Table 1 shows the distribution of students’ conceptions ofu-learning among the five categories.

As shown in Table 1, “the application of technology” category wasviewed as the major feature of u-learning for these students. All of theinterviewed students expressed this conception.Moreover, the categoryof “a platform for attaining information”was expressed by 18 students.The “active learning” category was expressed by 10 students, whereas

Fig. 1. Tree of conceptions of u-learning. Note: A, The applicationof technology; P, Aplatformfor attaining information; T, A timely guide; I, Increase of knowledge; L, Active learning.

140 P.-S. Tsai et al. / Internet and Higher Education 14 (2011) 137–141

the categories of “increase of knowledge” and “a timely guide” wereexpressed by only six and four students, respectively.

3.3. The tree of conceptions of u-learning

In order to clearly represent the interviewed students’ multipleconceptions of u-learning, this study applied the “tree of conceptionsof learning” method, proposed by Lin and Tsai (2008), to describe therelations between the conceptions of u-learning. After knowing thedistribution of students’ conceptions of u-learning, the researchersfirst organized the frequency of the students’ similar conceptions, andutilized themaximum frequency of conceptions as the root of the tree.As shown in Fig. 1, “the application of technology” category is the rootin this study, consisting of 22 students. Next, the researchers appliedthe students’ mixed views across two categories as the first-tierbranch. In this study, the categories of “a platform for attaininginformation,” “a timely guide” and “active learning” are the first-tierbranch overlap “the application of technology” category. Then, theresearchers used the students’ mixed understandings across threecategories as the second-tier branch and the students’ mixed viewsacross four categories as the third-tier branch to illustrate thecommonalities of the combinations across different conceptions ofu-learning. For example, 18 students among the 22 had “theapplication of technology” and “a platform of attaining information”categories as mixed views; three students among the aforementioned18 students held the conception “a timely guide.”Moreover, it is clearthat numerous students (n=21, 95%) held mixed categories ofconceptions of u-learning, especially A–P or A–P–L mixed concep-tions. Hence, five students expressed both “the application oftechnology” and “a platform for attaining information” categories,while another five students possessed “the application of technology”,“a platform for attaining information” and “active learning” categoriessimultaneously.

4. Discussion and conclusions

This study investigated the u-learning experience of studentsusing the phenomenographic method to describe their conceptions(e.g. from “the application of technology” to “active learning”). Thequalitative analysis of students’ conceptions of u-learning provided

Table 1The distribution of students’ conceptions of u-learning.

Student ID The applicationof technology

A platform forattaininginformation

A timelyguide

Increase ofknowledge

Activelearning

S01 ✓ ✓ ✓ ✓

S02 ✓ ✓ ✓

S03 ✓ ✓

S04 ✓ ✓ ✓

S05 ✓ ✓ ✓ ✓

S06 ✓ ✓ ✓

S07 ✓ ✓ ✓ ✓

S08 ✓ ✓

S09 ✓ ✓

S10 ✓ ✓

S11 ✓ ✓ ✓

S12 ✓ ✓

S13 ✓ ✓ ✓

S14 ✓ ✓ ✓ ✓

S15 ✓ ✓ ✓

S16 ✓ ✓

S17 ✓ ✓ ✓

S18 ✓ ✓ ✓

S19 ✓ ✓

S20 ✓ ✓ ✓

S21 ✓

S22 ✓ ✓

Total 22 18 4 6 10

their perspectives for researchers. This study further investigated thedistribution of these students’ conceptions of u-learning, and foundthat all of these students emphasized the major feature of u-learningas “the application of technology”, while many of them (n=21, 95%)had multiple conceptions of u-learning.

As illustrated in Fig. 1, through the tree of conceptions of learningmethod, this study also found that from the multi-tier branches, itwas also revealed that numerous students (n=18, 82%) emphasizethe features of u-learning as “the application of technology” and “aplatform for attaining information.” Among 18 students, five studentshad mixed perspectives among A and P; five students held mixedconceptions among A, P and L; two students had mixed views acrossA, P and I; two students held mixed perspectives among A, P and T;three students had mixed conceptions among A, P, I and L; and onestudent held mixed views across A, P, T and I. Moreover, it is expectedthat in-depth analysis of the students’ conceptions of learning will behelpful for understanding the relations among these conceptions, andfor developing better teaching designs to help students possesshigher-hierarchical level conceptions, thus supporting them to gainbetter learning performance (Lin & Tsai, 2008). For example, take thebranches relevant to the “active learning” category as an example,which were the highest hierarchical categories of conceptions of u-learning; this study found that two students had mixed perspectivesamong A and L; five students held mixed perspectives among A, P andL; and three students hadmixed views across A, P, I and L. This findingdo not exist in other methods which have been proposed to analyzeeach student's conceptions of learning based on the idea's occurrencefrequency and hierarchy level, such as using the most dominantcategory method (Koballa, Gräber, Coleeman, & Kemp, 2000; Tsai,2002, 2004; Tsai & Kuo, 2008), or categorizing “main” level ofconceptions of learning (Yang & Tsai, 2010). For example, by the mostdominant category method, if a student presents many ideas in thecategory of “a platform for attaining information,” but only afew views about “the application of technology” and “active learning,”he/she would be grouped into the “a platform for attaininginformation” category, and his/her mixed conceptions among “theapplication of technology” and “active learning” would be ignored.The method utilized in this study represents well students’ conceptionsof u-learning in refined detail, showing each participant variation andpotential in conceptualizing learning.

In addition, this study revealed findings similar to those of Yangand Tsai (2010). The categories of conceptions of technology-based

141P.-S. Tsai et al. / Internet and Higher Education 14 (2011) 137–141

learning at lower levels show a tendency of simply utilizing thetechnology. For example, in Yang and Tsai's (2010) study, the lower-level categories of conceptions of learning via online peer assessmentinclude “a drill for some related computer skills” and “a procedure forsubmitting assignments.” These categories are similar to the lower-levelones revealed by this study such as “u-learning as the application oftechnology” and “u-learning as a platform for attaining information.”

Based upon the finding of this study, researchers are encouraged todevelopmore adaptive u-learning systems or environments for helpingstudents possess higher-hierarchical level conceptions. Several studieshave indicated that engaging in inquiry practices gives students anopportunity to experience the activities, and further supports thedevelopment of inquiry abilities (NRC, 2000; Smith, Maclin, Houghton,&Hennessey, 2000;Wu&Hsieh, 2006); therefore, how to help studentshold higher level conceptions, and encourage them to engage in inquirypractices should be addressed in u-learning activities because the“active learning” category was defined as a way of allowing them toengage in inquiry practices.

This study has undertaken to establish an initial understanding ofstudents’ conceptions in a u-learning environment. The analysis ofstudents’ qualitatively different conceptions of u-learning provided aframework for researchers to better understand students’ perspectives.Several studies have revealed that students’ conceptions of learning arerelated to their approaches to learning and learning performance (Dartet al., 2000; Lee, Johanson, & Tsai, 2008; Tsai, 2004; Yang & Tsai, 2010).Future studies should include exploring the relationship amongstudents’ conceptions of u-learning, students’ approaches to u-learning,and learning performance.

Acknowledgement

The funding of this study is supported by the National ScienceCouncil, Taiwan, under grant contract numbers NSC 99-2511-S-011-005-MY3, NSC 99-2631-S-011-001, and NSC 96-2520-S-275-001-MY3.

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