1

行政院國家科學委員會補助專題研究計畫期中進度報告

發展數位語言學習的新研究議題與新研究問題之教學設計理論

計畫類別：個別型計畫計畫編號：NSC 98－2511－S－006－003－MY2執行期間：98 年 8 月 1日 至 99 年 7月 31 日

計畫主持人：劉繼仁共同主持人：劉子鍵計畫參與人員：張志藩 簡欣平

成果報告類型(依經費核定清單規定繳交)：X精簡報告 □完整報告

本成果報告包括以下應繳交之附件：X 赴國外出差或研習心得報告一份□赴大陸地區出差或研習心得報告一份X 出席國際學術會議心得報告及發表之論文各一份□國際合作研究計畫國外研究報告書一份

處理方式：除產學合作研究計畫、提升產業技術及人才培育研究計畫、列管計畫及下列情形者外，得立即公開查詢涉及專利或其他智慧財產權， 二年後可公開查詢

執行單位：國立成功大學外國語文學系（所）

中 華 民 國 99 年 6 月 16 日

2

The backgroundWe are living in a networked society in which various kinds of information and

communication technologies (ICT) are used in many situations, fields, and contexts to facilitatelanguage learning, including the first, second and other languages. Digital language learning(DLL), or computer assisted language learning (CALL), or technology enhanced languagelearning (TELL), is a trans-disciplinary field that has been influencing human languagedevelopment in various academic subjects and areas for more than half a century. Since the 1990s,ICT-embedded language learning has been the most widely used form of DLL, TELL, or CALL.

A number of studies and theories (see Chang, 2007; Chang, et al, 2007; Huang & Liou, 2007;Lan et al, 2007; Levine et al, 2007; Liaw, 2006, Liu & Chen, 2007; Sun, 2003; Sun, 2007; Wibleet al, 2001; Wible et al, 2003;Yang, 2001; Yang, 2003; Yang & Chen, 2007) have investigated theuse of various technologies in DLL in different situations and environments. However, so farthere has been neither formative research nor a corpus-based study published concerning thedevelopment of novel DLL research topics and research questions. Since Surry (2005) calls formore professionals, researchers and practitioners to understand the significance of the study ofchange—which is critical to the future of learning technology (LT) or educational technology(ET)—we may need to think about viable ways to make technology-assisted learning moresuccessful (Liu, 2008). Likewise, DLL, which shares some components, applications, models,and theories with ET (Chapelle, 2001), also has a similar need for more studies to develop newresearch dimensions and strengthen the vitality of new research tools, methodologies, and devices(Chapelle, 2007; Levy, 2007).

The purposeThe PI has conducted a study concerning the development of new research topics in learning

technology (LT; Liu, 2008) and published it in a LT journal. Hence, this research intends to be afollow-up study to execute what the research results suggested in that study. Values are what wetreasure or care most when engaging in learning, teaching, or research related activities (Richey,1998). This study aims to conduct “formative research”(Reigeluth & Frick, 1999) to develop,validate and refine the model in a designed case and the guidelines in the instructional designtheory for generating “value innovation”(Kim & Mauborgne, 2004a) in DLL research, with theaim of helping researchers and practitioners create new or previously unidentified research topicsand questions.

The purpose of this research project is for the principal investigator (PI) and the co-PI todevelop two IDTs—one for helping interested practitioners and researchers develop new researchtopics in DLL and the other for creating novel research questions with a two-year researchagenda, in which value innovation (Kim & Mauborgne, 2004a), the blue ocean strategy (Kim &Mauborgne, 2004b), and Liu’s (2008) five guidelines for developing new research topics inlearning technology and CALL, will be used as the innovation base. In the first year (2009-2010)research period, the researchers focused on the device and instructional design model for helpingdevelop new research topics or sub-topics in CALL. In the designed case for developing themodel and then the IDT, the researchers developed a corpus-based system, which is a collection

3

of journal paper titles of nine journals of DLL and LT in the ISI Web of Science. This corpussystem is developed and used to help interested researchers and practitioners to (a) understandpopular sub-topics in CALL as well as (b) use existing journal paper titles for developing newsub-topics in CALL. It is expected that the results of the study will provide useable knowledge tointerested researchers and practitioners in order to further investigate, identify, and developemerging DLL and the applications.

The significance of the study & the need for value innovation in DLL researchAn initial study concerning the development of new research topics in learning technology

(LT) and a refined framework for helping create novel research topics in DLL have beencompleted, and the research results have been published. Hence, this research will be animportant follow-up study to continue the long-term research on creation of new research topicsand research questions in DLL. Since new information and communication technologies (ICT)are continuously emerging, research-proven methods or theory-grounded guidelines that cansimulate innovative LT or LT related (such as DLL) research topics and questions are alwaysrequired (Latchem, 2006; Richey, 1998). DLL in this study is defined broadly as ICT that can beused to facilitate language learning in various fields and contexts. Values—which are significantin the process or product of learning (Reid & Petocz, 2004)—play a key role in DLL. Likewise,the value of DLL should be that, when applied or guided properly, technologies (including softand hard technologies) can facilitate efficient and effective language development, with morepersonal enrichment or enjoyment.

LT evolution has directly and indirectly influenced the development of teaching and researchof various fields and disciplines (Boylan, 2004), for example, DLL, and innovation is consideredas playing a major role in improving the current conditions of ICT-embedded learning andteaching (Chou, 2005; Hannan, 2005). However, when we discuss what“value innovation”(Kim& Mauborgne, 2004a) is and how it will cause the impact on current and future DLL research,some questions still need to be answered. For example, how can we create new values to developnovel research topics and research questions to promote DLL and its research and practice? Arethere any other values that we have not yet identified in DLL? If so, what are they, and how canwe take advantage of these new and meaningful ideas? DLL practitioners and researchers need tothink about these questions and try to answer them when developing and promoting DLL, andthis research aims to provoke thoughts for them in these tasks.

The literature reviewSince this research project involves a variety of technologies and technological applications

in human language learning, in order to develop foundations of relevant knowledge for theresearcher to conduct it, in this section, the brief literature review is divided into several parts,including (a) learning technology, (b) Internet-based Technologies (IBT) integrated into languagelearning, (c) novel research topics for advancing knowledge and developing applications in DLLstudies, (d) the need of a method for developing new research questions in DLL, (e) the blueocean strategy for value innovation in DLL research, and (f) the summary.

4

Learning technologyLearning (LT) is a trans-disciplinary field that has been directly and indirectly influencing

human development in various academic subjects and industries. With the rapid evolution oftechnologies, LT has been a promising and influential academic field full of new theories andpractices for human beings to further take advantage of the identified as well as potential meritsand conveniences. In general situations, learning technology (LT), to most researchers,practitioners, professors, and students, is associated with the two similar terms—instructionaltechnology (IT) or educational technology (ET). For some of them, LT can be an alternative to ITand ET. In this proposed research, LT in a broad sense is considered an alternative term to ET orIT. According to Davis and Eales (2007), successful factors of LT projects found in the literaturecan be categorized into four groups: (a) management and organizational factors, (b) collaborationand dissemination factors, (c) e-learning design factors, and (d) people factors. This summaryechoes what Vinge (2006) claims that the computer (hardware), the communication system(software), and the user constitute the ultimate “creativity machine”, which provides variouscontexts and opportunities to foster innovation. However, it should be noted that the possiblenegative effects of using LT tools is a good research question that remains to be investigated(McPherson, 2005).

In learning technology (LT; Rushby & Seabrook, 2008), technologies have two major forms(see Figure 1): hard and soft (Burgess & Gules, 1998; Heinich et al, 1999; Jonassen, 2004). Hardtechnologies, also known as information and communication technologies (ICT) in generalcontexts, may refer to hardware (eg, computer) and software (eg, email) (Jonassen, 2004;McDonough & Kahn, 1996) that people use to learn new knowledge and skills. Meanwhile, softtechnologies refer to well-designed instructional processes, techniques, principles or models thatare developed with behavioral and social methods as well as theories to engage learningindividually or in groups (Heinich et al, 1999), with or without the use of hard technologies

Figure 1: The interrelationship among various forms of technologies

Technologies

for teaching & learning

for communication & interaction

for individual & group uses

Hard technologies Soft technologies

Hardware

(eg, PCs and PDAs)

Instructional guidelines or

models to engaging learning

Software

(eg, Emails and Moodle)

Supports (eg, funding, people, context)

5

(Shoffner et al, 2000), to bring about the desired learning outcomes. This work is a reaction toRushby (2007) that in order to make the maximum use of hard technologies, practitioners andresearchers need to develop and promote the best practice of soft technologies in parallel,especially in disciplines such as language learning (Hoven, 2006; Lally, 2000).

The various forms of hard and soft technologies have been evolving to meet various needsof stakeholders in corporate, educational and other settings, as well as in academic disciplines.Apparently, soft technologies dominate the efficacy of the majority of hard technologies(McDonough & Kahn, 1996), and the former are more significant than the latter in practice andimpact (Burgess & Gules, 1998; McDonough & Kahn, 1996). Even if a new devise of hardtechnologies is invented to run with its full functionality automatically, its values depend on howit can be applied to facilitate human learning effectively and efficiently with personal enrichment(Liu, 2008).

Internet-based Technologies (IBT) integrated into language learningLiu and Chen (2007) develop a taxonomy of Internet-based technologies (IBT) integrated

into language curricula, which categories IBT (or ICT) uses in language learning into CALL,CMS, and LMS. Various kinds of Internet-based technologies have been developed and appliedto engage learners in interaction-enhanced, one-way or two-way written and oral communicationsto practice the target language. Based on the locus of control and the instructional mode ofInternet-based technologies (see Table 1), the researcher divides the hybrid course into threetypes, including (1) the integration of computer-mediated communication (CMC) tools into theclassroom, (2) the integration of the learning management system (LMS) into the classroom, and(3) the integration of CALL applications into the classroom. Each type of the hybrid course isdescribed as follows.

Table 1: The three types of integrating Internet-based technologies into the classroom (Liu & Chen, 2007)

Category Integrating CMC tools

(chat, conferencing,

forum, email, MSN

Messenger, Skype, etc.)

Integrating the LMS

(Open-source learning

platforms,Blackboard.com,

WebCT.com, etc)

Integrating CALL

applications (Live ABC,

language learning

websites, etc.)

Locus of control Mostly peer-supported;

tools only

Teacher-led, peer-supported, and

self-controlled;

Tool-enhanced content

Mostly self-controlled;

tool-enhanced content

Instructional mode drill-and-practice;

one-to-one,

one-to-group, and

group-to-group

collaboration

Lecturing, one-to-one,

one-to-group, and

group-to-group collaboration

Tutorials, testing,

simulations, games, etc.

6

According to Beatty (2003), the definition of CALL“is any process in which a learner uses acomputer, and as a result, improve his or her language”(p. 7). In this proposed study, thisdefinition is broadened that, in terms of digital language learning (DLL), technologies can beused to facilitate language learning through various digital technologies, and as a result, thelanguage learner will develop his or her target language in various language skills and areas.Since the 1960s, DLL, or computer-assisted language learning (CALL), has been developing as aprofessional, trans-disciplinary field for language learners all over the world. In addition, thereare a great number of researchers, professors, scholars, students, and practitioners engaging inDLL research, development, and applications. However, based on the current literature, there is alack of any models, methods, or guidelines for helping DLL researchers and practitioners developnew research topics and questions.

Novel research topics for advancing knowledge and developing applications in DLLstudies

Humans use language for communication in various forms to express one’s opinions,exchange life experiences and develop diverse civilizations. Becta (2004) and some scholars suchas Andrews et al (2007), Bax (2003) and Chambers & Bax (2006) call for more long-termresearch on integrating ICT into language learning and teaching to identify both benefits andproblems in such practices, and to make computer assisted language learning (CALL) realizableand normal in our daily life as the ultimate goal (Bax, 2003; Chambers & Bax, 2006). When weadvance our current knowledge in CALL (or DLL) as well as pursuit the so-called “thenormalization of CALL”(Bax, 2003), novel research topics are desired with technologicalevolution and paradigm shifts in language learning. The five major DLL academicjournals—Language Learning & Technology, CALICO Journal, Computer Assisted LanguageLearning, ReCALL, and System—provide some research subjects, topics and directions (seeAppendix A). However, new research topics and novel research questions will bring aboutinnovative developments and possibilities in DLL and beyond.

In addition, interested researchers and practitioners may find meaningful research topics andsubjects in the three international SSCI journals of educational technology or computer basedlearning, which are also indexed in Linguistics & Language Behavior Abstracts, include BritishJournal of Educational Technology, Computers & Education, and Journal of Computer AssistedLearning (see Appendix A). Some scholars attempt to find current research trends in an effort toprovide new possibilities for future studies. For example, Shih et al (2008) identify the recentresearch trends of e-learning in papers published in the five major LT journals indexed in SSCIfrom 2001 to 2005, finding that the most popular research topics of cognitive studies wereinstructional approach, learning environment, and meta-cognition. Some scholars—such asLagemann (2002) and Richey (1998)—call for “useable knowledge”in the research anddevelopment of LT and related fields (e.g., DLL). Hence, new research topics and eveninnovative research methodologies are needed for researchers and practitioners to furtherinvestigate, identify, and develop useable knowledge in DLL with emerging LT.

7

The need of a method for developing new research questions in DLLDigital language learning (DLL), or computer assisted language learning (CALL), also

known as technology-enhanced language learning (TELL) in general contexts, is one of thepromising academic areas within applied linguistics (Chapelle, 2001; Gruba, 2004; Levy andStockwell, 2006). Many applied linguists have realized cutting-edge technologies, if guided orapplied properly, can help all levels of learners develop their target language to a certain degree atanytime, anywhere. Language learning and development in both CALL and non-CALL contextsfoster “dynamic, nonlinear, and open nature of complex systems”(Larsen-Freeman & Cameron,2008, p. 200) for which many CALL researchers (e.g. see Bax, 2003; Levy & Stockwell, 2006)have been attempting to propose various ways and dimensions to identify, explore or investigatethe complicated attributes, processes, outcomes, impact, effectiveness, efficiency and otheraspects of DLL. In order to investigate and solve a problem or to advance knowledge in DLLpractice and research, the first step for us is to raise and define the research question(s) clearly.However, so far there has been no method specifically designed for interested researchers andpractitioners to develop applicable DLL research questions in an organized way witheffectiveness and efficiency.

The blue ocean strategy for value innovation in DLL researchNew values will bring about new thinking, practices and possibilities in DLL (Liu, 2008).

Conacher & Kelly-Holmes (2007) suggest that DLL researchers should explore the fourcharacteristics (or values)—diversity, flexibility, accessibility, and equality—to “establish aframework against which innovative practices can be measured”(p. 20.). The PI used valueinnovation (Kim & Mauborgne, 2004a) and blue ocean strategy (BOS; Kim & Mauborgne, 2004b)in the previous study to develop a framework for creating new research topics in LT and DLL.The BOS was designed to help companies move from competitive, crowded contexts (red oceans)to innovative, developmental territory (blue oceans) for future business and opportunities (Kim &Mauborgne, 2004b). Based on Kim & Mauborgne’thinking, in red oceans, companies competefor lower costs and more sales, which will make the market bloody (red); however, in blue oceans,competition is irrelevant but innovation is the key player. Kim & Mauborgne argue thatcompanies continuously develop and benefit from operating in such blue oceans, which theydefine as industries or market spaces that do not exist now but will be created soon and in whichnew demands and profitable opportunities will be generated. The BOS has been widely discussedand applied in industrial and academic fields, and DLL practitioners also need a similar strategyto innovatively apply DLL in current domains as well as create new domains for future researchand development.

The summaryBased on the current literature, there is a lack of any devices (e.g., a system), models,

methods, or guidelines for helping DLL researchers and practitioners develop new research topicsand questions. The PI of this proposed research conducted a similar study in mid 2007, which canbe considered a pilot study for this research project. It is assumed that (a) an IDT or modelspecifically designed for developing new research topics in DLL, and (b) an IDT or model

8

specifically designed for developing novel research questions in DLL would help interestedresearchers and practitioners conduct CALL or DLL related research effectively and efficiently.In addition, the research outcomes of this study will fill the gap that there is no formative researchbased model, guideline, or method for creating new research topics and questions in DLL.

The designed case in this studyIn order to develop an instructional design model or theory (Reigeluth & Frick, 1999) for

helping interested researchers and practitioners create new or previously unidentified researchtopics or sub-topics in DLL, TELL, or CALL, the researchers develop a corpus-based system fordeveloping new research topics in CALL. The researchers used—value innovation (Kim &Mauborgne, 2004a), the blue ocean strategy (Kim & Mauborgne, 2004b), and Liu’s (2008) fiveguidelines for developing new research topics in learning technology and CALL as the theoreticalbackground with the web searching and corpus linguistics techniques in AI—to develop thecorpus-based system with the journal paper titles in the nine selected journals of CALL and LT.Figure 2 shows the nine selected journals collected in ISI web of Science and the corpus-basedsystem (http://140.116.245.248/~bluesea/index.php). The available username and password of thecorpus-based system are both“bluesea”.

Figure 2: The corpus-based system for developing new research topics in CALL

The definitions of the three areas (red, blue and white oceans) in CALL research1. Red ocean research topics are those have already received considerable attention in the

literature.2. Blue ocean research topics are those that have received some attention (new or innovative

9

topics) in the literature.3. White ocean research topics are those that have received little or no attention in the

literature.

B. Calculation methodThe boundary between red and blue ocean research topics

In our system, we adopt normal distribution, which is the most commonly used model inprobability to define the boundary between red and blue ocean topics. We define the top2.5% area above two standard deviations (σ) as representing the red ocean topics, as shownin Figure 3, the area above 2 standard deviations(σ).

After collecting the number of citations for all the 9 journal papers in our database,papers that are cited more than 19 times are in the top 2.5 % of the distribution. Thus, if apaper is cited more than 20 times then it is defined as representing a red ocean researchtopic.

Figure 3: The Normal Distribution

The boundary of the blue and white ocean research topics in the two sections (2010and before)Because our system was built in 2010, and thus complete data was not available for thatyear, only that from the first quarter (Jan.-Mar.) is used.

For example:The definition for the boundary between the blue oceans and white oceans in 2008

There is two-year difference between 2008 and 2009. In our database, the average number ofcitations is 2.8. If the number of citations of a journal paper published in 2008 is over 6, based onthe pigeonhole principle, we can assume that, in 2008 and 2009, the number of citations of aspecific journal paper will be over 2.8 during the two years.

10

Another example:The definition for the boundary between the blue oceans and white oceans in 2006

There is four-year difference between 2006 and 2009. In our database, the average number ofcitations is 2.8. If the number of citations of a journal paper published in 2006 is over 12,based on the pigeonhole principle, we can assume that, in the past four years (2006-2009),the number of citations of a specific journal paper will be over 2.8 during the four years.

Figure 4: The chart of the number of citations, the number of journal papers, and the average number of

citations for the nine selected journals in the study

An instructional design model for the use of the corpus-based system to develop newresearch topics in CALL

Along with the evolution of various types of technologies applied to language learning (Liu,2008; Liu & Chen, 2007), in this ever-changing, multidisciplinary field, there are several basicbut important components establishing the “CALL equation”(Egbert, 2005). These componentsare adapted and few other elements are added to the diagram presented in Figure 5, including thelearner (with his or her prior knowledge, experiences, motivations, behaviors, and others), theso-called “hard” technologies(hardware and software) and “soft” technologies(identified waysor methods for using hard technologies) (Jonassen, 2004), hyperlinked learning contents, andinteractive learning tasks/activities, with or without the peer and/or instructor support. Figure 5shows an instructional design model, which is adapted and developed based on Egbert’s (2005) CALL equation. Its details of each of the components are being refined by the researchers.

11

Figure 5: An instructional design model adapted and developed based onEgbert’s (2005) CALL equation

The ongoing research agendaThe researchers used the first of Liu’s (2008) five guidelines to develop new sub-topics inCALL research in the first stage. They will explore the possibility of integrating moreimportant journals & their papers into our corpus. In addition, they will try Liu’s (2008) other four guidelines for developing new sub-topics in CALL research. Moreover, they will finalizethe instructional design model as well as the corpus for helping create new research topics inCALL.In the second year, the newly developed corpus-based system will be used by someresearchers and practitioners in CALL. In addition, another corpus-based system will bedeveloped for helping developed new research questions in DLL or CALL, and this will be amore challenging work.

The expected research publicationThe researchers will write up the results and then submit the paper to a SSCI journal for

possible publication in this summer.

12

ReferencesAndrews, R., Freeman, A., Hou, D., McGuinn, N., Robinson, A. & Zhu, J. (2007). The

effectiveness of information and communication technology on the learning of writtenEnglish for 5- to 16-year olds. British Journal of Educational Technology, 38, 2, 325-336.

Arthur, W. B. (2007). The structure of invention. Research Policy, 36, 274-287.Bax, S. (2003). CALL- past, present and future. System, 31, 1, 13-28.Beatty, K. (2003). Teaching and researching computer assisted language learning. Pearson

Education LimitedBecta (2004). What the research says about using ICT in modern foreign languages. British

Educational Communications and Technology Agency (Becta), Coventry. RetrievedOctober 13, 2008, fromhttp://partners.becta.org.uk/upload-dir/downloads/page_documents/research/wtrs_mfl.pdf

Boylan, M. (2004). What have we learned from 15 years of supporting the development ofinnovative teaching technology? Social Science Computer Review, 22, 4, 405-425.

Burgess, T. F. & Gules, H.K. (1998). Buyer-supplier relationships in firms adopting advancedmanufacturing technology: an empirical analysis of the implementation of hard and softtechnologies. Journal of Engineering and Technology Management, 15, 127-152.

Burnard, P. (2006). Reflecting on the creativity agenda in education. Cambridge Journal ofEducation, 36, 3, 313-318.

Chambers, A. & Bax, S. (2006). Making CALL work: Towards normalization. System, 34, 4,465-479.

Chang, K. -E., Sung, Y. - T., & Zheng, J. - W. (2007). Hypermedia authoring with writing processguidance. British Journal of Educational Technology, 38, 5, 851-860.

Chang, M.–M. (2007). Enhancing web-based language learning through self-monitoring.Journal of Computer Assisted Learning, 23, 187-196.

Chapelle, C. A. (2001). Computer Applications in Second Language Acquisition: Foundations forTeaching, Testing and Research. Cambridge, UK: Cambridge University Press.

Chapelle, C. A. (2007). Challenges in evaluation of innovation: Observations from technologyresearch. Innovation in Language Learning and Teaching, 1, 1, 30-45.

Chou, S.-W. (2005). Designing good institutional contexts for innovation in atechnology-mediated learning environment. Journal of Computer Assisted Learning, 21,269–280.

Collins, A., Joseph, D., & Bielaczyc, K. (2004). Design research: Theoretical and methodologicalissues. The Journal of The Learning Sciences, 13, 1, 15-42.

Conacher, J. E. & Kelly-Holmes, H. (2007). Thinking beyond the technology: Toward a broaderunderstanding of new language-learning environments. In J. E. Conacher, & H.Kelly-Holmes (eds.), New learning environments for language learning: Moving beyond theclassroom?. Frankfurt & New York: Peter Lang.

Cummings, J. N., & Kiesler, S. (2005). Collaborative research across disciplinary andorganizational boundaries. Social Studies of Science, 35, 5, 703-722.

de Jong, T. (2006). Computer simulations: Technological advances in inquiry learning. Science,312, 532-533.

Davis, H., & Eales, S. (2007). Editorial instruction: BJET special issue on critical success factorsin institutional change. British Journal of Educational Technology, 38, 6, 769-772.

Egbert, J. L. & Petrie, G. M. (Eds.) (2005). CALL Research Perspectives. Mahwah, NJ: LawrenceErlbaum Associates, Inc.

Ferdig, R. E. (2006). Assessing technologies for teaching and learning: Understanding theimportance of technological pedagogical content knowledge. British Journal of EducationalTechnology, 37, 5, 749-760.

Gruba, P. (2004). Computer Assisted Language Learning. In A. Davies and C. Elder (eds): TheHandbook of Applied Linguistics. London: Blackwell, pp. 623-648.

Hannan, A. (2005). Innovating in higher education: context for change in learning technology.

13

British Journal of Educational Technology, 36, 6, 975-985.Hartley, J. (2007). Teaching, learning, and new technology: A review for teachers. British Journal

of Educational Technology, 38, 1, 42-62.Hawkridge, D. (1999). Thirty years on, BJET! and educational technology comes of age. British

Journal of Educational Technology, 30, 4, 293-304.Heinich, R., Molenda, M., Russell, J. D., & Smaldino, S. E. (1999). Instructional media and

technologies for learning (6th edn.). Upper Saddle River, NJ: Prentice-Hall.Hoven, D. L. (2006) Communicating and interacting: An exploration of the changing roles of

media in CALL/CMC. CALICO Journal, 23, 2, 233-256Huang, H. -T., & Liou, H. -C. (2007). Vocabulary learning in an automated graded reading

program. Language Learning & Technology, 11, 3, 64-82.Hwang, G. -J., Lin, B. M. T. & Lin, T. - L. (2006). An effective approach for test-sheet

composition with large-scale item banks. Computers & Education, 46, 122-139.Jonassen, D. H. (Ed.) (2004). Handbook of research on educational communications and

technology (2nd edn.). Mahwah, NJ: Lawrence Erlbaum Associates, Publishers.Kanuka, H., Rourke, L., & Laflamme, E. (2007). The influence of instructional methods on the

quality of online discussion. British Journal of Educational Technology, 38, 2, 260-271.Kim, W. C., & Mauborgne, R. (2004a). Value innovation. Harvard Business Review, 82, 7/8,

172-180.Kim, W. C., & Mauborgne, R. (2004b). Blue ocean strategy. Harvard Business Review, 82, 10,

76-84.Lally, C. G. (2000). Emerging technologies, re-emerging techniques. The French Review, 74, 1,

72-80.Lan, Y. - J., Sung, Y. - T., & Chang, K. -E. (2007). A mobile- device- supported peer-assisted

learning system for collaborative early EFL reading. Language Learning & Technology, 11,3. 130-151.

Larsen-Freeman, D. & Cameron, L. (2008). Research Methodology on Language Developmentfrom a Complex Systems Perspective, The Modern Language Journal 92, 2: 200-213.

Latchem, C. (2006). Editorial: A content analysis of the British Journal of EducationalTechnology. British Journal of Educational Technology, 37, 4, 503-511.

Levine, L. E., Waite, B. M., & Bowman, L. L. (2007). Electronic media use, reading, andacademic distractibility in college youth. CyberPsychology & Behavior, 10, 4, 560-566.

Levy, M. & Stockwell, G. (2006). CALL Dimensions: Options and issues in computer assistedlanguage learning. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

Liaw, M. -L. (2006). E-learning and the development of intercultural competence. LanguageLearning & Technology, 10, 3, 49-64.

Liu, G. -Z. (2003). An instructional design theory for teaching Freshman English in a hybridweb-based instruction course in Taiwan. Doctoral Dissertation. 315 pages. IndianaUniversity.

Liu, G. -Z. (2005). Designing EFL learning through hybrid instruction. IATEFL Issues, 183, 10.Liu, G. -Z. (2008). Innovating research topics in learning technology: where are the new blue

oceans?. British Journal of Educational Technology, 39, 4, 738-747.Liu, G. -Z., & Chen, A. S.-W. (2007). A taxonomy of Internet-based technologies integrated in

language curricula. British Journal of Educational Technology, 38, 5, 934-938.Ma, Y., Williams, D., Prejean, L., & Richard, C. (2007). A research agenda for developing and

implementing educational computer games. British Journal of Educational Technology, 38,3, 513-518.

Mantovani, A. (2006). Complementarity between product and process innovation in a monopolysetting. Economics of Innovation and New Technology, 15, 3, 219-234.

McDonough, E. F. & Kahn, K. B. (1996). Using “hard”and “soft”technologies for global newproduct development. R&D Management, 26, 3, 241-253.

McPherson, M (2005). Editorial: Developing innovation in e-learning: lessons to be learned.British Journal of Educational Technology, 36,4, 585-586.

14

Reid, A., & Petocz, P. (2004). Learning domains and the process of creativity. AustralianEducational Researcher, 31, 2, 45-62.

Reigeluth, C.M. (1999). What is instructional-design theory and how is it changing? In C.M.Reigeluth, (ed.), Instructional-design theories and models: A new paradigm of instructionaltheory, Vol. II, 5-29. Mahwah, NJ: Lawrence Erlbaum Associates.

Reigeluth, C.M. & Frick, T.W. (1999). Formative research: A methodology for improvingeducational theories and models. In C.M. Reigeluth, (ed.), Instructional-design theories andmodels: A new paradigm of instructional theory (Vol. 2, pp. 633-651). Mahwah, NJ:Lawrence Erlbaum Associates, Inc., Publishers.

Reigeluth, C.M. (2003). Knowledge building for use of the internet in education. InstructionalScience, 31, 341-346.

Richey, R. C. (1998). The pursuit of useable knowledge in instructional technology. EducationalTechnology Research & Development, 46, 4, 7-22.

Rushby, N. (2007). Editorial. British Journal of Educational Technology, 38, 1, 3-4.Rushby, N. & Seabrook, J. (2008). Understanding the past—illuminating the future. British

Journal of Educational Technology, 39, 2, 198-233.Shih, M., Feng, J., & Tsai, C.–C. (2008). Research and trends in the field of e-learning from

2001 to 2005: A content analysis of cognitive studies in selected journals. Computers &Education, 51, 2, 955-967.

Shoffner, M. B., Jones, M. & Harmon, S. W. (2000). Paradigms Restrained: Implications of Newand Emerging Technologies for Learning and Cognition. The Journal of ElectronicPublishing, 6, 1. Retrieved May 11, 2008, fromhttp://hdl.handle.net/2027/spo.3336451.0006.111

Sun, Y.–C. (2003). Learning process, strategies and web-based concordancers: a case study.British Journal of Educational Technology, 34, 5, 601-613.

Sun, Y.–C. (2007). Learner perceptions of a concordance tool for academic writing. ComputerAssisted Language Learning, 20,4, 323-343.

Surry, D. W. (2005). Editorial. British Journal of Educational Technology, 36, 6, 933-935.The editor (1997). Editorial: University-supported learning. Journal of Computer Assisted

Learning, 13, 73–73.Tsai, C.- C., & Lin, S. S. J. (2001) Analysis of attitudes towards computer networks and internet

addiction of Taiwanese adolescents. CyberPsychology & Behavior, 4, 3, 373-376.Vinge, V. (2006). The creativity machine. Nature, 440, 411-411.Warschauer, M. (2000). On-line learning in second language classrooms: An ethnographic

study. In Network-based language teaching: Concepts and practice (pp. 41-58). New York:Cambridge University Press.

Wible, D., Kou, C.–H., Chien, F.–Y., Liu, A., & Tsao, N.–L. (2001). A web-based EFL writingenvironment: integrating information for learners, teachers, and researchers. Computers &Education, 37, 297-315.

Wible, D., Kou, C.–H., Tsao, N.–L., Liu, A., & Lin, H.–L. (2003). Bootstrapping in a languagelearning environment. Journal of Computer Assisted Learning, 19, 90-102.

Wray, K. B. (2005). Rethinking Scientific Specialization. Social Studies of Science, 35, 1,151-164.

Yang, S. C. (2001). Integrating computer-mediated tools into the language curriculum. Journal ofComputer Assisted Learning, 17, 85-93.

Yang, S. C. & Chen, Y.–J. (2007). Technology-enhanced language learning: a case study.Computers in Human Behavior, 23,860-879.

Yang, S. S. C. (2003). Integrating ICT into second language education in a vocational high school.Journal of Computer Assisted Learning, 19, 447-461.

Zenios, M., Goodyear, P. & Jones, C. (2004). Researching the impact of the networkedinformation environment on learning and teaching. Computers & Education, 43, 205-213.