何文超个人博客 » 第二语言 http://www.hewenchao.com www.hewenchao.com Thu, 12 Jan 2012 05:36:18 +0000 en hourly 1 http://wordpress.org/?v=3.3.1 第二语言口语技能网上学习 E-Learning of Second Language Speaking Skills http://www.hewenchao.com/2007/e-learning-of-second-language-speaking-skills/?utm_source=rss&utm_medium=rss&utm_campaign=e-learning-of-second-language-speaking-skills http://www.hewenchao.com/2007/e-learning-of-second-language-speaking-skills/#comments Wed, 14 Nov 2007 14:00:00 +0000 何文超 http://www.hegwan.com.au/hewenchao/?p=30 . . . → Read More: 第二语言口语技能网上学习 E-Learning of Second Language Speaking Skills]]>

E-Learning of Second Language Speaking Skills

 

 

He, Wenchao

CoCo Research Centre

Faculty of Education and Social Work, University of Sydney, Australia

 

8 November 2007

 

 

 

Introduction

 

The continual growth of information and communication technologies (ICT) has much facilitated online learning. Second language (L2) learners can easily get access to huge amount of relevant online resources for free and commercial courses as well. Within formal training programs, online second language teachers keep trying to develop and improve their students’ comprehensive skills of the target language. However, not all skills of a language can be taught online easily. When teaching languages at a distance, one of the main challenges is the development and practice of speaking skills (Hampel, 2003). On the other hand, learners often feel more confident and can take more risks and trials when they practise speaking using computers in a private workspace than in a face-to-face setting such as a real classroom or real-life communication situation (Gong, 2002; Kataoka, 2000). The gap between the affordance of online oral second language teaching and the demand from learners is expected to be further bridged.

 

Hence, under the mechanical-meaningful-communicative framework (Paulston, 1971a, 1971b; Pennington, 1989, 1996), this paper will review and synthesize recent relevant empirical studies from three aspects, and articulate their implication for further action of bridging such gap.

 

 

Theoretical Framework

 

The theoretical framework adopted in this study is based on classification of language learning. One example is the structural pattern drills for language teaching raised by Paulston (1971a, 1971b)—mechanical drills, meaningful drills and communicative drills. This framework helps language teachers organize their instruction according to different grades, stages and periods with corresponding objectives. As for beginners, teachers are advised to use mechanical drills, in which there is complete control of the response and only one correct way of responding. The ability to practice mechanical drills without necessarily understanding them is an important criterion in distinguishing them from meaningful drills. In a meaningful drill, there is still control of the response although it may be correctly expressed in more than one way. The teacher always knows what the student ought to answer. The main difference between a meaningful drill and a communicative drill is that in the latter the speaker adds new information about the real world. The expected terminal behavior in communicative drills is normal speech for communication or, if one prefers, the free transfer of learned language patterns to appropriate situations.

 

For the purpose of computer assisted language learning (CALL), Pennington (1989, 1996) further defines spoken language’s competence with “mechanical aspect” and “meaningful aspect”. The mechanical aspect of speech involves learning to discriminate and produce sounds of a language and tie these together prosodically in fluent strings of sounds comprising syllables, words, phrases and longer utterances or articulation and decoding of individual sounds (phonemes), while meaningful aspect involves learning to build as well as to decompose grammatically coherent utterances and to tie these to communicative functions according to rules of pragmatic appropriateness in a given speech community.

 

Pennington’s framework focuses on speech itself regardless the sequencing structure of learning or teaching a language. Mechanical aspect and meaningful aspect can be used separately to explain learners’ speaking level. For example, some L2 learners may know how to communicate appropriately but their pronunciation or fluency could be awkward. However, one of the characteristics of Paulston’s communicative drills—expecting speakers to add new information from their real world, is still worthwhile for reexamining online L2 speaking instruction. This is because Pennington’s framework “pays too little attention to the Internet” (Kisner, 1997, p. 13), but the development of information and communication technologies has increased the affordance of online environment for learn-teacher and learner-learner communication similar to the real world. Hence, in this study, I add a “communicative aspect” to Pennington’s framework, which helps further articulate the recent empirical studies on L2 speaking online instruction.

 

 

Recent Studies on L2 Speaking Online Instruction

 

Mechanical Aspect

 

Pronunciation has dominated the mechanical aspect of L2 speaking instruction with computer assisted. Pennington (1995) reports the situation in last century that, to practice speaking, L2 learners mainly use multimedia products incorporated extensive texts, graphics, animation, audio, and digitized audio or video clips. With some software, computers can produce relatively natural speech from individual phonemes stored as digital codes that are strung together by rule as the user types on the keyboard. This ‘synthesis-by-rule’ technology has the advantage that it can convert any text to speech thus enabling learners to gain exposure to a diversity and quantity of input. In such a mode, the computer keeps outputting but not “listens” to the learners.

 

Later in 1990s, automatic speech recognition (ASR) had been developed to the point where it could be used in language learning applications. Students began to be able to “talk” with their computers. While the American company Syracuse and the French company Auralog both began to employ this technology to design software for computer assisted pronunciation training (CAPT), Ordinate Corporation used ASR to evaluate students’ spoken English by means of its 10-minute PhonePass test administered by computer over the telephone. However, the product later has been proven failed to reflect students’ real pronunciation level (Hincks, 2001).

 

On the other hand, speech-recognition-based language learning programs were also evaluated. Hincks (2002) investigated whether such program would improve the general goodness of pronunciation. Eleven students were given a copy of the program Talk to Me by Auralog as a supplement to a 200-hour course in Technical English, and were encouraged to practice on their home computers. But the result is that such pronunciation training using ASR-based language learning software did not demonstrably improve the mean pronunciation abilities of the students. However, results from the PhonePass test indicate that use of the program was beneficial for the students who began the course with an ‘intrusive’ foreign accent.

 

You may notice that the same researcher (Hincks, 2001, 2002) has used a proven suspicious  tool—PhonePass to implement the pre- and post-tests and then concludes that Talk to Me does not work for intermediate students. This result could be further suspicious.

 

Although using ASR for evaluation has to bear the risk of inaccuracy, its evaluation function kept being developed. But this time, evaluation and instruction have been integrated, and the role evaluation turned to assist instruction. MyET is an example of such development. It is a web-based program employing automatic speech analysis system (ASAS) to identify the words spoken into the recording device, and it can analyze the speech on pronunciation, pitch, timing and emphasis. It then displays the spectrum and contour of the user’s utterance, and provides a scoring mechanism with corrective feedback information that helps users to improve their pronunciation. MyET can explicitly pinpoint learners’ pronunciation errors by giving one on one feedback that compares the learner’s pronunciation with a model pronunciation (L-Labs, 2007).

 

Chen’s (2004) study on college students who used MyET found significant positive correlations between machine scorings and human graders. He suggested that subjects with different levels of language proficiency should be invited to further test the scoring validity of MyET. Tsai (2006) accepted the suggestion and continued the study. The result is that MyET can only distinguish between beginning and higher level learners. On the other hand, not much difference was found between the scores for intermediate and advanced learners. This conclusion is similar to Hincks’s (2002) finding on Talk to Me. In order to solve this problem, Tell Me More’s “individual package”, a later edition of Talk to Me, now provides three-level solution—beginner, intermediate and advanced. Each one allows learners to alter the various elements of the program to match their individual levels closely (Auralog, 2007).

 

ASR-based CAPT systems now are widely developed by different institutes around the world, but in common, their typical functions can be described with a sequence of five phases: Speech recognition, Scoring, Error detection, Error diagnosis and Feedback presentation (Neri, Cucchiarini, & Strik, 2003). But the first two have much criticism. Speech recognition accuracy is only good for native speakers (90% accuracy), but it performs much less well for non-native speakers. Therefore its application in L2 learning environment leaves suspicious (Coniam, 1999; Derwing, Munro, & Carbonaro, 2000), especially when such mechanical drill demands high accuracy since it supposes only one correct response (Paulston, 1971a, 1971b). Scoring system is based on the comparison between native speakers’ and learners’ utterances, but two utterances with the same content that may both be very well pronounced still have the waveforms that are very different from each other. So the scores are always confusing, especially when the results indicate that advanced learners even have less scores than lower level learners (Reesner, 2002; Tsai, 2006). So doubts should be expressed to the pedagogical value of these types of displays (Mackey & Choi, 1998; Neri, Cucchiarini, Strik, & Boves, 2002; Wildner, 2002).

 

It seems that the studies above are limited in the scales of computer and software themselves—either reporting how the programs work (e.g. Neri et al., 2003; Pennington, 1995)  or evaluating whether those programs really work (e.g. Chen, 2004; Coniam, 1999; Derwing et al., 2000; Hincks, 2001, 2002; Mackey & Choi, 1998; Reesner, 2002; Tsai, 2006; Wildner, 2002). Since there are many problems with those programs, why not try to go back to the original educational objective—improving leaners’ L2 speaking skills? If some technologies consumed much time and budget but failed to help learners achieve the objective, we could think about other approaches—maybe going back to traditional classroom for clues.

 

In terms of clues from traditional classroom, Engwall & Bälter (2007) suggest that, since human teacher – learner interaction is vastly more effective than current CAPT pedagogy, pronunciation training software may be improved by studying how feedback is distributed in the real language classroom. Then they interviewed with teachers and students and observed their activities in classroom, focusing on four aspects—when pronunciation feedback should be given, for which errors, what kind of feedback should be used, and how to promote student motivation. After comparing the feedback from traditional classroom and current CAPT programs, they bring forward a list of strategies that may be useful for CAPT and then they create a virtual teacher to test those features. The result from users’ questionnaire indicates that, the virtual tutor with 3D computer animations successfully makes the learning environment more interesting and engaging, and provides more effective feedback. This study and its suggestion provide the compensation to the drawbacks of speech recognition’s inaccuracy and error detection. While those drawbacks can not overcome from the technical perspective, we may think of integrating real teachers into virtual pronunciation classroom by using CMC technologies, such as audio-conferencing (Lamy, 2004; Volle, 2005), voice chat (Jepson, 2005) and video-conferencing (McIntosh, Braul, & Chao, 2003). However, real teachers for online language teaching may be supposed to convey higher level drills, such as meaningful drills and communicative drills, rather than mechanical drills. Hence, further studies on this kind of integration are recommended.

 

Meaningful Aspect

 

From meaningful aspect, online L2 learners are supposed to correctly response in more than one way but they do not need to add new information to the “class” from the real world. They should be taught to understand grammatically coherent utterances and then speak appropriately in an instructional environment (Paulston, 1971a, 1971b; Pennington, 1989, 1996). To achieve these instructional objectives, conversation interaction is essential. Its benefits for learners’ acquisition of second language have been investigated, claimed and proven (Gass, 1997; Long, 1996; Alison Mackey, Perdue, & McDonough, 2000; Pica, 1994).

 

In terms of oral conversation for meaningful aspect, a typical mode to convey online L2 instruction is human – machine conversation (HMC). The ideal scenario of HMC would be for a learner to speak to the computer and for the computer to ‘‘understand’’ and respond in a sufficiently appropriate and native-like manner to provide good target language input. But this is not likely a realistic aim given the current state of natural language processing (Stewart & File, 2007). As Feigenbaum (2003) has observed, real difficulty lies in managing ‘‘the ‘understand’ part: the semantics that attach real-world meaning to the word-symbols, then use those meanings for knowledge organization and inference’’ (p. 33). As a result, currently the most practical way to enable the computer response correctly is pre-storing corresponding utterances in a dialogue system. Since natural language is formulaic, automatic, and rehearsed, rather than prepositional, creative, or freely generated (Fillmore, 1976), pre-stored utterances used in L2 speaking instruction can aid learners’ speaking production by lightening the processing burden and thus facilitating fluency, and increase their listening comprehension of the full message speakers wish to convey (Wray, 2000, 2002).

 

In Let’s Chat by Steart and File (2007), a learner hear and see the virtual tutor’s question and then select and submit one favorite from a list of responses. The virtual tutor then continues the dialogue with elaboration prompt and a brief story. This system “offers a fertile environment for the acquisition and rehearsal of L2 social conversation skills” and such practice can enhance learners’ “grasp of idiomatic, native-like modes of expression by ‘conversing’ with it, thereby achieving higher levels of confidence and fluency in subsequent natural language interactions with human partners” (p. 114). Since Let’s Chat tends to prepare learners’ information for their speaking in real life, it still does not provide learners with the opportunity to speak out. A similar web-based conversation environment CandleTalk (Chiu, Liou, & Yeh, 2007), on the other hand, employs ASR to recognize a learner’s speaking out the selection from the suggested responses. This practice can improve learners’ sociocultural ability and sociolinguistic ability that aid them to select proper speech acts based on various sociocultural factors and to control over the language forms to perform the speech acts (Cohen & Olshtain, 1994). The result of a comparative experiment shows that there is a significant difference between the pretest and posttest oral performance after learners’ using the system (Chiu et al., 2007). Because there is still no evidence to prove that Let’s Chat can improve learners’ L2 speaking performance after the practice, those L2 speaking instruction system with ASR, such as CandleTalk, seem more recommendable.

 

Communicative Aspect

 

While the meaningful aspect of L2 speaking instruction expects specific response from learners, the communicative aspect of it, however, emphasizes the free transfer of learned language patterns to appropriate situations (Paulston, 1971a, 1971b). It can be realized in structured or unstructured instructional environment where computer mediated communication (CMC) technology is employed.

 

Live virtual classroom (LVC), based on audio-conferencing or video-conferencing, allows us to run a structured training program in real time in which the instructors and learners are online at the same time using the Internet. Many platforms can facilitate it, such as Centra, WebEx, IBM/Lotus Sametime, InterWise, etc. The skills needed by instructors, the use of slides, the support for lecture-based instruction, and classroom-like metaphors of hand-raising, question posing and the writing on a whiteboard are example of traits that make it easy to bridge from traditional classroom to LVC (Driscoll & Carliner, 2005). LVC requires much attention on the design of effective learning (Masie & Rinaldi, 2002), especially when L2 speaking learners need to adapt themselves to a new type of oral interaction, because the oral competence in synchronous environment requires more content knowledge and procedural knowledge than in traditional classroom (Lamy, 2004). Most of L2 speaking learners believe that technical issues have negative effect on the learning experience (Hampel, 2003). However, if they met any difficulty and then tried to negotiate it with teachers and peers, they would have more L2 production (Gass & Varonis, 1994; Kramsch, 1986; Varonis & Gass, 1985). But unfortunately, resulted from the lack of non-verbal communication in online environment, most of L2 speaking learners, unless group-working in “breakout rooms” of the LVC, may have little opportunity to engage in asides or spontaneous spoken chat during their tutorials (Heins, Duensing, Stickler, & Batstone, 2007). Furthermore, by spelling out, repeating and ensuring students’ comprehension, teachers tend to control and speak more in LVC than in traditional classroom during L2 speaking instruction (ibid), which may continually limits the communicative opportunities. In the rest of the time besides the teacher’s speech, students still can not experience satisfied interaction because users’ simultaneously speaking will usually lead to a simultaneous stop with awkward silence (Hampel, 2003).

 

While there are so many drawbacks in LVC for L2 speaking instruction, McIntosh, Braul, & Chao (2003) turned to an asynchronous approach—Wimba Voice Board, an asynchronous virtual classroom embedded in WebCT. The teacher in it directs debates based on different dilemmatic topics and students pose their speeches to response. The study indicates that students show the greatest enthusiasm in the activities with a high level of peer-to-peer interaction and they show a preference for interaction with classmates with which they are socially comfortable. But at the same time, they also suffer from technical issues such as the poor quality of sound and computer freezing.

 

Besides these structured instruction, unstructured L2 speaking practice, such as voice chat with peers, is also beneficial. Englishtown, an L2 distance education website, not only gives teacher-oriented conversation classes every hour all day, but also creates a virtual community comprising different voice chat rooms for their learners’ further practice after “class”. But such voice chat room has been suggested integrating into the context of unit study and basing on the “homework” assigned from conversation class, which may make the voice chatting more engaging and informative (He, 2007). 

 

 

Reflection and Implication

 

The mechanical-meaningful-communicative framework (Paulston, 1971a, 1971b; Pennington, 1989, 1996) provides us an appropriate checklist for today’s e-learning of L2 speaking skills. Based on this checklist and the recent research review, we can at least notice two problems, from the perspectives of e-learning developers and L2 teachers:

 

Integration of the three aspects

 

Currently we seldom see any e-learning provider integrating the three aspects of L2 speaking instruction synthetically. But if learners’ different skills of L2 speaking were developed separately and there was not any continual evaluation, they would not be aware of their zones of proximal development (Vygotsky, 1978) by thinking of what has been actually developed and what could be developed potentially. So the internal relationship of the mechanical-meaningful-communicative framework for L2 speaking instruction should be further explored.

 

Teacher education

 

Since it is reported that there are many problems in L2 speaking virtual classrooms, L2 online teachers need to improve their comprehensive skills of ICT. Hu (2005) notices that “under supportive conditions teachers tend to shift toward student-centred instructional approaches as they increase their use of ICT” (p. 281). However, according to Heins et al. (2007), L2 teachers do tend to create a strong control environment in LVC and such teaching style is quite different from their face-to-face classrooms. Is it because they lack the so-called “supportive conditions”? Kessler’s (2007) study can demonstrate this. Since L2 teacher education has not seen dramatic increases in perceived effectiveness as technology has become more readily available, most L2 teachers have to pursue informal study on ICT outside their degree programs, and specifically, they reflect that teaching L2 speaking skills with ICT is the most difficult for them. So we should provide more support for teacher education to overcome this disadvantageous situation.

 

 

Conclusion

 

It appears that the mechanical, meaningful and communicative drills from traditional classrooms for L2 speaking instruction have become available in an online environment through the last decade by creating APR-based pronunciation and conversation training programs and synchronous and asynchronous virtual classrooms and communities. While the meaningful aspect of these seems developed well without much criticism, the mechanical and communicative aspects need to be further improved since there are quite many problems from the technological and pedagogical perspectives. Furthermore, the integration of the three aspects is recommended and L2 teachers need more supports for their speaking instruction using ICT.

 

 

References

 

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]]> http://www.hewenchao.com/2007/e-learning-of-second-language-speaking-skills/feed/ 0 英孚教育Efekta网上学习系统的改进探讨 Englishtown.com’s Efekta System: Could Be Further Improved http://www.hewenchao.com/2007/englishtown-com-s-efekta-system-could-be-further-improved/?utm_source=rss&utm_medium=rss&utm_campaign=englishtown-com-s-efekta-system-could-be-further-improved http://www.hewenchao.com/2007/englishtown-com-s-efekta-system-could-be-further-improved/#comments Wed, 31 Oct 2007 14:00:00 +0000 何文超 http://www.hegwan.com.au/hewenchao/?p=31 . . . → Read More: 英孚教育Efekta网上学习系统的改进探讨 Englishtown.com’s Efekta System: Could Be Further Improved]]>

Englishtown.com’s Efekta™ System : Could Be Further Improved

 

 

 

He, Wenchao

CoCo Research Centre

Faculty of Education and Social Work, University of Sydney, Australia 

 

October 30, 2007
 

 

1.  Introduction

 

This paper reports on aspects of the possibilities and potentials for Englishtown.com’s further improvement from the perspective of user experience. It could help online language teaching program developers, both from Englishtown.com or other institutes consider the ways that they could make progress.

 

Englishtown.com is an online English learning website operated by Englishtown Inc, a division of Education First Group (EF) which is said to be the world’s largest private educational organization, with 26,000 staff, 300 schools, and 75 offices in 50 countries. Englishtown asserts that they have combined EF’s 40 years experience in language training with over $40 million in research and development to their Efekta™ System  for learning English (Englishtown, 2007a, 2007b, 2007c).

 

There are four main components in Efekta™ System (Englishtown, 2007b):

 

l        Teachers:  live, online teaching, 24 hours a day 

l        iLab:  interactive tutorials and study tools 

l        Coaching:  constant feedback and guidance 

l        Community:  classmates from 120 countries 

 

Teachers in Englishtown.com give 45-minute-long conversation classes every hour for the different levels of students based on different topics. Averagely, eight students of the same level will participate in one class. Students can make their own plans for conversation class and self-study in iLab but it is not compulsory for them to keep strict with the plans. In iLab, students will take their lessons by participating in different interactive activities. The lessons are divided into 15 levels and every level has 8 units. Based one topic, every unit has 13 parts: Introduction, Movie, Simulation, Map, Listening, Speaking, Reading, Writing, Review, Conversation Class, Writing Class, Net Tour and Test. While studying the lessons, students will use study tools if needed, such as translator, pronunciation lab, grammar lab, podcast, etc. In Writing Class, students will be requested to write an article with a given topic in relation to what is taught in the previous parts. A writing teacher will review the writing assignment, compose the coaching note and send a feedback email to the student. Besides learning the lessons, students can also make friends in a virtual community and have voice chat with their classmate. Generally, Englishtown can meet most of the needs of English learning from the students with different language and social backgrounds.

 

Though Englishtown has achieved some success and been recognized by many personal and corporate clients, it still need to be improved. As the rapid development of  learning technologies and theories has increased the affordance for online learning (Conole & Dyke, 2004), only those education providers keep adapting themselves to emerging technologies and to the dynamic needs of students and clients, can maintain and increase their predominance in the more and more competitive global education market.

 

Hence, this paper will focus on the shortcomings and outdated components of Englishtown.com and provide suggestions for its further development. The developers of Englishtown could consider this paper as a reference for their future work, while other distance education providers, including Englishtown’s competitors, would consider surpassing Englishtown or doing better in their own fields by employing some idea from this paper.

 

 

2.  Placement Test and Study Plan

 

Before enrolling in any course of Englishtown, users will be asked to take a placement test to determine which level of course they are advised to take. Placement is “a process of matching students and courses to achieve the best fit between what students know and what they need to know…[It helps make] the best possible match between a student’s current achievement status and the prerequisites of various alternate course sequences” (Frisbie, 1982). Englishtown’s placement test is significant for their realizing the slogan of “customized for each student” and they say they will “evaluate your [users’] weaknesses, interests, schedule and personality”. Based on that data, they create a customized study plan for users (Englishtown, 2007c).

 

Englishtown does provide a placement test concerning grammar, listening and reading to determine a user’s level according to the score he or she gets. However, they do not really “evaluate” users’ interest, schedule and personality and create a plan really based on that result. In stead, the only thing that the users will experience concerning the “evaluation” is being asked to answer the following multiple choice questions:

 

l        What is your main reason for wanting to learn English? Professional? Academic? Social? Travel? Other?

l        Which area of English would you like to focus on? Speaking? Pronunciation? Listening? Reading? Writing? Grammar? Vocabulary?

l        How many hours per week do you intend to study? Light – 1 to 2 hours a week?  Normal – 3 to 4 hours a week? Intensive – 5 or more hours a week?

l        How many conversation classes do you plan to attend each week? One per week?  Two per week? Three or more per week?

l        For how long do you want to keep your study plan active? 3 months? 6 months? 12 months? 18 months?

l        When do you prefer to study? Morning? Daytime? Evening? Weekend? Weekdays?

 

It seems that the developers for this part misunderstood the word “evaluation”. Actually, rather than directly asking for the result, “evaluation is an applied inquiry process for collecting and synthesizing evidence that culminates in conclusions about the state of affairs, value, merit, worth, significance…” (Mabry, 2005). If Englishtown was really evaluating users’ interest, schedule and personality, the users should be asked to provide some personal information to let the system make conclusions and suggestions for their own study plans. However, by asking the questions above, Englishtown virtually let users directly make the final conclusions. Even though the users do submit their answers, the significance of the data deserves suspicion. Since the user have not known much about what exactly is in the system, it is difficult for them to imagine the teaching style and the most useful component in the system, the outcomes of the courses and the time they should spend on it. When is asked “what is your main reason for wanting to learn English”, the users would be confused with the meaning of “English” in the question—the English courses in Englishtown or the English spoken by native English speakers? When is asked “which area of English would you like to focus on”, the users would consider whether they are being asked the weakness and whether this information determines the structure of their courses…

 

When the “customized study plan” is created, the users will receive a changeable calendar with random located course names according to the answers to the third, fourth and sixth questions in the “evaluation” (See Figure 1). Then the system will provide some pieces of study advice based on the answers to the first two questions. The disappointing content of the advice is basically the repeat of the introduction of some components of the system. For example, if users answered “writing” to the second question, the advice would be “The Englishtown Writing class is a great way to develop your Writing skills. Submit your essay to a teacher and get detailed feedback within 48 hours.”

 

Englishtown tries to let the potential users imagine how they could convey learner-centred curriculum, especially when the users are asked to process the study planning with the “evaluation”. However, no curriculum can claim to be truly learner-centred unless the learner’s subjective needs relating to the process of learning are taken into account (Nunan, 1988). Englishtown has not linked users’ subjective needs, such as their will to overcome the personal weakness in English, to the content, structure, procedure, objectives, learning style and assessment method of the courses. Every user actually does receive a personalized suggestion for the appropriate level and weekly study plan. Virtually they are still provided the same courses because there is not any change of the courses according to the result of the pre-evaluation.

 

 

Figure 1  Weekly Study Plan Calendar

 

Back to the placement test, without a timer, different users spend different time on the test, which could lead to the fallibility of the result of grammar and reading test. Furthermore, in the listening test, the audio clips can be played unlimitedly and some of the questions even use the same audio clips.

 

One of Englishtown’s Competitors—GlobalEnglish.com, has a better placement test with a timer in every session and a limitation of times (twice) for listening to the same audio clips in listening test, which is worthwhile for Englishtown to refer.

 

The fatal objection to Englishtown’s goal—“customized for each student” is not only the suspect placement test and the poor designed questionnaire, but the lack of a cyclical needs assessment and summative evaluation plans during the whole period of the courses. (Smith & Ragan) (1999) created a figure (see Figure 2) to interpret that the conclusions of a needs assessment should provide the reasons for developing or providing the appropriate instruction (p. 32).  So the really customized study plan is not a calendar or some advice, but specific instruction that meets the users’ exact needs. Different from traditional face-to-face learning environment, e-learning system can prepare different solutions for predicted result from needs assessment and provide the most suitable one to the right user. A further evaluation for the study plan after implementation would provide the basis for modification of the solutions.

 

Figure 2  Relationship Between Needs Assessment and Evaluation

 

According to “discrepancy” model of needs assessment (Kaufman & English, 1979; Rossett, 1988), the placement test and the questionnaire should help find out the gap between “what is” (what learners are currently able to do) and “what ought to be” (what learners should able to do) and determine which of these gaps should be addressed within the instruction—the customized solution. Without a pedagogical context, new users with different social backgrounds usually don’t know much about these two statuses and the gaps between them. So in order to create a customized study plan and provide the most appropriate solution, it would be better for Englishtown to analyze other more concrete information from users and make up the determination, rather than to let the users input their preference based on speculation. And the instruction, including the suggested study plan, should be scientifically in relation to the analysis of the data collected.

 

 

3.  Conversation Class

 

The benefits of conversational interaction between native and nonnative speakers or between nonnative speakers in their acquisition of second language have been investigated, claimed and proven (Gass, 1997; Long, 1996; Mackey, Perdue, & McDonough, 2000; Pica, 1994). Englishtown highlights its conversation class in many occasions and does give great effort to maintain and promote it by employing lots of certified, native-speaking English teachers to teach online 24 hours a days and encouraging users to participate more in it. However, conversation class in Englishtown still has two main weaknesses, detailed in the following subsections:

 

 

3.1  Lack of Preparative Materials

 

Englishtown’s conversation classes are separated from the topic within a study unit. There are different conversation class topics for every day and students can choose their favorite topics by taking the conversation classes on specific days during the week. Before entering the virtual classroom, students are encouraged to do some preparation by listening to a dialog and studying the new vocabulary. We do know that it is impracticable to arrange teachers to give the conversation class based on a specific unit because there are too many units and there may be not enough students available for the class at the same time and in the same unit, which leads to extreme increase of the cost. As a result, the preparation session for conversation class becomes important. However, currently this session is quite simple and doesn’t have much pedagogical significance. For the one hand, only if the class has been started can the students know the structure of the lesson. While looking through the content presented on slides, they are asked to answer questions. This leads to students’ high cognitive load and a higher cognitive load should result in more errors (Ayres & Sweller, 1990). Since our working memory is limited (Miller, 1956), if we read, listened and spoke at the same time, our brain would be overloaded. According to Sweller (2007), conversation class teachers’ PowerPoint-based instruction “can backfire if the information on the screen is the same as that which is verbalized, because the audience’s attention will be split between the two.” Furthermore, language classrooms which require oral communication are more anxiety-provoking (Horwitz, 2001; Kim, 1998). This emotional factor further increases students’ cognitive load. To overcome this problem, the conversation class teachers could utilize students’ schemas* by providing more preparative materials to them, such as the details of the subtopics, activities and tasks in class. Teachers could even ask students to do some preparation for specific questions and provide some websites for them to find useful information. These activities before class would help activate students’ schemas which help them answer questions and solve problems “automatically” without much consideration in working memory while they are in class. So they could focus on improving their spoken English skills, rather than the content of the topics. To realize this, Englishtown should create a path for conversation class teachers to provide preparative materials to students.

 

 

3.2  Cursory Feedback from Teachers

 

Conversation class teachers will grade and feedback on students’ performance in class. The problem is that there is insufficient quantitative standard to support the grading and feedback. As a result, students don’t know their progress and exact weakness. See some samples below:

 

Sample 1: I hoped you enjoyed talking about France in today’s lesson and learnt some interesting information about the country as well as some English vocabulary. You participated well throughout the class and used appropriate intonation in the reading. Good work! Grade: 90%

Sample 2: You have developed some really good skills. You simply need to fine tune these to improve your English; practice makes perfect! See you again soon in class. Grade: 83%

Sample 3: Your vocabulary is very good! Thank you for your enthusiastic participation in class today. Keep practising the vocabulary you have learnt in class today so that you continue improving. Keep reading books and listening to television so that you improve your grammar. Hope to see you soon. Grade: 80%

Sample 4: You did a great job! Thanks for your excellent contributions to today’s lesson. I enjoyed hearing your ideas and opinions about parties. You demonstrated a solid understanding of the topic and showed that your skills in English are strong. Keep up the good work and see you in class again soon! Grade: 88%

Sample 5: Excellent! You are speaking very well in class. You have great skills and you have a sound understanding of the topic areas. I hope that my corrections during class have helped. Keep up the good work! See you again soon in class. Grade: 86%

 

        In the feedback samples, those words underlined and in red have focused on specific points in relation to language learning, such as intonation, tune, vocabulary and understanding. It helps students recall what they said and heard during the class and be aware of their zones of proximal development (ZPD) † by thinking of what has been actually developed and what could be developed potentially. Though after class the teacher could not provide further help, the students could know their updated goals and then give more effort on them. But it seems that the teachers focused more on what students had achieved while seldom described the potential development levels for students.

 

        The comment in blue in the samples seem either too simple or irrelevant to the students’ personal situation known from class. In Sample 2, 4 and 5, teachers gave much positive feedback without details. Students will want to know what exact aspects they have done well. Though general positive feedback may motivate the students at first, they would ignore it if they received too much without satisfying reasons. On the other hand, the first sentence in Sample 1 and the fourth sentence in Sample 3 are just repeating what have been said in class and the audiences are the whole class.

 

Because different students have different preference for feedback in second language learning (Brandl, 1995), it would be better for Englishtown to let the students choose the  kind of feedback they would receive before class and let teachers know their options. If the teachers even could see the portfolio of every student, they would provide more relevant and useful feedback. Furthermore, though the system provides flexible learning environment, students should be still encouraged to take the conversation class given by the same teacher according to the teacher’s personal time table, rather then encouraged to try classes from different teachers through out the whole learning duration to demonstrate how “flexible” the system is. The more the teachers know about their students, the more effective and relevant the feedback could be.

 

To raise the quality of feedback, Englishtown could also create a criteria system to assist teachers’ evaluation work and let students know how the grading comes out. Hyland (Hyland, 2001) pointed out that over a half of online second language learners wanted to know about their strengths and weaknesses, which, from their perspectives, was considered to be the main purpose of teachers’ written feedback (p. 241). While most teachers prefer not to interrupt the communication by correcting students’ errors in class (Engwall & Bälter, 2007) and students’ performance is more likely to improve if they are encouraged to correct errors by themselves (Hendrickson, 1978; Lyster, 1997), it would be better to assign students some small oral practice tasks in relation to their personal errors and weaknesses perceived by the teachers in class when giving feedback according to the criteria system. Thanks to the student-only voice chat room in Englishtown, students have the opportunity to do the tasks with their peers after the conversation class.

 

 

4.  Online Community

 

Englishtown builds an online community for English learners by promoting their friendship. Actually it is like a SNS (Social Networking Service) website, where users are asked to create a profile that includes personal information such as gender, age, nationality, introduction, interest, etc, and can upload their photos and write articles and comment. Based on that the profiles, users can search for their pen pals according to some conditions they input, and then use English to communicate with each other by sending text message. There are also some chat rooms with different topics, where users can practice English instantly, but only subscription members are allowed to use voice chat rooms. The voice chat rooms are labeled with levels of English—Beginner, Elementary, Intermediate and Advanced.

 

        While the era of Web 2.0 has arrived, many SNS websites become popular and have much influence on people’s life on line. The educational potentials of SNS websites are worthwhile for us to explore and realize. Online learning website can also integrate the functions of typical SNS website to analyze learners, to help instruction and to enrich users’ learning experience (He, 2007a, 2007b, 2007c). Englishtown’s SNS product—Englishtown Friends, is still in its Beta. It has not been integrated into the main instruction system.

 

Englishtown could begin to promote this integration in “Student writing”. It is a place in the system for users to post their own writing. Users can also comment on other’s articles. Actually this is like a discussion board. Users can post whatever they like. Some users post their written assignments finished in a unit’s learning but most of the messages are like casual writing. The so-called 9 million users seem seldom participate in such a section shown in the column of “Student Center”. Since 2003, there have been only 13,018 messages in it, which is quite a small number. This may be because:

 

        (a) the users are not required to participate in it while they are learning in the system;

        (b) teachers don’t give feedback for the writing in it;

        (c) since the writings are not linked to the authors’ profile, it is difficult to develop and maintain a friendship in it.

 

        To encourage learners to participate more and to realize the instructional functions, Englishtown could integrate three things: (a) written assignments from every unit, (b) teachers’ coaching notes for written assignments and (c) Englishtown Friends (users’ profiles). This means that the section of “Student writing” could directly display every user’s written assignments submitted from Writing Class in unit study and teachers review them and write coaching note there. Every user could read and comment on others’ assignment and relative coaching note. Teachers could answer users’ further questions referring to a specific assignment. When an author’s name is clicked, the page could turn to his or her profile page in Englishtown Friend. Users’ profile pages could also display all the written assignments. Considering users’ privacy, the system could let the users decide whether the system publishes their writing and relative coaching note.

 

        This integration could not only promote peer learning but also enlarge the significance of teachers’ coaching—it becomes open to everyone! Furthermore, from peers’ writings, users could find more favorable friends because they know more about a user’s background, interest, goals and other information. Typical friend finder will not help find the right person like this.

 

Besides written assignment, users would have more to discuss about what they have learned in a unit. The discussion board could also build separated folders for each unit’s topic. While learning in a unit, users could click a link to turn to the relative folder in discussion board and post a message. They could reflect what they think about the topic, ask or answer questions and provide further materials such as some pictures and video clips. As usual, they could find their favorable friends during the discussion. Besides text version, voice chat room could be another good place to discuss and share something about a unit’s topic. Then every unit could have its own voice chat room.

 

        Furthermore, during conversation class, participants more or less disclose some personal information such as their interests, goals, locations, occupation, etc, some of which may become the base for further communication and even friendship. Hence, a tracking record of classmates with links to their profiles would be benefit for those who would like to process further interaction.

 

        Last but important, assessment for users’ participation in the activities above should be taken into account. The system could report how much the user has participated in the community during a unit’s learning through commenting on others’ written assignments, posting message or chatting in voice chat room about the topic, making new friends, and maintaining friendship by sending private message or chatting in text or voice chat room.

 

 

5.  Some Bugs

 

While evaluating different aspects of Englishtown.com, the author experienced some bugs:

 

l   Inappropriate Suggested Learning Time—the suggested time for every session is not like the real situation. If you finished a task much quicker than expected, it would indicate that you haven’t completed the session and you are not allowed to continue to next session, especially for the Writing Class—you could actually finish the written assignment within 30 minutes while the system expect you to spend 120 minute. To avoid this error, the suggested time could be designed to be displayed dynamically according to learners’ previous completion time for a specific session. That is, the current "predicted time" for completing a session is based on previous average time spent on the same kind of session.

l   Unchangeable Input—it seems that once writing class teachers submit their grading and comments on students’ writing assignments, they can not make any change by themselves until an administrator with higher privilege help. The author has experienced that a teacher provide much positive feedback for the writing assignment but gave a very low grade—9%. The author received three same feedback emails from the teacher. It seems that the teacher wanted to change the grade by further submitting or something, but failed. Then the author requested the administrator to help let the teacher reexamine the assignment. Several days later, the author received an email indicating that the grade has been changed to 90%. Hence, it would better to develop an error avoidance mechanism for teachers.

l   Inconsistent Statistic Data—it is said that Englishtown.com has millions of users all over the world. But in terms of the exact number, they have different versions in different web pages. From the “about us” page, they have 2 million users; from the message sent by the moderator of “Englishtown Friends”, they have 7 million users; and from most other pages, such as the register page, they have 9 million users. The numbers of active users, former users and total users may be changing every moment. So the places that show the numbers could be replaced as some variables defined and controlled by administrators. Then once a variable is changed, all pages including the variable will be changed automatically.

 

 

6.  Conclusion

 

There are always a gap between advertisement and real situation, a gap between clients’ expectation based on advertisement and the real experience and a gap between technologies’ potentials and the current status of a product. Englishtown.com has successfully set up a good example for e-learning by providing proven English courses. However, since learning science and technologies keeps developing, previous success of Englishtown does not guarantee forever success unless it also keep being improved based on updated technologies, feedbacks and researches.

 

        In this paper, we have discussed the weaknesses of Englishtown mainly from the aspects of placement test and study plan, conversation class and online community, and provided solutions. We can conclude that currently Englishtown provides poor placement test and study planning tools and does not really customize students’ learning; Conversation class provides insufficient preparative materials and cursory feedback; online community’s instructional potentials have not been fulfilled; and there are some bugs influence users’ experience. However, these weaknesses could be eliminated by better design, such as creating a better learner analysis system, a path for conversation class teachers provide preparative materials, a better feedback system with more explicit criteria, an SNS-integrated learning system, etc. All in all, Englishtown should keep being improved if they want to keep the dominant status in online English learning industry.

 

 

7. References

 

Ayres, P., & Sweller, J. (1990). Locus of difficulty in multi-stage mathematics problems. The American Journal of Psychology, 103, 167-193.

 

Brandl, K. K. (1995). Strong and weak students’ preferences for error feedback options and responses. The Modern Language Journal, 79(2), 194-211.

 

Conole, G., & Dyke, M. (2004). What are the affordances of information and communication technologies? ALT-J, 12(2), 113-124.

 

Englishtown. (2007a). Company Info.   Retrieved October 26, 2007, from http://www.englishtown.com/Sp/lp/CompanyInfo.aspx

 

Englishtown. (2007b). How it works.   Retrieved October 26, 2007, from http://www.englishtown.com/Sp/lp/HowItWorks.aspx

 

Englishtown. (2007c). Who We Are.   Retrieved October 26, 2007, from http://www.englishtown.com/Sp/lp/WhoWeAre.aspx

 

Engwall, O., & Bälter, O. (2007). Pronunciation feedback from real and virtual language teachers. Computer Assisted Language Learning, 20(3), 235-262.

 

Frisbie, D. A. (1982). Methods of Evaluating Course Placement Systems. Educational Evaluation and Policy Analysis, 4(2), 133-140.

 

Gass, S. M. (1997). Input, interaction, and the second language learner. Mahwah: Erlbaum.

 

He, W. (2007a). From Web 2.0 to Edu 2.0—2.0  culture promoting the grassroot revolution in educational and training industry. Unpublished Bachelor’s Thesis, Beijing Normal University at Zhuhai, Zhuhai.

 

He, W. (2007b). Online schooling: make it more appropriate.   Retrieved October 29, 2007, from http://www.hewenchao.com/Article_Show.asp?ArticleID=243 

 

He, W. (2007c). SNS, from an Educational Perspective.   Retrieved October 29, 2007, from http://www.hewenchao.com/Article_Show.asp?ArticleID=242 

 

Hendrickson, J. M. (1978). Error correction in foreign language teaching: Recent theory, research, and practice. The Modern Language Journal, 62, 387-398.

 

Horwitz, E. (2001). Language anxiety and achievement. Annual Review of Applied Linguistics, 21, 112-126.

 

Hyland, F. (2001). Providing Effective Support: investigating feedback to distance language learners. Open Learning: The Journal of Open and Distance Learning, 16(3), 233-247.

 

Kaufman, R., & English, F. W. (1979). Needs assessment: concept and application. Englewood Cliffs: Educational Technology Publiscations.

 

Kim, S. Y. (1998). Affective experiences of Korean college students in different instructional contexts: Anxiety and motivation in reading and conversation courses. Unpublished Doctoral Thesis, The University of Texas, Austin.

 

Long, M. H. (1996). The role of the linguistic environment in second language acquisition. In W. C. Ritchie & T. K. Bhatia (Eds.), Handbook of language acquisition (Vol. 2, pp. 413-468). New York: Academic Press.

 

Lyster, R. R., L. (1997). Corrective feedback and learner uptake. Studies in Second Language Acquisition, 19, 37-66.

 

Mabry, L. (2005). Assessment. In S. Mathison (Ed.), Encyclopedia of evaluation. Thousand Oaks: Sage.

 

Mackey, A., Perdue, S., & McDonough, K. (2000). How do learners perceive interactional feedback? Studies in Second Language Acquisition, 22(4), 471-497

 

Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63, 81-97.

 

Nunan, D. (1988). The learner-centred curriculum. Cambridge: Cambridge University Press.

Pica, T. (1994). Research on negotiation: What does it reveal about second-language learning conditions, processes, and outcomes? Language Learning, 44, 493-527.

 

Rossett, A. (1988). Training needs asessment. Englewood Cliffs: Educational Technology Publiscations.

 

Smith, P. L., & Ragan, T. J. (1999). Instructional Design (2nd ed.). Upper Saddle River: Prentice-Hall.

 

Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and Instruction, 4, 295-312.

 

Sweller, J. (2007). Help! My brain is overloaded!   Retrieved October 29, 2007, from http://www.unsw.edu.au/news/pad/articles/2007/mar/Cognitive_load_theory.html

 

Vygotsky, L. S. (1978). Mind in Society. Cambridge: Harvard University Press.

  

 


* A schema is a cognitive construct that organizes the elements of information according to the manner with which they will be dealt. It effectively increases the amount of information that can be held in working memory by chunking individual elements into a single element. (Sweller, 1994)

†  The zone of proximal development (ZPD) is “the distance between the actual developmental level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance, or in collaboration with more capable peers” (Vygotsky, 1978).

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Teaching and Learning Languages in the Virtual Community of Second Life


He, Wenchao

CoCo Research Centre
Faculty of Education and Social Work, University of Sydney, Australia

25 September 2007

1. Introduction


Second Life is an Internet-based virtual world launched in 2003, developed by Linden Lab, which came to international attention via mainstream news media in late 2006 (Sege, 2006; Harkin, 2006). Its users, called “Residents”, interact with each other through motional avatars in a downloadable client program called the Second Life Viewer, provided an advanced level of a social network service combined with general aspects of a metaverse. Residents can explore, meet other Residents, socialize, participate in individual and group activities, create and trade items (virtual property) and services from one another. All of the content (buildings, scenery and people) in Second Life is constructed by the residents and so it has become a place where our imagination is given freedom to create and explore. The Second Life Grid provides a unique and flexible platform for educators interested in distance learning, computer supported cooperative work, simulation, new media studies, and corporate training.


The educational potentials of Second Life are being explored around many educators and using it to teach and to learn languages has become a pretty popular topic recently. (see www.avatarlanguages.com and www.languagelab.com ) This paper tries to report and analyze this topic using notions of “Affordance” and its taxonomy and “Conventions” (Gibson, 1977; Norman, 1999; Conole & Dyke, 2004).



2. Affordance


The word affordance was coined by the perceptual psychologist J. J. Gibson (1977) to refer to the actionable properties between the world and an actor (a person or animal). To Gibson, affordances are relationships. They exist naturally: they do not have to be visible, known, or desirable. Conole and Dyke (2004, p.p.115-120) develop this concept by clarifying a taxonomy, which can help us infer the educational potential and possibilities of Second Life. And now we focus on the affordance for teaching and learning languages:


(1) Accessibility


As introduced by Second Life’s website, students and educators can work together on the Second Life Grid from anywhere in the world as part of a globally networked virtual classroom environment. They don’t have any additional hardware or equipment to get access to Second Life. The students and educators can easily download the program and install it to their computers and then use its basic functions for free. So far Second Life provides four editions of languages — English, German, Japanese and Korean, which satisfy those who using the system of these language and those who know at least one of these languages.


Furthermore, there are more and more traditional classroom environments integrate the activities in Second Life Grid to provide new opportunities for enriching an existing curriculum, in the situation of which the accessibility can be guaranteed by the education providers.


(2) Speed of change


The introduction of voice into Second Life has led teachers to offer a different sort of language class – one that is both centered on the student carrying out tasks to produce a piece of work and that involves the student talking with real people in the language they are learning to gain specific information and, of course, practice their language skills. This, to a large extent, avoids outdated instruction and enables students to navigate their way through the myriad of changing information and to benefit from the change of the real world concerning the language that they are learning.


(3) Diversity


Virtual language schools in Second Life offer access to a vast range of diverse and different experiences that can inform learning to replicate complex behavior by the approach termed as SurReal Quests (Avatar Languages, 2007), since the quests combine the realism of communication with real people, the very real information available on the net and the virtual encounters within Second Life. SurReal Quests are intended specifically for language education and therefore combine the social and communicative aspects of Second Life with the wealth of information available on the web.


(4) Communication and collaboration


Second Life’s voice capabilities have enhanced the communication and collaboration in languages being learnd by allowing residents to chat with each other in a way similar to talking with a group of people in a room. The students can communicate with other people (whether complete strangers, acquaintances, friends or colleagues) in a 3D setting regardless of where they are physically located in real life. For language teaching the addition of voice to Second Life must offer one of the most significant advances in technology in recent years – language students can socialize in their target language at anytime of the day without leaving home. Furthermore, communities and groups can be formed and developed around shared interests and students can work together in pairs or teams to develop the quests of the teachers such as producing podcast, blog and other materials. The completed materials could also be used as a basis for future activities with other students; perhaps a student carries out an activity based upon the information given in a previous student’s podcast, such as finding places, following directions or taking part in mini treasure hunts.


(5) Reflection


It can not be denied that the speed and pace of information change militates against reflection. It leaves no space for contemplation and considered judgment, and promotes a more pragmatic, reflexive immediate response to new information, as it is pixilated across our screens (Conole and Dyke, 2004, p.118). To avoid this situation, when processing the instruction, language schools in Second Life can assign the students to different locations on the island to discuss their topics in smaller groups and they can teleport from one location to the other and saved the text of their discussions which later they may be assigned to analyze for the best statements on those topics (Bump, 2007). So this can help balance the need of experiencing the rapid information change as well as the reflection.


(6) Multimodal and non-linear


Within Second Life, an approach with as varied tasks involving a wide range of language skills being practiced can be processed. This non-linear process forms a multimodal environment in which the students can adopt more individualized strategies and pathways aiming at different emphases, such as reading and listening (both for gist and for specific information), interviewing (both with peer students and other strangers), writing (appropriate use of vocabulary and style for the target audience), speaking (including pronunciation, intonation for maintaining interest). The role of the teacher is to ensure that practice leads to the actual development of the various language skills.


(7) Risk, fragility and uncertainty


This aspect of Second Life mainly focuses on the language educators. Different from setting up the own teaching and learning platform, the educators experience low risk as all the properties are in a huge and safe system—Second Life, rather than in a small office or something like that. The familiarity with Second Life of the learners before learning also provides them scaffolding which help them make sure more factors within the learning environment and avoid uncertainty. In this case, the students need not to learn and practice every new language learning platform that they are interested in. They can transfer among different language schools within the same system.


(8) Immediacy


Second Life, as instant virtual world, of course guarantees the immediacy. Every student responses directly and immediately since they have any request from both the teachers and the peers.



3. Conventions


When designing a graphical screen layout, designers greatly rely on conventional interpretations of the symbols and placement including three kinds of constraints (Norman, 1999). Designing language learning instruction in Second Life also experiences them:


(1) Physical constraints


The system requirements for Second Life are high, especially for the graphic card. It is well known that Second Life usually crash fairly often, which makes the educator embarrassed on resuming class after an unexpected downtime of the system. The cost of teaching in Second Life is pretty high due to the pricing of the lands…These are all the physical constraints, which may be the obstacles for promoting the learning products in Second Life.


(2) Logical constraints


As the students are from all over the world, logically it is known that they are in different time zone. So it also will be the challenge for language educators to assign synchronous tasks because some students won’t be available at some specific time.


(3) Cultural constraints


There are also other virtual worlds such as IMVU and There, the functions of which are different from that of Second Life to some extent. Those users coming from other virtual world or having been using other relevant software such as IM, would experience the logical constraints because they feel that something, such as voice, are not available in Second Life based on their experience and the culture in other software environments.


These conventions prohibit something while encourage others, which should be taken into account when designing online language courses in Second Life.


4. Discussion


Based on the deductive work on the potential and possibilities of teaching and learning languages in Second Life, some questions may appear:


(1) Will teaching and learning languages in virtual world such as Second Life be the trend?


I don’t think so. This is because (a) the affordance is for behavior of teaching and learning itself but not for every potential students and teachers who may prefer not to use it, (b) the advantages of the limitlessness in virtual worlds will be evident only when the participants have some limitations in real world, such as time and space and (c) some constrains being the roles of drawbacks can not disappear in a short time or never disappear.


(2) What should traditional language schools do?


The affordance of virtual world for language teaching and learning does have great thread on traditional language schools. Yet the predominance of traditional models is difficult for the emerging ones to replicate or imitate. Conversely, the affordance of virtual world can be integrated to the traditional instruction by providing extra exciting experience to students. In such a process of integration, it would be essential to analyze and identify the different aspects of the affordance of virtual world and what exactly they are, but not to do what have been done in virtual world directly.


(3) How can the virtual world be improved to satisfy teaching and learning languages to a larger extent?


This is the predominance of the application of the taxonomy of affordance and convention. The common procedure is (1) to identify and analyze every aspect of the taxonomy, (2) to find out the weak points (such as Second Life’s incapability with many graphic cards), (3) to clarify the target situation (such as aiding the teaching and learning to what extent on what specific points and levels), (4) to find out the gap between (2) and (3), and (5) to deal with the gap.



5. References


Avatar Languages. (2007). SurReal Language Quests. Retrieved September 20, 2007, from http://avatarlanguages.com/blog/?p=14

Bump, J. (2007). Teaching English in Second Life. Retrieved September 20, 2007, from http://currents.cwrl.utexas.edu/spring07/bump

Harkin, J. (2006). Get a (second) life. Financial Times, 17 November.

Norman, D. A. (1999). Affordance, Conventions and Design. Interactions, May and June, 38-42.

Conole, G. & Dyke, M. (2004). What are the affordances of information and communication technologies?. ALT-J: Research in Learning Technology, 12(2), 113-124.

Sege, I. (2006). Leading a double life. The Boston Globe, 25 October.


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