Student Speech: Email, Chat, and Spoken Language of Korean University Students

The results of research into the language learning potential of two forms of computer mediated communication (CMC)—asynchronous email and synchronous chat—have indicated that there are a number of advantages to the use of these forms of language production, both in terms of language produced and learner attitudes. This research focused on a detailed analysis of the language production of three classes of Korean freshman university students to assess how their language varied across the three forms of spoken language, email and synchronous chat. Class A wrote emails to each other, Class B communicated through synchronous chat, and students from Class C were recorded during small group conversations. The language was then analyzed for complexity and accuracy, and compared across a range of variables. The results showed that there was not a clear distinction between language produced in asynchronous email, language produced in synchronous chat, and language produced when engaging in facetoface communication. There were no clearly identifiable features to suggest they formed distinct language categories. Accordingly, it is suggested that other factors, such as task type and purpose of communication, may have as much influence on the language produced as the particular form in which it occurs.

STEM Journal, Vol 18, No 2, 2017

Student Speech: Email, Chat, and Spoken Language of

Korean University Students

Were, Kevin T

(Kookmin University)

Were, Kevin T (2017) Student speech: Email, chat, and spoken language of

Korean university students STEM Journal, 18(2), 157-178

The results of research into the language learning potential of two forms of mediated communication (CMC)—asynchronous email and synchronous chat—have indicated that there are a number of advantages to the use of these forms of language production, both in terms of language produced and learner attitudes This research focused on a detailed analysis of the language production of three classes of Korean freshman university students to assess how their language varied across the three forms of spoken language, email and synchronous chat Class A wrote emails to each other, Class B communicated through synchronous chat, and students from Class C were recorded during small group conversations The language was then analyzed for complexity and accuracy, and compared across a range of variables The results showed that there was not a clear distinction between language produced in asynchronous email, language produced in synchronous chat, and language produced when engaging in face-to-face communication There were no clearly identifiable features to suggest they formed distinct language categories Accordingly, it is suggested that other factors, such as task type and purpose of communication, may have as much influence on the language produced as the particular form in which it occurs

computer-I INTRODUCTION

Since the early 1990’s, research into the use of the asynchronous exchange of e-mail in language learning has found that students produce more language when communicating through email compared to when they engage in face-to-face communication Beauvois (1998) concluded that CMC increased class participation, Beauvois (1995) and Gonzalez-Bueno (1998) noted that students were more willing to participate in an electronic context compared to face-to-face interaction, and Gonglewski (2001) found email lists created

opportunities for authentic communication Gonzalez-Bueno (1998) even identified the same increase in productivity when comparing email with writing in-class paper and pencil assignments, suggesting that the difference may be more than that of the distinction between the immediacy of speaking and the ability to plan in writing Research into synchronous CMC (internet relay chat) has produced similar results with some research showing that learners’ face-to-face communication improves after participation in CMC activities (e.g., Beauvois, 1995; Blake, 2000; Kern, 1995; Warschauer, 1996), indicating that language skills may be transferable from CMC to face-to-face communication Kern (2006) notes, however, that we still need to learn how to make the best uses of computers

to accomplish specific language learning goals, posing the question: What kind of language does the learner engage in during a CMC activity?

Savignon (2007) notes that we are used to making a distinction between oral language and written language, but with the development of electronic communication it is becoming more difficult to find a difference between the two, although CMC may be closer to oral discourse than to written discourse Warschauer (2000) asserts that with the advent of computer based communication human interaction now occurs through a text-based form, and the division between speech and writing has been overcome, with the interactional and reflective aspects of language merged in a single medium, i.e CMC In addition, studies conducted on the social dynamics of CMC have found that it results in communication which is more equal in participation than face-to-face discussion, with those who normally don’t contribute to discussions benefiting most from the increased

participation – those with less power and authority In Warschauer’s (2000) view CMC is

creating new discourse communities, new literacies and new identities – a different

language learning

In my own classes I introduced an email component as part of the assessment for my freshman English language conversation classes Students were required to send the instructor a series of emails throughout the semester as part of their participation assessment in the class During this process it was noticeable that students communicated far more in their emails than they did when they were required to speak during class This could be explained simply as the difference between writing and speaking As a written medium, email allows students more time to plan and process their language output than

is available when they have to communicate orally Communicative classroom environments emphasizing group-work also favor more social, outgoing students, so it could be expected that quieter, less outgoing students would feel more comfortable using

a written medium where they aren’t face to face with other interlocutors It is also possible that task type and the speaking/writing difference contributed more to the difference than any other factor

Other studies have researched the differences between one form of CMC and different

forms of language production (most often speaking), but Abrams (2003) notes that research examining the possible differences between synchronous CMC and asynchronous CMC in terms of lexical richness, density, and syntactic complexity is not yet available The research described in this paper was devised in order to provide a contribution to fill this gap, while also comparing the CMC language varieties of Korean freshman university students with their spoken language output

II LITERATURE REVIEW

1 Writing and Speech

EFL conversation classes typically focus on communication and teachers strive to maintain a good percentage of class time where students are listening to or speaking English While this oral practice is necessary, the development of communicative ability

is achieved through more than simple listening/speaking time-on-task, however Savignon (2007), for instance, writes that, “the principles of communicative language teaching (CLT) apply equally to reading and writing activities that involve readers and writers engaged in the interpretation, expression, and negotiation of meaning” (p 213) In assessing the difference between speaking and writing, Biber (1988) studied a wide range of linguistic features taken from diverse text types, and concluded that the range of linguistic variation across spoken/written texts could not be reduced to a single factor, and there were “few,

if any, absolute differences exist between speech and writing” (p 385) Halliday (1989) showed how the process of speaking was a different representation of language than the product of writing, while also noting that computer mediated communication (CMC) has further blurred the distinction between spoken language and written language

Payne and Whitney (2002) write that the only cognitive difference between spoken language and CMC is step 3 of Levelt’s articulator/speech comprehension system (Levelt, 1989) In this model of language production, utterances are conceptualized as pre-verbal thought (step 1) Then a preverbal message (communicative intention) enters the formulator for lexical access and grammatical and phonological encoding (step 2) After this, either speech-motor functions are utilized (step 3) to produce the utterance, or it is sent back through the speech comprehension system as sub-vocalized internal speech to check accuracy or comprehension Based on this model, it is argued that speaking and chatting are almost identical psycho- linguistically, with their only major difference being the involvement of the articulator (the speech-motor system, step 3)

Shekary and Tahririan (2006) also note that in CMC interaction learners need not be concerned with such issues as pronunciation, hesitations, status, gender, race, and so on

In this view, language is a purely cognitive process and language learning is akin to structuring language competence with performance merely its externalization However,

we still need to learn and develop recognizable pronunciation and intonation to be understood when speaking, develop listening ability, and confront those socio-psychological factors that play a large part in face-to-face interaction in order to function adequately when speaking in an L2 If, as Smith (2003) has argued, negotiation in CMC requires a new type of interaction, it may only be an intermediate model that has to be built upon by developing those skills necessary for oral interaction

Ko (1996) found three distinct groups of occurrence when comparing linguistic features relating to interactivity and informativity in spoken, written and synchronous CMC language use, concluding that CMC output was more similar to spoken language overall

as it was “interpersonally involved, syntactically fragmented, with a low degree of information focus and elaborateness” (p 35) These similarities of synchronous CMC interaction to spoken language as well as its benefits for second language learning have been elaborated by other researchers; for instance, Blake (2000), who asserts that CMC interaction produces similar language learning benefits to oral interaction, particularly in relation to collaborative tasks Chun (1994), Kern (1995), and Kitade (2000) all point out that CMC resembles oral communication although being written

2 Uptake and Language Transfer

Research results often assert that learner use of CMC satisfies the interactional conditions for optimal language learning, providing opportunities for learners to interact and negotiate meaning with an authentic audience, and allowing involvement in authentic tasks in a learner-centered atmosphere with ideal stress/anxiety level (Egbert & Jessup, 1996) At times it appears as if the research data only tenuously fits the theoretical construct however Hamzah’s (2004) examples of focus-on-form instances more often seem to be negotiations for clarifying meaning instead Smith (2003) presents data where

an interlocutor says ‘OK’ at the end of an interaction routine which he interprets to indicate understanding of the meaning of what was said This could be interpreted in other ways though—for instance, a desire to move on and lack of interest in negotiating any further Ellis and Barkhuizen (2005) cite the research of Hawkins (1985) who showed how learners often fake comprehension Even confirmation of understanding doesn’t imply uptake will become procedural knowledge Shekary and Tahririan (2006) point out in this regard that

in an interaction routine it is important that the final reply expresses the correct structure for uptake to occur Smith (2005) found though that, even if uptake occurs, there is a lack

of positive effect of learner uptake in a SCMC environment: “uptake had no effect on whether target items were acquired or not” (p 51)

The same tendency to fit data to the construct can be found in Kitade’s (2000) study where it is noted that feedback indicates students think their Japanese level has improved through chat (IC interaction) leading to the conclusion that the learners language improved through the collaborative meaning-making activity The following comment by the same student remains unacknowledged, however: “It would have improved even more if someone had observed our interaction and provided guidance for my Japanese” (p 160)

In this case at least it appears that the interaction alone is not enough and indeed there are often social constraints on the amount of negotiation learners will undertake (Ellis & Barkhuizen, 2005)

While the quantification of interactional processes and language features provides a model of the nature and form of language use in CMC, and it is asserted that CMC competence can be transferred to spoken discourse, there is little evidence for this In comparing the effects of synchronous CMC and asynchronous CMC on oral output, Abrams (2003) found an increase in quantity of language in the SCMC group but no significant difference in lexical density, diversity, or syntactic complexity amongst the three This is not enough to show transfer of competence and in fact her results support the view that transfer does not occur, which she explicitly states in relation to asynchronous CMC while confirming the obvious point that group discussion benefits oral interaction Liu (2011) similarly notes that CMC could help to prepare learners to participate in face-to-face communication, but it could delay language learning for intermediate and advanced learners if they become too accustomezd to untimed online chatting

3 Language Mode and Task Type

In contrast to the view that CMC represents a new approach to language learning,

researchers such as Salaberry (2000) note only that, “CMC may constitute a new

communication environment capable of creating new conditions for language interaction”

(p 22) This note of restraint (‘may’) tempers the enthusiastic embrace of CMC as a

pedagogical tool found in other studies to a consideration of exactly what pedagogical benefits may be available from incorporating CMC into language learning In noting that the use of technological resources should serve the pedagogical design of learning activities and that design must incorporate the constraints of the medium, he gives the example of the reduced means of expression in email which may force learners to focus more on morphological features of L2 useful for development of lexicon, morphology, and syntax There are different dynamics of interaction in online environments compared

to face-to-face communication, and Kern (2000) asserts that, as a result, teachers need to develop new tasks, find new ways to guide and monitor interaction and to evaluate

performance, but it is still not clear how to transfer language abilities across the different modalities

Halliday’s (1989) dictum that in “making language work for us in ways it never had to before, it will have to become a different language in order to cope” (p 82) has some support through the research into use of CMC, but the proclaimed benefits for language learning may be premature In some cases the results could be as much a function of the type of task as the mode in which it is performed, a conclusion reached by Bygate (1999), Crookes (1990) and others Yanguas (2010) for instance, found similarities in language in task-based interaction across different modes, determining that task nature may have been more significant than language mode in the type and focus of learner negotiations Finally,

in a meta-analysis on the relative effectiveness of interaction in CMC and face-to-face contexts using journal articles and dissertations published between 1990 and 2012, Ziegler (2013) found no significant differences between the two modes, suggesting that mode of communication has no significant impact on L2 learning outcomes and language development

III RESEARCH METHODOLOGY

This study was designed to assess the comparative English performance of groups of Korean freshman students at Kookmin University in three different language modes: small group face-to-face discussion, paired interviews, paired email interaction, and paired internet chat (IRC) It is a descriptive research project, prepared with the objective of comparing how the different production modes affect language output and, in particular, whether the CMC results conform to data and conclusions from other studies Previous research (for example, Kern, 1995; Ko, 1996) has generally found a continuum of more complex and accurate language production in written modes to less complexity and accuracy in spoken language Part of the objective in this research was to see if this applies

to the language output of this group of students, and if their language output, based on measures of complexity and accuracy, could be categorized as belonging to three distinct types

1 Research Hypotheses

The research hypotheses are:

1) There will be more accurate language use in CMC compared to face-to-face communication

2) There will be more complex language use in CMC compared to face-to-face

The fact that students from the researcher’s classes were used as subjects for this study presented a number of difficulties The first was the ethical problem of using one’s own students for research The second was the requirement for all students to follow the same syllabus This made it problematic to employ an experimental research project that necessarily would require different treatments Accordingly, it was decided to maintain the same main syllabus content as input for all three groups and to give the same subject matter as additional assignment work for the groups, but to ask each group to present it in

a different language mode The classes were consequently designated according to the following schema: Class A: email; Class B: internet chat; Class C: small group (3 - 4 students) oral discussion

3 Data Collection

Classes all used the text English Firsthand 2 (Helgesen, Brown, & Wiltshier, 2010) as

the primary study material for the semester and class time centered on listening and pair

or small group activities The data for analysis came from homework assignments based

on topic themes in the text related to class content

Students were required respond to the topics according to their group designation 1) Class A: Email

Students were required to write a minimum of 3 emails each between pairs of students

on the topic Each email had to have a minimum of 6 sentences In practice this meant that the amount of output reflected each student’s motivation or interest, from those who wrote

the bare minimum of six single clause sentences with five to seven words in each (e.g “I

feel sympathy for your problem I do a part-time jobe in weekends But I bought too many

things So I can’t save money till now I hope you get a side job soon And let’s save money toghether See you.”) to others with as many as twelve sentences of up to fifteen words

with coordination or subordination

2) Class B: Internet Chat

Students were given the same instructions as the email group and asked to write a minimum of at least 10 lines of output per student In all cases this was exceeded with the number of turns ranging from 15 to 36

3) Class C: Small Group (3-4 students) Oral Discussion

Students were placed in groups of 3 or 4 and required to meet with the instructor weekly for 6 weeks In preparation for the meetings each student was asked to prepare a short one

to two minute response to the topic After each short presentation was given the group was asked to comment or ask questions for a total session time of 10 to 15 minutes All sessions were recorded using a Sony portable cassette recorder (TCM-400DV) and recordings were subsequently transcribed for analysis

Measures of Language Output

Number of AS-Units Defined by Foster et al as … a single speaker’s utterance consisting

of an independent clause or sub-clauses Examples of independent

clauses from Foster et al (with / marking the clause boundaries): That’s right/ Turn left/ You go to the main street of Twickenham Examples

of independent sub-clauses: how long you stay there/ three months/

Oh, poor woman (pp 365-6)

Total no of words The total output for each student during each session calculated as a

simple count of tokens

TABLE 2

Measures of Language Complexity

1 Mean turn length The total number of words (tokens) divided by the number of turns

for the speaker/interlocutor

(analyzed as 1 AS-unit with 3 subordinate clauses marked with /)

2) So I’m ah I’m won a prize at the running contest / but nowadays I don’t have time for exercising, sports / so I can’t very well in sports,// but my parents manage a bowling center /so when

I was young I always bowling in my free time, /so now I can well,

uh I’m good at bowling

(analyzed as 2 AS-units divided at //, the first with 2 subordinate clauses, and the second with 3 subordinate clauses.)

3 Number of different

verb forms

Verb forms identified were tense (present, past, future), modality (should, have to, must.), aspect (simple, continuous, perfect)

4 Type-token ratio The total number of different words used (types) was divided by

the total number of tokens Tokens equaled the total number of words from each particular student It is important to use text segments of equal length as type/token measures decrease as text length increases (Ellis & Barkhuizen, 2005) and accordingly, this measure was followed with segments of 50 words each

TABLE 3

Measures of Language Accuracy

1 Error-free clauses

(errors per AS-unit)1

Errors per AS-unit (Bygate, 1999) Total number of error free clauses divided by total number of independent clauses, sub-clausal units and subordinate clauses

2 Target-like use of verb

1 Lexical errors are comprised of: (1) errors of omission, where a linguistic unit or units would have to be supplied in order to eradicate the error; (2) errors of over-suppliance, where a linguistic unit or units would have to be deleted to eradicate the error; (3) errors of permutation, where the order of linguistic units would have to be changed to eradicate the error; and (4) errors of substitution (a combination of 1 and 2), where a linguistic unit or units would have to be deleted and another or others supplied to eradicate the error (Lennon, 1991) These include missing articles, copula, modal or other vocabulary word, prepositions; incorrect verb tense or aspect; incorrect word order; added words that do not belong

Chat (averages for 6 students)

Speaking (averages for 10 students)

The higher number of AS units for both email and chat reflects the fact that in both CMC modes the AS units have less total words than in the spoken data What is noticeable

is how short the conversational turns are in the chat transcripts Of the three transcripts (each between 2 students) there is only one where sentences are extended into longer coordinated or subordinated structures Overwhelmingly, turns are structurally simple, containing one idea unit with no elaboration

Examples from the chat data:

Example 1

A: How long have you been diet?

B: Ummm … about one month

A: We have to get some exercise

B: Aha…

A: …we went there …

Generally though, the spoken exchanges tend towards being more extended coordinated

or subordinated speech, such as in these examples:

2 Results for Hypothesis 1

There will be more accurate language use in CMC compared to face-to-face communication

TABLE 5

Results for Language Accuracy (Averages of Raw Scores)

Error-free clauses (errors per AS-unit) 0.38 0.54 0.37

Target-like use of vocabulary (% of clauses without lexical

errors – total lexical errors/total no of AS-units)

0.73 0.46 0.75

As a proportion of total clauses, the higher percentage of error-free clauses in the chat data supports the view that sentence or text length may be a more significant indicator of accuracy than the language mode In accord with the expected order of accuracy, spoken language has the lowest target-like use of verb tenses compared to the data from both CMC modes Examples from the spoken data show the lack of consistency in the use of past tense verbs: