Language Learning & Technology
http://llt.msu.edu/vol10num3/emerging/
September 2006, Volume 10, Number 3
pp. 8-14
Copyright © 2006, ISSN 1094-3501 8
EMERGING TECHNOLOGIES
Bots as Language Learning Tools
Luke Fryer
Kyushu Sangyo University
Rollo Carpenter
jabberwacky.com
ABSTRACT
Foreign Language Learning (FLL) students commonly have few opportunities to use their target
language. Teachers in FLL situations do their best to create opportunities during classes through
pair or group work, but a variety of factors ranging from a lack of time to shyness or limited
opportunity for quality feedback hamper this. This paper discusses online chatbots' potential role
in fulfilling this need. Chatbots could provide a means of language practice for students anytime
and virtually anywhere.
211 students used two well-known bots in class and their feedback was recorded with a brief
written survey. Most students enjoyed using the chatbots. They also generally felt more
comfortable conversing with the bots than a student partner or teacher. This is a budding
technology that has up to now been designed primarily for native speakers of English. In their
present state chatbots are generally only useful for advanced and/or very keen language students.
However, means exist now for language teachers to get involved and bring this technology into
the FLL classroom as a permanent tool for language practice.
CHATBOTS TODAY
Learning a language is not easy. Even under the best conditions students face cultural differences,
pronunciation problems, ebbing motivation, a lack of effective feedback, the need to learn specialized
language, and many other obstacles during their studies. Students in foreign language learning situations
commonly face all of these general challenges while having little or no opportunity to use their language
of study beyond the classroom. Students learning a language at the post-secondary level have a few
means of practice, such as language lab work, where students classically listen to a recording then repeat
and/or write in a workbook. More recently, students might interact with some language software during
laboratory periods. During class, students may or may not practice with other students and only in the
smallest classes do students get a chance to practice one-on-one with their teacher. The practice students
might obtain in class is often not very interactive and potentially plagued by lack of confidence, shyness,
and unchecked mistakes in grammar and pronunciation (students in pairs or group practice).
Technology is opening up many new possibilities for language learning, and the internet has enormous
potential. As Benson (2001) describes it, “…the internet is also so strongly supportive of two basic
situational conditions for self-directed learning: learners can study whenever they want using a potentially
unlimited range of authentic materials” (p. 139).
One area the internet has opened up is the use of chatterbots for language practice. “A chatterbot is a
computer program designed to simulate an intelligent conversation with one or more human users via
auditory or textual methods.” (Wikipedia, Chatterbot, 2006). A bot is “a software program that imitates
the behavior of a human, as by querying search engines or participating in chatroom or IRC discussions”
(The American Heritage® Dictionary, 2000, para. 1). It is important here to point out that the above
reference to “conversation” does not mean speech. All references in this paper to ‘talking to a bot’
concern typed, textual input.
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Before discussing present day bots it is critical to cover their rich history. When did the idea of artificial
intelligence (AI) come about? Artificial intelligence predates computers; in fact it can be traced back to
Greek mythology (Buchanan, 2002, para.1). While the idea of AI is very old, it has only been since World
War II that taking steps towards making AI a physical reality has been a possibility (Buchanan, 2002,
para.2). Although there have been a great number of important contributors to the field, for the purposes
of this column we will turn directly to Alan M. Turing and his paper, “Computer Machinery and
Intelligence”. In this work Turing asks the question “Can machines think?” (Turing, 1950).
He very quickly comes to the conclusion that the words “machine” and “think” are too difficult to define.
For this reason he decides to answer the question by asking a different, but related question. This question
is now known as the famous “imitation game”. In its final version it has a person X alone in a cubicle
with a typing input device connected to both a computer A and another human being B. X, conversing
with A and B through this typing device, must determine which is the computer. Both A and B can use
every device at their disposal to convince X that they are a human being. Turing proposed, that
circumstances being the same, that if the judge was as likely to mistake a woman for a man as a computer
for a man, the computer should be considered a reasonable facsimile of a human being. If the machine is
indistinguishable from a human being, under the above conditions and to the defined degree, then it must
possess intelligence (Turing, 1950).
Chatbots began with the program ELIZA written by Joseph Weizenbaum in the early 1960’s. ELIZA was
a computer program designed to interact with someone typing in English. The software gave the
appearance of understanding and authentic interaction, but relied on keywords and phrases to which it had
programmed responses. The software could not really understand the conversation taking place but could
appear very human-like. Its communication was based on a kind of 1960’s psychoanalysis called
“Rogerian analysis”. The program simply asked questions based on what the person typed in
(Weizenbaum, 1966). In the forty years that followed, computing power rose in step with Moore's Second
Law of Computing Power and a variety of new computer languages were written. Both of these factors
strengthened the generations of chatbots created since the 60s. The conception of the internet in the 60s
and its exponential growth, beginning in the late 80s and continuing to this day, encouraged the creation
of many more chatbots and made it possible for anyone to talk to them online.
There are 750 million EFL speakers in the world (Graddol, 2000), many of whom live in countries with
relatively few native speakers and have little opportunity to practice English. A chatterbot’s purpose, as
previously stated, is to carry on a conversation with a human being. This makes chatterbots a potentially
valuable resource for EFL learners. Their value as learning tools is limited, however, by their still
growing language abilities and design. In their present state they are most useful to higher level students.
This is because most of them were designed to interact with and entertain native speakers. They are
generally not designed to interact in a human-like fashion. For example, many, if asked “Do you have a
family?” might respond in a fashion similar to ALICE’s reply “I was created by Dr. Richard S. Wallace.”
(Alice, July 31, 2006). This, though factual, is not a human-like response.
Although this kind of conversation may be a positive challenge for some accomplished students, it is not
good for students who have yet to master the basics. In addition, chatbots are generally incapable of
interpreting spelling and grammar mistakes or are poor at it. Therefore they do not always meet beginner
students’ needs. Yet, looking at the progress chatbots have made, especially in the last ten years, their
potential value is immeasurable. One of their strong points is their convenience, being readily available to
students with computer access, at home or at school. They are ready to chat when and wherever students
are. They are generally free or cheap via subscription.
Chatbots usefulness goes far beyond their price and convenience. Six ways in which they do this are: (1)
Students tend to feel more relaxed talking to a computer them to a person. In 2004 85% of 211 first and
second year, mixed major university students, when asked whether they felt more comfortable talking to a
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human or computer on a questionnaire taken after using ALICE for 20 minutes during class, chose the
chatbot. (2) The chatbots are willing to repeat the same material with students endlessly; they do not get
bored or lose their patience. (3) Many bots provide both text and synthesized speech, allowing students to
practice both listening and reading skills. (4) Bots are new and interesting to students. For example, 74%
of the 211 students in the same group, when asked to write about their 20 minute experience using
Jabberwacky, defined the bot as funny or entertaining. These kinds of positive communicative
experiences with chatbots could create new or renewed interest in language learning and improve
students’ motivation. Once one bot becomes old and familiar it could be replaced with a new bot, a new
personality, thus ensuring novelty. A bot like Jabberwacky, on the other hand, is one of a new breed of
bots that themselves learn and grow as they interact, ensuring novelty in another way.
(5) Students have an opportunity to use a variety of language structures and vocabulary that they
ordinarily would not have a chance to use. Examples of this language are slang and taboo words or
phrases. This kind of language is important for students to know and understand, but are rarely taught and
even more difficult to practice, even in ESL situations where there are plenty of native speakers to
practice with. (6) Chatbots could potentially provide quick and effective feedback for students’ spelling
and grammar. Some bots are designed to overlook spelling and grammar mistakes, some are designed to
correct them, and others can only respond to correct spelling and grammar (although admittedly they are
not yet skilled at the first two).
In 1991 Dr. Hugh Loebner began what is now an annual competition offering a prize of $100,000 to any
AI that could pass the Turing Test. Though an AI has not yet won the prize, it has focused the field to
some degree and as a result of the competition the range of chatbots has grown both in quality and in
number.
The winner of the latest Loebner Prize (2005), Jabberwacky, takes a notably different approach to other
chatbots. It learns from every interaction it has with its visitors. Where ALICE has been programmed
with 45,000 conversational patterns, Jabberwacky has so far learnt more than 8 million on its own. It is
not just the huge variety that makes it seem more lifelike, but also the fact that it will often strongly claim
to be human – naturally so, as those it has learnt from believe themselves to be human. Jabberwacky
tends to have long conversations with its users, who find it amusing and oddly ‘addictive’. Though its
responses are often unpredictable or unexpected, this will improve as it continues to learn, and the very
nature of its ability to keep people talking is potentially of significant value for language learning.
Through its observations of the patterns of conversational language, the Jabberwacky AI can learn any
language with equal ease, extending its value beyond EFL to all FLL. To varying degrees of quality it
has already learned around 30 languages, including Romanized Japanese, and increased conversation with
language teachers could massively improve its abilities. Likewise, spelling and grammatical errors are
patterns that it can be taught to respond to, simply by a process of dedicated training.
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A recent development at Jabberwacky is the opportunity for individuals or groups to start teaching ‘their
own’ bot. Each bot will continue to benefit from the huge pool of conversational data, yet will over time
come to resemble the speech patterns and personality of its teacher(s) more and more strongly. A bot can
be created that talks a specific language, starting conversations appropriately. Another could have a
strong tendency to correct common grammatical errors when observed. Equally, one can simply create a
‘persona’ that appeals to the particular target market for a FLL course. All this is achieved with zero
technical knowledge – simply by talking to the bot, correcting the bot, or talking to ‘oneself’.
Rollo Carpenter of Jabberwacky.com and Jonathan Freeman of Goldsmiths College, London have
recently proposed a “Personal” advancement of the Turing Test based around an “impersonation game” in
which the program must convince its testers that it is a person that they themselves know – an individual
human, not just any human. Instead of “Can machines think?” they ask “Can machines be?” The full
paper can be found at http://www.jabberwacky.com/s/ptt100605.pdf.
Another approach to building chatbots, frequently used on the internet is AIML (Artificial Intelligence
Markup Language), which can be found at found at Alicebot.org. This type of chatbot does not learn from
interaction itself, but is scripted by a 'botmaster' with moderate technological skills. It is best described by
its creator, Richard S. Wallace, in his own words, which can be found in Appendix B.
CHATBOTS IN USE
As the title to this article suggests, bots are a potentially valuable tools for language teachers/learners.
Though a chatbot has not yet been designed from the ground up as a language teacher or even as an
explicit language learning tool, in their present state, they do have a number of uses. Chatbots,
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communicators by nature, can help students with much needed practice, review and confidence. Six ways
in which chatbots can be potentially useful to the interested teacher are:
1) Free Speaking: In a classroom with computers at every desk, this is a great way to give the students a
chance to experiment. It is an excellent reward for those students who have completed their class
work early. Depending on the class, the second time you assign students to free speak with a chatbot
it may be helpful to give the students a topic to focus on. Assign a topic not attached to class work if
this is meant to be a break rather than an extension of class.
2) Review: This has to be the most practical use of chatbots. In FLL situations it is common for students
to spend a class covering material that they never get the opportunity to actually use. At the end of a
class the teacher might reserve 10-15 minutes for students to try out their new language skills. This
can be done with the textbook or without, depending on the teacher’s goals.
3) Self Analysis: Some chatbot WebPages provide a ‘view transcript’ function. This can be an excellent
means of having students evaluate themselves, their partners, or even the bots. Simply have the
students chat away in either of the above exercises, then view, print or email their transcripts to
themselves.
4) For the Teacher: With the subscription of a bot like Jabberwacky, a teacher can keep track of studentbot conversations and get an idea of how students are progressing, what kind of language they need
help with and perhaps most importantly, what kind of language and topics they want to learn more
about.
5) Listening: Chatbots have varying degrees of skill in turning text into audio. ALICE bot, in its 99
dollar a year version, uses Oddcast's streaming audio to good effect. Jabberwacky on the other hand,
uses a computer’s already-present text-to-speech function to produce more than adequate audio.
Simply turning this option on can make the experience more fun and interesting for beginner students
as they can read and listen at the same time. For more advanced students, however, a piece of paper
covering the screen except where he or she is typing (enter scissors and a little imagination), is a
means of forcing the student to focus in on the audio and encourage them to reply as best they can.
Though perhaps challenging and occasionally fraught with miscommunication, there is no risk to the
student’s confidence and when real communication occurs there is an invaluable sense of
accomplishment.
6) Finally, all of the above suggested uses assumed that computers were available in the classroom. In
situations where this is not the case, similar exercises can be assigned as homework. If the teacher
wishes to check and ensure the students are doing their assignments, again transcripts might be
printed and brought to class or cut, pasted, and emailed to the teacher.
FINAL REMARKS
Though chatbots at present have their uses, there is as yet no chatbot designed from the bottom up to meet
the needs of FLL students. There are a number of directions such chatbot designs could and almost
certainly will take in the years to come. It seems clear that chatbots must appear as human as possible if
they are going to truly be useful to language students. They must have families, histories, likes and
dislikes. Simply put, they must have lives of their own. The more believable they are as human beings,
the greater the quality of the potential conversation.
Chatbots for self-practice via casual conversation, independent of class, may be more useful to higher
level students. For lower-level or less eager students, bots designed for specific tasks may be better
learning tools. A chatbot could be designed to turn all conversations towards the use of the present
continuous verb tense, thus forcing the student to deal with and use this portion of grammar. Another
example might be a chatbot designed to talk about family and relationships, to coincide with a similar
topic in class. The students could be given an assignment of finding out about one or a number of bots’
families, using the language they have learned in class. The number of such potential bots is limited only
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by one’s imagination. There are countless potential topics, and there is also a whole range of student
levels, from rank beginner to near native for whom chatbots could be designed to interact.
AI technology is a budding field of applied linguistics. It is a field that desperately needs language
teachers to get involved if chatbots are to become the invaluable tool they have the potential to be.
APPENDIX A – RESOURCE LIST
For those interested in trying a few of the chatbots online now, a good place to start is with the
competitors for the “Loebner prize”. http://www.loebner.net/Prizef/loebner-prize.html lists its annual
most “human-like” chatbot. One giant list of chatbots is:
• http://directory.google.com/Top/Computers/Artificial_Intelligence/Natural_Language/Chatterbots/
Other helpful sites are:
• http://www.jabberwacky.com/yourbot
• http://www.alicebot.org
• http://www.abenteuermedien.de/jabberwock/
• http://en.wikipedia.org/wiki/turing_test
• http://cogsci.ucsd.edu/~asaygin/tt/ttest.html
• http://www.turinghub.com
For teachers and students of languages other than English there are some chatbots available. Two German
chatbot can be found at:
• http://www.yellostrom.de/
• http://www.elbot.de/
Two French chatbots can be found at:
http://francois.parmentier.free.fr/
APPENDIX B - ALICEBOT
AIML (Artificial Intelligence Markup Language) is a free, open source standard for creating chat bots like
the DAVE ESL bot available from the ALICE A.I. Foundation (www.alicebot.org). Because of its open
source approach, AIML is said by some to have captured more than 80% of the world market for chat bot
technology. The design principle of AIML is minimalism. In theory, anyone who knows enough HTML
to design a web page can learn enough AIML to begin creating a chat robot. ESL teachers themselves
are not beyond learning how to train the very bots that their students will be using in future courses.
In fact the primary skill in bot training (being a botmaster) is not technical but literary, that is, being able
to write creative, original, witty replies that keep the student engaged and interested in the bot's
conversation. The art of being a botmaster is more like being a screenwriter creating a character, than
being a computer programmer. (Wallace, personal communication, August, 2005)
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ABOUT THE AUTHORS
Luke Fryer came to Japan in 1999 on the Jet Program. He is a Lecturer at Kyushu Sangyo University.
His research interests lie in teacher expectations, learner autonomy, and anything related to how new
technologies can help learners.
Email - fryer@ip.kyusan-u.ac.jp
Rollo Carpenter is an independent researcher, creator of the learning AI technology demonstrated at
Jabberwacky.com, and winner of the 2005 Loebner Prize. Previously CTO of a Californian web
application software company, he is now based in the UK, focusing on AI for entertainment and
companionship, which demonstrate educational value.
Email- rollocarpenter@mac.com
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Benson, P. (2001). Autonomy in language learning. Malaysia: Pearson Education
Buchanan, (2002). Brief history of artificial intelligence. Retrieved on May 16, 2005, from
http://aaai.org/AITopics/bbhist.html,
Graddol, D. (2000). The future of English. The British council. Retreived on April 10, 2005, from
http://www.britishcouncil.org/learning-elt-future.pdf
Turing, A.M. (1950). Computer machinery and intelligence? Mind, 59, 433-460. Retrieved on January 30,
2005, from http://loebner.net/Prizef/TuringArticle.html
Weizebaum, J. (1966). ELIZA--A computer program for the study of natural language communication
between man and Machine [Electronic Version]. Communications of the ACM, 9. Retrieved May 10th,
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