Freudbot: An Investigation of Chatbot Technology in Distance Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A chatbot named Freudbot was constructed using the open source architecture of AIML to determine if a famous person application of chatbot technology could improve student-content interaction in distance education. Fifty-three students in psychology completed a study in which they chatted with Freudbot over the web for 10 minutes under one of two instructional sets. They then completed a questionnaire to provide information about their experience and demographic variables. The results from the questionnaire indicated a neutral evaluation of the chat experience although participants positively endorsed the expansion of chatbot technology and provided clear direction for future development and improvement. A basic analysis of the chatlogs indicated a high proportion of on-task behaviour. There was no effect of instructional set. Altogether, the findings indicate that famous person applications of chatbot technology may be promising as a teaching and learning tool in distance and online education. Chatbots are agents programmed to mimic human conversationalists. The first and still quite successful chatbot was ELIZA (Weizenbaum, 1966), a computer program designed to emulate a Rogerian therapist, a type of self-directed therapy where the patient’s discourse is redirected back to the patient by the therapist usually in the form of a question. “Its name was chosen to emphasize that it may be incrementally improved by its users, since its language abilities may be continually improved by a teacher. Like the ELIZA of Pygmalion fame, it can be made to appear even more civilized, the relation of appearance to reality, however, remaining in the domain of the playwright.” (Weizenbaum, 1966, p.2) The playwright in this case is the programmer but instead of classic Artificial Intelligence, ELIZA was programmed with rules to give the illusion of understanding. Essentially, ELIZA was programmed to recognize keywords and choose an appropriate transformation based on the immediate linguist context. Weizenbaum used the term ‘script’ to refer to the collection of keywords and associated transformation rules. Even though ELIZA is easily exposed as a fraud in the Turing sense, the popularity of the Rogerian therapist script remains high and there are a number of sites that allow you access to ELIZA. It is interesting to note that of all the scripts planned and developed by Weisenbaum, the Rogerian therapist script was the most enduring. Arguably the most successful chatbot today is ALICE (Artificial Linguistic Internet Chat Entity), 3 time winner of the Loebner Prize, the holy grail for chatbots. ALICE was written by Richard Wallace and although no chatbot has passed the Turing test in the Loebner competition, ALICE has been judged the most human-like chatbot in 2000, 2001, and 2004. Like ELIZA, ALICE has no true understanding and is programmed to recognize templates and respond with patterns according to the context. Moreover, like ELIZA, ALICE is incrementally improved with the addition of new responses. Unlike ELIZA, ALICE is programmed to talk to people on the web for as long as possible on any topic. Compared to the ELIZA’s knowledge of 200 keywords and rules, ALICE is embodied by approximately 41,000 templates and associated patterns. Perhaps the most important difference between ALICE and ELIZA is that ALICE is written in AIML (Artificial Intelligence Markup Language), an XML-based open source language with a reasonably active development community. There are also a variety of AIML parsers available written in Java, Perl, PHP, and C++ that permit interaction through a variety of interfaces, from simple web pages to Flash-based (or other) animation, instant messaging, and even voice input/output. In addition, Pandorabots, a web service that promotes and supports the use of ALICE and AIML is reporting support for over 20,000 chatbots on their site (http://www.pandorabots.com). At Pandorabots, would-be botmasters can easily create their own chatbot by modifying the personality of ALICE or by starting from scratch. An AIML chatbot is suitable for many educational applications but our interest was in the famous personality application. Specifically, we were interested in whether students would enjoy and benefit from chatting with famous historical figures in psychology. As a distance education provider, we are always looking for ways to improve the interaction between student and course content over the web. Chatting with an historical figure via the internet may be intrinsically more interesting than the same information presented in a standard third party format over the web. In terms of a theoretical rationale, there are several bases for investigating a famous personality application of chatbot technology as learning tool in distance education. Social constructionist theories of learning emphasize collaboration and conversation as a natural and effective means of knowledge construction and elaboration. The work of Graesser and colleagues on AutoTutor is based largely on these theories (see Graesser,Wiemer-Hastings, Wiemer-Hastings, Kreuz, & Tutoring Research Group 1999). A second rationale is found in the work of Cassell and colleagues on Embodied Conversational Agents (ECA). Cassell indicates that motivation for their research is based on the primacy of conversation as a natural skill learned early and effortlessly in life (Cassell, Bickmore, Campbell, Vilhjalmsson, & Yan, 2000). A conversational interface to a famous psychologist should be engaging and intuitive. A third rationale is provided through cognitive resource theory that argues linguistic rules governing conversational exchanges are automatic in nature due to frequency of use and consequently, free up additional resources to devote to encoding, understanding, and learning. Finally, according to the media equation (Reeves & Nass, 1996), people are predisposed to treat computers, television and other instances of media as people. They describe a number of experimental studies that generally show no differences in how media is ‘treated’ in comparison to people. The social rules that govern human-human interactions appear to govern human-computer interactions as well. If this is the case, then people may be predisposed to interact with a famous person application on the computer given the close fit of the application to human and conversational characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it