Artificial Intelligence in Education 

About: Artificial Intelligence in Education is an academic conference. The conference publishes majorly in the area(s): Intelligent tutoring system & Learning environment. Over the lifetime, 2218 publications have been published by the conference receiving 42444 citations.

Intelligent Tutoring Goes To School in the Big City

Abstract: This paper reports on a large-scale experiment introducing and evaluating intelligent tutoring in an urban High School setting. Critical to the success of this project has been a client-centered design approach that has matched our client's expertise in curricular objectives and classroom teaching with our expertise in artificial inte lligence and cognitive psychology. The Pittsburgh Urban Mathematics Project (PUMP) has produced an algebra curriculum that is centrally focused on mathematical analysis of real world situations and the use of computational tools. We have built an intelligent tutor, called PAT, that su pports this curriculum and has been made a regular part of 9th grade Algebra in 3 Pittsburgh schools. In the 1993-94 school year, we evaluated the effect of the PUMP curriculum and PAT tutor use. On average the 470 students in experimental classes outperformed students in comparison classes by 15% on standardized tests and 100% on tests targeting the PUMP objectives. This study provides further evidence that laboratory tutoring systems can be scaled up and made to work, both technically and pedagogically, in real and unforgiving settings like urban high schools.

Methodological Issues in the Content Analysis of Computer Conference Transcripts

Abstract: This paper discusses the potential and the methodological challenges of analyzing computer conference transcripts using quantitative content analysis. The paper is divided into six sections, which discuss: criteria for content analysis, research designs, types of content, units of analysis, ethical issues, and software to aid analysis. The discussion is supported with a survey of 19 commonly referenced studies published during the last decade. The paper is designed to assist researchers in using content analysis to further the understanding of teaching and learning using computer conferencing. SCENARIO Professor Jones has just completed her first university course delivered entirely on- line. The 13-week semester class has left Jones in a state of mild exhaustion. However, the course is finished, the marks have been assigned, and now, thinks Jones, time for some reflection, analysis and perhaps a publishable paper. Jones smiles, confident in the knowledge that the complete transcript of messages exchanged during the course has been captured in machine-readable format. She feels that this accessible data will confirm her hypothesis that students in the on-line course had engaged in much higher levels of discourse and discussion than any she had experienced in ten years of face-to-face instruction. Further, she is interested in investigating the impact of the collaborative learning activity that she instituted in the middle of the course. Jones is quickly disappointed. The 13-week discussion generated 950 messages. Merely reading them takes her four days. Attempts at cutting and pasting illustrations of higher level thinking into a word processor, have resulted in a hodge-podge of decontextualized quotations, each disparate enough to have Professor Jones questioning her own definitions of higher order thinking. Realizing that the analysis is going nowhere, Professor Jones goes back to the literature and finds a set of criteria laid down by an expert in the field that define the broad areas of thinking skills she sees being developed in the transcripts. Heartened, but now running out of time Professor Jones hires two graduate students to review the messages and identify the incidents of higher order thinking as defined by the expert. Two weeks later, the students report their results: not only have they failed to agree on 70% of the categorizations, but one student has identified 2032 incidents in the transcript, while the other has found only 635 incidents. To add to her misery, Professor Jones also learns that her University's ethics committee, concerned with the large increase in use of computer conferencing for credit courses, has ruled that without informed consent from students, her analysis does not conform with the guidelines of the university's ethical research policy. Feeling overwhelmed and depressed, Professor Jones returns to the educational literature once again, only to find that most of the methodological issues she has been dealing with have not been addressed by major researchers in the field. She also finds that

The Behavior of Tutoring Systems

Abstract: Tutoring systems are described as having two loops. The outer loop executes once for each task, where a task usually consists of solving a complex, multi-step problem. The inner loop executes once for each step taken by the student in the solution of a task. The inner loop can give feedback and hints on each step. The inner loop can also assess the student's evolving competence and update a student model, which is used by the outer loop to select a next task that is appropriate for the student. For those who know little about tutoring systems, this description is meant as a demystifying introduction. For tutoring system experts, this description illustrates that although tutoring systems differ widely in their task domains, user interfaces, software structures, knowledge bases, etc., their behaviors are in fact quite similar.

Authoring Intelligent Tutoring Systems: An analysis of the state of the art

Abstract: This paper consists of an in-depth summary and analysis of the research and development state of the art for intelligent tutoring system (ITS) authoring systems. A seven-part categorization of two dozen authoring systems is given, followed by a characterization of the authoring tools and the types of ITSs that are built for each category. An overview of the knowledge acquisition and authoring techniques used in these systems is given. A characterization of the design tradeoffs involved in building an ITS authoring system is given. Next the pragmatic questions of real use, productivity findings, and evaluation are discussed. Finally, I summarize the major unknowns and bottlenecks to having widespread use of ITS authoring tools. (http://aied.inf.ed.ac.uk/members99/archive/vol_10/murray/full.html)

Adaptive and Intelligent Web-based Educational Systems

Abstract: Currently, Web-based educational systems form one of the fastest growing areas in educational technology research and development. Benefits of Web-based education are independence of teaching and learning with respect to time and space. Courseware installed and maintained in one place may be used by a huge number of users all over the world. A challenging research goal is the development of adaptive and intelligent Web-based educational systems (W-AIES) that offer some amount of adaptivity and intelligence.