Artificial Intelligence in Education H.U. Hoppe et al. (Eds.) IOS Press, 2003
A Web-Based Tutoring Tool with Mining Facilities to Improve Learning and Teaching Agathe Merceron and Kalina Yacef ESILV - Pˆole Universitaire L´eonard de Vinci, France,
[email protected] School of Information Technologies - University of Sydney, Australia,
[email protected]
Abstract. With the emergence of e-learning, flexible education, and the increasing number of students in some fields, online teaching tools are becoming more and more important. Such tutoring tools allow students to practice at their own pace, providing them with proper explanations and feedback when they make mistakes. They allow for storing complete student answers, including mistakes, in a database. It becomes possible to mine this database, extract pedagogically relevant information and provide feedback to the teacher. This paper illustrates our approach with the Logic-ITA, a teaching tool for formal proofs currently in use in the School of Information Technologies at the University of Sydney.
1 Introduction With the emergence of e-learning, flexible education, and the increasing number of students in some fields, online teaching tools are becoming more and more important. Online teaching tools provide a more or less personalised environment where learners can practice at their own pace, have access to tutorial lessons, be given explanations and feedback on their performance and so on. These benefits to the learners are extremely valuable and we assist to a ”quiet revolution taking place in the classrooms” [4]. However, less attention has been given to the reflection and monitoring that can be made to improve the teaching. Moreover, since online teaching tools are computer-based, they allow for storing complete student answers, including mistakes made while solving exercises. The fact that they are online tools means that all this information, for all students using the tool, can be stored on a common server rather than stored locally. Having electronic access to complete student answers makes it possible to extract pedagogically relevant information and provide feedback to the teacher about how a class, a group of students or an individual student is going. The Logic-ITA [1, 7] is a web-based Intelligent Teaching Assistant system that is currently used within the School of Information Technologies, University of Sydney. Its aim is to facilitate the whole teaching and learning process by helping the teacher as well as the learner [9]. It allows students to practice formal proofs in propositional logic whilst receiving feedback and also keeps the lecturer informed about the progress the class is making and problems encountered. The system embeds the Logic Tutor, a web-based intelligent tutoring system destined to the students, along with tools dedicated to the teacher for managing teaching configuration settings and material as well as for collecting and analysing data. A multimedia article on the Logic Tutor can be found at [1] and a description of the Logic-ITA at [6]. We are now extending the capabilities of the system to provide more intelligent help
201
to the teacher. In this paper we describe the impact that such a tool can have on the whole process of teaching and learning and in particular how we extract information mining the database of students answers to improve teaching. In this preliminary work, mining is limited to queries and associations of mistakes. Some researchers have explored ways to provide assistance to the teachers [8, 5, 6, 9]. However in terms of help in diagnosis and assessment of learning, analysis and synthesis of results we found very little work. [5]’s PepiDiag and PepiProfil system, like the Logic-ITA, collects data from students’ exercises, reports them to the teacher and provides tools to analyse these results. One main difference resides in the fact that it processes one student’s data at a time, whereas the Logic-ITA combines data from all students. The paper is organized as follows. Section 2 provides some background information about the Logic-ITA that is useful to understand the rest of the paper. Section 3 describes the impact of the Logic-ITA on learning. Ways to extract information from the database through SQL queries and association of mistakes are given in Section 4. The value of this information for teaching purposes is described in Section 5. Section 6 concludes the paper. 2 The Logic-ITA The purpose of the Logic-ITA is to help students to master formal proofs in propositional logic. The student’s side of the system, the Logic Tutor, proposes logic exercises to students and has the ability to apply logic rules to propositional formulas. It monitors the resolution of a particular exercise by a student, checks whether formulas entered by the student are correct, provides meaningful error messages in case they are not. If the student wants to, the Logic Tutor can retrieve an exercise that fits best his/her level and weaknesses (the student has also the choices of retrieving a specific exercise or creating his/her own). One task of the teacher’s components of the Logic-ITA is to organize all exercises done or attempted by students, intermediary results and messages in a database that can be mined to find information. Without going into too much detail here, it is useful to understand how exercises are monitored by the system. An exercise is a set of formulas from propositional logic. This set is composed of the premises plus one particular formula called the conclusion. Solving an exercise consists in deriving the conclusion from the premises, by using rules of logic in any number of steps. A step of the derivation works as follows. The student selects formulas, either premises or formulas already derived, applies a logic rule to them and obtains a new formula which is added to the set. If the student makes a mistake in a step, the Logic Tutor gives immediate feedback about the nature of the mistake and a tip to correct it. The derivation stops when either the last formula obtained by the student is equal to the conclusion, or the student gives up. As an example consider the exercise below with premises and the conclusion introduced by .
!
"
#$
Consider Figure 1. The column %&('*),+.-/'0- refers to the premises used, 1324)657'*& to the line number of the derivation, the column 8"90&:),2;< is a formula, =>2?-*@A+.B?+.CD
