Antonija Mitrovic

A comparative analysis of cognitive tutoring and constraint-based modeling

Numerous approaches to student modeling have been proposed since the inception of the field more than three decades ago. What the field is lacking completely is comparative analyses of different student modeling approaches. In this paper we compare Cognitive Tutoring to Constraint-Based Modeling (CBM). We present our experiences in implementing a database design tutor using both methodologies and highlight their strengths and weaknesses. We compare their characteristics and argue the differences are often more apparent than real: for specific domains one approach may be favoured over the other, making them viable complementary methods for supporting learning.

Constraint-Based Tutors: A Success Story

Student modeling (SM) is recognized as one of the central problems in the area of Intelligent Tutoring Systems. Numerous SM approaches have been proposed and used with more or less success. Constraint-based modeling is a new approach, which has been used successfully in three tutors developed in our group. The approach is extremely efficient, and it overcomes many problems that other student modelling approaches suffer from. We present the advantages of CBM over other similar approaches, describe three constraint-based tutors and present our future research plans.

Supporting collaborative learning and problem-solving in a constraint-based CSCL environment for UML class diagrams

We present COLLECT-UML, a constraint-based intelligent tutoring system (ITS) that teaches object-oriented analysis and design using Unified Modelling Language (UML). UML is easily the most popular object-oriented modelling technology in current practice. While teaching how to design UML class diagrams, COLLECT-UML also provides feedback on collaboration. Being one of constraint-based tutors, COLLECT-UML represents the domain knowledge as a set of constraints. However, it is the first system to also represent a higher-level skill such as collaboration using the same formalism. We started by developing a single-user ITS that supported students in learning UML class diagrams. The system was evaluated in a real classroom, and the results showed that students’ performance increased significantly. In this paper, we present our experiences in extending the system to provide support for collaboration as well as domain-level support. We describe the architecture, interface and support for collaboration in the new, multi-user system. The effectiveness of the system has been evaluated in two studies. In addition to improved problem-solving skills, the participants both acquired declarative knowledge about effective collaboration and did collaborate more effectively. The participants have enjoyed working with the system and found it a valuable asset to their learning.

Intelligent Tutors for All: The Constraint-Based Approach

This paper presents a new type of intelligent tutoring systems, called constraint-based tutors. The system have been thoroughly evaluated and proven to achieve significant learning gains.

KERMIT: A Constraint-Based Tutor for Database Modeling

KERMIT is an intelligent tutoring system that teaches conceptual database design using the Entity-Relationship data model. Database design is an open-ended task: although there is an outcome defined in abstract terms, there is no procedure to use to find that outcome. So far, constraint based modelling has been used in a tutor that teaches a database language (SQL-Tutor) and a system that teaches punctuation and capitalisation rules (CAPIT). Both systems have proved to be extremely effective in evaluations performed in real classrooms. In this paper, we present experiences in using CBM in an open-ended domain. We describe systems architecture and functionality. KERMIT has also been evaluated in the context of genuine teaching activities. We present the results of an evaluation study with students taking a database course, which show that KERMIT is an effective system. The students enjoyed the systems adaptability and found it a valuable asset to their learning.

Experiences in Implementing Constraint-Based Modeling in SQL-Tutor

The problem with most student modeling approaches is their insistence on complete and cognitively valid models of students knowledge. Ohlsson [10] proposes Constraint-Based Modeling (CBM) as a way to overcome intractability of student modeling, by generating models that are precise enough to guide instruction, and are computationally tractable at the same time. The paper presents our experiences in building SQL-Tutor, an ITS built upon CBM. CBM is extremely computationally efficient. State constraints, which form the basis of CBM, are very expressive; we have encountered no situations where constraints were unable to diagnose student answers. The time needed to acquire, implement and test a constraint is less than times reported for the acquisition of production rules. The initial evaluation of SQL-Tutor proved the validity of design and appropriateness of CBM.

Fifteen years of constraint-based tutors: what we have achieved and where we are going

Fifteen years ago, research started on SQL-Tutor, the first constraint-based tutor. The initial efforts were focused on evaluating Constraint-Based Modeling (CBM), its effectiveness and applicability to various instructional domains. Since then, we extended CBM in a number of ways, and developed many constraint-based tutors. Our tutors teach both well- and ill-defined domains and tasks, and deal with domain- and meta-level skills. We have supported mainly individual learning, but also the acquisition of collaborative skills. Authoring support for constraint-based tutors is now available, as well as mature, well-tested deployment environments. Our current research focuses on building affect-sensitive and motivational tutors. Over the period of fifteen years, CBM has progressed from a theoretical idea to a mature, reliable and effective methodology for developing effective tutors.

Supporting Learning by Opening the Student Model

Intelligent tutoring systems (ITSs) provide individualised instruction by maintaining models of their students. Traditionally, these models have been hidden from the student. However, recent work in the area has suggested educational benefits in exposing the student model. This approach, known as open student modelling, allows the student to inspect their model thereby facilitating reflection, which is known to enhance the learning process. To date, few evaluations have been conducted to determine the effects that open student models have on learning. This is the focus of our work. In particular, we are interested in whether even a simple open model can have a positive effect on learning. We have exposed the student model in e-KERMIT, and performed an evaluation study. Subjective results from the study are encouraging, although a more extensive study is needed to draw reliable conclusions.

Learning SQL with a computerized tutor

SQL, the dominant database language, is a simple and highly structured language; yet, students have many difficulties learning it. This paper presents SQL-Tutor, an Intelligent Teaching System designed as a guided discovery learning environment, which helps students in overcoming these difficulties. We present design issues and the current state in the implementation of the system, with special focus on individualization of instruction towards a particular student.

NORMIT: a Web-enabled tutor for database normalization

The paper describes the design and development of NORMIT, an intelligent tutoring system (ITS) that teaches database normalization to university students. NORMIT is a Web-enabled system, and we discuss its architecture and techniques used to deal with multiple students. We also discuss constraint-based modeling (CBM), the underlying student and domain modelling approach. NORMIT is the first in the series of constraint-based tutors developed at ICTG that teaches a procedural task, and we comment on the suitability of CBM for such tasks. We also discuss the plans for the evaluation of the system and future work.