Intelligent and adaptive tutoring for active learning and training environments

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  • This article was downloaded by: [University of California Davis]On: 17 November 2014, At: 22:48Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

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    Intelligent and adaptive tutoringfor active learning and trainingenvironmentsClaire Kenny a & Claus Pahl aa School of Computing, Dublin City University , IrelandPublished online: 07 May 2009.

    To cite this article: Claire Kenny & Claus Pahl (2009) Intelligent and adaptive tutoring for activelearning and training environments, Interactive Learning Environments, 17:2, 181-195, DOI:10.1080/10494820802090277

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  • Intelligent and adaptive tutoring for active learning and trainingenvironments

    Claire Kenny and Claus Pahl*

    School of Computing, Dublin City University, Ireland

    (Received 3 September 2007; final version received 13 March 2008)

    Active learning facilitated through interactive and adaptive learning environ-ments differs substantially from traditional instructor-oriented, classroom-basedteaching. We present a web-based e-learning environment that integratesknowledge learning and skills training. How these tools are used most effectivelyis still an open question. We propose knowledge-level interaction and adaptivefeedback and guidance as central features. We discuss these features and evaluatethe effectiveness of this web-based environment, focusing on different aspects oflearning behaviour and tool usage. Motivation, acceptance of the approach,learning organisation and actual tool usage are aspects of behaviour that requiredifferent evaluation techniques to be used.

    Keywords: automated tutoring; correction; personalisation; feedback; guidance;skills training; database programming

    1. Introduction

    Intelligent and adaptive computer-based tutoring has been pursued for morethan 40 years (Hartley, 1973; Patel, Scott, & Kinshuk, 2001). Teaching modesfocusing on behavioural control, discovery-type learning and teaching throughrational argument have been implemented using computer-based tutoring,simulation and teaching of problem-solving skills. Question and answer-basedconversations have always played a major role (Scott, 2001). This earlier workwas seminal and pioneering in understanding learners as being active constructorsof knowledge (Laurillard, 1993). We now have the technology to implementintelligent and adaptive systems as practical solutions (Grabinger, 1996). Werealise that skills and knowledge are best acquired within realistic contexts thatallow learners to actively participate in knowledge construction and skills training(Nardi, 1997).

    In this paper, we refer to a specific context in particular computing education. Incontexts such as computing, engineering, science or medicine, the combination ofconceptual knowledge and practical skills is often of paramount importance. Incomputing, execution models and abstract software development paradigms on theone hand, and programming on the other, are examples that illustrate this point. We

    *Corresponding author. Email: Claus.Pahl@dcu.ie

    Interactive Learning Environments

    Vol. 17, No. 2, June 2009, 181195

    ISSN 1049-4820 print/ISSN 1744-5191 online

    2009 Taylor & FrancisDOI: 10.1080/10494820802090277

    http://www.informaworld.com

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  • can often distinguish between classical conceptual knowledge-oriented learning andskills-oriented training.

    We present an interactive learning and training environment with an automated,adaptive tutoring system at the core (Kenny, 2006). This environment supports theStructured Query Language (SQL) part of a database courseware system. It aims toprovide students with an environment that integrates a range of aspects needed tobecome a knowledgeable and skilled database programmer. After being initiallyrestricted to tutoring systems, the focus of researchers has shifted towards moreflexible adaptive hypermedia systems to allow the learner a higher degree of control(De Bra, Brusilovsky, & Houben, 1999; Brusilovsky, 2000). Instructional design forthese types of active learning environments is still an area of active research and thelearner behaviour in these systems is not well understood (Murray, 1999). Our aim isto demonstrate that, to be effective, active learning using an automated tutorrequires scaffolding support in the form of immediate and meaningful high-levelfeedback and personalised guidance (Ravenscroft, Tait, & Hughes, 1998; Winnips,2001; Chou, Chan, & Lin, 2002).

    We present and evaluate an intelligent and adaptive tutoring system for databaseprogramming which supports active learning and skills-oriented training. At the coreis an analysis and correction feature that provides immediate, knowledge-levelfeedback to the student for solutions submitted to the system. The system alsoprovides student-controlled adaptive guidance across a range of problems based onan accumulative analysis of the errors a student makes. We describe the environmentand its objectives and discuss the relationship of the instructional design that theenvironment supports to theoretical principles. We address the students learningbehaviour and discuss the effectiveness of the environment with its specific activelearning and training support.

    2. Active learning and training environment, principles and objectives

    2.1. An online database programming environment

    The interactive SQL learning and training tutor is embedded into an online coursewaresystem for a second year undergraduate database course. The SQL section forms acentral component of this course, as database programming is a core learningobjective. Database programming (that is, defining, updating and querying databasetables) is a skill that requires training on the part of the student. Databaseprogramming in SQL also requires conceptual understanding of the underlying datamodel with its structures, operations, and constraints. The environment providesdifferent features for the different aspects of SQL programming:

    . Conceptual knowledge. Conceptual knowledge is presented in a virtual lecturesystem based on an audio-visual presentation.

    . Procedural knowledge. SQL and its underlying data model are about theexecution of instructions. SQL is a language that implements databasedefinition and manipulation operations. Procedural knowledge is presented inan animated tutorial system that illustrates the execution of these operations ina step-by-step fashion.

    . Programming skills. SQL programming is the core activity, supported by aninteractive tutorial that guides the student through exercises to be worked onwithin the system. SQL queries are often complex and difficult to formulate.

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  • 2.2. An interactive database programming tutor design principles

    The interactive tutorial is a focal element of this investigation; see Figure 1 for anarchitectural overview. The design of this feature is guided by objectives derivedfrom teaching and learning best practices, and research into online learning:

    . Learning-by-doing and active learning. Active learning is a successful way oflearning practical tasks (Grabinger, 1996). Students can actively create andexecute programming solutions. This form of procedural knowledge genera-tion leads to a richer and more successful learning experience. Activeconstruction of knowledge and skills results in an increased ownership bythe student in the learning process.

    . Realistic setting. We replicate the real-world situation of database program-ming by having students develop their solutions in