Designing interactive learning environments

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  • Journal of Computer Assisted Learning (1996) 12,33-46

    Designing interactive learning en vironmen ts Y. Akpinar and J. R. Hartley Computer Based Learning Unit, Leeds University

    Abstract As computers become more prominent in classroom instruction their modes of use are extending, for example as surrogate teachers in tutoring or as curriculum enrichment in simulation applications where students are more investigative in their learning methods. However, within the classroom such programs often have effects and are used in ways that were not always anticipated by their designers. This argues for computer assisted learning (CAL) environments in which the software is interactive but is able to adapt to different styles of learning and teaching. This paper argues for and describes the design principles of such environments, taking as illustration an application in the fraction domain. Following its implementation, initial evaluation data taken from school-children showed marked performance improvements, and indicated how design features of the system (FRACTIONLAB) contributed to their understanding.

    Keywmds: Computer assisted learning; Fraction domain; Interaction languages; Interactive learning environments.

    Introduction

    The capabilities of the electronic computer have stimulated the design of a variety of instructional programs. Responding to behaviourist views of a feedback-controlled shaping of learning, tutorial packages have been developed and shown performance improvements particularly in achieving competence objectives through practice (e.g. Suppes et al., 1968). However in these types of programs the initiatives given to the student are limited. The material, tasks and feedback comments are pre-stored, and the user has to operate under the control of the program, answering questions or undertaking tasks within highly directed formats. Spontaneous questions or suggestions from the student, or other requests for remedial help are not permitted unless they have been specifically anticipated by the teacher author, since the program has no conceptual knowledge of the domain but operates under pre-stored prescriptions.

    Accepted 9th May 1995

    Comes ndence: J.R. Hartle Corn uter Based Learning Unit, Lee& Kversity, Leeds, LS?9JT, I& Email: poshnaster@cbl.leeds.ac.uk

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  • 34 Y. Akpinar & J.R. Hartley

    These programs are, nevertheless, conceived as surrogate teachers able to be assimilated within the conventional organisation of the classroom. But they need careful preparation so that error and diagnostic feedback will be understood and related to the underpinning concepts of the domain. Limited resources may also encourage teachers to have pairs of students working together with the advantage of increasing peer interaction (Carney, 1986; Hawkins et al., 1982) and this can be an important influence on learning (Podmore, 1991). Hence the introduction of even such prescribed and directed programs can cause a shift towards greater learner and teacher involvement in instruction though the programs were not specifically designed to encourage this re-orientation.

    So-called artificial intelligence techniques have led to the development of tutorial programs that contain domain knowledge in a form which allows them to generate task materials and answer types of students' questions (Anderson e f al., 1985; Anderson e f al., 1986; Burton & Brown, 1982; Brown, 1985). These systems can, therefore, give greater interactive support to students but they tend to be highly specialised and have been implemented as proof-of-concept rather than as institutional packages which are used in day-today teaching. Moreover, as Newman et al. (1989) point out, such systems though sophisticated, are far from taking adequate account of the social context of learning. Although relatively few evaluation studies of these types of programs in the context of classroom learning are in evidence, a two-year qualitative study of eight classrooms by Schofield et al. (1994) with Anderson's geometry tutor (Anderson, 1986) noted that rather than replacing teachers, the program became an additional enriching resource. Moreover, while recognising the greater skills of the human teacher, students very much welcomed the program since it placed the type and amount of support more clearly under the control of students, and to which the teacher could respond. But as Schofield e f al. noted "none of these changes were envisioned by the system's developers".

    Similar comments can be made about other forms of computer assisted learning. Simulation programs are designed to encourage investigation as students form and test hypothesis about the underlying model. However this again requires careful preparation so that learners have an adequate conceptual framework on which to base and modify their hypotheses (Bork, 1987) and simulation programs are not usually designed to deliver this support. In the classroom, the programs are often used by small groups of students and there is evidence (Van Lehn, 1988) that these student interactions and explanations result in clear learning benefits. However the Conceptual Change in Science Project (Hartley et al., 1991) which used both simulation and qualitative modelling programs showed that unless such discourse reached the students' causal beliefs (in contrast to operational talk about the system and its displays) conceptual change could not guaranteed. A teacher is required to engineer such interchanges, but the designers had not given detailed consideration to these wider modes of use and classroom -upport, and the changing styles of teachinghearning that might ensue. To

    fair, these consequences were illuminated by evaluation studies that

  • Designing interactive learning environments 35

    focused not only on learning benefits but on the social context in which the learning took place.

    A further example is that of LOGO (Papert 1980) which provides pupils with a computer language to reveal, exploit and extend their knowledge in a principled way, for example in Turtle geometry. A computational metaphor of variables, patterns, nested procedures and recursions acts as a framework for this development which links children's direct experience (e.g. in drawing shapes) to organised procedures expressed in the LOGO language. Papert's conception was that of individual learners building up their own 'libraries' of LOGO procedures that represented their extending knowledge. However in practice, and not entirely as a result of a shortage of computing resources, LOGO is seen as a collaborative activity for small groups of children, though the language was not designed from this viewpoint.

    In summary we argue that computer assisted learning programs should be designed to take greater account of their possible and differing modes of use, and the varying requirements of direction, support and exploratory/investigatory methods that might be employed in the classroom. Hence the aim is to widen the design focus to develop what we consider to be interactive learning environments (ILEs). What is meant by the term and its functional components will be described briefly, and then illustrated by an example (FRACTIONLAB) taken from the fraction domain. Data from two initial validation studies with school children form a concluding discussion.

    Interactive Learning Environments

    ILEs should be designed to support a variety of teaching and learning styles, regulating the locus of control between student and system, and accommodating task-based methods that are feedback rich, illustrative mechanisms that support conceptual understanding, and learner-controlled investigations and problem solving. The functional components of such ILEs have been discussed in detail elsewhere (Akpinar, 1994) but in outline they consist of

    an 'object world representing the domain, together with: a student-system interaction language by which learners can operate on the object-world in ways which show the effects of their actions (thus providing immediate feedback) and which link to representations of the object world and its relations at higher levels of abstraction.

    Thus learning is envisaged not only as an improvement in performance but as a development of understanding at a more abstract and general level. Further components are:

    a Lesson Office (Draper ef al., 1991) that is needed for specifying and managing the task curriculum, and providing student records; user-system interfaces which are required for students to apply the interaction language and manipulate the object-world, and for teachers to specify and customise types of curriculum tasks for the Lesson Office.

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    A more detailed architecture of an ILE is shown in Fig. 1 and it is clear that a domain representation (i.e. the conceptual and procedural knowledge summarising the cumculum) is a crucial prerequisite for the ILE design since it determines the 'objects' (concepts or procedures) their attributes and inter-relationships and hence the operations users can perform on them. This is shown in the 'Component Specification and Interaction' box in the Environment panel which also has an interface to allow the teacher/designer to set out this analysis of the domain. The representation language (i.e. the student-system interaction language) should, as noted above, enable students to operate on the object-world and, ideally, allow them to develop their procedural or explanatory models of the 'world' at higher levels of abstraction.

    Domain Representation

    Component Specification

    3 . 1 L

    Interface iz I L

    Curriculum-Task

    %- Interface

    Task Manager

    Screen Design F

    v Interface Fig. 1. The architecture of LEs

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