Designing Artefacts for Inquiry and Collaboration ...

European Educational Research Journal, Volume 3, Number 1, 2004

KEYNOTE

Designing Artefacts for Inquiry and Collaboration When the Learner Takes the Lead [1] JULES M. PIETERS University of Twente, The Netherlands

ABSTRACT The availability of user-friendly tools for designing learning environments resulted in an innovative shift of design focus. This shift has been noticed from a user-centred, although passive and reactive, design approach to a participatory, at responsibility and self-directedness directed, design approach. This latter innovative and promising approach empowers co-designers (teachers and even learners) to actively participate in designing learning environments leading to higher learning outcomes. New pedagogical perspectives and approaches in which teachers (as domain experts) and learners are assumed to cooperate on a basis of equity and mutual responsibility will be offered a practical context for the implementation in powerful learning environments. In this article the potentials of learners as designers of their own learning environments are discussed. Support tools needed to play this role appropriately are discussed as well.

In former days, practical experience as part of the curriculum was supposed to be of less value than the theoretical principles that were taught to students. Practical work was considered to be only supportive to the development of scientific knowledge. When pragmatism as a philosophical approach came into play through the work of James and Dewey, identifying truth with utility and workability, beliefs about the role of activity and experience in education changed. Education was no longer considered a process of pouring and of passive reception of knowledge but as an active process of construction. Action was the primary source for developing knowledge. The laboratory for science teaching and the workplace for industrial training became the intellectual 77

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battlegrounds for solving problems and as a consequence for constructing knowledge on scientific principles. The scientific discovery approach advocated by many educators as the basic method for active involvement in learning became a popular method for science teaching and training in industry, also known as learning by doing. Constructivism further supported the idea of an active meaning-seeking experience in a realistic environment. In this article we will focus on the learner being able to actively design by inquiry his or her media-mediated environment for discovery learning in which he or she alone or together with colleagues can learn. We will focus on the perspectives from which we will discuss the integration of knowing and designing. These perspectives will also be historically elaborated. Traditional and current models for designing aimed at knowledge development are introduced. Deviations to these models will be discussed. These deviations pertain to the role of the learner, from a passive receiver of objectivist knowledge to an active producer of meanings and interpretations. This role of an active learner can be assumed within reach for every learner. However, support is needed and therefore we will discuss the role of support in different ways, ranging from knowledge-dependent to knowledge-independent strategic support tools, from delivery by teachers to delivery by colleague learners. Therefore collaborative support will be dealt with in this respect. Perspectives Adopting a constructive view on learning means that instruction and training are considered to be instrumental to support the transformation of action and experience during task execution into knowledge. Powerful environments are to be designed to provide the learner access to that support with which encountered problems can be solved. These multimedia environments, developed by highly specialised cognitive engineers, enable the learner to selects his (or her) own trajectories through the media landscape. A constructivist approach could offer more to the learner: learner-friendly tools from which the learner not only selects his trajectory, but selects or even creates the landscape too. These provocative ideas do not match very well with current instructional design theories. A need for a new design approach in which the learner is the key player is necessary. Instructional design and development is the systematic application of principles of learning and instruction to the design, development, and implementation of instructional systems. It involves a set of processes that analyses the learning subject matter, prescribes instructional strategies, and evaluates learning outcomes. It has most often been described in terms of those processes or activities, but how do designers conceive the domain knowledge and the processes involved? Instructional design and development are considered in terms of individual conceptions at different levels of expertise of instructional designers. These levels of expertise are the net result of a process of knowledge acquisition. 78


DESIGNING ARTEFACTS FOR INQUIRY AND COLLABORATION

Despite promising developments from passive expository teaching to active discovery and its positive outcomes, questions regarding the epistemology of the knowledge conveyed and constructed, and the adequate process of designing supportive environments for discovery remain. Two perspectives are considered to be crucial in this respect. The first one is the knowledge perspective, and the second is the active and self-directed one. Through education and training, learning processes are created which support learners to optimally acquire new knowledge and exploit existing knowledge. This entails a view on instruction and learning in which the teacher or instructor are not the one presenting knowledge, but supporting knowledge acquisition and knowledge construction by the learner. At this point we adhere to the description of learning presented by Resnick (1989). She states that learning is at first a process of knowledge construction and not of knowledge absorption; secondly, learning is knowledge dependent, taking place on the basis of prior or current knowledge already acquired; thirdly, learning is exacerbated towards the social and physical situation in which knowledge has to be used. Knowledge is usually considered to be composed of experiences, skills, information, or beliefs stored in our memory. Knowledge can be classified into a number of types. According to Alexander et al (1991), domain knowledge can be classified into declarative knowledge (‘knowing that’ or ‘how-it-works’ knowledge: knowing what the definition of differential calculus is or knowing the characteristics of a ‘bad news’ conversation), procedural knowledge (‘knowing how’ or ‘how-to-do-it’ knowledge: being able to perform a differential calculus or being able to conduct a ‘bad news’ conversation) and conditional knowledge (‘knowing where and when’ or ‘how-to-decide-what-todo-and-when’ knowledge: given a problem being able to apply a differential calculus to find a solution or being able to conduct a ‘bad news’ conversation at the right time and in the right situation). Alexander et al (1991) interpret these three types of knowledge as conceptual knowledge and they distinguish this kind of knowledge from metacognitive knowledge (‘knowledge about knowledge’: being able to reflect or discuss about a conducted ‘bad news’ conversation). In cognitive research literature metacognitive knowledge is sometimes classified as being identical to conditional knowledge. Gott et al (1993), for example, also discuss strategic knowledge, by which is meant conditional knowledge as well as metacognitive knowledge. De Jong & Ferguson-Hessler (1996) further elaborated these views on knowledge by introducing situational knowledge and strategic knowledge. From the previous discussion, knowledge can not be discovered as consisting of separate parts of declarative and procedural entities and of attitudes, motives, and intentions dissociated from these entities. An integrated concept of to-be-acquired or constructed meaningful experiences is our first perspective. Gagné & Merrill (1990) have already discussed this problem. Today, a lot of discussions on competencies pertain to the integration of knowledge, skills and intentions (e.g. Stoof et al, 2002). 79


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Secondly, the systematic process of designing instruction assumes reality to be objective, causal and deterministic, and the models often have a rulebased character. Designing powerful learning environments for scientific discovery requires a notion of tasks and activities to be carried out by selfdirected learners in stead of carefully analysed goals and objectives to be achieved by passive recipients. Therefore in the context discussed above of the acquisition and exploitation of knowledge, a re-engineering of the process of designing for discovery learning is needed. The context of the powerful learning environments discussed in this article is discovery learning. Discovery learning is a highly self-directed and constructive way of learning (De Jong & Van Joolingen, 1998) with the purpose of acquiring deep, flexible and transferable knowledge. In discovery learning, learners are invited to construct their knowledge by extracting the required information from the discovery learning environment by stating hypotheses, doing experiments and drawing conclusions; in short, by acting as a scientist. Research discussed by De Jong & Van Joolingen shows that pure discovery learning is not always the best approach. Learners may encounter problems during discovery learning, such as generating the right hypotheses, interpreting data correctly, or regulating their own learning processes properly. This new way of learning calls for an active environment full of experiences that allows enough freedom for learners to discover, but which also contains sufficient structure to support learners in the actions and the discovery process when necessary. For example, teachers or instructional designers can provide learners with direct access to domain knowledge, assist hypothesis generation, give feedback on predictions, or regulate the learning process. Current instructional models for expository teaching do not emphasise this balance as one of the crucial design issues. A related issue pertains to the explicit and predetermined nature of the goals and sub-goals which learners are required to achieve in models meant for expository teaching. In contrast, when designing discovery learning environments, the designer does not always know which end goals the learner will achieve. More emphasis is put on the development of possible tasks carried out by the learner. Learners are expected to be increasingly responsible for their own knowledge construction process, and the designer does not need to specify in detail the learning path from start-state to end-state. Learners do acquire advanced knowledge in order to solve complex domain- or context-dependent problems. Advanced knowledge is required for solving problems in most professions, where cases are unique and unpredictable, so transfer skills are essential. In order to prepare learners to acquire these transfer skills, learners need learning conditions that stress the interconnections between knowledge within cases as well as different perspectives or viewpoints on those cases that reflect the perceptions of different entities. Learners need flexible representations of the knowledge domain and representations that reflect the uncertainties and inconsistencies of the real

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world. Knowledge acquisition is a staged process where individuals actively construct increasingly complex, compiled representations of their knowledge. Recently, discussions have been started about the dissociation of knowledge entities and their motives, intentions and attitudes with which these entities are associated. An integrative view would be more preferable and more in line with practice of learning. Competencies are defined in this integrative way to express the inevitable link between cognitive, affective and behavioural components of learning outcomes in the context of immediate use. More in particular, when discovery learning is involved, then tasks and activities are considered as the main events constituting a learning process and having knowledge as a relevant output. Knowledge, as we have already discussed, does not consist of symbols and images attracted from books, mathematical formulas, or philosophical systems; it requires an active disposition of the learner to interact with, to interpret, and to elaborate these symbols and images. The structure of this socially embedded knowledge must include living systems of inquiry, learning subcultures sharing similar norms and values about how to create valid social knowledge (Kolb, 1984). History of Instructional Design and Technology In the previous section characteristics of designing discovery learning environments were discussed. Also, the role of the learner as being active and self-directed, and eventually being able to design his or her own learning environment, was introduced. In this section we would like to position the learner as designer in the context of instructional design. As Martin (1984) has already pointed out, the learner, in particular the adult learner, is able to design as a designer, has the ability to create conditions to design their own learning. The same design activities are applied. Martin also stressed the abilities as these are meant in his above cited description: problem-solving skills, self-change, self-control, and decision-making. The design activities are expressed as well by Knowles, who is considered one of the founding fathers of modern adult learning theory, in his definition of self-directed learning as ‘a process in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing and implementing appropriate learning strategies and evaluating learning outcomes’ (Knowles, 1975). In this definition the design activities are clearly exemplified. To further elaborate on the potential design abilities of learners, we may use a historical sketch of instructional design and technology as a context (based on Anglin, 1995, and Richey, 1995). After the first generation of the behaviourist assembly-line linear instructional design theories and the second generation of cognitively oriented instructional systems design, a third generation emerges: learner-centred learning systems design. It is the learner that controls the learning process and the instructional designer only sets conditions for an effective learning process. 81


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Learning design and needs assessment are integrated. To fulfil learners’ needs, designers can create educational or learning landscapes in which learners can stroll along many learning tools, including questioning and assessment tools: for instance, real learning landscapes in schools, companies or community colleges (see, for examples, Treep & Pieters, 1990; Pieters & Brouwer, 1992) in which teachers in another role, as facilitator, can inform learners and give them advice; and, moreover, artificial landscapes in which learners learn in partnership with the learning technologies (see, for examples, Pea, 1993, 1999; Jonassen, 2000). Even novice learners might gain from certain computer tools that support learning processes. They might engage in cognitive activities out of their reach without the technological partnership. This kind of system lets the learner engage in intellectual activities at a level that transcends the limitations of his own cognitive system. Needs assessment is integrated in such a learning environment. From this overview of current characteristics of instructional design we may infer the essential activities learners as designers need to carry out. These activities resemble the ones described by Martin and Knowles, but one essential activity needs to be added: needs assessment. This activity, normally carried out by a professional analyser and problem-solver, can be carried by learners themselves by being able to ask the right questions. This stressed the need for a more sophisticated needs assessment and subsequent needs analysis, directed to questions like: who is asking questions, what does the question asker intend to know (what is his purpose), to whom are the questions addressed, what questions can be asked, can each question be asked, what information is expected to be received, how is the information analysed, and how much time and money is available to ask questions (Pieters, 1997). From instructional technology we may learn that not only needs assessment as a technical activity is necessary to uncover the needs for learning, but this activity should be socially embedded to uncover socially oriented knowledge needed by the learner. Instructional design approaches that offer learners a major role in the process of designing their own learning environment will leave the above mentioned questions to the learners. Changing Approaches for Designing Learning Environments The main characteristic of the approaches presented in the previous historical sketch is solving instructional problems according to a general idea of problemsolving: problem analysis, solution generation, and evaluation and implementation of the solution. This prototypic model of solving problems stemmed from the General Problem Solver by Newell & Simon (1972). What we may infer from the discussion above is that learners are expected to be able to independently initiate and carry out the major design activities to reach appropriate learning outcomes. Learners, by carrying out these activities, are solving their own learning problems. But how can this deterministic process of designing learning be compared to reality?

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The characteristics of the deterministic process of designing instruction, as discussed above, have been criticised in recent years. General problemsolving models were not fully empirically founded by research on expert– novice differences and on context-bounded transfer of training. The models also had limited prescriptive value, were closed systems and failed to integrate instructional development, which often led to passive instruction. Recent research on designing instruction by experts provides evidence that experts differ from novice designers in approaching instructional problems (Rowland, 1992; Pieters & Bergman, 1995). Experts never follow some specific predetermined model, but instead design intuitively, simultaneously considering alternative solutions, as if they develop solution schemes that can be applied in different sequences and for different purposes dependent upon the situation. Many authors contend the complexity of the design process and its iterative character (Rowland, 1992; Goel & Pirolli, 1992; Tessmer & Wedman, 1995). Schön (1987) has already introduced learners in alternative theories and approaches like the solution-driven approaches and the reflection-in-action approach. In the solution-driven approach, designers adopt a mode of problemsolving that is solution-driven. Designers think more in terms of solutions rather than in terms of problems. Their approach is not systematically based, but they immediately react to stimuli in the design environment. The reflection-in-action approach is far from systematically based, but is oriented towards knowing-in-action. Designers develop situated theories while acting in a world of practice. These situative theories are an integration of scientific principles, experience, and intuitions, closely connected to the situation of designing, and are developed through working in a very situated context. This perspective introduced by Schön is very relevant for describing the characteristics of learners as designers. Another point of discussion that is relevant to our beliefs about learners as designers is the focus on teaching and learning in instructional design. Traditionally, instructional design aimed at the identification and classification of learning goals and the design and development of a delivery system that instructs learners to achieve these goals. Most of the resulting products were ‘directive’ in nature, implying that the emphasis was on teaching and not on learning. For at least two reasons we assume that existent instructional design models should not be applied to this new and, as explained, seemingly paradoxical task. Firstly, most models of instructional design are tailored to an expository mode of teaching based on the objectivist tradition. Whereas in the expository mode of teaching the decisions on the context and structure of the information are fully in hand of somebody (or something) else than the learners, in discovery learning the learners are expected to take more initiatives. An intriguing design issue concerns the balance between allowing freedom and giving direction to the learners. Related to this is the role of goals and sub-goals, discussed above, which learners are required to achieve in models meant for expository teaching. In discovery learning the (sub-)goals are less clear beforehand. As in discovery learning, an emphasis is on learners’ 83


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increasing responsibility for their own knowledge construction process; the designer does not need the opportunity to specify in detail one path from startstate to end-state. In most existing models, on the contrary, the determination of detailed (sub-)goals is central and this influences all other activities by the designer. Giving freedom to the learner also requires goals defined as tasks to be defined by the learner. Secondly, the reason why even current instructional design models are not suitable to designing discovery learning environments, and to learners as designers, is that these models do not fit properly with the actual design process of a designer. These models pretend that when the designer easily follows the features of the model, the development of an instructional design will smoothly occur. Not only is this very doubtful, practice shows that the design of instruction is a complex problem-solving task (Rowland, 1992). Almost all models have a linear and deterministic structure, but research showed that the design process might not be linear at all. This linearity principle used in many instructional design models is called the ‘waterfall methodology’, which is characterised by a linear fashion of designing. De Hoog et al (1994) describe alternative models like a spiral model and a web-structure model often used in software engineering. Another design methodology which also has its roots in software engineering is rapid prototyping. In rapid prototyping, prototypes are created in a non-linear fashion, which are iteratively tested and which may or may not evolve into a final product (Tripp & Bichelmeyer, 1990). In conclusion, tasks derived from needs assessment and design processes that are based on expert designing or on prototyping characteristics, defined by Schön as solution-driven designing, together determine the design activities carried out by learners as designers and will result in a process that Schön called knowing-in-action (Schön, 1983). Effects of this ‘learners as designers’ approach have empirically been demonstrated by a number of studies by Kafai & Resnick (1996), under the heading of constructionism, and also rhetorically supported by Perkins (1986) and reiterated by Jonassen (1994), that the only people who significantly benefit from the design process and the use of tools were the designers, not the learners. In similar vein, one can argue that learners will benefit more from their own design activities than from those carried out by professionals or teachers as designers. Kafai & Resnick (1996) noticed that in the Game Design Project, each design had a considerable impact on the students’ learning and thinking. Integration of Knowing and Designing From Expository to Discovery: from teaching to learning Mentioned before, the main elements in traditional models refer to defining goals and objectives and designing instructional solutions that are intended to

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move learners into the direction of the goals by dissipating degrees of freedom (see Jonassen, 1991, for a discussion of objectivist and constructivist approaches in education). Whereas in the expository mode of teaching the decisions on the context and structure of the instruction presented are almost fully determined by someone or something external to the learner, in discovery learning learners are invited to take initiative and to independently carry out tasks. The emphasis in education and training has moved from teaching and formal instruction to learning. Activities that are or have to be carried out by the learner are the main focus of those who are designing learning environments. The learning activities are packed in tasks learners have to carry out. In well-known constructivist learning environments like the cognitive apprenticeship environments (Brown et al, 1989; Collins et al, 1989), the anchored instruction environments like Jasper Woodbury Adventures (Cognition and Technology Group at Vanderbilt, 1997), the CISLE environments (Scardamalia & Bereiter, 1996) or environments aimed at cognitive flexibility (Spiro & Jengh, 1990), but also the Game Design Project (Kafai & Resnick, 1996), all activities are devoted to invite the learner to solve problems and carry out discovery tasks. Instruction is reduced to the guidelines and conditions given about how to act in the environment and to the description of the problem. Learning activities are taking place, although not pre-planned and directed by some remote control (teacher or environment) in the sense supposedly designed in traditional instruction. From Designer to Teacher to Learner In the history of self-directed learning at least two developments have appeared. The first one pertains to the control over the learning process, from the teacher or instructor to the learner. Shuell (1996) described the differences between teachers as initiators of learning and learners that take the lead in this process. In this section we will discuss these developments and further elaborations on the role of the learner in taking initiative. The second development is quite old but has recently gained new and full attention (Perkins, 1996; Kafai & Resnick, 1996). In this approach learners are invited to be active in designing artefacts. These artefacts may, on the one hand, be concrete objects and, on the other hand, learning artefacts, in the case of one learner designing instruction for another learner. Eventually this latter development may lead to learners designing their own learning. In self-directed learning of the first kind, learners acquire certain learning outcomes by carrying out specific learning functions (this term is introduced in the field of learning and instruction by among others, Shuell [1996] but has a longer history in mechanical engineering). These functions can be initiated by the teacher, as in traditional instruction, or by the learner, as in self-directed or self-regulative learning. Shuell (1996) recognises the major role of learning functions and he describes 10 functions, from expectations to synthesis. Each function is an essential part of the learning process and is related to cognitive, 85


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metacognitive, and affective activities a teacher or a learner may carry out. The learning functions are compared to the instructional events by Gagné (Gagné et al, 1987), referring to the various stages of the transformation of information and the regulation of this process of transformation. Shuell’s functions are headed by three main functions related to cognitive, metacognitive, and affective functions. Recently, Vermunt & Verloop (1999) further elaborate on this distinction and they describe these various functions as learning activities. In self-directed learning of the second kind, learners act as designers. The activities designers normally carry out in developing and producing artefacts, like the ones discussed earlier, are the basics learners need to design relevant artefacts like concrete objects, e.g. making games in the Logo projects of Papert (1990), creating flying objects in recent projects carried out by our group, or learning artefacts by using thinking tools like the ones described by Perkins (1986, 1996), cognitive tools by Lajoie & Derry (1993), and mindtools (Jonassen, 2000). These ‘learners as designers’ activities are directed to build knowledge bases that let learners engage more in mindful activities, leading to more meaningful and transferable knowledge about the domain that covers these activities. Tools have been designed for various purposes and to serve an impressive number of functions. Jonassen (1995) writes that it is the irony of education that only few tools have been designed to optimise the process of education, by facilitating learning. Learning tools are special kinds of educational tools. Educational tools are meant to facilitate the whole process of education on the level of organisation or classroom. Cognitive (learning) tools are specially designed to promote and support the acquisition and construction of knowledge and the practice of skill of the individual learner. These cognitive tools are to be differentiated from task-specific tools and have to be generalisable tools that can facilitate cognitive processing (Jonassen, 1995). Jonassen sets limits by characterising cognitive tools. They can be regarded as internal or external to the learner: internal by, for instance, cognitive or metacognitive learning strategies; external by as both mental and computational devices that support, guide, and extend the thinking processes of their users. Both extend the knowledge acquisition and construction and skill practice processes of the individual learner. The teacher can apply these tools in order to design powerful learning environments, but on the other hand, the learner can apply these tools as well. The self-directed activities needed to design and create are already described by Martin (1984) as essentials skills for defining objectives and content of learning, like generating alternatives, making decisions, searching for information, understanding, classifying, and assessing, ordering, and storing information, for defining strategies and choosing resources and information, like searching for information, collecting information, understanding, and classifying, manipulating and organising information, and for evaluating outcomes, like monitoring, comparing, planning, generalising. Simons (1993) also describe these relevant activities in a discussion on constructivism and the role of the learner as designer. Five main functions are to be fulfilled: designing 86



the learning; organising the learning; monitoring and testing the learning; judging the learning progress and providing feedback; and maintaining the ongoing learning processes. These five functions all can be divided into more specific subcategories or functions. For instance, the first main function (designing the learning) consists of, amongst others, the functions choosing learning goals, illuminating the relevance of learning goals, retrieving and finding connected and required prior knowledge and choosing learning activities. The second main function has subcategories functions like executing learning activities aiming to reach understanding and executing learning activities directed at integration of new material with existing ideas. As a final example, subcategories of the third main function are monitoring learning progress, repairing failing learning plans and reflecting on the process of learning that is or has been going on. According to Simons, these functions may be executed by learners (learner-centred designs), by teachers (teacher-centred designs) (this term is used indicating real teachers, or media like books, computers, video or audiotape, or fellow learners) or in a cooperation between teachers and learners (cooperative designs). For instance, teachers may choose the learning goals, learners may do so or the choice occurs in cooperation (or negotiation). Another example is that teachers may remind learners of prior knowledge, or learners may do it on their own, or they may cooperate to find relevant prior knowledge. These new responsibilities learners may take in order to design and create artefacts for exploring domains and for learning, call for new roles by those who support these processes or cooperate with learners, like teachers and other instructional agents. Pieters (1994) described different roles, based on a distinction made by Simons (1991), for teachers facing these new challenges of learning and instruction: challenges that are related to not only new developments of information and communications technology, but also to new insights in learning and instruction, and especially in the transfer of learning. These teachers’ roles can be easily applied to learning and training situations as well. The first role Simons describes is instructor as external monitor. The instructor monitors the learning process and clarifies the decisions that have to be made by learners in order to optimise the learning outcomes. The second role is instructor as expert model. In this role, the instructor demonstrates domain-specific problem-solving and thinking skills, with a clear emphasis on the process of reaching outcomes and not on the outcome alone. The third role is directed to metacognitive aspects of intellectual functioning. The instructor has the role of metacognitive guide that stimulates reflection and articulation of thinking and regulation processes. The fourth role comprises scaffolding. During the first phases of the instructional and learning process the instructor is the one who is in charge but gradually this influence fades and learners take over the responsibility. The fifth role is directed toward goal setting, to gaining self-confidence and to promoting motivation and self-control and consequently to attributing success and failure. 87


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In recent discussion about self-directedness and the role of learners and teachers constructivist beliefs and ideas about learning are addressed. Duffy & Cunningham (1996) define learning with constructivism as knowledge construction. In their view, all knowledge is constructed and learning is a process of construction, multiple perspectives and many views can be constructed, knowledge is content-dependent and learning should occur in contexts to which it is relevant, learning is mediated by tools and signs, learning is inherently social-dialogical activity, learners are distributed, multidimensional participants in a social-cultural process, and knowing how we know is the ultimate human accomplishment. In similar vein, Wilson (1996) focused on the learning environment characteristics when he asserted that a constructivist learning environments is a place where meaningful, authentic activities help the learner construct understandings and develop skills relevant to solving problems. Related to educational practice, several interactions of learners with learning environments may be discerned, forming a scale from teacher- to learner-centred designs (Simons, 1993). At the one extreme of this scale, learners either follow the lines that were drawn for them, or they try to reconstruct their own learning environment by leaving out certain assignments, by reinterpreting assignments or by filling in missing values in the design. For instance, when the design is incomplete or wrong, the learner may add learning activities the designer did not ask for. At the other extreme of the scale, the learner should be able to take the necessary design decisions at the right time and in the right way. The decisions refer to the choice and explication of (personal) learning goals, the choice of learning activities and their sequence, the monitoring of ongoing learning activities and their results, the seeking of help when problems occur, the way to find and use feedback and the way one can keep oneself motivated and concentrated. The Role of Inquiry The role of needs assessment and needs analysis can be discussed within the framework of cognitive tools to support learners for designing artefacts. Needs assessment and needs analysis pertain to the situation in which a designer is asking questions about ‘finding the problem’. In a powerful learning environment a learner may take over this activity and it includes the (in)ability of the learner to adequately articulate his knowledge need, and subsequently being able to find and define the problem (the difference between what is known and what should be known). Again, in the constructivist sense, learners should be able to trace bugs in their knowledge base. The learning environment can contribute to the activation of cognitive, metacognitive, and self-regulatory processes needed to ‘find the problem’, finding the discrepancy of what is known and what should be known. This activation is supposed to happen as a consequence of support the learning environment provides in letting the learner ask questions. The effectiveness of questioning behaviour is 88



determined by three factors: (1) a perceived lack of information, (2) a felt need of information (the learner must be motivated), and (3) the socialcommunication environment (Van der Meij, 1994). The first factor is related to the incompleteness of the knowledge base of the learner. The learner must experience a bug in order to be able to raise ‘debugging’ questions. The second factor pertains to the motivation of the learner. In order to receive the information needed to fill the knowledge gap, the learner must be stubborn and tenacious. The third factor pertains to the choice of the source, the kind of question to be asked, and the way the question is asked. Social and communicational rules will associate this process. Questioning research says that the tactic to overcome the knowledge problem can be formulated as triggering a cognitive conflict. This tactic includes three types: surprise, perplexity, and discoordination. Surprise will happen when a learner applies a rule that appears not to function in the way meant. Letting the learner formulate and disconfirm hypotheses can facilitate surprise. Perplexity exists when a learner will be confronted with two competing solutions or plausible needs. Presenting problems with competing solutions can stimulate this. Discoordination will happen when the learner is forced to integrate ideas or needs that appear not to have any relation beforehand. This can be facilitated by teaching-back or peer tutoring, or letting the learner try to convince colleagues. Questioning research pointed out that questioning could be considered a four-stage process. The first stage consists of the establishment of a cognitive conflict. The second stage includes finding the problem and planning the solution. The third stage is the one in which the question is put. In the fourth stage the answer is processed. The Role of Technology Technology no longer controls learning, but plays a supportive role, informing and advising learners. The instructor’s role is integrated in this supportive function, also by advising and metacognitively supporting learners. In some instances the role of the instructor is amplified by technology. Instructor and technology collaborate in supporting learners to achieve outcomes that were not possible before. In this sense, technology not only supports learners but also supports the instructor by playing an effective and affective role in knowledge acquisition and knowledge construction, as well as in practice of learners’ skills. Recently developed intelligent technologies afford learners a partnership with results greatly dependent upon joint effort. The partnership with computer technologies and tools is very real in this respect. It entails, according to Salomon et al (1991) and Salomon (1993) three major ingredients one also finds in human partnership: (a) a complementary division of labour that (b) becomes interdependent and that (c) develops over time. An interesting point, indicated by these authors, is that even novice learners may gain from certain 89


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computer tools that support cognitive processes. The partnership with computer technologies may carry out some of the lower level intellectual operations, thus circumventing the need to first achieve automatisation of these operations. Novice learners may be able to engage in cognitive activities out of their reach without the technological partnership. Current computer simulation within multimedia systems allows the construction of a simulated reality in which learners do not need to commit anything to memory, thus allowing them to generate and test the wildest hypotheses about real and imaginary systems. This kind of environment lets learners engage in intellectual activities at a level which transcends the limitations of their own cognitive systems. As Pea (1987) has already indicated, the use of cognitive tools can change the ratio between assessing prior knowledge and constructing new knowledge, in favour of the latter. In this respect, new technologies can create learning opportunities and facilities that will also change the role of the trainer and instructor. These new roles develop during times in which learning environments also gradually differ. In short, learning environments can be discerned historically into three broad categories and related roles for instructional agents. The first category stems from developments in behaviourist approaches to teaching, like programmed instruction. The environment that sets conditions and parameters for action heavily controls learning. The role of media and technology is separated from the role of the teacher or instructor. The second category of learning environments has been influenced by cognitive learning theory. More emphasis is laid on aspects of adaptive instruction and on knowledge representations as conditions for learning. Instructors adapt technology and collaborate with technology in order to optimise learning outcomes. The role of technology in instruction and the role of the instructional agent are integrated. The third, recent, category (see Jonassen, 1995, 2000) encompasses constructivist beliefs and ideas about learning and instruction. Technology no longer controls learning, but plays a supportive role, informing and advising learners. The teacher’s role is integrated in this supportive function, also by advising and metacognitively supporting learners. In some instances this role is amplified by technology. Teacher and technology collaborate in supporting learners to achieving outcomes that were not possible before. In this sense, technology not only supports learners but also supports the instructor by playing an effective and affective role in knowledge acquisition and knowledge construction, as well as in practice of learners’ skills. Cognitive technology facilitates learners to actively engage in creation of knowledge that reflects their comprehension and conception of the information rather than focusing on the presentation of objective knowledge. Cognitive technology can also be addressed to the functions of questioning described above. Cognitive assessment tools are learner controlled, not teacher or technology driven. These are cognitive reflection tools and amplification tools that help learners to adequately assess their own knowledge needs and to 90



construct their own realities using the constructs and processes in the environment in order to overcome the knowledge problem. The issue is about cognitive tools for ‘self-designing’ learning environments, from the beginning of defining the problem (feeling the need: ‘what do I know’ against ‘what should I know’) to the end of constructing a learning landscape. What tools are needed and what tools are available to amplify learners’ design capabilities are major questions. The Need for Support Learners as designers may not always have the ability or capacity to accept and use additional information needed to perform that task. This is what Carroll (1990) calls the paradox of sense-making: in order to act one must learn, and in order to learn one must act. To learn, people must interact meaningfully with a programme or task, but to interact they must first learn. Support can be helpful in solving this paradox. Support can take several forms and can take place on several occasions: the individual young learner gets help from the teacher, the teacher informs learners about the procedure to solve a particular mathematical problem, the teacher may ask the learner to make his (or her) problem-solving explicit, the learner can click on the help button to receive additional information in a computer-based learning environment, the employee receives additional support from his colleagues in the workplace, the learner receives support from his colleagues in a discussion with his professor. In these situations a tool is provided by a teacher or another instructional agent in order to induce cognitive and metacognitive processes. These cognitive tools afford learners to become an active participant in their own knowledge acquisition and construction. The basic problem with the paradox of sense-making is that of finding the right balance between support and letting go. Too little support obstructs learning; too much support hinders performance. In general, instructors tend to err on the ‘safe’ side by giving too much support. To work adequately with multimedia support systems users sometimes turn to help systems for help. Unfortunately, these help systems often are so complex that most users need training in dealing with them. This distracts them from their core task as users get busy with finding their way into (and out of) the help system. Too little support is occurring when designers disregard the support that is given to them. Often new users of design systems commit many mistakes because they have a tendency to act before ‘reading everything’. Often these mistakes tend to accumulate, making error recovery too complex to handle by these users. Two strategies are needed to prevent such deadlock: the programmes must be adapted so that severe errors (i.e. errors that jeopardise task continuity) are blocked; the documentation should help users develop cognitive skills in dealing with help and support systems as well as with errors 91


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associated with working with these kinds of systems. In many support manuals, one or two of these components are missing. Detrimental effects from support can be expected on several grounds. First, learners might have no adequate prior knowledge for performing the task or for dealing with an open environment in which they have to find their own way. Second, learners may lack cognitive or metacognitive skills needed to handle open learning situations and open support environments. Third, learners might be overloaded. A double task is to be performed by the learner, the primary task is learning by acting or performing, and concurrently a secondary task has to be performed, searching and browsing a help system. A high cognitive load is put on the learner’s cognitive system. Fourth, learners might have motivational problems with working with the support tools, not knowing the necessity or relevance of these tools. Fifth, learners might not feel challenged to work with the support tool. The task can also be carried out without the information provided by the tool. Sixth, the information offered by the support tool might overwhelm learners, not knowing what to do with the support information or what to expect from the information. Seventh is the incompatibility of support. For example, conceptual or declarative information is presented whereas procedural information is needed. These detrimental effects of support tools can be ascribed to three major causes, earlier described in Pieters & van der Meij (1994): • Firstly, a constructivist problem. These problems are related to the fact that the learner cannot apply strategies and capabilities needed in a constructivist approach. The learner is not aware of the information needed and is not capable of articulating the need. Cognitive variables like, for example, insufficient prior knowledge, domain knowledge, tool knowledge, and strategic knowledge as well, are responsible for this problem. Also, metacognitive variables like, for example, self-regulative skills, are related to this problem. • Secondly, a minimalist problem. This problem is due to the fact that the rules of designing minimalist support (with reference to the minimal manual [Carroll, 1990]) are not obeyed. Too much support is provided. The learner does not know what to expect from the support tool; no explanations about the system to work with are needed. Also, information received can be compatible to the task at hand. • Thirdly, an intentional or motivational problem. Associated with the problems mentioned above, the learner must be in the mood for learning when confronted with a learning task. Intentional problems are related to goal setting, to planning and controlling, and to the need for effective and easy solutions. Helping learners as designers to overcome the support problems discussed in the preceding paragraphs needs to happen in a compatible way with the activities to be carried out as a designer. But, as we have already discussed, designing and producing learning environments is becoming a complex task due to considerable changes from expository goal-based learning activities to 92



inquiry goal-free activities. The main reasons for this change are the increasing availability and use of support tools based on information and communications technology, the changing nature of the learning environments, and the shift from designing such environments by professional designers to designing by teachers and instructors, and by learners as co-designers when teachers and learners are cooperating in a design community (Murray et al, 2003). In this article we even suppose learners to be designers of their own learning. Supporting that kind of design process with help from external information and from peer support, also with teachers and peers, can contribute to levelling some of the obstacles on the road to implementing these kinds of tools in practice and to creating an effective learning environment. An interesting and challenging elaboration of learners as independent designers is learners supported by colleagues (among which we may also count teachers or subject matter experts). In recent research literature, this kind of thinking and working is called participatory design as context for collaboratively designing and learning, and informed participation as approach for collaborative knowledge construction (among others, Fischer & Ostwald, 2002). To overcome problems with support as described earlier and to support learners as designers, collaboration in designing is a promising future. The availability of user-friendly tools for designing learning environments has also resulted in an innovative shift of design focus. Several researchers have noticed this shift from a user-centred, although passive and reactive, design approach to a participatory, at responsibility and self-directedness directed, design approach (Fischer, 2002; Fischer et al, 2003). This latter innovative and promising approach empowers co-designers (teachers and learners) to actively participate in designing learning environments leading to higher learning outcomes. Co-designers’ actions mutually and interactively support the collaborative process of designing learning environments, e.g. in analysing, designing, evaluating, implementing (like designing solutions for difficult problems by sharing representations [Van Bruggen & Kirschner, 2003]), but also facilitating an appropriate social, cultural, and technical infrastructure (Fischer et al, 2003). Co-designing, or participatory designing with teachers as domain experts, in this way, offers more support and more compatible support than current support systems do in the context of a distributed process of social cognition. New pedagogical perspectives and approaches in which teachers (as domain experts) and learners are assumed to cooperate on a basis of equity and mutual responsibility will be offered a practical context for the implementation in powerful learning environments, is defined by the strength of the cognitive and social support provided (Fischer et al, 2001). In many current educational cases, rich tools that facilitate the process of designing learning environments individually support teachers and instructors in schools and universities. These tools also become available for designing by learning, individually or cooperatively. Most tools offer technical support for the design and production process. With user-friendly interfaces and powerful technology, tools for instructional design allow designers to create attractive 93


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technological advanced learning environments without the need for specialised technical knowledge, for instance, about computer programming. Tools also offer conceptual support, aimed at supporting the design of powerful and effective learning environments, often within the context of a learning paradigm, such as the above discussed constructivist learning or competency based learning. The means of providing designers with this kind of conceptual support is the subject of ongoing research (see, for instance, Kuyper, 1998; Van den Akker et al, 1999; Pieters et al, 2003). With the above noted shift from professional designers to teachers and learners as the main group of designers, the question of providing conceptual collaborative support becomes more significant. Collaboratively designing by teachers and learners (including peers) can be best supported by: • A database of information and base material for the design of the learning environment (information tools). Information in databases can be structured along the task structure. An example can be found in studies into the use of information during architectural design (De Vries & De Jong, 1997, 1999). Two phases in the design process were distinguished: defining the problem and determining the solution process to realise the design. In the architectural design process these two phases have an effect on the way the information system is used. In the first phase the process can be described as ‘browsing’, unstructured jumping from item to item; in the second phase, ‘searching’, designers are looking for specific information. These different uses of the information system have their bearing on the design of the information, which can be hierarchical (structured) or network-like (unstructured). • Cognitive tools for supporting the design process. An important means of supporting designers is that of cognitive tools (e.g. Lajoie, 1993, 2000). Cognitive tools help users in handling information and knowledge by integrating these into the task. Cognitive tools can support tasks in at least three ways: – Firstly, by external representation of information. By storing information in an external representation, working memory is relieved and the representational affordances of the representation (Zhang, 1997; Suthers, 1999; Van Bruggen & Kirschner, 2003) can direct further task execution. – Secondly by structuring the tasks. By providing a structure for the task, like fill-in forms, the number of choices is reduced, leading to a simplified task. – Thirdly, by automating tasks. A cognitive tool can automate part of the task, as is found in wizards (e.g. Kuyper, 1998; Kuyper et al, 2001) that take the user through a number of question forms and perform the task for the learner. • A design space for communication and discussion among teachers, learners and subject matter experts leading to participatory designing. • Social-cognitive tools to facilitate and structure communication and collaboration among teachers and learners. Social communication is 94



dependent upon at least three psychological mechanisms that determine social behaviour, including messages sent to a co-designer: a cognitive component, an affective component, and an intentional component (Ajzen, 2002). The cognitive component determines the content of the message which is related to prior (domain) knowledge and expected expertise of the receiver, the affective component the emotional value related to perceived relational value, and the intentional component is responsible for the actual expression (like the function of an interface) related to the conditions under which the message is transmitted. Social-cognitive tools can provide conditions for an effective communication by which not only ‘objective’ information is transmitted but also the value and meaning of the message is communicated, e.g. by using an electronic form with room for expressing appreciation. Tools also provide conditions for technology-mediated communication by offering opportunities to extend options for collaboration among designers, like storing experiences and structuring communication traces and by sharing external representations allowing users to share views on the design process in building and exploring design spaces (e.g. Van Bruggen & Kirschner, 2003). • Technological tools to construct learning material. The aforementioned tools provide a structure for learners with which they can more profoundly carry out tasks that may lead to artefacts, whether these are concrete artefacts or learning artefacts, and that support the development and construction of knowledge based on activities and experiences. Conclusions The aim of this article was to give an overview of opportunities for learners to be actively involved in their knowledge development. Our discussion started with the historical perspectives on learning, knowledge development and instructional design. We argue that learners learning within a discovery learning environment are in fact actively making meaning out of their activities and their experiences. The way learners create a learning environment based on the discovery tasks to be carried out can be compared to the way actual instructional designers do their job. The main activities to be carried out based on analysis, synthesis and evaluation and implementation, very well resemble the main activities learners may carry out when going through a process of learning. This way of working means a more independent learning by the learner, in fact learners as designers of their own learning. Evidence provided by cases of self-directed learning and self-regulatory learning proves this approach to be effective although there are some doubts about the fully independent way of working. Learners have problems with the freedom provided by learning environments that let them create their own learning trajectory. These problems are identical to the problems learners experience with plain discovery learning. To overcome these problems, and also the problems learners as designers encounter, support can be provided. We 95


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discussed several ways of support and also the ineffectiveness of support when learning and learner characteristics do not match with the support presented. Alternative forms of providing support, especially those based on new cognitive technologies, were discussed and we came to an interesting and challenging new form, in which tools for improving communication among learners, teachers, subject matter experts and technology are suggested. ‘Learners as co-designers for co-inquiry and cooperation’ can typify this potential alternative for instruction in education. With these alternatives learning can really transcend the individual activity and become a distributed cognitive, metacognitive and affective activity. To let learning not be the result from a solitary, unsupported thinking by learners (Jonassen, 1994). We planned to do research within a European context (www.kaleidoscope.fr) to further investigate the power of participation in designing learning by those who can contribute to the distributive development of expertise in a socially meaningful way. Note [1] Revised version of a keynote speech at ECER 2003, Hamburg.

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Correspondence: Jules M. Pieters, Faculty of Behavioral Sciences, University of Twente, PO Box 217, NL-7500 AE Enschede, The Netherlands. ([email protected]).

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