INTRODUCTION
In higher education, students are often asked to demonstrate critical thinking, academic literacy (Geisler, 1994), expertlike use of knowledge, and creation of knowledge artifacts without ever having been guided or scaffolded in learning the relevant skills. Too frequently, universities teach the content, and it is assumed that the metaskills of taking part in expert-like activities are somehow acquired along the way. Several researchers have proposed that in order to facilitate higher-level processes of inquiry in education, cultures of education and schooling should more closely correspond to cultures of scientific inquiry (e.g., Carey & Smith, 1995; Perkins, Crismond, Simmons & Under, 1995). Points of correspondence include contributing to collaborative processes of asking questions, producing theories and explanations, and using information sources critically to deepen one’s own conceptual understanding. In this way, students can adopt scientific ways of thinking and practices of producing new knowledge, notjust exploit and assimilate given knowledge.
BACKGROUND
The best practices in the computer-supported collaborative learning (CSCL) paradigm have several features in common: consideration in an interrelated manner of the development of technological applications, use of timely pedagogical models, and attention to the social and cognitive aspects of learning. Emphasis is placed on creating a collaborative community that shares goals, tools, and practices for taking part in an inquiry process.
Synthesizing these demands, Hakkarainen and his colleagues at the University of Helsinki have developed a model of progressive inquiry as a pedagogical and epistemological framework. It is designed to facilitate expert-like working with knowledge in the context of computer-supported collaborative learning. It is primarily based on Scardamalia and Bereiter’s (1994) theory of knowledge building, on the interrogative model of scientific inquiry (Hintikka, 1999; Hakkarainen & Sintonen, 2002), and on the idea of distributed expertise in a community of learners (Brown & Campione, 1994). The model has also been implemented and studied in various educational settings from elementary to higher education (see, e.g., Hakkarainen, Jarvela, Lip-ponen, & Lehtinen, 1998; Lipponen, 2000; Veermans & Jarvela, 2004; Muukkonen, Lakkala, & Hakkarainen, 2005; Lakkala, Lallimo, & Hakkarainen, 2005; Lakkala, Ilomaki, & Palonen, 2007).
The Progressive Inquiry Model
In progressive inquiry, students’ own, genuine questions and their previous knowledge of the phenomena in question are a starting point for the process, and attention is drawn to the main concepts and deep principles of the domain. From a cognitive point of view, inquiry can be characterized as a question-driven process of understanding; without research questions, there cannot be a genuine process of inquiry, although in education, information is frequently conveyed or compiled without any guiding questions. The aim is to explain the phenomena in a deepening question-explanation process, in which students and teachers share their expertise and build new knowledge collaboratively with the support of information sources and technology.
The progressive inquiry model specifies certain episte-mologically essential processes that a learning community needs to go through, although the relative importance of these elements, their order, and actual contents may involve a great deal of variation from one setting to another. As depicted in Figure 1, the following elements have been placed in a cyclic, but not step-wise succession to describe the progressive inquiry process (Hakkarainen, 2003; Muuk-konen, Hakkarainen, & Lakkala, 1999, 2004):
a. Distributed expertise is a central concept in the model. Progressive inquiry intends to engage the community in a shared process of knowledge advancement, and to convey, simultaneously, the cognitive goals for collaboration. Diversity in expertise among participants, and interaction with expert cultures promotes knowledge advancement (Brown et al., 1993; Dunbar, 1995). Acting as a member in the community includes sharing cognitive responsibility for the success of its inquiry. This responsibility essentially involves not only completing tasks or delivering productions on time, but also learners taking responsibility for discovering what needs to be known, goal setting, planning, and monitoring the inquiry process (Scardamalia, 2002). There should be development of students’ (and experts’) social metacognition (Salomon & Perkins, 1998): students learning to understand the cognitive value of social collaboration and gaining the capacity to utilize socially distributed cognitive resources.
b. The process begins by creating the context to anchor the inquiry to central conceptual principles of the domain or complex real-world problems. The learning community is established by joint planning and setting up common goals. It is important to create a social culture that supports collaborative sharing of knowledge and ideas that are in the process of being formulated and improved.
c. An essential element of progressive inquiry is setting up research questions generated by students themselves to direct the inquiry. Explanation-seeking questions (Why? How? What?) are especially valuable. The learning community should be encouraged to focus on questions that are knowledge driven and based on results of students’ own cognitive efforts and the need to understand (Bereiter, 2002; Scardamalia & Bereiter, 1994). It is crucial that students come to treat studying as a problem-solving process that includes addressing problems in understanding the theoretical constructs, methods, and practices of scientific culture.
d. It is also important that students explain phenomena under study with their own existing background knowledge by constructing working theories before using information sources. This serves a number of goals: First is to make visible the prior (intuitive) conceptions of the issues at hand. Second, in trying to explain to others, students effectively test the coherence of their own understanding, and make the gaps and contradictions in their own knowledge more apparent (e.g., Hatano & Inakagi, 1992; Perkins et al., 1995). Third, it serves to create a culture in which knowledge is treated as essentially evolving objects and artifacts (Bereiter, 2002). Thoughts and ideas presented are not final and unchangeable, but rather utterances in an ongoing discourse (Wells, 1999).
e. Critical evaluation addresses the need to assess strengths and weaknesses of theories and explanations that are produced, in order to direct and regulate the community’s joint cognitive efforts. In part, it focuses on the inquiry process itself, placing the process as the center of evaluation and not only the end result. Rather than focusing on individual students’ productions, it is more fruitful to evaluate the community’s productions and efforts, and give the student participants a main role in this evaluation process. Critical evaluation is a way of helping the community to rise above its earlier achievements, creating a higher-level synthesis of the results of inquiry processes.
f. Students are also guided to engage in searching deepening knowledge in order to find answers to their questions. Looking for and working with explanatory scientific knowledge is necessary for deepening one’s understanding (Chi, Bassok, Lewis, Reiman, & Glaser, 1989). A comparison between intuitive working theories produced and well-established scientific theories tends to show the weaknesses and limitations of the community’s conceptions (Scardamalia & Bereiter, 1994). The teacher of a course must decide how many of the materials should be offered to the students and how much they should actually search out for themselves. Questions stemming from true wonderment on the part of the students can easily extend the scope of materials beyond what a teacher can foresee or provide suggestions for. Furthermore, searching for relevant materials provides an excellent opportunity for self-directed inquiry and hands-on practice in struggling to grasp the differences between various concepts and theories.
g. Generating subordinate questions is part of the process of advancing inquiry; learners transform the initial big and unspecified questions into subordinate and more specific questions, based on their evaluation of produced new knowledge. This transformation helps to refocus the inquiry (Hakkarainen & Sintonen, 2002; Hintikka 1999). Directing students to return to previously stated problems, to make more subordinate questions and answer them, are ways to scaffold the inquiry.
h. Developing new working theories arises out of the fresh questions and scientific knowledge that the participants attain. The process includes publication of the summaries and conclusions of the community’s inquiry. If all productions to the shared database in a collaborative environment have been meaningfully organized, participants should have an easy access to prior productions and theories, making the development of conceptions and artifacts a visible process.
Figure 1. Elements of progressive inquiry
Cases of Progressive Inquiry in Higher Education
Progressive Inquiry in a Cognitive Psychology Course
In a study reported by Muukkonen, Lakkala, and Hakkarainen (2001), the progressive inquiry model was implemented in a cognitive psychology course with the use of the Future Learning Environment (FLE). The FLE is an open-source collaborative tool that has the progressive inquiry model embedded in its design and functionality (http://fle3.uiah.fi/; Muukkonen et al., 1999). All the students in the course were guided, during the first two lectures, to formulate research problems. In the beginning, they individually produced these formulations. They continued by discussing their research problems with a peer and, finally, within a small group, selected the most interesting questions to pursue. These questions were then presented to all the participants in the lecture. After this initial problem setting, the technology-mediated groups (three groups of 4-7 volunteers) were instructed to continue their inquiry processes between the weekly lectures in the FLE. The tutor-facilitators took part in the FLE, whereas the teacher conducted the weekly lectures without participating in the database discourse. The rest of the students also formed groups based on their questions, but continued their inquiry process by writing learning logs and commenting on the logs produced by other members of their group without collaborative technology.
A comparative analysis of the knowledge produced by the students in the two conditions provided evidence that the technology-mediated groups were more engaged in problem-setting and redefining practices. Further, they reflected on the process they had undertaken, in respect of the collaboration and their individual efforts. In the productions of the groups who had not used collaboration tools, the social and communal aspects of inquiry and knowledge building were not evident at all in their learning logs, although they were engaged in collaboration during the lectures. The type of comments they provided to two of the learning logs written by other members of their group were very general, and they concentrated mainly on evaluating the level of writing, not on advancement of ideas. However, many of the learning logs were conceptually well developed and integrated. Discourse interaction within the FLE was different in respect of the participants sometimes engaging in extensive dialogues with ideas presented by the fellow students.
Progressive Inquiry in a Design Course
Two studies carried out by Seitamaa-Hakkarainen and her colleagues (Seitamaa-Hakkarainen, Lahti, Muukkonen, & Hakkarainen, 2000; Seitamaa-Hakkarainen, Raunio, Raami, Muukkonen, & Hakkarainen, 2001) analyzed a collaborative design process as it occurred in a complex and authentic design task of designing clothing for premature babies. The framework of the studies was based on evidence from cognitive research on expertise, which indicated that novices in design tend to generate problem solutions without engaging in extensive problem structuring; experts, by contrast, focus on structuring and restructuring the problem space before proposing solutions (Glaser & Chi, 1988). The studies described in this case were designed to examine whether an expert-like engagement in design process would be supported in the FLE-environment. Features of the environment were used to encourage the users to engage in expert-like designing, and to enable graphic presentation of the knowledge artifacts in the form of importing students’ drafts and prototypes into the collaborative environment and developing multiple versions of the designs.
During the collaborative design course, the students were first guided to find out information about the constraints of their design task, such as the size of the babies, special needs for the usability of the clothing, and about the materials. Then they were asked to produce their own sketches and work in small groups to share design ideas and develop their designs. Following this development, each group produced a prototype, which was tested by actual end users in a hospital. Feedback and suggestions were then used to develop advanced design ideas.
In these studies of designing with the support of a networked collaborative environment, Seitamaa-Hakkarainen et al. (2001) found that a key aspect of these environments is the provision of tools for progressive discourse interaction between the designers and users of the future products. Further, the environments offer shared spaces and tools to elaborate conceptual knowledge related to the design problem. The collaborative technology made design thinking more explicit and accessible to the fellow designers, and enabled participants to share their ideas and construct a joint understanding of design problems and solutions.
Supporting and Guiding Students’ Progressive Inquiry Processes
A special question in implementing progressive inquiry and knowledge-building practices in higher education is the teacher’s or tutor’s role in supporting and guiding students’ collaborative inquiry. In progressive inquiry, the traditional role of a teacher as an expert, who delivers the essential information by lecturing, is radically changed. The important roles of the teacher and the facilitators of collaboration are:
1. to create the context for the collaborative inquiry practices by organizing the community’s activities and establishing the underlying conditions of the educational setting (Lakkala et al., 2005), and;
2. to supervise and scaffold the process, keep it active and in focus during the progression of the course, and to help students gradually take on themselves the responsibility for the higher-level cognitive processes (Scardamalia, 2002).
Our recent studies indicate that, in order to successfully engage students’ in progressive inquiry, the whole educational setting should be carefully planned and constructed to support the eligible activities, because expert-like inquiry practices do not emerge spontaneously. However, it does not mean pre-planning detailed tasks, but indirectly designing conditions for the community’s activities (Jones, Dirckinck-Holmfeld, & Lindstrom, 2006). Building on previous studies (e.g., Bielaczyc, 2001; Guribye, 2005; Lakkala et al., 2005; Paavola, Lipponen, & Hakkarainen, 2002), we have started to use the notion pedagogical infrastructures to illustrate how the pedagogical design of collaborative inquiry practices resembles the construction of basic physical infrastructure to support smooth and effective functioning of people’s daily activities. We have developed the framework of pedagogical infrastructures (Muukkonen, Lakkala, & Paavola, in press; Lakkala, Muukkonen, Paavola, & Hakkarainen 2008), consisting of technical, social, epistemological, and cognitive infrastructure, to be used to classify, design, and evaluate the elements of educational settings based on technology-enhanced collaborative inquiry. The separate infrastructures exist in parallel, and in a successful educational setting, all aspects are taken care of and designed to foster collaborative knowledge creation: appropriate technology is easily accessible and it is used meaningfully (technical infrastructure); there is deliberate collaboration built into the tasks (social infrastructure); students’ activity is organized to be creative working with knowledge, not just internalizing certain content (epistemological infrastructure); and students’ autonomy and the development of skills are supported by explicit cognitive modeling of expert-like practices (cognitive infrastructure).
In addition to appropriate and supportive overall design of the educational setting for progressive inquiry, timely guidance and tutor’s participation throughout the process is important for further shaping and directing students’ engagement in inquiry. In one study (Muukkonen et al., 2005) we compared students’ technology-enhanced inquiry practices in two conditions, either with or without tutor participation. As evidence for the tutors’ role, the process analysis recovered a more focused problem-setting tendency in tutored groups: instead of opening up new lines of questions, the tutored groups were more likely to present subordinate questions to previous ones. The results of another study, comparing three tutors’ scaffolding practices (Lakkala et al., 2007b), indicated that the kind of advice and expert model that the tutor offered had an effect on the style of the inquiry discourse in the group: either it concentrated more on theory reviewing, focusing of the inquiry, or generating of divergent ideas. The scaffolding that appears to have promoted deepening discourse may be characterized as explicitly built on the students’ preceding discourse and, accordingly, as providing a content-specific and well-timed expert recommendation to refocus the inquiry.
FUTURE TRENDS
Productive changes in educational systems towards establishing inquiry-based approaches in studying and teaching call for an alignment of pedagogical and institutional goals and actions (Muukkonen et al., 2004). Learning technologies also need to be critically viewed for their role in fostering expert-like skills in advancing knowledge. For instance, availability of scaffolding, support for multiple forms of collaboration, and shared development of knowledge objects are challenges for designing learning technologies.
CONCLUSION
The progressive inquiry model may be utilized in a variety of educational settings to provide a heuristic framework for the key activities and epistemic goals of a knowledge-building community. The community may provide multiple levels of expertise and, equally importantly, social support for engaging in a strenuous quest for learning and advancing knowledge. Especially in higher education, a progressive inquiry approach may support the development of academic literacy, scientific thinking, and epistemic agency, particularly when integrated with the use of appropriate collaborative technology and supportive arrangements in curriculum design.
KEY TERMS
Distributed Expertise: Cognition and knowing are distributed over individuals, their tools, environments, and networks.
EpistemicAgency: Taking responsibility over one’s own learning efforts and advancement of understanding.
Knowledge Building: A framework for collective knowledge advancement and development of knowledge artifacts.
Learning Community/Community of Learners: All participants in a learning process (students, teachers, tutors, and experts) have valuable expertise and skills, which benefit collective efforts.
Metaskills: Skills involved in academic literacy, as well as metacognitive skills related to planning, monitoring, and regulating comprehension-related activities.
Progressive Inquiry: A pedagogical model for structuring and supporting a group of learners in a deepening question-explanation process.
Pedagogical Infrastructures: In the present context, the concept is intended to refer to the elementary preconditions that should be designed to shape and support collaborative inquiry practices in educational settings.
Scaffolding: Providing support, which enables a learner to carry out a task that would not be possible without that support, and enabling the learner gradually to master that task without support.
