Description

Technology-enabled learning environments such as company Intranets and the World Wide Web, which rely on networking technology are becoming a common way of training technical professionals in corporate settings.  Asynchronous instruction using network technology enables any time, anywhere learning by incorporating the use of discussion databases, e-mail and multimedia. This type of technology-enabled learning is referred to as an asynchronous learning network (ALN). While ALNs provide the benefit of anytime, anywhere learning and can reduce costs associated with travel and lodging, important questions remain concerning the learning effectiveness of these environments.
 One component of ALNs which can have a major impact on the effectiveness of the instruction is the instructional design strategy chosen to develop and teach courses. The most common approach used today is heavily text-based, and is supported with audio, animations, and a discussion database to support collaborative team work.  ALN courses using this instructional design approach may be subject to the same weaknesses found with other types of distance learning programs and classroom settings which rely on passive learning. Knowledge is produced and information is understood by learners, but not to the extent where the knowledge can be used for effective problem-solving  outside the classroom. Whitehead (1929) referred to this as the "inert knowledge" problem. A number of studies have shown that traditional approaches to instruction (such as readings, lectures, and demonstrations of key points which focus on declarative and procedural information) often produce inert knowledge (Bereiter & Scardamalia, 1985; Bransford, Franks, Vye & Sherwood, 1989; Gick & Holyoak, 1983; Perfetto, Bransford, & Franks 1983).
 Cognitive apprenticeship (Collins, Brown, & Newman, 1989) is an instructional innovation which was introduced to address the problem of inert knowledge. This approach is based on the underlying principles of apprenticeship learning and focuses on the use of such strategies as modeling expert behavior and coaching students to mimic expert skills until they are competent in their performance. This approach also includes a cognitive component which focuses on teaching the cognitive and metacognitive skills associated with a specific domain of knowledge. The cognitive and  metacognitive components of learning deal with the processes and strategies used to problem solve and are used in situations which require learners to extend their knowledge to novel or complex situations outside of the classroom.
 The aim of the proposed study was to determine how well an on-line (ALN) cognitive apprenticeship program lends itself as an instructional design model for teaching complex problem-solving skills to adult learners.  Specifically, this study explored 1) the extent to which the primary components of cognitive apprenticeship (content, instructional strategies, sequencing, and sociology) can be applied in an ALN environment, 2) the learning effectiveness of this approach in teaching Object Oriented Analysis problem-solving skills to business professionals and 3) the relationship among characteristics of learners (such as gender, level of education, learning style, and experience with online courses) and skill acquisition in this type of learning environment.

Research Abstract

Cognitive apprenticeship is an instructional design model which focuses on the development of higher level thinking skills such as problem-solving. In this study, cognitive apprenticeship was tested for its effectiveness in teaching technical skills to adult learners in an on-line learning environment.

Two six-week Object Oriented Analysis (OOA) courses were offered to IBM professionals and NYU graduate students during the winter and spring semester of 1999. An Asynchronous Learning Network (Lotus LearningSpace, Domino version) was used as the online platform for these courses. Students accessed the courses using either a Lotus Notes client or a web browser. The courses were collaborative and varied in terms of the instructional design: traditional text based with audio or cognitive apprenticeship.  The first course was similar to what is typically used today for on-line courses and included reading assignments and collaborative team exercises. The second course implemented cognitive apprenticeship as the instructional design method.  While the content of the course was the same as the first class, the structure was different.  Using techniques such as expert modeling, coaching, scaffolds, articulation, reflection, and exploration, students learned how to solve Object Oriented Analysis problems.

Forty-three students were recruited for the study, twenty IBM professionals, and twenty-three NYU graduate students. The results of data analysis on pretests indicated no difference between the groups in their initial knowledge of OOA. After the completion of each six-week course, a posttest was administered. A panel of three expert OOA professionals was recruited to assess student performance.  Solutions were rated based on the inclusion and quality of four components: a Use Case, Object Model, Interaction Diagram, and Glossary of Objects.  The results of data analyses revealed that while both groups showed significant improvements in OOA knowledge as a result of the OOA course, the cognitive apprenticeship group outperformed the text-based group on aspects of the OOA solution which required complex problem-solving  (creating Object Models and Interaction Diagrams). No difference between the groups was observed with respect to their ability to identify a Use Case.  The text-based group scored higher with respect to creating a Glossary of Objects. It is felt that students spent their time on tasks that were considered most important to them or on those with which they were most comfortable completing. The overall conclusion is that the cognitive apprenticeship group developed better complex problem-solving skills than the text-based group.

Kathleen Snyder, Ph.D.
Applied Learning Sciences
IBM T.J. Watson Research Center