Designing as Construction of Representations: A Dynamic Viewpoint in Cognitive Design Research

This article presents a cognitively oriented viewpoint on design. It focuses on cognitive, dynamic aspects of real design, i.e., the actual cognitive activity implemented by designers during their work on professional design projects. Rather than conceiving de-signing as problem solving - Simon's symbolic information processing (SIP) approach - or as a reflective practice or some other form of situated activity - the situativity (SIT) approach - we consider that, from a cognitive viewpoint, designing is most appropriately characterised as a construction of representations. After a critical discussion of the SIP and SIT approaches to design, we present our view-point. This presentation concerns the evolving nature of representations regarding levels of abstraction and degrees of precision, the function of external representations, and specific qualities of representation in collective design. Designing is described at three levels: the organisation of the activity, its strategies, and its design-representation construction activities (different ways to generate, trans-form, and evaluate representations). Even if we adopt a "generic design" stance, we claim that design can take different forms depending on the nature of the artefact, and we propose some candidates for dimensions that allow a distinction to be made between these forms of design. We discuss the potential specificity of HCI design, and the lack of cognitive design research occupied with the quality of design. We close our discussion of representational structures and activities by an outline of some directions regarding their functional linkages

Schematic Representation: How Students Creating IT?

Penelitian ini bertujuan untuk mendeskripsikan proses terbentuknya representasi skematis murni dan representasi skematis campuran yang diciptakan oleh siswa selama menyelesaikan word problem. Jenis penelitian yang digunakan adalah kualitatif yang bersifat deskriprif. Dalam penelitian ini melibatkan 45 siswa kelas 8. Sedangkan untuk memilih subjek tidak dipilih secara acak, namun dipilih berdasarkan kemampuan siswa dalam menciptkan representasi skematik. Pengumpulan data dilakukan dengan meminta siswa untuk menyelesaikan Tugas Pemecahan Masalah secara think aload, yaitu siswa diminta untuk menyuarakan apa yang dipikirkannya. Selain itu siswa juga menuangkan pikirannya mengunakan kertas dan pensil. Hasil penelitian ini menunjukkan bahwa proses representasi skematis murni diciptakan siswa dengan membuat gambar skema berupa garis besar dari masalah dan dilengkapi dengan beberapa keterangan pokok yang ada dalam masalah. Sedangkan proses representasi skematis campuran diciptakan siswa dengan membuat gambar skema yang dilengkapi dengan keterangan-keterangan dan gambar nyata yang sesuai dengan situasi dalam masalah. Kedua jenis representasi skematis ini sangat efektif dalam membantu siswa dalam menyelesaikan word problem

Leveling transparency via situated intermediary learning objectives (SILOs)

When designers set out to create a mathematics learning activity, they have a fair sense of its objectives: students will understand a concept and master relevant procedural skills. In reform-oriented activities, students first engage in concrete situations, wherein they achieve situated, intermediary learning objectives (SILOs), and only then they rearticulate their solutions formally. We define SILOs as heuristics learners devise to accommodate contingencies in an evolving problem space, e.g., monitoring and repairing manipulable structures so that they model with fidelity a source situation. Students achieve SILOs through problem-solving with media, instructors orient toward SILOs via discursive solicitation, and designers articulate SILOs via analyzing implementation data. We describe the emergence of three SILOs in developing the activity Giant Steps for Algebra. Whereas the notion of SILOs emerged spontaneously as a framework to organize a system of practice, i.e. our collaborative design, it aligns with phenomenological theory of knowledge as instrumented action

Teaching for wisdom in modern early education

Teaching for wisdom (especially at the early educational stages) requires personal competence by the teacher, interesting teaching aids and modern, motivating techniques that stimulate and develop the child’s potential abilities and competences related to general and practical intelligence and creativity. In early education, an especially needed type of children’s/students’ activity is that which leads to the direct experiencing of the surrounding cultural, natural, technical and social reality. Such activity is undertaken by individuals through internal emotional involvement, which leads to experiencing values in an in-depth way, supporting development and gaining all kinds of practical experience, which in turn fosters maturity towards wisdom. The environment where Teaching for wisdom should be deliberately organized is school (preschool). Factual knowledge and the methodical competences of teachers can support the organization of educational situations that allow children/students to experience values and wisdom, develop their potential cognitive abilities, gain experience in the interpretation and evaluation of wise/unwise behavior, and develop the habits of wise behavior. These situations should be a source of getting students ready to use wisdom in life and to shape their value systems. The proposal of a detailed competence scope for the notion of wisdom is presented in the this article

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments