Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

Modeling functional requirements using tacit knowledge: a design science research methodology informed approach

The research in this paper adds to the discussion linked to the challenge of capturing and modeling tacit knowledge throughout software development projects. The issue emerged when modeling functional requirements during a project for a client. However, using the design science research methodology at a particular point in the project helped to create an artifact, a functional requirements modeling technique, that resolved the issue with tacit knowledge. Accordingly, this paper includes research based upon the stages of the design science research methodology to design and test the artifact in an observable situation, empirically grounding the research undertaken. An integral component of the design science research methodology, the knowledge base, assimilated structuration and semiotic theories so that other researchers can test the validity of the artifact created. First, structuration theory helped to identify how tacit knowledge is communicated and can be understood when modeling functional requirements for new software. Second, structuration theory prescribed the application of semiotics which facilitated the development of the artifact. Additionally, following the stages of the design science research methodology and associated tasks allows the research to be reproduced in other software development contexts. As a positive outcome, using the functional requirements modeling technique created, specifically for obtaining tacit knowledge on the software development project, indicates that using such knowledge increases the likelihood of deploying software successfully

The Role of Application Domain Knowledge in Using OWL DL Diagrams: A Study of Inference and Problem-Solving Tasks

Diagrammatic conceptual schemas are an important part of information systems analysis and design. For effectively communicating domain semantics, modeling grammars have been proposed to create highly expressive conceptual schemas. One such grammar is the Web Ontology Language (OWL), which relies upon description logics (DL) as a knowledge representation mechanism. While an OWL DL diagram can be useful for representing domain semantics in great detail, the formal semantics of OWL DL places a burden on diagram users. This research investigates how user’s prior knowledge of the application domain impacts solving inference tasks as well as schema-based problem-solving tasks using OWL DL diagrams. Our empirical validation shows that application domain knowledge has no effect on inference performance but enhances schema-based problem-solving performance. We contribute to the conceptual modeling literature by studying task performance for a highly expressive modeling grammar and introducing inference tasks as a new task type