Olaf Schröder

Representing semantic knowledge with 2-dimensional rules in the domain of functional programming

One of the many difficult problems in the development of intelligent computer aided instruction (ICAI) is the appropriate design of instructions and helps. This paper addresses the question of optimizing instructional and help material concerning the operational knowledge for the visual, functional programming language ABSYNT (ABstract SYNtax Trees). The ultimate goal of the project is to build a problem solving monitor (PSM) for this language and the corresponding programming environment. The PSM should analyse the blueprints of the students, give comments and proposals (SLEEMAN & HENDLEY, 1982). First, we will explain our motivation for choosing this domain of discourse. Second, we will shortly present the programming environment of ABSYNT. Third, we represent the development of two alternative 2-D-rulesets (appendix A, B), which describe the operational semantics of the ABSYNT interpreter. The development of the 2-D-rules was guided by cognitive psychology and cognitive engineering aspects and results of an empirical study. The study showed that the rules were comprehensible even for computer novices.

Towards the Theory-Guided Design of Help Systems for Programming and Modelling Tasks

This paper describes an approach to the design of online help for programming tasks and modelling tasks, based on a theoretical framework of problem solving and learning. The framework leads to several design principles which are important to the problem of when and how to supply help information to a learner who is constructing a solution to a given problem. We will describe two example domains where we apply these design principles: The ABSYNT problem solving monitor supports learners with help and proposals for functional programming. The PETRI-HELP system currently under development is intended to support the learning of modelling with Petri nets.

Instruction-Based Knowledge Acquisition and Modification: The Operational Knowledge for a Functional, Visual Programming Language*

Abstract This contribution deals with instruction-based knowledge acquisition in a fairly complex but well-defined domain. The domain is the operational knowledge about the interpreter of ABSYNT, a functional, visual programming language which was developed in our project. Runnable specifications of the ABSYNT-interpreter were translated into sets of visual rules, serving as instructional material for students to acquire the operational knowledge. We are concerned with the following questions: 1. 1. How do subjects acquire the operational knowledge while simulating the interpreter of ABSYNT with the help of the instructional material? 2. 2. How can the operational knowledge gained by subjects be described? For example, does this knowledge differ from the instructional material? If the mental representation of the operational knowledge is isomorphic to the instructional material, then hypotheses about certain performance aspects can be stated. An experiment was conducted in which dyades of programming novices acquired the computational knowledge for ABSYNT by computing the value of ABSYNT-programs with the help of the instructions, thus simulating the interpreter. The hypotheses were disconfirmed. The results suggest that the mental representation of the operational knowledge consists of larger units than the instructional material, leading to the following hypotheses about the acquisition process and the mental representation of the operational knowledge: 1. 1. When faced with a difficulty, there will be problem solving with the help of the instructions. Thus new knowledge is acquired by failure-driven learning. 2. 2. When faced with familiar situations, compound rules are built. Thus the existing knowledge is improved by success-driven learning.

Diagnosing and Evaluating the Acquisition Process of Problem Solving Schemata in the Domain of Functional Programming

This paper describes an approach to model studentsknowledge growth from novice to expert within the framework of a help system, ABSYNT, in the domain of functional programming. The help system has expert knowledge about a large solution space. On the other hand, in order to provide learner-centered help there is a model of the studentsactual state of domain knowledge. The model is continuously updated based on the learners actions. It distinguishes between newly acquired and improved knowledge. Newly acquired knowledge is represented by augmenting the model with rules from the expert knowledge base. Knowledge improvement is represented by rule composition. In this way, the knowledge contained in the model is partially ordered from general rules to more specific schemas for solution fragments to specific cases (= example solutions). The model is implemented but not yet actually used for help generation within the help system. This paper focuses on knowledge diagnosis as accomplished by the model, and on an empirical analysis of some of its predictions.

The Acquisition of Functional Planning- and Programming Knowledge: Diagnosis, Modeling, and User-Adapted Help

Abstract A three-level approach to model processes of problem solving and the acquisition and optimization of knowledge was developed. First, a general theoretical framework describes problem solving phases, impasse driven knowledge acquisition, and success driven knowledge optimization. Second, a State Model of hypothetical intermediate knowledge states may be used for online diagnoses of learners domain knowledge and for generating learner-adapted help and information. Third, a Process Model closes the gap between the theoretical framework and the State Model. The approach enables a variety of empirical predictions about problem solving actions, action and time constraints, and effects of help information. In addition, it has implications for the design of intelligent knowledge communication systems. The ABSYNT Problem Solving Monitor (PSM) was developed in line with these design requirements. It supports learners acquisition of basic programming concepts while working in a visual, functional programming language. The learner may test hypotheses about solution proposals, plans and intentions, and incomplete plan fragments. Thus help is supplied at impasses, the use of preknowledge is encouraged, and different problem solving phases are supported. In addition, a State Model is designed to supply help adapted to the current knowledge state of the learner.

WULPUS - An Intelligent Problem Solving Environment Delivering Knowledge Based Help and Explanations in Business Management Simulation

Business mangement simulation plays an increasing role in schooling and post-qualification. In complex simulation games the interrelationships between decisions and results are intransparent. This is one reason for inefficient knowledge acquisition. Another reason is the forward chaining architecture of “classical” simulation games.

Erklärungsgenerierung in Petri-Help

In dieser Arbeit werden, ausgehend vom wissenschaftlichen Erklarungsbegriff Formen der Erklarung und Erklarungsgenerierung in der Kunstlichen Intelligenz eingefuhrt und diskutiert. Im Anschlus daran wird das Intelligente Hilfesystem Petri-Help vorgestellt und es werden Implikationen fur die Erzeugung von Erklarungen abgeleitet. Schlieslich werden Maglichkeiten der Erklarungsgenerierung unter den beschriebenen Pramissen aufgezeigt.

WULPUS Wissensbasierte Hilfen und Erklärungen für ein betriebswirtschaftliches Planspiel

In der betriebswirtschaftlichen Aus- und Weiterbildung werden in zunehmenden Mase Planspiele eingesetzt, um dem steigenden Bildungsbedarf kostengunstig zu begegnen. EDVgestutzte Simulationen und Planspiele haben durch die forcierte Vermittlung von Schlusselqualiflkationen eine neue Bedeutung erlangt. Man erhofft sich dadurch einerseits die Vertiefung der Analyse- und Problemlosefahigkeiten und andererseits die Verbesserung der Teamfahigkeit.

Zur Diagnose und Modellierung von Wissensveränderungen im Rahmen einer Stocksituationstheorie

Dieser Beitrag beschreibt einen Ansatz zur Modellierung hilfegeleiteter Wissenserwerbsprozesse beim Problemlosen. Ausgangspunkt ist eine theoretische Konzeption, die motivationale und volitionale Aspekte der Handlungssteuerung mit Aspekten des Lernens verbindet. Wissenserwerb wird dabei als Wechselspiel des Erwerbs neuen Wissens mit Hilfen nach Stocksituationen sowie der Wissensoptimierung durch Komposition aufgefast. Fur diese theoretische Konzeption werden fur die Domane des Programmierens in der graphischen funktionalen Sprache ABSYNT zwei unterschiedlich abstrakte lauffahige Realisationen vorgestellt: ein internes Modell der sukzessiven Wissensstadien eines Lernenden und ein externes Modell der Wissenserwerbsprozesse, die die Ubergange zwischen den Stadien ermoglichen. Das interne Modell ist integrierter Teil eines Hilfesystems zum Erwerb von Programmierwissen fur ABSYNT. Es ist in der Lage, unter Nutzung zeitprotokollierter Problemlosedaten online Losungsentwurfe zu untersuchen und moglichst wissensstandsangepaste Hilfen zu generieren. Es beschreibt die Wissensentwicklung als Fortschreiten auf von Mikroregeln uber Losungsschemata bis hin zu spezifischen Losungsbeispielen fur Programmieraufgaben und fur Teilprobleme aus diesen. Mikroregeln, Schemata und Losungsbeispiele bilden dabei eine partielle Ordnung hinsichtlich einer Spezialisierungsrelation. Das externe Prozesmodell enthalt daruber hinaus hypothetische Grunde (in Form von Wissenserwerbs-und Problemloseprozessen) fur das Fortschreiten uber die Wissensstadien. Es ist als kognitives Wissenserwerbsmodell zur Modellierung kontinuierlicher Wissenserwerbsprozesse und der dabei ablaufenden Handlungs- und Verbalisationssequenzen konzipiert. Internes Modell, externes Modell und die zugrundeliegende theoretische Konzeption beschranken sich gegenseitig, und es wird maximale Konsistenz zwischen ihnen angestrebt.

Entwurf eines Hilfesystems für Petrinetzmodellierer

Es wird die Konzeption eines Hilfesystems vorgestellt, das Personen bei der Modellierung mit Petrinetzen auf verschiedenen Entwurfsebenen mit wissensstandsbezogenen Hilfen unterstutzen soll. Das Hilfesystem soll Benutzern mit unterschiedlichem Erfahrungshintergrund zu jedem Zeitpunkt optimale, dem aktuellen Wissensstand des jeweiligen Benutzers angepaste Hilfen zur Verfugung stellen. Unerfahrenen Benutzern soll es moglich sein, sich durch die Interaktion mit dem System in die Modellierung mit Petrinetzen einzuarbeiten und das hierfur erforderliche Wissen schrittweise zu erwerben und zu optimieren.