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Automated instructional design for CSCL: A hierarchical task network planning approach
Affiliation:1. Department of Computer Science, Institute of Mathematics and Statistics, University of Sao Paulo, Rua do Matao, 1010, Cidade Universitaria, CEP 05508-090 Sao Paulo, SP, Brazil;2. Computing Institute, Federal University of Alagoas, Campus A.C. Simoes, BR 104, Norte, km 97, Cidade Universitaria, CEP 57072-970 Maceio, AL, Brazil;3. Department of Computer Systems, Institute of Mathematics and Computional Sciences, University of Sao Paulo, Avenida Trabalhador Sao-carlense, 400 Centro, CEP 13566-590 Sao Carlos, SP, Brazil;1. School of Control Science and Engineering, Dalian University of Technology, Dalian City, PR China;2. Department of Electrical Computer Engineering, University of Alberta, Edmonton, AB T6R 2V4, Canada;3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland;1. Nagoya Institute of Technology, Department of Computer Science, Gokisho, Showa, Nagoya, Aichi, 466-8555, Japan;2. University of the Ryukyus, Department of Electrical Engineering, Nakagami, Nishihara, Okinawa, 903-0213, Japan;1. Faculty of Phil. and Arts, University of Kragujevac, Jovana Cvijica bb, 34000 Kragujevac, Serbia;2. Faculty of Economics, University of Nis, Trg kralja Aleksandra Ujedinitelja 11, 18000 Nis, Serbia;3. Faculty of Economics, University of Kragujevac, Djure Pucara Starog 3, 34000 Kragujevac, Serbia;4. Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac, Serbia;5. College of Applied Mechanical Engineering, Trstenik, Serbia;1. School of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy;2. Institute of Mathematics, University of Warsaw, Warszawa, Poland;3. Department “Methods and Models for Economics, Territory and Finance”, Sapienza University of Rome, Rome, Italy
Abstract:In Computer Supported Collaborative Learning (CSCL), one of the most important tasks for instructional designers is to define scenarios that foster group learning. Such scenarios, defined as Units of Learning (UoLs), comprise different components and are organized according to pedagogical approaches to orchestrate group learning processes. Examples of UoL components are learning objects, student roles, student characteristics (e.g., background, preferences, learning styles, etc.), instructional/learning goals, and activities, among others. Thus, the instructional design (ID) of a proper UoL for CSCL is a complex task that requires practice and experience. This is particularly true when designing, developing, adapting, and customizing UoLs, taking into consideration different instructional/learning goals and individual preferences of students. This paper therefore proposes using a Hierarchical Task Network (HTN) planning approach to automate and optimize the tasks of designers. To accomplish that, we define an initial CSCL scenario as “an ID task” and “a set of information related to students and the domain to be taught.” Then we propose a model that formally describes ID for CSCL as HTN planning, where the initial CSCL scenario is adapted and refined according to student needs. In this model, the ID strategies are defined as hierarchical tasks and methods into a planning domain definition, and the initial CSCL scenario is defined as a planning problem definition. To validate our approach, we develop a CSCL courseware generator that (i) helps designers to set up an initial CSCL scenario; (ii) automatically generates a personalized UoL based on a given initial scenario; and (iii) supports the adaptation of UoLs.
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