E-Collaborative Help-Seeking Using Social Web Features

E-Collaborative Help-Seeking Using Social Web Features

Silke Schworm (University of Munich, Germany) and Markus Heckner (Accenture Information Management Services, Germany)
DOI: 10.4018/978-1-61520-729-9.ch006

Abstract

Many help systems fail because users do not perceive them as helpful and refuse to use them. Obviously there is a gap between the intentions of the help content authors and the achievement of objectives concerning the perceived usefulness by help users. Current help systems show considerable weaknesses concerning (1) the comprehensibility of the help content, and (2) the format of the help output. Users are often seriously challenged with understanding the instructions given by the system, which usually is not adequately adapted to users’ prior knowledge or their vocabulary. This problem is strengthened by the implementation problem of missing feedback channels. The current paper aims to address these issues by presenting an information architecture for an online help system, which constitutes the basis for a dynamic help system, gradually developed by experts and users. It combines earlier models of design patterns with features for user contribution from social software.
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Introduction

Help systems of computer-based learning environments are designed to help learners to complete a task or to solve a problem which they cannot solve on their own. Unfortunately learners often perceive those help systems as not being helpful at all and they refuse to use them (Aleven, Stahl, Schworm, Fischer, & Wallace, 2003). Thus, many current help systems fail due to the gap between the intentions of the help system designers and the objectives of the help system users. For a successful help-seeking process the learners have to be able to clearly formulate their help request and to look for the appropriate help. Help is appropriate if it enables the learner to complete the task (Mercier & Frederiksen, 2007). However, systems sometimes do not contain the appropriate help to enable the learners to solve their problems, since help content authors often do not know enough about the actual problems and tasks of the learners. Additionally content authors are domain experts and often do not share the learners’ vocabulary, which makes retrieving and understanding of help difficult for the learners. One possibility to bridge this gap is to address aspects of communication between help designers and users by merging approaches from educational science and information architecture. The authors developed a help system which combines elements of a design pattern language, expert-lay-communication and social computing to enable feedback processes, collaborative annotation and retrieval of help artifacts. This help system fosters interaction between help seekers and help designers and therefore is an effective tool for e-collaborative knowledge construction.

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Academic Help-Seeking

Academic help-seeking describes help-seeking activities within learning contexts. In learning contexts help-seeking is essential for the successful construction of knowledge as it is a necessary resource-based learning strategy (Karabenick & Newmann, 2006). In contrast to other strategies of self-regulated learning, it requires interaction with teachers, peers or computer-based learning environments. This chapter focuses on the features of effective help systems in computer-based settings. However, the cognitive processes underlying computer-based help-seeking processes are quite similar to those in face to face settings.

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